The Role of DNA Damage-Induced Cellular Senescence in the Pathophysiology of Mtbi

The Role of DNA Damage-Induced Cellular Senescence in the Pathophysiology of mTBI

Nicole Schwab

A thesis submitted in conformity with the requirements for the degree of Master of Science

Department of Laboratory Medicine and Pathobiology

University of Toronto

The Role of DNA Damage-Induced Cellular Senescence in the Pathophysiology of mTBI

Nicole Schwab

Master of Science

Department of Laboratory Medicine and Pathobiology

University of Toronto

2019

Abstract

The pathophysiological mechanism whereby mTBI leads to chronic symptoms and neuropathology is unknown, although it is known that cellular senescence underlies several neurological disorders. I hypothesize that mTBI causes DNA damage-induced cellular senescence, leading to the acute and chronic neurological dysfunction reported in individuals who have suffered from mTBI. Using a cohort of 38 donated brains with mTBI history, I have found extensive DNA damage with immunohistochemistry (γH2AX, a marker of double-stranded DNA breaks) not seen in control brains. Furthermore, gene expression analysis using NanoString revealed activation of DNA damage response pathways, insufficient expression of DNA repair proteins, and upregulation of pro-inflammatory and cellular senescence pathways. This study suggests that DNA damage-induced cellular senescence may be the underlying pathophysiological mechanism of acute and chronic brain dysfunction after mTBI, and represents potential therapeutic targets for treatment of mTBI-induced brain dysfunction.

Acknowledgements

First, I would like to thank my supervisor, Dr. Lili-Naz Hazrati, for having me as her graduate student and providing me with invaluable guidance and consistent support throughout my MSc research.

I would like to thank Yvonne Zhong for helping us perform NanoString experiments and guiding me with statistical analysis as well as Paula Marrano for her patience and support in teaching me various immunohistochemistry techniques throughout this project. In addition, I thank our collaborator, Dr. Anne Wheeler, and her lab members for giving me mice to use for preliminary work.

Lastly, I would like to thank my advisory committee, Dr. JoAnne McLaurin and Dr. Peter Wells, for their consistent support and constructive feedback, and for committing their time to the success of my research project.

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Table of Contents

Abstract ii

Acknowledgements iii

Table of Contents iv

List of Tables and Figures vi

List of Abbreviations vii

List of Appendices viii

1. INTRODUCTION 1

1.1 Background 1

1.1.1 Mild Traumatic Brain Injury 1

1.1.2 The association between mTBI and neurodegenerative disease 3

1.1.3 From “Punch Drunk” to Chronic Traumatic Encephalopathy 4

1.1.4 Oxidative Stress, DNA damage, and the DNA Damage Response 9

1.1.5 Cellular Senescence and the Senescence-Associated Secretory Phenotype (SASP) 11

1.2 Rationale and Hypothesis 13

1.3 Specific Aims 14

1.4 Scientific Impact 14

2. MATERIALS AND METHODS 16

2.1 Cases and sample acquisition 16

2.2 Immunohistochemistry for Neuropathology and DNA damage 16

2.2.1 Image Analysis 17

2.3 NanoString Gene Expression Assay 17

2.3.1 nSolver Analysis 18

2.4 Mouse CCI Model 18

3. RESULTS 20

3.1 Cohort demographics and clinical presentation 20

3.2 Neuropathological assessment 22

3.3 Immunohistochemistry 23

3.3.1 mTBI brains accumulate extensive DNA damage marked by γH2AX 23

3.4 Nanostring 34

3.4.1 DDR signalling 34

3.4.2 DNA repair genes 36

3.4.3 Regulators of cellular senescence 38

3.4.4 SASP factors 40

3.5 Clinicopathological correlation 42

3.6 DNA damage and cellular senescence are evident in a CCI mouse model 43

4. DISCUSSION 46

4.1 Evidence of DNA damage in human concussed brains 46

4.2 Impaired DNA repair capacity in human concussed brains 48

4.4 Clinicopathological correlation in human concussed brains 51

4.5 Evidence of DNA damage and cellular senescence in a CCI mouse model 53

4.6 Cellular senescence as the pathophysiological mechanism of mTBI-induced brain dysfunction 54

5. FUTURE DIRECTIONS 57

6. CONCLUSION 60

7. REFERENCES 61

APPENDICES 79

List of Tables and Figures Figure 1: Cellular senescence and the SASP Table 1: Cohort demographics Figure 2: Proportion of neuropathological diagnoses Figure 3: γH2AX control case Figure 4: γH2AX stage 1 staining Figure 5: γH2AX stage 2 staining Figure 6: γH2AX stage 3 staining Figure 7: γH2AX quantification results Figure 8: GFAP staining in a case versus control Figure 9: H3K27Me3 staining in a case versus control Figure 10: Lamin B1 staining in a case versus control Figure 11: Histogram of DDR gene expression in human cohort Figure 12: Boxplot of DNA repair gene expression in human cohort Figure 13: Histogram of DNA repair gene expression in human cohort Figure 14: Boxplot of senescence gene expression in human cohort Figure 15: Boxplot of SASP gene expression in human cohort Table 2: Clinical presentation in senescent and non-senescent cases Figure 16: γH2AX and Lamin B1 staining in CCI mice versus sham Figure 17: Histogram of DDR and senescence gene expression in CCI mice Figure 18: Histogram of SASP gene expression in CCI mice Figure 19: Overview of DNA damage-induced senescence pathway in mTBI

List of Abbreviations

Note: A complete list of gene names is included in Appendix 1

8-OhDG: 8-oxo-2’-deoxyguanosine AD: Alzheimer’s disease ALS: amyotrophic lateral sclerosis Aβ: amyloid beta BER: base-excision repair CCI: controlled cortical impact CTE: chronic traumatic encephalopathy DDR: DNA damage response DSB: double-stranded break FTD: fronto-temporal dementia GFAP: glial fibrillary acidic protein MCI: mild cognitive impairment mTBI: mild traumatic brain injury NFT: neurofibrillary tangle PD: Parkinson’s disease p-tau: hyperphosphorylated tau protein ROS: reactive oxygen species SAHF: senescence-associated heterochromatin foci SASP: senescence-associated secretory phenotype SSB: single-stranded break TBI: traumatic brain injury TDP-43: TAR DNA-binding protein 43

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List of Appendices

Appendix 1: List of genes included in NanoString custom panel

Appendix 2: NanoString mouse neuroinflammation panel

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1. INTRODUCTION

1.1 Background

1.1.1 Mild Traumatic Brain Injury

Traumatic brain injury (TBI) is a leading cause of death and disability worldwide, affecting an estimated 10 million individuals each year (1). In particular mild TBI (mTBI), which includes concussions and sub-concussive blows to the head (2), affects the largest proportion of these individuals. It is difficult to determine the exact incidence of mTBI, as many individuals do not seek medical attention (3), and as a result it is estimated that the true prevalence of mTBI is substantially higher than officially reported (4). It is important to note that some sub-populations experience mTBI at a higher incidence than others, for example professional athletes (5), survivors of domestic abuse (6), and military personnel (7). Individuals in these groups may also underreport their injuries due to various barriers, such as fear of repercussions from a violent partner, not wanting to sit out of play, lack of education on mTBI, or not having the resources to report. It is clear from population statistics that mTBI is extremely common and can be considered a substantial public health issue.

For decades it was thought that concussions have little to no consequences to brain health, however it is now clear that the exact opposite is true. mTBI, especially when experienced repetitively (8), is linked to several long-term symptoms which are broad in nature, involving mood, behavior, and cognition (9). In some individuals, mTBI results in acute symptoms such as headache, nausea, fatigue, and confusion (10, 11) which may resolve anywhere from one week to a few months (12). However, an estimated 20% of individuals who experience repetitive mTBIs go on to be diagnosed with post-concussive syndrome (13), defined as the absence of resolution of symptoms 3 months post-injury (14). The long term sequelae of repetitive mTBIs can therefore include symptoms of post-concussive syndrome such as mood disorders (15) (particularly anxiety and/or depression), sleep disturbances (16), cognitive deficits (including memory and attention

1 problems) (17), and an increased risk of being diagnosed with dementia or a neurodegenerative disease later in life (18). The reported prevalence rate of depression following mTBI varies between studies and ranges from 12% (19) to 44% (20), but it has been shown that depression at one month post-injury significantly predicts progression to post-concussive syndrome up to one year post-injury (21). This same study found that over 20% of mTBI patients reported headaches, sleep disturbances, irritability, forgetfulness, and poor concentration one year post-injury (21). In fact, one of the most reported symptoms in individuals with post-concussive syndrome is fatigue and an inability to keep up with their work (22). It is important to note that the prevalence of post- concussive symptoms vary between studies depending on methodology, study population, and timing of assessment. In particular, there is a tendency for mTBI patients to overestimate their pre-injury mood and productivity levels such that they perceive their pre-injury functioning as above average, known as the “good old days” bias (23). In addition, mTBI patients tend to over- report sleep disturbances with subjective measurements, such as self-reporting, when compared to objective measurements (24). Despite possible discrepancies in the reported prevalence of specific symptoms, it is clear that some individuals who experience mTBI recover fairly quickly and some continue to experience debilitating symptoms chronically. Currently, it is unclear what differentiates individuals who recover quickly, and those which go on to experience post- concussive syndrome and/or permanent disability.

As mTBI affects nearly all populations, with some sub-populations at higher risk than others, it is considered a significant public health issue which requires further clarification. Currently, the molecular cause of the acute and chronic effects of mTBI remain unknown and no standard clinical tools for diagnosis nor prognosis have been implemented. By extension, there are no effective treatments for the long-term sequelae of mTBI and it remains a large burden on global public health. In order to address this issue, we must have an understanding of the foundational pathophysiological mechanisms involved in mTBI.

1.1.2 The association between mTBI and neurodegenerative disease

A history of mTBI is considered a primary risk factor for the diagnosis of dementia and some neurodegenerative diseases later in life, including Alzheimer’s disease (AD) (25), Parkinson’s disease (PD) (26), amyolateral sclerosis (ALS) (27), fronto-temporal dementia (FTD) (28), and chronic traumatic encephalopathy (CTE) (29). A majority of the data linking mTBI to neurodegenerative diseases is epidemiological, relying on retrospective data of large cohorts. In a nation-wide cohort study of over 800,000 individuals in Sweden revealed that having at least one mTBI in their life was significantly associated with a 70% increased risk of early-onset dementia (30), although they did not find associations between mTBI and disease-specific dementia, such as that caused by AD. In another study of 350,000 veterans in the United States, mTBI with no loss of consciousness was associated with a 2-fold increased risk of being diagnosed with dementia later in life (31). In various epidemiological studies, TBI has been shown to be associated with AD-related dementia, with TBI increasing the risk of developing AD by anywhere between 58% and 82% (32). In particular, two meta-analyses have been rigorously conducted regarding the association between TBI and AD. The first analysed 11 case-control studies of head trauma with loss of consciousness, and found a pooled relative risk of 1.82 after controlling for heterogeneity across studies and family history of dementia (33). The second major meta-analysis looking at this association found a significant association between a history of TBI and AD, with an odds ratio of 1.58 (34). In addition to AD and non-AD dementia, TBI patients are significantly more likely to be diagnosed with PD compared to non-injured controls (1.7% versus 1.1%) (35). Furthermore, TBI is reported in retrospective case-control studies to increase the risk of FTD diagnosis with odds ratios varying from 3.3 to 4.4 (36). It is clear from the epidemiological evidence that TBI is a risk factor for various neurodegenerative conditions later in life, all of which are primarily characterized by the pathological misfolding and/or aggregation of proteins in brain cells. The details of pathological findings after mTBI will be outlined in the next section, but it is likely that the heterogeneity in neurodegenerative diseases associated with mTBI is a reflection of underlying dysfunctional molecular processes in brain cells.

In addition to epidemiological data, experimental evidence with mice suggests that mTBI leads to widespread, non-specific neurodegeneration. In a controlled cortical impact (CCI) model in mice, a model of mTBI used to produce reproducible and controlled head injuries to experimental

3 animals, extensive neurodegeneration marked by de Olmos silver staining was noted after injury (37). This neurodegeneration was widespread, and affected the frontal cortex, hippocampus, corpus callosum, afferent pathways, visual cortex, and thalamus. The authors noted that the diffuse nature of this degeneration likely accounted for the neurological deficits seen in CCI mice. In other studies, both widespread neurodegeneration and pro-inflammatory mediation through the activation of microglia and astrocytes has been found (38). Experimental models of mTBI using animals therefore supports the notion that head trauma leads to neurodegenerative disease and neurological deficits, however these studies tend to report widespread neurodegenerative changes and neurological deficits, which do not necessarily translate to a specific disease phenotype. In addition these models fail to give an account of the underlying cause of these effects, but simply report the catastrophic end-stage consequences of head trauma.

1.1.3 From “Punch Drunk” to Chronic Traumatic Encephalopathy

More recently, mTBI has been proposed to cause CTE, a progressive neurodegenerative disease characterized so far in approximately 200 cases (39) by the presence of hyperphosphorylated tau protein (p-tau) in the depths of cortical sulci. Tau protein normally functions as a microtubule- associated protein, playing a role in stabilization of microtubules (40). Under pathogenic conditions, such as AD and CTE (41), tau is hyperphosphorylated resulting in its dissociation from microtubules and assembly into abnormal accumulations called neurofibrillary tangles (NFTs) (42), resulting in cell dysfunction and death (43) and cognitive decline (44). In CTE the gross neuropathological findings are often minimal, and the brain may look normal with no evidence of head trauma (45). In some severe cases, however, gross pathology of CTE can include the presence of a cavum septum pellucidum, septum fenestration, medial temporal lobe atrophy, and/or pallor of the substantia nigra and locus coeruleus (46). In general, cases of CTE usually do not present with any gross neuropathological changes and its diagnosis is therefore reliant on microscopic findings. The diagnosis of CTE is reliant upon the presence of perivascular p-tau deposits in neurons and astrocytes, in the form of NFTs or pre-tangles, in the depths of cortical sulci (47). Although CTE involves the same protein as found in AD, an important contrast between the two diseases is that in AD p-tau is found in solely neurons and begins in the medial temporal lobes, whereas in CTE p-tau is found in neurons and glial cells and begins in the frontal

4 lobes (48). In addition to these differences, it was recently found that the pathological tau protein in CTE is structurally different than found in AD (49). Indeed, it was found that CTE tau forms a hydrophobic cavity not seen in AD, suitable for the incorporation of co-factors such as fatty acids (49).

It is important to note that although the diagnosis of CTE based on p-tau is a fairly recent phenomenon, the idea that head trauma causes brain disease is not novel. The association between TBI and long-term symptoms was first described in the 1920s, when Harrison Martland reported a novel condition he called ‘punch drunk syndrome’ in boxers (50). Martland described these boxers has having an unsteady gait, appearing intoxicated, tremors, and in some cases cognitive decline. Importantly, Martland did not pathologically characterize these individuals and it has been suggested that these symptoms were the result of an acute parenchymal brain injury (51). This condition became known as “dementia pugillistica” (52) and the term CTE was later coined in 1940 in a case study of one professional boxer who presented with depression, violence, and poor memory (53). Throughout the next half century, case series were performed (54-56), often on groups of retired boxers, in an attempt to pathologically characterize CTE and link its emergence to TBI. In a landmark paper entitled “the aftermath of boxing”, Corsellis et al. (57) described, for the first time, the neuropathology of dementia pugilistica in 15 retired boxers. This series reported neurofibrillary degeneration in the substantia nigra and temporal lobe, cerebellar scarring, and septal abnormalities. The interest in CTE re-emerged in 2005, when Omalu et al (58) reported CTE in a retired football player. This study raised important questions about the prevalence of CTE in other populations, as a majority of previously reported case series were performed on retired boxers. Since the publication of this study in 2005 several larger case series (described in detail below) have sought to characterize the neuropathology of CTE, primarily in players of American football and other popular contact sports. However despite the growing number of publications studying CTE, the disease has only been characterized in approximately 200 cases (39). The current understanding of the neuropathology of CTE is therefore based on a relatively small number of cases when compared to other neurodegenerative diseases such as AD.

The first ever consensus criteria for the neuropathological diagnosis of CTE was written in 2016 by McKee and colleagues out of Boston University along with the NINDS/NIBIB (National Institute on Neurological Disorders and Stroke/National Institute of Biomedical Imaging and Bioengineering) panel (47). This criteria was established by seven neuropathologists who blindly evaluated 25 cases of various tauopathies, 10 of which were confirmed cases of CTE. The panel reached general consensus on the pathology of all cases, including the 10 CTE cases. The group identified only one feature required for CTE diagnosis, which is the presence of p-tau aggregates in neurons, astrocytes, and/or cell processes in the perivascular regions at the depths of cortical sulci. This criteria did not have a lower bound and, as such, one focus of tau in this region is sufficient for a post-mortem diagnosis of CTE. Seven neuropathological features, five involving tau and two not involving tau, were identified as supportive features for the diagnosis of CTE: 1. p-tau pre-tangles and NFTs in superficial layers II-III of the cortex, 2. NFTs or pre-tangles in CA2 and dendritic swellings of CA4 of the hippocampus, 3. p-tau in neurons and astrocytes of subcortical nuclei, including the mammillary bodies, amygdala, nucleus accumbens, thalamus, midbrain tegmentum, nucleus basalis of Meynert, raphe nuclei, substantia nigra, and locus coeruleus, 4. p-tau in astrocytes in the subpial and periventricular regions, 5. p-tau gain- and dot- like structures, 6. any of the gross macroscopic features as described above, and 7. Neuronal inclusions in the hippocampus, temporal cortex, or amygdala of TAR DNA-binding protein 43 (TDP-43), an RNA/DNA binding protein which normally functions to repress transcription and pre-mRNA splicing (59) but becomes hyperphosphorylated, ubiquitinated, and cleaved in pathogenic conditions such as FTD and ALS (60).

The reported clinical presentation of CTE can vary between individuals, including both behavioural and cognitive changes. Behaviourally, individuals with CTE have been described as being irritable, aggressive, depressed, and anxious (61). Furthermore, cognitive changes such as short-term memory impairment and attention deficits in these individuals have been described (61). It has also been suggested that suicidality is a common feature of CTE (62). It is important to note, however, that the clinical presentation reported in CTE is not unique to the disease. For example, depression, anxiety, aggression, and short-term memory loss are all reported in CTE, but are also common to withdrawal from drugs or alcohol (63), various endocrine disorders (64), and some may be attributed to mental health issues common in the general population (65). As

6 the clinical presentation of CTE has been generally determined using retrospective interviews with next-of-kin and not with longitudinal studies, we are therefore unable to confidently attribute these symptoms to CTE pathology, making the idea of CTE as a syndrome quite controversial.

Although the diagnostic criteria for CTE requires only the presence of a single p-tau aggregate and is supported by the presence of TDP-43 inclusions(47), individuals diagnosed with CTE often present with additional pathological changes not defined by the consensus paper. In a highly cited case series of 202 American football players in 2017, for example, 99% of individuals who played for the National Football League were diagnosed with CTE (66). However, within those diagnosed with CTE, 61% presented with diffuse neuritic amyloid-beta (Aβ) plaques, which are folded aggregates of Aβ peptides. While the normal physiological function of Aβ is unclear and may be involved in various physiological functions (67) Aβ plaques are implicated in over 50 human diseases (68) and are a main toxic pathological finding in AD brains (69). In another case series in 2015, 52% of individuals diagnosed with CTE presented with Aβ pathology either as diffuse or neuritic plaques, and Aβ pathology was associated with worsened dementia, the presence of comorbidities, parkinsonism and motor symptoms, and more severe p-tau pathology when controlled for age (70). Another pathological entity commonly found in CTE cases is ɑ- synuclein, a soluble synaptic maintenance protein which abnormally aggregates in PD (71). In a case series of CTE in 2013, 22% of CTE cases presented with ɑ-synuclein pathology primarily in the olfactory bulb and medulla (61). Interestingly, ɑ-synuclein in the neocortex has been associated with increased Aβ plaques and p-tau pathology in CTE, and has therefore been suggested as the cause of motor symptoms in some individuals with CTE (72). Finally, although TDP-43 is included in the diagnostic consensus paper as merely a supportive feature of CTE, its accumulation is actually quite common in the disease. For example, TDP-43 inclusions were found in 85% of CTE cases in a 2013 case series of head trauma(61), and in 48% of CTE cases in a series published in 2017(66), although the extents and distributions of this pathological entity were not specified in the study.

In a recent study, Goldfinger et al. (73) re-examined 14 of the 15 retired boxers described in Corsellis’ 1973 paper(57) in which the neuropathology of CTE was first published. Using

7 modern-day techniques and the most up-to-date neuropathological criteria for CTE (47), only 7 cases (50%) met the criteria for the diagnosis of CTE. In fact, the most controversial and important finding in this paper was not the diagnosis of CTE, but the diagnosis of age-related tau astrogliopathy (ARTAG). ARTAG describes the accumulation of p-tau in individuals over 60 years of age, particularly the presence of thorn-shaped astrocytes and clusters of astrocytes with perinuclear cytoplasmic p-tau (74). In 10 of the 14 (74%) cases re-examined by Goldfinger et al (73), ARTAG pathology was identified. The authors of this paper raised the question that perhaps CTE and ARTAG exist on the same spectrum of neuropathological disorders, and that CTE may not be a unique disease in itself.

The neuropathology of CTE, in combination with established epidemiological and experimental evidence linking mTBI to a wide range of neurodegenerative diseases, emphasizes that the neuropathology of mTBI is complex. In addition, the current diagnostic criteria for CTE has shown to be non-specific, and may represent a spectrum of tauopathies. What these neurodegenerative conditions all have in common is the misfolding, hyperphosphorylation, and/or abnormal aggregation of proteins in brain cells. Chronic mTBI brains have been found to present with a variety of pathological entities common to AD, PD, FTD, and ALS, and mTBI has been linked epidemiologically to several sub-types of dementia, implying that the neuropathology of mTBI is diverse and may not be limited to a specific disease. Furthermore, as the diagnostic criteria of CTE does not have a lower bound, cases of CTE often present with very scarce, focal p-tau pathology in one brain region which may not be sufficient to explain the debilitating and widespread symptoms reported by many of these individuals. (61). Indeed, in a new review published out of Boston University, the authors explicitly state that the relationship between concussions and onset of cognitive and psychiatric symptoms cannot be sufficiently explained by CTE pathology (75). It may therefore be more accurate to describe the long-term consequences of mTBI as a disease with “polypathology”, or the co-existence of multiple pathologies (76), rather than a tauopathy as described in CTE. The heterogeneity of pathological findings and broad-range of symptoms and dementia types after mTBI suggests that there are underlying molecular changes causing overall brain dysfunction and a susceptibility towards brain disease in general in this population. Therefore, a better understanding of the underlying molecular pathways

8 active after mTBI is required in order to grasp the neuropathological changes and clinical symptoms presented after head trauma.

1.1.4 Oxidative Stress, DNA damage, and the DNA Damage Response

An immediate effect of mTBI is the increased production of reactive oxygen species (ROS) and reactive nitrogen species past normal physiological levels, and the simultaneous decreased production of antioxidants (77). This is referred to as oxidative stress, defined as a state of metabolism in which the production of ROS outweighs the production of antioxidant defenses (78). Oxidative stress has various adverse effects on brain cells, possibly contributing to the pathophysiology of mTBI. Elevated levels of various markers of oxidative stress have been found in the plasma of individuals who have experienced TBI (79), and the degree of oxidative stress has been positively associated with the severity of injury (80). Furthermore, blocking oxidative stress via phenserine (an inhibitor of acetylcholinesterase which mimics the endogenous antioxidant response) was shown to rescue cognitive deficits induced by mTBI in a mouse model (81). The results of oxidative stress in the brain can include lipid peroxidation (82), cell death (83), and DNA damage (84) among other severe repercussions, and many of these outcomes have been reported in studies of TBI. For example, increased lipid peroxidation in cortical neurons has been shown in a rat model of repetitive mTBI with a dose-dependent effect (85). Taken together, the literature indicates that oxidative stress occurs after mTBI, and that this effect is dose- dependent (i.e. oxidative stress increases with repeated injury) and severity-dependent (i.e. oxidative stress increases with increased severity of injury).

One of the most detrimental effects of increased oxidative stress in the brain is damage to DNA. There are several types of DNA lesions, including single-base oxidation, single-stranded breaks (SSBs), and double-stranded breaks (DSBs), all of which may be induced by pathological oxidative stress (86). For example the oxidized form of guanine, 8-hydroxydeoxyguanosine (8- OHdg) is dangerous to the cell, as it can be incorrectly incorporated by DNA replication machinery leading to mutations which may be harmful to the function of the cell (87). Interestingly, there is a suggested link between increased oxidative stress and impairment of DNA damage repair machinery in individuals with major depressive disorder (88), indicating a potential

9 role for accumulation of DNA damage in the emergence of mood disorders commonly reported following mTBI.

The various forms of DNA damage accumulate with the natural ageing process (89). This is in part due to endogenous sources, such as metabolic ROS, and partly due to exogenous agents such as radiation, alcohol and drug abuse, and UV light (90). Because our cells are normally faced with these lesions, they are equipped with an evolutionarily conserved endogenous repair pathway called the DNA damage response (DDR) (91). The DDR is a large-scale, complex, and dynamic pathway which functions to restore integrity of DNA following a lesion (92). Failure of the DDR to properly repair DNA results in cellular senescence or apoptotic cell death (93), and as such it plays a crucial role in maintaining the integrity of the cell. The DDR pathway relies on an vast number of enzymes, transcription factors, and signalling molecules in order to quickly respond to structurally diverse breaks in DNA. DSBs, which may be induced with radiation, ROS, or drugs among other sources (94), are by far the most lethal form of DNA damage as very small numbers of these lesions are capable of inducing apoptosis or cellular senescence (95). After a DSB, the conserved H2A histone family member X (H2AX) becomes phosphorylated at Ser139 by the serine/threonine protein kinase ataxia telangiectasia mutated (ATM) (96), which is a central sensor in the initial recognition of DSBs by the DDR (97). γH2AX, the phosphorylated form of H2AX, foci accumulate near the DSB in order to propagate DDR signalling to downstream effector proteins, such as p53, cell-cycle arrest proteins, such as Check kinase 2 (Chk2), and DNA repair proteins, such as breast cancer type I susceptibility protein (BRCA1) (98). The purpose of this orchestrated response is to transiently inhibit the cell cycle long enough for repair enzymes to flock to the DSB, marked by γH2AX foci, and successfully restore DNA (99). Efficient DNA damage repair is therefore integral for maintaining genomic integrity and cellular function.

Deficiencies in DNA repair are known to underlie several neurological conditions in both humans and animal models. In fact, inefficient DNA repair has been proposed as an important factor in premature aging (100) and the development of neurodegenerative diseases (101). In AD, a two- fold increase in DNA damage has been found in the cortex compared to healthy controls (102). Furthermore, AD brains have been reported as having decreased base-excision repair (BER) pathway activity (103). Furthermore, defects in DNA repair machinery has been linked to alpha- 10 synuclein pathology and reduced dopaminergic innervation consistent with PD (104). Defects in DNA repair and accumulation of various DNA damages has been further characterized in several neurodegenerative disorders including ALS (105) and FTD (106). DNA damage has therefore been suggested to play a role in age-related cognitive decline and pathology (107). In fact, accumulation of DNA damage has been shown to predict progression from mild cognitive impairment (MCI) to AD prior to the emergence of any neuropathology (108).

1.1.5 Cellular Senescence and the Senescence-Associated Secretory Phenotype (SASP)

When the DDR is persistently activated, for example in cases of extensive and persistent DNA damage, cell-cycle arrest is abnormally prolonged (109). In mitotic cells, such as glial cells in the brain, this results in activation of pathways for cellular senescence (110). Senescence is a state of permanent cell-cycle arrest characterized by chronic inflammation, morphological changes including changes in gene expression, and self-maintenance through autocrine reinforcement (111). One of the most damaging effects of senescent cells is the constant secretion of pro- inflammatory factors such as interleukins, cytokines, chemokines, and matrix metalloproteinases (112). Together this is called the senescence-associated secretory phenotype (SASP), and it is maintained through a series of positive feedback loops in which the secreted pro-inflammatory molecules (SASP factors) reinforce the DDR through oxidative stress (113). Furthermore, SASP factors have paracrine effects such that they can induce cellular senescence in cells of the surrounding tissue (114). Cells with this senescent phenotype accumulate with age (115), resulting in widespread tissue dysfunction which is the driver of age-related ailments. In the context of the

11 brain, the accumulation of senescent glial cells is thought to drive cognitive decline and pathology associated with ageing (116) (Figure 1).

Senescent cells present with gene expression changes consistent with cell-cycle arrest and secretion of pro-inflammatory factors, along with elevation of several biomarkers including beta- galactosidase (117) and p16INK4A (118), an enzyme which breaks down β-galactosides into monosaccharides and tumor suppressor protein, respectively. Senescent cells also present with various morphological changes, including the enlargement of astrocytic cell bodies (119), loss of lamin B1 expression on the nuclear membrane (120), and loss of histone H3K27Me3 (trimethylation of lysine 27 on histone H3 protein subunit) expression on chromatin (121). Lamin B1 normally functions to tether heterochromatin to the inner nuclear membrane, preventing its transcription (122). However, in senescent cells lamin B1 expression is reduced (120), resulting in rearrangement of heterochromatic regions into senescence-associated heterochromatic foci (SAHF) (123) and large-scale changes in gene expression (124). Importantly, B-type lamin misregulation and the subsequent relaxation of heterochromatic regions has been linked to tauopathies in humans and suggested as a mechanism of neuronal death in neurodegenerative diseases (125). In addition to lamin B1, senescent cells show a reduction in H3K27Me3, a trimethylated histone which plays various physiological roles in development, proliferation, and

Figure SEQ Figure \* ARABIC 1 Senescent cells take on the senescence-associated secretory phenotype (SASP), characterized by the secretion of pro-inflammatory proteins, and referred to as SASP factors. SASP factors have autocrine effects such that senescence is maintained, as well as paracrine effects such that surrounding cells can become senescent. The accumulation of senescent cells is associated with ageing and age-related disease, neurodegenerative disease, and cognitive impairment. 12 differentiation (126). Loss of the trimethylation status of H3K27Me3 has been reported to induce senescence through the up-regulation of SASP and p16 pathways (121), and its loss is therefore considered a marker of senescent cells.

Senescence has differential effects on overall brain health depending on the type of cell affected. When astrocytes become senescent they no longer provide trophic support to the neuron, disturbing normal neuronal function (127). Oligodendrocytes may lose their ability to myelinate and therefore disrupt axonal health when they become senescent (128). Affected microglia impairs the brain’s immune system and cell clearance ability (129). Lastly, senescent endothelial cells may disrupt the integrity of the blood-brain barrier (130). Cellular senescence in glial cells therefore has enormous repercussions for integrity of neuronal function and overall brain health, resulting in widespread tissue dysfunction and inevitable neurological symptoms. The role of senescent cells in cognitive decline and p-tau pathology has been demonstrated in a transgenic mouse model of AD, in which eliminating senescent cells through senolytic intervention resulted in reduced tau phosphorylation, improved cognitive outcomes, and the prevention of the upregulation of senescence genes (131). To date, only one paper has shown accumulation of senescent cells in the context of TBI. In this study young and aged mice were subjected to a CCI protocol of mTBI, and then assessed for neurological outcome and various markers of senescence and inflammation in microglia (132). The authors found that markers of senescence, including γH2AX and p16INK4A, were significantly elevated in the aged mice compared to young mice, but that they are also elevated in response to TBI regardless of the age of the animal. This paper therefore provided the first experimental evidence showing that markers of senescence are elevated in response to TBI.

1.2 Rationale and Hypothesis

The pathophysiological mechanism by which mTBI exerts acute and chronic symptoms and pathology is currently unknown. Furthermore, it is unclear how mTBI predisposes some individuals to long-term sequelae including post-concussive syndrome, dementia, and neurodegenerative diseases later in life. The accumulation of DNA damage and senescent cells

13 has been shown in various neurodegenerative diseases, normal physiological ageing, and age- related diseases. I hypothesize that mTBI causes DNA damage and the subsequent acquisition of cellular senescence in glial cells and that this is the underlying pathophysiological mechanism driving the acute and chronic symptoms and neuropathological changes associated with mTBI.

1.3 Specific Aims In order to investigate this hypothesis, I will address the following specific aims:

(1) Assess the extent and distribution of DNA damage in post-mortem human brains with history of mTBI. (2) Assess evidence of cellular senescence and SASP in post-mortem human brains with history of mTBI. (3) Validate human findings in a controlled cortical impact (CCI) mouse model of mTBI.

1.4 Scientific Impact mTBI represents a growing public health concern, as millions of individuals are affected each year. Approximately 20% of these patients go on to have chronic disability as a result of their injury, severely affecting their quality of life (13). Currently, the lack of a fundamental understanding of how mTBI affects the brain is major barrier for developing effective treatments for some of the most debilitating symptoms such as persistent headache, depression, and short- term memory problems. These symptoms can make it impossible for an individual to return to work/normal life.

This study aims to identify the early pathophysiological changes caused by mTBI, rather than focusing on end-stage pathology. This will facilitate diagnosis and prognosis, as individuals most often seek medical attention for an mTBI within 24 hours (133). In particular, this study introduces novel targets for the discovery of peripheral tissue biomarkers, which may be used in a clinical setting for diagnosis or prognosis. An understanding of early-stage phenomenon after mTBI may also allow for the development of therapeutic interventions, as it is easier to prevent accumulation 14 of pathology before it occurs than it is to eliminate already established pathology. This research has the potential to uncover the fundamental cause of neurodegenerative diseases resulting from mTBI, including CTE, and provide the clinicopathological correlation currently missing from the understanding of mTBI.

2. MATERIALS AND METHODS

2.1 Cases and sample acquisition

A collection of 38 brains have been donated for their use in research on mTBI. All case is male, aged between 15 and 87 years old, and all have a long history of mTBI. A majority of these individuals were involved with professional or semi-professional contact sports including football (Canadian Football League), hockey (National Hockey League), rugby, boxing, and other extreme sports. Informed consent for both study participation and brain autopsy was given by either the participant prior to death, or by the participant’s next of kin. Information on clinical presentation was collected from next of kin and available medical records. The use of this material has been approved by the Ethics Review Board at the Hospital for Sick Children.

2.2 Immunohistochemistry for Neuropathology and DNA damage

Brains were fixed in formalin and sampled according to the National Institute on Aging Association (NIA-AA) guidelines for the neuropathological assessment of Alzheimer’s disease (123). Brain regions sampled included cortical, subcortical, cerebellar, and brainstem areas. The samples were processed and embedded in paraffin. Following embedding, samples were cut into six micron sections and mounted on glass slides. Each section was stained with Luxol fast blue and hematoxylin and eosin (LFB/H&E), followed by a full neuropathological assessment with the following antibodies: Phospho-Tau (Ser199, Ser202) (polyclonal rabbit, #44-768G: Thermo Scientific, 1:1000), TDP-43 (polyclonal rabbit, #PA5-29949, Thermo Scientific 1:500), β- amyloid (monoclonal mouse, DAKO, M0872, 1:50), and α-synuclein (monoclonal rabbit, Thermo Scientific #701085, 1:500). Each case was diagnosed by a staff neuropathologist. In addition, to assess DNA damage each section was stained with γH2AX (monoclonal mouse, 1:1000, Ser139, #05-636; Millipore), a robust marker of DSBs. Sections were also stained with GFAP (polyclonal rabbit, Omnis; Dako), a marker of astrocytes, H3K27Me3 (polyclonal rabbit ,#07449, Millipore), a histone for which loss associated with senescence, and LaminB1 (monoclonal rabbit, Abcam, #133741) a nuclear membrane protein for which loss is associated with senescence.

2.2.1 Image Analysis

The hippocampus of each case was analyzed for γH2AX. Each slide was scanned with an Aperio Scanscope AT2 at 40x magnification. In each slide containing the hippocampus, three regions of interest were chosen blindly from each of the following areas: the ependymal lining, subependymal areas, surrounding cortical tissue, subpial areas, CA1-CA3 of the hippocampus, and surrounding white matter. In each region the number of γH2AX-positive ependymal cells, astrocytes, oligodendrocytes, and neurons were counted and divided by the total number of each cell type in that region to create a positive cell density score for each cell type. The mean positive cell density score for each cell type was then calculated for each case (not shown). As DNA damage is often found in clusters and not uniformly distributed throughout the tissue, blind analysis of random regions of interest may not be representative of distribution. Therefore cases were then categorized into three stages of positivity based on the distribution of γH2AX. Stage 1 was defined as having γH2AX in the ependymal lining only. Stage 2 was defined as having γH2AX in the ependymal lining as well as γH2AX-positive astrocytes in the sub-ependymal region, hippocampus, or surrounding cortical areas. Stage 3 was defined has having γH2AX in the ependymal lining, at least one significant cluster of γH2AX-positive astrocytes as described in stage 2, in addition to γH2AX-positive oligodendrocytes in the white matter.

2.3 NanoString Gene Expression Assay

Of the 38 donated brains with a chronic history of mTBI, 11 cases had sufficiently high quality RNA for analysis of gene expression using NanoString nCounter Technology. These were compared to 1 control brain with no history of trauma. NanoString nCounter is a microarray tool for analysis of mRNA targets that has been optimized for use in fixed tissue, such that it picks up mRNA fragments allowing for accurate quantification of mRNA in post-mortem tissue. The nCounter system first utilizes a hybridization step in which a capture and reporter probe (a colourful barcode unique to each target) hybridize onto target mRNAs. Next, any unbound probes are removed and the target/probe complexes are aligned and immobilized using electric current. Finally, the coloured reporter probes are counted by the digital analyzer and each mRNA target is quantified by RNA count number. For this study, a custom panel of genes was created consisting 17 of 169 genes involved in the DDR and cellular senescence, including SASP factors (Appendix 1). Six housekeeping genes were used for normalization. From each of the 11 cases and 1 control, formalin fixed paraffin embedded shavings from the hippocampus were used for isolation of total RNA. This was accomplished using the RNeasy FFPE Kit by Qiagen (Qiagen Inc., Toronto, ON, Canada) with no changes to the manufacturer protocol. Total RNA was quantified using the Nanodrop 2000 spectrophotometer (NanoDrop Technologies, Wilmington, DE, USA). 200ng RNA was used from each sample for gene expression profiling, performed with the digital multiplexed NanoString nCounter analysis system (NanoString Technologies, Seattle, WA, USA).

2.3.1 nSolver Analysis

Raw data was normalized against 6 housekeeping genes. Normalized data was then analysed and visualized using nSolver software (NanoString technologies). The log2 fold change or log2 RNA count number was calculated using normalized RNA count numbers. Statistical significance between cases and the control was determined using an unpaired student’s t-test with significance set at p≤0.05.

2.4 Mouse CCI Model

For this study, mice were donated by Dr. Anne Wheeler’s lab at the Peter Gilgan Research Centre. All CCI protocols were performed at the PGRC by members of Dr. Wheeler’s lab, and tissue was shared with our lab. The mice were kept under standard laboratory conditions with free access to food and water, and all experiments complied with the Animals for Research Act of Ontario and the Guidelines of Canadian Council on Animal Care.

8-week-old male C57BL/6 mice (Jackson Laboratories, Bar Harbor, ME) were subjected to a closed-skull Controlled Cortical Impact model. Briefly, the mice were anesthetized with

18 isoflurane and impacted with an Impact One Stereotaxic Impactor (Leica, Buffalo Grove, IL) with a 5mm tip over the parietal bone at a depth of 1.5mm and a dwell time of 100ms. During the impact, mice were stabilized using a stereotaxic frame as to prevent movement of the head. Both CCI and sham animals received preoperative injections of buprenorphine (0.05mg/kg), saline (0.5ml), and xylocaine (0.1ml) and post-operative injections of bupivacaine (0.1ml). Sham animals received all procedures without any actual impact.

Following the CCI procedure, post-mortem tissue from five mTBI mice and one sham was processed by the same procedures as described in humans. The mouse tissue then underwent immunohistochemistry for γH2AX (monoclonal mouse, 1:1000, Ser139, #05-636; Millipore) and Lamin B1 (monoclonal rabbit, Abcam, #133741). In addition, mRNA from the brain of mice was extracted from paraffin embedded blocks and used with the NanoString nCounter Inflammation Panel for mice. The protocol for this experiment was the same as with the human cohort, detailed above.

3. RESULTS

3.1 Cohort demographics and clinical presentation

Cases were all between the ages of 15 and 87, with a mean age of 57 years old. With the exception of two cases who experienced mTBI unrelated to sport, each individual was exposed to mTBI through their involvement with contact sports including football, hockey, rugby, and boxing. A majority of these individuals experienced chronic exposure to mTBI (length of exposure greater than 10 years). Those cases for which exact length of exposure was unavailable, it is estimated that they were exposed to chronic mTBI due to the nature of their athletic career.

In 35/38 (92.1%) of cases with a history of mTBI, the individual suffered from either (1) neurobehavioral and/or psychiatric symptoms (including depression, anxiety, suicide, erratic behavior, and alcoholism among others), or (2) cognitive dysfunction and/or dementia associated with a neurodegenerative disease. Two cases (5.26%) presented with motor dysfunction which was attributed to diagnosis of PD or ALS. The most common clinical characteristic of the individuals in this cohort was the presence of a mood disorder, comprising 42.1% of cases. Control cases with no history of head trauma did not present with neurobehavioral, psychiatric, or cognitive symptoms. (Table 1)

Table 1: Case demographics for donated brains with history of mTBI, including age, nature of exposure to mTBI, length of exposure to mTBI, and pre-mortem clinical presentation.

3.2 Neuropathological assessment

Each case underwent brain autopsy and a full neuropathological assessment according to NIA- AA criteria. In this cohort, 13 (34.2%) cases did not have any evidence of neuropathological changes and were not given a diagnosis, despite presenting with pre-mortem neurobehavioral symptoms including suicide. In 15 (40%) cases, substantial neuropathological changes were found resulting in diagnosis of a neurodegenerative disease. Included in these diagnoses were AD, PD, FTD, and ALS. 10 (26%) cases presented with focal, scarce perivascular p-tau lesions in the frontal cortex consistent with very early CTE (Figure 2).

Figure SEQ Figure \* ARABIC 2 Proportion of neuropathological changes found in 38 cases of individuals with history of mTBI. 15 (39.5%) cases were diagnosed with a neurodegenerative disease, including AD, PD, ALS, and FTLD. 13 (34.2%) cases did not present with any neuropathological changes. 10 (26.3%) cases were diagnosed with early stage CTE, characterized by scarce focal p-tau lesions in the depths of cortical sulci.

3.3 Immunohistochemistry

3.3.1 mTBI brains accumulate extensive DNA damage marked by γH2AX

In 28/38 (73.7%) brains with history of mTBI DNA damage was seen throughout the brain by immunohistochemistry with γH2AX. This reactivity was not seen in control cases with no mTBI history (Figure 3). The pattern and distribution of γH2AX staining was consistent in all of these cases, and was quantified and subsequently sorted according to a three-level scale representing the extent and distribution of DNA damage. Fourteen (50%) cases were considered stage 1, which presented with DNA damage throughout the ependymal lining only (Figure 4). Often, 100% of the cells in the ependymal lining were positive for γH2AX. Five (17.9%) cases were considered stage 2, which presented with DNA damage throughout the ependymal lining, and additionally in astrocytes in sub-ventricular and sub-pial areas, and surrounding cortical grey matter (Figure 5). Nine (32.1%) cases were considered stage 3, which presented with DNA damage in the ependymal lining, astrocytes in grey matter (peri-neuronal satellite cells), sub-pial region, and surrounding cortical tissue, and additionally in oligodendrocytes of the white matter (Figure 6). DNA damage was seen primarily in glial cells, particularly ependymal and subependymal cells as well as peri-neuronal astrocytes in the grey matter and oligodendrocytes in white matter. DNA damage was not seen in neurons. Control brains with no history of mTBI were not positive for γH2AX. The mean positive cell density for each cell type was calculated from three regions of interest from the ependymal lining, subependymal areas, surrounding cortical tissue, subpial areas, CA1-CA3 of the hippocampus, and surrounding white matter - revealing progressive increases in number of positive cells with each stage. Stage one cases had a mean positive cell density of 46% for ependymal cells, and no positive astrocytes or oligodendrocytes. Stage two cases had a mean positive cell density of 74% for ependymal cells, 12% for astrocytes, and no positive oligodendrocytes. Stage three cases had a mean positive cell density of 96% for ependymal cells, 51% for astrocytes, and 34% for oligodendrocytes. No γH2AX reactivity was seen in neurons (Figure 6).

Figure SEQ Figure \* ARABIC 3 Control brain showing no γH2AX in the hippocampus and surrounding regions at low power (A), the ventricle is marked with a red asterisk. At high power, no DNA damage is seen in the ependymal lining (green arrow) and subependymal cells (B), astrocytes (orange arrow) of the isocortex (C), oligodendrocytes (blue arrow) of the white matter (D), or neurons (yellow arrow) and glial cells in the hippocampus (e). Scale bar represents 2 mm in A, 50 um in B and D, and 100 um in C, and E.

Figure SEQ Figure \* ARABIC 4: Stage 1 staining in a case with mTBI history at low power (A) with the ventricle marked by a red asterisk. At high power, DNA damage is evident in the ependymal lining(green arrow) (B, C) but not in astrocytes (orange arrow) of the isocortex (D), oligodendrocytes (blue arrow) of the white matter (E), or neurons (yellow arrow) and glial cells in the hippocampus (F). Scale bar represents 2 mm in A, 50 um in B, D, and E, 20um in C, and 100um in F.

Figure SEQ Figure \* ARABIC 5 Figure 5: Stage 2 γH2AX staining in a case with mTBI history at low power (A) with the ventricle marked by a red asterisk. At high power, DNA damage is evident in the ependymal lining (green arrow) (C), astrocytes (orange arrows) preferentially in perivascular regions of the isocortex (C-E) subependymal region (F), and hippocampus (H). No DNA damage is seen in oligodendrocytes (blue arrow) of the white matter (G) or in neurons (yellow arrow) of the hippocampus (H). Scale bar represents 2 mm in A, 50 um in B, D, E, and F, and 100um in C, G, and H.

Figure SEQ Figure \* ARABIC 6 Stage 3 γH2AX staining in a case with mTBI history at low power (A) with the ventricle marked by a red asterisk. At high power, DNA damage is evident in the ependymal lining (green arrow) (B), astrocytes (orange arrow) of the isocortex (C) and subependymal region (D), oligodendrocytes (blue arrow) of the white matter (E), and glial cells throughout the hippocampus (F, G). No neurons (yellow) in the hippocampus are positive for γH2AX (G). Scale bar represents 2 mm in A, 100 um in B, 50um in C-E, and 200um in F and G.

3.3.2 Morphological changes consistent with senescence in mTBI brains.

Astrocytes in individuals with history of mTBI which were γH2AX positive showed significant morphological changes consistent with cellular senescence compared to controls (Figure 8). GFAP reactivity in serial sections of mTBI revealed that astrocytes with DNA damage were

significantly enlarged, presenting with swollen cytoplasm (Figure 8B and D) compared to healthy,

Figure SEQ Figure \* ARABIC 7 Immunohistochemistry for γH2AX revealed 28 (73.7%) cases had evidence of DNA damage in the hippocampus, isocortex, white matter, and ependymal lining. 14 cases were classified as stage 1 (damage in ependymal cells only), 5 cases stage 2 (damage in ependymal cells and astrocytes), and 9 cases stage 3 (damage in ependymal lining, astrocytes, and oligodendrocytes). Stage one cases had a mean positive cell density of 46% for ependymal cells, and no positive astrocytes or oligodendrocytes. Stage two cases had a mean positive cell density of 74% for ependymal cells, 12% for astrocytes, and no positive oligodendrocytes. Stage three cases had a mean positive cell density of 96% for ependymal cells, 51% for astrocytes, and 34% for oligodendrocytes. No γH2AX reactivity was seen in neurons. normal astrocytes (Figure 8C and E). Immunofluorescence with GFAP revealed substantial axonal beading of cellular processes in these astrocytes as well (Figure 8F).

mTBI brains also showed loss of two nuclear proteins whose loss are implicated in cellular senescence. First, the histone H3K27Me3 (Figure 9C and D) is lost in mTBI brains compared to controls (Figure 9 A and B). The distribution of H3K27Me3 loss was localized to areas of DNA damage (Figure 9D subpanel). Second, the nuclear membrane protein lamin B1 is lost in mTBI brains compared to controls (Figure 10).

Figure 8 Photomicrographs showing sub-pial positive immunostaining of glial cells with γH2AX (A). In adjacent section, GFAP immunostaining shows abnormal ballooning of the cell body of astrocytes in the sub-pial area (B and D) when compared to a comparable section from healthy control (C and E), shown with a red arrow. The circles in D and E show comparable nuclear sizes in case and control but swollen cell body of astrocyte is evident in case. GFAP immunofluorescence (F) reveals beading of astrocytic processes in individuals with mTBI history. Scale bar represents 100 mm in A and B, 40 mm in C, 10 mm in D and E and 17 mm in F.

Figure SEQ Figure \* ARABIC 9: H3K27Me3 is normally expressed in its trimethylated form in astrocytes (A) and oligodendrocytes (B) of a healthy control brain. In contrast, in a brain with mTBI history H3K27Me3 is lost in astrocytes (C) and ependymal cells (D, larger image) in the same cells where DNA damage is found (D, small inset).

Figure 10: Lamin B1 nuclear membrane expression is lost in a case with mTBI history (B) compared to its normal expression in the isocortex of a healthy control (A).

3.4 Nanostring

3.4.1 DDR signalling

In brains with mTBI history six genes (NRF2 (p=0.04), ATM (p=0.01), FANCD2 (p=0.01), CHEK1 (p=0.04), CHEK2 (p=0.05), and TP73 (p=0.02)) involved in the DDR to DSBs were upregulated significantly when compared to controls (Figure 11). Respectively, these genes function as an antioxidant (134), a serine/threonine kinase which phosphorylates H2AX in response to DSBs (135), a protein ubiquitinated in response to DNA damage to localize with BRCA1 (136), two checkpoint kinases activated in response to DNA damage to arrest the cell cycle (137), and a tumour suppressor gene which is involved in the cellular response to stress (138). Six additional genes, also involved in the DDR and known to be upregulated following DNA damage, were upregulated in mTBI brains although these were not statistically significant. These include MCPH1, GADD45A, GADD45B, and GADD45G, RAD1, PPP1R15A (Figure 11). mTBI brains also displayed significant decreased expression of two genes which are known to be negatively regulated in the DDR (Figure 11). These include MDM2 (p=0.04) which is degraded upon DNA damage (139), RNF8 (p=0.0009) whose inhibition results in sustained CHK2 activation and an enhanced stress response (140).

Interestingly, mTBI brains showed decreased expression of genes involved in the DDR specifically to single-stranded DNA breaks (141) and UV-damage (142), although not all of these were statistically significant. These included DDB1 (p=0.04), DDB2 (p=0.24), ATRIP (p=0.01), and ATR (p=0.02) (Figure 11). Additionally two genes encoding checkpoint proteins, RAD17 (p=0.0003) and HUS1 (p=0.002) were significantly downregulated in mTBI brains (Figure 11). Depletion (143) and inactivation (144) of these genes, respectively, has been linked to genomic instability in response to cellular stress, including DNA damage.

Figure 11: Histogram showing the mean fold change (log2) of genes involved in the DDR between cases compared to a control. Genes which are down- regulated are involved in genomic stability in response to stress (RAD17, HUS1), proteins which are degraded upon DNA damage (MDM2), proteins which respond to UV damage and single-stranded breaks (DDB1, DDB2, ATRIP, ATR), and genes whose inhibition lead to DDR-mediated cell-cycle arrest and repair (RNF8). Genes which are up-regulated are all involved in DDR signalling in response to DNA damage. Statistical significance was determined using a student t-test with significance at p≤0.05. A log2 fold change of 1 corresponds to a fold change of 2, a log2 fold change of 2 corresponds to a fold change of 4, a log2 fold change of 3 corresponds to a fold change of 8.

3.4.2 DNA repair genes

Of the 88 genes involved in DNA repair processes, 53 showed significant down-regulation in gene expression in mTBI brains relative to the control (Figure 12). Some particularly important DNA repair genes which showed down-regulation in cases compared to controls are BRCA1, LIG4, OGG1, POLD3, RAD51B, MSH4, OGG1, and PARP3 (Figure 13).

Figure 12: Expression of genes encoding DNA repair proteins, which showed a statistically significant change between the control and cases (p≤0.05, student’s t-test), expressed as log2 RNA count number. DNA repair genes showed a general trend towards reduced expression in cases compared to the control. A full list of DNA repair genes can be found in appendix 1.Each square represents one gene.

Figure SEQ Figure \* ARABIC 13: Down-regulation of various DNA repair genes in a mTBI brain (red) compared to a control (blue) expressed as normalized RNA count number. BRCA1 is a master regulator of downstream DNA repair genes, including OGG1, LIG4, and RAD51B, as well as a mediator of p53-mediated cellular senescence.

3.4.3 Regulators of cellular senescence

Six genes with functions in protecting gene integrity and delaying senescence were significantly down-regulated in mTBI brains compared to controls (Figure 14). These include MIF (p=0.003), CCNH (p=0.004), TERF2 (p=0.001), MNAT1 (p=0.04), and GSK3B (p=0.0003). Defects in these genes have been associated with senescence (145), dysregulation of cell-cycle kinases (146), loss of telomere integrity (147), loss of CDK kinase activation (148), and induction of senescence (149) respectively. ID1, RELA, NFKB1, and CDK7 were also down-regulated, consistent with reports on senescence, however these were not statistically significant.

Two genes associated with senescence were significantly up-regulated in mTBI brains (Figure 14). TERT, which is up-regulated in response to shortened telomeres (150), was significantly over-expressed (p=0.04) in mTBI brains. Furthermore IFNG, a soluble cytokine which induces senescence through p53 signaling (151), was significantly over-expressed (p=0.04) in mTBI brains. Four other genes which are positively associated with senescence were upregulated, TP53, PARP3, ETS1, and SERPINE1, although these were not statistically significant.

Figure 14 Down-regulation of genes involved in preventing senescence (MIF**, CCNH**, TERF2***, MNAT1*, GSK3B***, ID1, RELA, MTOR***, NFKB1, and CDK7) and up-regulation of genes which act to drive cellular senescence (TP53, PARP3, ETS1, SERPINE1, TERT*, and IFNG*) in cases (mean) versus control, expressed as log2 RNA count number. Statistical significance was determined using an unpaired student’s t-test with significance denoted at p≤0.05. Each square represents one gene.

3.4.4 SASP factors

Compared to the control, brains with history of head trauma showed significant increased expression of several pro-inflammatory chemokines, cytokines, interleukins, and receptors (Figure 15). These include the following: CCL1 (p=0.04), CCL11 (p=0.02), CCL13 (p=0.02), CCL16 (p=0.03), CCL20 (p=0.04), CCL25 (p=0.03), CCL26 (p=0.01), CCL3 (p=0.03), CCL4 (p=0.0001), CCL8 (p=0.0007), CXCL1 (p=0.005), CXCL11 (p=0.02), CXCL5 (p=0.02), CXCL6 (p=0.03), CXCL8 (p=0.02), CXCR2 (p=0.02), IL12B (p=0.03), IL13 (p=0.02), IL15 (p=0.01), IL1A (0.02), IL1B (p=0.01), IL2 (p=0.03), IL4 (0.03), IL6 (0.04), IL7 (0.02), and IL6R (p=0.0004). Additionally, mTBI brains showed significantly increased expression of two other pro-inflammatory genes, NFATC2 (p=0.007), and NOX4 (0.04). These genes encode a transcription factor which regulates the immune response and an NADPH oxidase which produces ROS and contributes to genomic instability and DNA damage, respectively (152, 153)

One chemokine which has been associated with cognitive decline as seen in models of AD, CXCL12, was significantly down-regulated (p=0.0006) in concussed brains.

Figure 15 Up-regulation of pro-inflammatory SASP factors in cases (mean) compared to a control, expressed as log2 RNA count number. This boxplot includes the following genes: CCL1*, CCL11*, CCL13*, CCL16*, CCL2, CCL20*, CCL25*, CCL26*, CCL3*, CCL4***, CCL8***, CXCL1**, CXCL11*, CXCL12***, CXCL2, CXCL3, CXCL5*, CXCL6*, CXCL8*, CXCR2*, IL11, IL12A, IL12B*, IL13*, IL15*, IL1A*, IL1B*, IL2*, IL4*, IL6*, IL7*, Il6R, NFATC1***, NFATC2**, and NOX4*. Statistical significance was determined using an unpaired student’s t-test with significance denoted at p≤0.05. Each square represents one gene.

3.5 Clinicopathological correlation

A case was considered “senescent” if they showed evidence of DNA damage with immunohistochemistry for γH2AX, and evidence of cellular senescence through changes in gene expression. Using this criteria, 28 (73.7%) cases were considered “senescent”. Within this group, 26 (93%) were symptomatic, including mood disorders (52%) and cognitive deficits/dementia (48%). In comparison, in the 10 brains not considered “senescent, 7 (70%) were symptomatic, including mood disorders (57%) and cognitive deficits/dementia (43%). (Table 2).

Table 2: Proportion of senescent (defined here by the simultaneous presence of DNA damage and gene expression reflective of cellular senescence) and non-senescent cases with symptoms pre-mortem, further classified into either mood or cognitive/dementia symptoms. Mood symptoms include anxiety, depression, and irritability, while cognitive/dementia symptoms include memory problems, dementia, or symptoms of a neurodegenerative disease.

3.6 DNA damage and cellular senescence are evident in a CCI mouse model

In the mice subjected to a 1-strike CCI protocol, immunohistochemistry with γH2AX revealed extensive DNA damage throughout the hippocampus (Figure 16A) and isocortex (Figure 16B), with no reactivity seen in sham animals. Furthermore, CCI mice showed loss of lamin B1 nuclear epression (Figure 16C) with no loss seen in sham mice (Figure 16D).

CCI mice also showed evidence of the DDR and cellular senescence through gene expression analysis with NanoString. The DDR gene ATM was up-regulated in CCI mice compared to sham controls with extreme significance (p≤0.0001) (Figure 17). Genes implicated in SASP, including pro-inflammatory factors, cellular senescence, or aging were also significantly up-regulated in CCI mice compared to sham controls (p≤0.0001) (Figure 17) and included the following: Serping1 (a regulator of the complement cascade and inflammation (143)), Hmgb1 (a mediator of senescent phenotype dependent on p53 (144)), Hras (a biomarker of senescence involved in cell-cycle checkpoints (145)), Nfatc2 (regulates DNA damage-induced apoptosis suppression (146)), Nfkb1 (an inflammation-inducing transcription factor (147)), Plau and Plaur (plasminogen activator and receptor; implicated in aging (148)), Trp53 (potent inducer of senescence (149)), and TNFRSF14 (pro- inflammatory pathway implicated in senescence (150)). These mice also showed significant upregulation (p≤0.0001) of pro-inflammatory

cytokines, chemokines, and interleukins involved in the SASP (Figure

18).

Figure SEQ Figure \* ARABIC 16: Mice subjected to a 1-strike CCI protocol accumulated extensive DNA damage, marked by γH2AX, in the hippocampus (A) and isocortex (B) not seen in sham animals. These mice also showed significant loss of nuclear membrane protein lamin B1 (C) compared to sham animals (D) 44

Figure SEQ Figure \* ARABIC 18: Upregulation of genes involved in the DDR (ATM) and the SASP (Serping1, Hmgb1, Hras, Nfatc2, Nfkb1, Plau, Plaur, Tnfrsf14, Trp53). All genes were extremely statistically significant (p≤0.0001) by means of a student’s t-test.

Figure SEQ Figure \* ARABIC 17: Up-regulation of pro-inflammatory chemokines, cytokines, and interleurkins in CCI mice (light grey) compared to sham mice (dark grey). All were statistically significant (p≤0.0001) with a student’s t-test.

4. DISCUSSION

mTBI is a prominent public health concern, causing debilitating symptoms in millions of individuals each year. Despite this, the pathophysiological mechanism of mTBI is not well understood and there is no consensus on what causes the pathology, symptoms, and propensity towards neurodegenerative disease in these individuals. In this study I hypothesize that mTBI causes DNA damage and the subsequent acquisition of cellular senescence. In order to test this hypothesis, the aims of this study were to: 1. Assess the extent and distribution of DNA damage in post-mortem human brains with extensive history of mTBI, 2. Assess evidence of cellular senescence and SASP in post-mortem human brains with extensive history of mTBI, and 3. Validate human findings in a CCI model of mTBI in mice.

4.1 Evidence of DNA damage in human concussed brains

In a cohort of donated brains with mTBI history, I have shown extensive DNA damage using immunohistochemistry with γH2AX, a marker of DSBs. Accumulation of this damage occurred in a consistent pattern of distribution in concussed brains. γH2AX was present throughout the ependymal lining in every case which was positive for γH2AX. This distribution progressed to astrocytes of the surrounding isocortex, subependymal region, and grey matter in some cases, and to oligodendrocytes of the surrounding white matter in some cases. It is important to note that control brains with no history of mTBI were not reactive for γH2AX, and therefore did not have evidence of DNA damage. This suggests that DNA damage emerged as a result of mTBI history, although causality may not be established here.

Although not every mTBI case was positive for γH2AX, this does not necessarily mean that they were without DNA damage. It is possible that these individuals accumulated other forms of DNA damage, such as SSBs, single-base oxidation, or deamination. In these cases, γH2AX would not pick up the damage as it specifically marks DSBs. It is also possible that some chronic cases of mTBI no longer possess physiological H2AX on their DNA. It has been shown that exposure to chronic oxidative stress or a deficient antioxidant response can lead to the degradation of H2AX

46 protein by the proteasome (163). In this circumstance, the individual would not have any H2AX available to be phosphorylated by ATM following a DSB. This idea is especially relevant in chronic cases of mTBI in which the individual played a long professional sports career and experienced immeasurable numbers of concussions throughout their career. With this in mind, the immunohistochemistry assay for γH2AX may even underestimate the number of DSBs in this cohort, as many would be considered chronic cases (Table 1). Interestingly, a deficiency in H2AX has been associated with chronic neurobehavioural symptoms and an impaired response to ROS (164). If the degradation of H2AX does indeed occur in individuals with chronic exposure to concussion, this may therefore explain the emergence of severe symptoms in individuals despite having no γH2AX reactivity and scarce pathology. This study is therefore limited in that it evaluates only DSBs using immunohistochemistry. This is due to the use of formalin fixed and paraffin embedded post-mortem brain tissue, as this tissue is notoriously difficult to assay DNA damage with immunohistochemistry. Despite this limitation and the potential underestimation of DNA damage in this cohort, immunohistochemistry for γH2AX provided evidence for a significant amount of DNA damage in most (74%) of the brains of individuals with a history of mTBI.

To further support the notion that DNA damage is present in the brains of individuals with mTBI history, I used NanoString nSolver to analyse the gene expression of genes involved in DDR signalling. These genes encode proteins which are expressed, activated, and recruited to lesions in response to DNA damage. Compared to a healthy control, brains with a history of mTBI showed significant increased expression of DDR signalling genes including ATM, which phosphorylates H2AX to γH2AX in response to DSBs (96), NRF2, an antioxidant transcription factor which is activated in response to oxidative stress and inflammation (134), CHK1 and CHK 2, which arrest the cell-cycle to allow for proper DNA repair (165), and p73, a master regulator of the cell’s response to DNA damage and stress an inducer of cellular senescence (138). Furthermore, brains with a history of mTBI showed significantly reduced expression of some genes which are known to be degraded or inactivated in association with DNA damage, such as MDM2 (39), RNF8 (140), RAD17 (143), and HUS1 (144), as well as genes involved in the response to SSBs and UV damage, such as DDB1 (142), DDB2 (142), ATRIP (141), and ATR (141). Increased expression of genes involved in UV DNA damage is not expected in this study, as we are analysing gene expression in the brain where UV light would not be a cause of DNA damage. However, it is

47 unclear why pathways involved in the response to SSBs would be decreased in this cohort. It is possible that these individuals do not possess any SSBs and thus would not need to activate a response to such a break. In addition, as it is known that DSBs are the most lethal form of damage for the induction of cellular senescence (111), it is possible that the response to DSBs simply takes more precedence over other forms of DNA damage. This is unclear from this observational data, and thus this remains a speculation. In general, however, the changes in gene expression of genes involved in the DDR in brains with a history of mTBI reflect activation of the DDR and, by extension, the presence of DNA damage in this cohort, reflect activation of the DDR and, by extension, the presence of DNA damage in this cohort.

4.2 Impaired DNA repair capacity in human concussed brains

Genes which encode DNA repair proteins showed a general trend of decreased expression in mTBI brains compared to a control. In particular BRCA1, the DNA repair gene known to transcriptionally activate other downstream DNA repair genes such as OGG1, LIG4, and RAD51B (166), was down-regulated. This result is somewhat counterintuitive, as one might predict that in the wake of DNA damage the cell would up-regulate expression of DNA repair genes as to efficiently repair the lesion. However, it has been shown that transcriptional repression of DNA repair genes is a hallmark of cellular senescence and that knocking down specific DNA repair genes, including BRCA1, is sufficient to induce markers of premature senescence in vivo (167). BRCA1 is somewhat of a master regulator, in which it acts to: 1. repair DNA lesions (168), 2. transcriptionally activate other downstream DNA repair proteins(166), and 3. regulate p53 gene expression such that it activates cellular senescence pathways(169). In turn, activation of the p53 senescence pathway through DNA damage- induced cellular senescence causes the repression of DNA repair genes (170). In this way, the cell promotes the accumulation of further DNA damage and therefore maintain the senescent phenotype.

The mechanism by which DNA repair genes are down-regulated in association with cellular senescence may be due to chronically increased levels of oxidative stress. In a study on hyperglycemia, for example, it was found that exposure to high levels of glucose resulted in brains increased levels of ROS in hepatocytes (171). Initially, this led to increased expression of DNA

48 repair genes, however long-term exposure to high levels of glucose eventually led to the reduced expression of DNA repair genes and subsequent accumulation of damage (171). In addition, decreased levels of DNA repair genes have been reported in AD brains. Indeed, a reduction in BRCA1 expression has been reported in the brains of human AD patients as well as an amyloid mouse model of AD (172). This same study reported that accumulation of Aβ drives the depletion of BRCA1, and suggests that depletion of BRCA1 may contribute to the cognitive decline seen in AD. In fact, reduced expression of DNA repair genes due to increased levels of oxidative stress has been implicated with several human diseases, including AD (173), diabetes (174), obesity (175), and glaucoma (176).

Using immunohistochemistry for GFAP, H3K27Me3 and Lamin B1, this study showed morphological changes in human concussed brains which are consistent with reports of cellular senescence. Astrocytes in the brains of individuals with a history of mTBI presented with swollen, enlarged cell bodies and beading of cellular processes. These morphological changes may reflect cellular dysfunction and the acquisition of SASP in this cell. Indeed, senescent astrocytes have a swollen soma and enlarged cell processes, reflective of increased transcription and secretion of pro-inflammatory SASP factors (119). In addition to astrocytic changes, mTBI brains had decreased expression of the epigenetically modified histone H3K27Me3. Normally, this modified histone is expressed on chromatin and acts as a transcriptional repressor, downregulating nearby genes through the formation of heterochromatin (126). H3K27Me3 is associated with the repair of DBSs through transcriptional regulation of the p21 pathway (177), and loss of H3K27Me3 in the context of persistent DNA damage has been reported to induce cellular senescence through the activation of p16 and p21 pathways (121). Loss of H3K27Me3 expression on chromatin is therefore a marker of cellular senescence. Lastly, mTBI brains showed reduced expression of Lamin B1, a nuclear envelope protein which acts to tether chromatin to the inner nuclear membrane and silence gene expression (122). Loss of lamin B1 expression on the nuclear membrane is considered a biomarker of cellular senescence (120), and this loss results in chromatin rearrangement and significant changes in gene expression (124). Furthermore, studies on laminopathies have suggested that misregulation of lamins may underlie the progression of several tauopathies and neurodegenerative diseases, such as AD (125).

Indeed, the relaxation of heterochromatin due to lamin dysfunction has been suggested as an underlying mechanism of neuronal death in AD (125).

NanoString gene expression analysis in brains with a history of mTBI revealed upregulation of several genes which are implicated in driving cellular senescence. These included p53, PARP3, ETS1, SERPINE1, TERT, and IFNG. It is known that IFNG, a soluble pro-inflammatory cytokine, induces senescence through the activation of p53 (151). Together, increased expression of these genes suggests activation of the p53 pathway. Further, PARP3 and TERT are both activated in response to DNA damage (178, 179) resulting in dysregulation of telomeres and contribute to the activation of downstream senescence pathways (180). Lastly SERPINE1 and ETS1, a plasminogen activating inhibitor and proto-oncogene transcription factor respectively, have both been reported to induce cellular senescence through activation of the p53 pathway (181, 182). Together, up-regulation of these genes indicates that mTBI brains have an activated p53 senescence pathway, indicative of stress-induced early onset senescence.

Consistent with these changes, mTBI brains also showed down-regulation of genes which have been associated with preventing cellular senescence. Indeed, individuals with a history of mTBI showed significantly decreased expression of TERF2, MIF, and GSK3B. Consistent with our finding of up-regulation of TERT and PARP3, down-regulation of TERF2 is associated with a loss of telomere integrity associated with senescence (147). Macrophage migration inhibitory factor, or MIF, has been associated with delaying premature cellular senescence(145), and so decreased expression of this gene suggests loss of this protective function in this cohort. Interestingly, inhibiting GSK3B has been shown to induce senescence through enhanced glycogenesis in vivo (149). Taken together, the up-regulation of genes reported to drive cellular senescence and the simultaneous decreased expression of genes reported to protect against cellular senescence suggests the acquisition of cellular senescence in mTBI brains.

Further supporting the gene expression changes consistent with cellular senescence, brains with history of mTBI showed significant up-regulation of pro-inflammatory SASP factors. These genes encode interleukins, chemokines, and cytokines which are consistently reported to be secreted by SASP cells (110-114). Pro-inflammatory SASP factors were significantly up-regulated in this cohort, providing evidence for the acquisition of SASP in brains with a history of mTBI.

Interestingly, mTBI brains showed significant downregulation of chemokine CXCL12. It is unclear why expression of CXCL12 is decreased in this cohort, however it has been reported that reduced levels of CXCL12 were found in a mouse model of AD (154). Furthermore, to test if CXCL12 reduction was associated with cognitive functioning the authors of this paper antagonized CXCL12 receptors in wild-type mice, and reported significant impairment in learning and memory (154). It is therefore possible that CXCL12 plays a role in cognitive functioning, and its downregulation in this cohort is reflective of this function.

4.4 Clinicopathological correlation in human concussed brains

It is difficult to make a causal association between symptoms reported after mTBI and subsequent post-mortem pathology. In other words, symptoms of mTBI lack clinicopathological correlation, as cases often present with microscopic foci of perivascular tau in the cortex yet present with severe symptoms (75). It is extremely unlikely that a focal NFT in the cortex causes such deficits, however cellular senescence may explain this phenomenon. SASP factors have paracrine effects on all cell types in the brain (183), including neurons and their support cells. For example, senescent microglia create a toxic pro-inflammatory environment (129), senescent oligodendrocytes may disrupt myelination (128), and senescent endothelial cells may disrupt the integrity of the blood-brain barrier (130). These effects put overall brain health at risk, and may lead to the widespread symptoms seen in mTBI. Microglial senescence in specific results in increased microglia-mediated neuroinflammation, and has been suggested as a driving force for accumulation of β-amyloid pathology (132), α-synuclein pathology (184), and cognitive decline associated with tau pathology in AD(131).

Nearly every case in this study suffered from neurobehavioural or cognitive symptoms and the most commonly cited symptom in this cohort was the presence of a mood disorder, predominantly depression and/or anxiety. Cases which were considered “senescent”, by the presence of DNA damage and gene expression changes, had a larger proportion of symptomatic individuals than cases not considered senescent. However, these two groups had similar proportions of mood and cognitive symptoms within those symptomatic cases. Although I hypothesize that cellular senescence is the driver of acute and chronic symptoms after mTBI, a 51 clinicopathological correlation cannot be concluded from this cohort for several reasons. First, the number of cases in his cohort is too small to reach a statistically significant correlation. This is especially important, as the prevalence of mood disorders in the general population is not negligible. In fact, according to the National Alliance on Mental Illness, 1 in 5 adults experience a mental illness, approximately 7% of adults will have a severe depressive episode in a given year, and approximately 18% of adults suffer from some sort of anxiety disorder (185). These numbers may not represent the true prevalence of mood disorders, as many individuals suffer in silence and do not seek medical attention or a formal diagnosis (186). It is therefore difficult to discern the effects of mTBI from the normal presentation of a mood disorder in the general population.

Another barrier in establishing clinicopathological correlation is that, like many other observational post-mortem studies, this project relies on retrospective data for clinical information. The details of individuals’ symptoms were collected by structured interviews with next of kin, as well as guidance from any available medical records. Quantifying these assessments is not possible as there is no baseline prior to mTBI to compare symptoms to. This is in contrast to, for example, studies in which an individual in the emergency room for a TBI are asked to fill in a questionnaire rating the presence of symptoms before and after injury. Observational post-mortem studies therefore do not take into account individual differences in mood and behavior prior to obtaining mTBI. It is therefore not possible to distinguish from retrospective interviews whether a symptom emerged due to mTBI. Another important factor in assessing these retrospective interviews is that families of individuals who donate their brains for concussion research are often seeking some sort of explanation for their mood disorder or erratic behavior. This motive may subconsciously influence the answers to interview questions, potentially exaggerating or minimizing the presence of certain symptoms in order to favour a diagnosis. It is also important to note that in brain banks such as these, cases are usually donated because they presented with symptoms during life and are suspected of having CTE or another brain disease. Thus, the proportion of individuals who are symptomatic and have pathology may be higher than the general population of sports players.

With these points in mind, a correlation between senescence and clinical presentation may not be made from this study. That being said, the accumulation of senescent cells has been associated

52 with cognitive decline(116), depression(187), and age-related disease(115), so it is not unlikely that this correlation exists. The question of whether senescence drives the symptoms associated with mTBI must therefore be addressed in either experimental animal studies of mTBI or longitudinal prospective cohort studies in humans who experience mTBI.

4.5 Evidence of DNA damage and cellular senescence in a CCI mouse model

The closed-skull CCI model was used to induce mTBI in wild-type mice. Histological examination revealed DNA damage in the form of DSBs as shown by immunohistochemistry with γH2AX. Damage was evident throughout the hippocampus and isocortex, and affected primarily glial cells. Furthermore, in the same region as DNA damage was found loss of Lamin B1, a biomarker of cellular senescence. The findings of DNA damage and cellular senescence, as shown in the human concussed cohort, are therefore validated in an animal model of mTBI. This is paramount in establishing a link between mTBI and senescence, as it eliminates possible confounding variables that are known to impact DNA damage and repair, caused by other insults or factors such as substance abuse that cannot be controlled for in a heterogeneous human study population. The use of this mouse model therefore allows us to establish a causal relationship between mTBI and cellular senescence.

Furthermore, using a NanoString panel of inflammation designed for the mouse, this experimental model showed increased expression of genes involved in the DNA damage response and the driving of cellular senescence. This includes important genes such as ATM, SERPING1, HMGB1, HRAS, NFATC2, NFKB1, PLAU, PLAUR, TNFRSF14, and p53. Briefly, these genes are involved in mediating inflammation (SERPING1 (155), NFKB1 (159), PLAU (160), PLAUR (160)), regulating senescence pathways (HMGB1 (156), HRAS (157), NFATC2 (158), p53 (161)), and activating DNA repair proteins through phosphorylation (ATM (135)). Consistent with these changes in gene expression, CCI mice showed extremely significant upregulation of pro-inflammatory SASP factors, including chemokines, cytokines, and interleukins. These changes in gene expression indicate the acquisition of cellular senescence due to mTBI in mice. Overall, these results indicate that mTBI causes the accumulation of DNA damage and cellular senescence in mice.

4.6 Cellular senescence as the pathophysiological mechanism of mTBI-induced brain dysfunction

This project is proposing DNA damage-induced cellular senescence as the pathophysiological mechanism by which mTBI causes acute and chronic effects, such as cognitive decline, a propensity towards neurodegenerative disease, and neurobehavioural changes (Figure 19). Following mTBI several stresses occur, including oxidative stress (77) which may lead to significant DNA damage(84). In this study, we have shown that DNA damage is present in the brains of individuals with a history of mTBI as well as in mouse brains following a CCI protocol. The presence of DNA damage initiates the activation of the DDR, beginning with the serine/threonine kinase, ATM (188). Following DNA damage, ATM is activated via autophosphorylation (189) and phosphorylates downstream substrates such as H2AX (into its activated form γH2AX) (190) and protein kinase Chk2 (191). γH2AX is critical for the recruitment of several DNA repair proteins (in particular it forms a complex with DSB repair proteins RAD50, MRE11, and NBS1 known as the MRN complex (192)) and chromatin remodeling complexes (193), such that the DSB can be properly repaired. The MRN complex feeds back to activate ATM, creating a feed-forward loop allowing for the expansion of activated γH2AX over large regions of chromatin as to optimize repair of DSBs (194). The activation of kinase Chk2 by ATM allows for the direct phosphorylation of the critical senescence regulator p53 on serine 20, resulting in its activation and stabilization (195). Activation of p53, a transcription factor, induces cell-cycle arrest (196) and SASP (197) which inevitably leads to ageing and age-related diseases such as neurodegenerative disease through cellular dysfunction caused by senescence (198). Another function of ATM is the phosphorylation and subsequent activation of BRCA1 (199), a DNA repair protein which also regulates the transcription of downstream repair proteins OGG1, ERCC3, and LIG4 among others (166). Following DNA damage, BRCA1 and its downstream effectors are normally activated with the intention of repairing DNA lesions (166). However when p53 is constituently active, as is the case when DNA damage is persistent and leads to activation of cellular senescence pathways described above, BRCA1 is transcriptionally repressed by p53 (marked in red) (170). Thus, activation of senescence pathways decreases the cell’s ability to repair DNA, resulting in further accumulation of damage and a positive feedback loop in which senescence is maintained (200).

Figure SEQ Figure \ * ARABIC 19: Overview of proposed pathway of DNA damage-induced cellular senescence in the context of mTBI. TBI causes oxidative stress and, subsequently, DNA damage. In response to DNA damage, ATM is activated via autophosphorylation and goes on to activate H2AX into its phosphorylated form γH2AX. Formation of γH2AX leads to to recruitment of the MRN complex, composed of repair proteins RAD50, NBS1, and MRE11. The MRN complexThrough feeds this backproposed to further pathophysiological activate ATM, leading mechanism, to a cascade senescent of γH2AX cells formation can accumulate across a in the brain broad chromatin domain. ATM activates Chk2 kinase, which phosphorylates p53 into its active form for the induction of senescence pathwaysas a andresult cell of-cycle mTBI. arrest. It is Following known thatDNA thedamage, accumulation ATM activates of senescent BRCA1 andcells downstream plays a role in ageing repair proteins for DNA repair - however when p53 is activated due to persistent DNA damage and activation of cellular senescence (183),pathways, neurodegenerative BRCA1 transcription pathology is repressed (131), by cognitive p53, leading decline to an (13 inability1), and to depressionrepair DNA and(187). Cellular further accumulationsenescence of DNA damage may thustherefore maintaining be the the key senescent to understanding phenotype. the Together, complex this pathology leads to theand broad range of induction of SASP, and cellular dysfunction which is associated with ageing and age-related disease. symptoms attributed to mTBI (described in chapter 1) through dysfunction of various glial cells as described above. In this study we have shown increased expression of γH2AX through immunohistochemistry, and increased expression of ATM, CHK2, and p53 through gene expression analysis in a cohort of human brains with a history of mTBI. Furthermore, we have observed a reduction in expression of BRCA1 and its downstream targets in this cohort. Thus, we propose DNA damage-induced cellular senescence as the pathophysiological mechanism leading to symptoms and a propensity towards neurodegenerative disease in individuals who experience mTBI.

4.7 Limitations

There were several limitations and barriers in this study. First, the human brain bank was composed of post-mortem formalin-fixed tissue. As such, many useful techniques used for assessing biomarkers of DNA damage and cellular senescence were unsuitable. For example, staining for beta-galactosidase is the most commonly used and accepted biomarker of senescence (117), yet it cannot be detected using immunohistochemistry in fixed tissue. Thus, we are relying on indirect evidence of cellular senescence in this study - namely, changes in gene expression consistent with activation of senescence pathways. Furthermore, because of the use of fixed tissue we are unable to assess some forms of DNA damage. This includes 8-OHdG, a biomarker detectable with high-performance liquid chromatography, immunohistochemistry, and electrochemical detection among other quantitative methods (201). 8-OHdG is a biomarker of single-based oxidative damage, and indicates the presence of oxidative stress (202). However, immunohistochemistry with 8-OHdG is difficult in fixed tissue, and was unsuccessful in this cohort. Despite this limitation, this study shows extensive DNA damage and evidence of DNA damage signalling in human brains with a history of mTBI.

Another uncontrollable limitation of this study is the inclusion of only males in the human cohort. While concussion occurs frequently in both male and female populations (203), cohorts of donated brains with a history of mTBI tend to be mostly male (204), as is the case with this cohort. Interestingly, men and women experience concussion differently with women reporting on average longer recovery time and a greater number of symptoms (205). It is unclear why this discrepancy occurs, and as such having a sex-balanced cohort would be invaluable. With that being said, the use of a CCI model in mice in the future will allow for the inclusion of sex-balanced groups and the opportunity to study differences between the male and female experience of mTBI.

5. FUTURE DIRECTIONS

This study has shown an association between mTBI and markers of DNA damage and cellular senescence in human brains. In addition, this study validated these human findings in a CCI mouse model of mTBI indicating that mTBI causes DNA damage-induced senescence. In order to further characterize the underlying molecular pathways driving acute and chronic symptoms and pathology following mTBI, experimental animal models must be further utilized. Therefore, the first future direction of this study is to fully characterize cellular senescence pathways in a CCI mouse model of mTBI. In this model I would induce mTBI and characterize behavioural and cognitive phenotypes following injury through the use of a battery of tasks for testing anxiety, depression, and memory in mice. This battery would include the sucrose preference task for quantifying “sickness behaviour”, defined as decreased activity and increased idleness and grooming (206), open field and elevated plus maze tasks for depression (207), and forced swim and tail suspension tasks for testing anxiety (208). Following these measures, the mice would be sacrificed and undergo neuropathological assessment, examination of markers of DNA damage (γH2AX, 8-OHdG), and markers of senescence (p16INK4A, β-galactosidase, lamin B1, H3K27Me3), as well as gene expression and proteomic analysis of DNA damage signalling pathways, DNA repair pathways, and SASP. This series of experiments would allow the use of techniques not suitable for the fixed tissue used in our human studies, such as 8-OHdG, p16INK4A, β-galactosidase, and proteomics, and would give an in-depth analysis of senescence after mTBI. Most importantly, this study would allow us to make clinicopathological correlations between mTBI symptoms and cellular senescence not possible in a human retrospective cohort study.

Once cellular senescence is fully characterized in the context of mTBI, it may be targeted for therapeutic intervention. There are several different senolytic interventions available, which function to selectively eliminate senescent cells. First, we could induce a CCI in the p16-3MR transgenic mouse model. This mouse uses the p16INK4A promoter, a marker of senescent cells, to drive the expression of a modified herpes simplex virus thymidine kinase (209). This kinase is able to convert the ganciclovir into a DNA chain terminator, resulting in the apoptosis of senescent cells (210). In other words, giving these mice ganciclovir allows for the selective depletion of

57 approximately 70-80% of senescent cells (209). Following a CCI in these mice, we can then test if ganciclovir administration rescues the mTBI phenotype, resulting in reduced pathology and neurological and behavioural deficits, using the same readout measures as described above. If senolytic intervention rescues phenotype following mTBI, this would represent a novel therapeutic intervention for clinical trial. As a possible alternative to the p16INK4A mouse model, we could use the CNS bioavailable senolytic agent ABT623 to induce apoptosis in senescent cells (211)

Lastly, one of the major gaps in knowledge in the understanding of mTBI is the role of sex in mTBI outcomes. It is known that following a concussion females tend to experience more symptoms and for a longer period of time (205). Indeed, women generally take significantly longer to return to normal life following mTBI (212). It is unclear why this discrepancy occurs, but the use of sex-balanced groups in mouse models of mTBI allows for further research into this dimorphism. Research has shown that estrogen and estrogen metabolites can cause DNA DSBs, which are specifically repaired by BRCA1 (213). In this study we have shown that BRCA1 expression is reduced following mTBI, and that BRCA1 depletion is a common characteristic of many human diseases (214). Thus, it is possible that BRCA1 depletion following mTBI makes cells more susceptible to DNA damage induced by estrogen. By extension, it is therefore possible that women are exposed to more DNA damage than men due to the presence of estrogen. Interestingly, ovariectomy in rats has been shown to protect against DNA damage in the hippocampus and improve cognitive outcomes (215). It is therefore very possible that DNA damage caused by estrogen following mTBI causes females to be more susceptible to symptoms of mTBI such as short-term memory loss and attention deficits. A future direction of this study may therefore be to use a BRCA1 heterozygous knock out (+/-) mouse in a CCI model, with the same readout measures as mentioned above, to test the hypothesis that female mice would have worsened outcomes compared to male mice due to estrogen-induced DNA damage. Going further, we could perform an ovariectomy in female mice to remove the effect of estrogen on DNA damage and therefore test the hypothesis that female and male mice would have comparable outcomes in the absence of estrogen-induced damage. This experiment could highlight the potential temporary use of estrogen blockers by women following mTBI, in order to mitigate the effects of estrogen-induced DNA damage.

Overall, this project provides ample opportunity for the development of therapeutic interventions, such as senolytic drugs for mitigating mTBI symptoms and estrogen blockers for mitigating sex- differences in concussion outcomes. However, before the safety and efficacy of such interventions can be assessed we must have a solid understanding of the pathophysiological mechanism of cellular senescence in the context of head trauma. Therefore, the immediate future direction of this project is to characterize the role of cellular senescence in producing pathology and symptoms following mTBI in a mouse model.

6. CONCLUSION

To summarize, in this project I have shown evidence of DNA damage and acquisition of cellular senescence in a cohort of human brains with a history of mTBI through immunohistochemistry and gene expression analysis. This observational work on humans has shown an association between mTBI history and DNA damage-induced senescence. In addition, I have validated these results in a CCI model of mTBI in mice, indicating that mTBI causes DNA damage-induced senescence in the absence of extraneous factors. This project suggests that cellular senescence is an early pathophysiological mechanism active following mTBI, and raises the possibility that this is the cause of acute and chronic symptoms and pathology after head trauma. However, future studies regarding the role of senescence on symptoms and pathology must be performed, as clinicopathological correlation was not established in this study.

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APPENDICES Appendix 1: List of genes included in NanoString custom panel, with housekeeping genes bolded at the end.

Gene Symbol Gene Name

APEX 1 Apurinic/Apyrimidinic Endodeoxyribonuclease 1 APEX 2 Apurinic/Apyrimidinic Endodeoxyribonuclease 2 ATM Ataxia Telangiectasia Mutated Serine/Threonine Kinase ATR Ataxia Telangiectasia And Rad3-Related Protein Serine/Threonine Kinase ATRIP ATR Interacting Protein BARD1 BRCA1 Associated RING Domain 1 BLM Bloom Syndrome RecQ Like Helicase BMI1 Polycomb Group RING Finger Protein 4 BRCA1 Breast Cancer Type 1 Susceptibility Protein BRCA2 Breast Cancer Type 2 Susceptibility Protein BRIP1 BRCA1 Interacting Protein C-Terminal Helicase 1 CCL1 Chemokine (C-C Motif) Ligand 1 CCL11 Chemokine (C-C Motif) Ligand 11 CCL13 Chemokine (C-C Motif) Ligand 13 CCL16 Chemokine (C-C Motif) Ligand 16 CCL2 Chemokine (C-C Motif) Ligand 2 CCL20 Chemokine (C-C Motif) Ligand 20 CCL25 Chemokine (C-C Motif) Ligand 25 CCL26 Chemokine (C-C Motif) Ligand 26 CCL28 Chemokine (C-C Motif) Ligand 28 CCL3 Chemokine (C-C Motif) Ligand 3 CCL4 Chemokine (C-C Motif) Ligand 4 CCL7 Chemokine (C-C Motif) Ligand 7 CCL8 Chemokine (C-C Motif) Ligand 8 CCNH Cyclin H CDK2 Cyclin-Dependent Kinase 2 CDK7 Cyclin-Dependent Kinase 7 CETN2 Centrin 2 CHEK1 Checkpoint kinase 1 CHEK2 Checkpoint kinase 2 CITED2 Carboxy-terminal domain 2 CXCL1 C-X-C Motif Chemokine Ligand 1 CXCL11 C-X-C Motif Chemokine Ligand 11 CXCL12 C-X-C Motif Chemokine Ligand 12 CXCL2 C-X-C Motif Chemokine Ligand 2 CXCL3 C-X-C Motif Chemokine Ligand 3 CXCL5 C-X-C Motif Chemokine Ligand 5 CXCL6 C-X-C Motif Chemokine Ligand 6 CXCL8 C-X-C Motif Chemokine Ligand 8 CXCR2 C-X-C Motif Chemokine Receptor 2

DDB1 Damage specific DNA binding protein 1 DDB2 Damage specific DNA binding protein 2 DMC1 DNA meiotic recombinase 1 ERCC1 Excision Repair Cross-Complementation Group 1 ERCC2 Excision Repair Cross-Complementation Group 2 ERCC3 Excision Repair Cross-Complementation Group 3 ERCC4 Excision Repair Cross-Complementation Group 4 ERCC5 Excision Repair Cross-Complementation Group 5 ERCC6 Excision Repair Cross-Complementation Group 6 ERCC8 Excision Repair Cross-Complementation Group 8 ETS1 ETS Proto-Oncogene 1 Transcription Factor EXO1 Exonuclease 1 FANCA Fanconi anemia complementation group A FANCD2 Fanconi anemia complementation group D2 FANCG Fanconi anemia complementation group G FEN1 Flap structure-specific endonuclease 1 GADD45A Growth arrest and DNA damage inducible alpha GADD45B Growth arrest and DNA damage inducible beta GADD45G Growth arrest and DNA damage inducible gamma GFAP Glial fibrillary acidic protein GSK3B Glycogen synthase kinase 3 beta GTF2H1 General transcription factor IIH Subunit I H2AFX H2A histone family member X HMGB1 High mobility group box 1 HUS1 Checkpoint protein HUS1 ID1 Inhibitor of DNA binding 1, HLH protein IFNG Interferon gamma IL10 Interleukin 10 IL11 Interleukin 11 IL12A Interleukin 12A IL12B Interleukin 12B IL2 Interleukin 2 IL4 Interleukin 4 IL6 Interleukin 6 IL7 Interleukin 7 IL6R Interleukin 6 receptor LIG1 DNA ligase 1 LIG3 DNA ligase 3 LIG4 DNA ligase 4 MAG1 DNA-3-methyladenine glycosylase MAP3K13 Mitogen-activated protein kinase kinase kinase 13 MBD4 Methyl-CpG binding domain 4, DNA glycosylase MCPH1 Microcephalin 1 MDC1 Mediator of DNA damage checkpoint 1 MDM2 MDM2 proto-oncogene MGMT O-6-methylguanine-DNA methyltransferase MIF Macrophage migration inhibitory factor MLH1 MutL homolog 1 80

MLH3 MutL homolog 3 MMS19 MMS19 homolog, cytosolic iron-sulfur assembly component MNAT1 MNAT, CDK activating kinase assembly factor MPG N-methylpurine DNA glycosylase MSH2 MutS homolog 2 MSH3 MutS homolog 3 MSH4 MutS homolog 4 MSH5 MutS homolog 5 MSH6 MutS homolog 6 MTOR Mechanistic target of rapamycin kinase MUTYH MutY DNA glycosylase NBN Nirbin NEIL1 Nei like DNA glycosylase 1 NEIL2 Nei like DNA glycosylase 2 NEIL3 Nei like DNA glycosylase 3 NFATC1 Nuclear factor of activated T cells 1 NFATC2 Nuclear factor of activated T cells 2 NFKB1 Nuclear factor kappa beta subunit 1 NOX4 NADPH oxidase 4 NRF2 Nuclear factor, erythroid 2 like 2 NTH1 NTH like DNA glycozylase 1 OGG1 8-oxoguanine DNA glycosylase PARP1 Poly(ADP-ribose) polymerase 1 PARP3 Poly(ADP-ribose) polymerase 3 PCNA Proliferating cell nuclear antigen PMS1 PMS1 Homolog 1, mismatch repair system component PMS2 PMS2 Homolog 2, mismatch repair system component PNKP Polynucleotide kinase 3’-phosphatase POLB DNA polymerase beta POLD1 DNA polymerase delta 1, catalytic subunit POLD2 DNA polymerase delta 2, accessory subunit POLD3 DNA polymerase delta 3, accessory subunit POLL DNA polymerase lambda PPP1R15A Protein phosphatase 1 regulatory subunit 15A PRKDC Protein kinase, DNA-activated, catalytic subunit RAD1 RAD1 checkpoint DNA exonuclease RAD17 RAD17 checkpoint clamp loader component RAD18 RAD18, E3 ubiquitin protein ligase RAD21 RAD 21 cohesin complex component RAD23A RAD23 homolog A, nucleotide excision repair protein RAD23B RAD23B homolog B, nucleotide excision repair protein RAD50 RAD50 double strand break repair protein RAD51 RAD51 recombinase RAD51B RAD51 paralog B RAD51C RAD51 paralog C RAD51D RAD51 paralog D RAD52 RAD52 homolog, DNA repair protein RAD54L RAD54 like 81

RAD9A RAD9 checkpoint clamp component A RELA RELA proto-oncogene, NFKB subunit RNF168 Ring finger protein 168 RNF8 Ring finger protein 8 RPA1 Replication protein A1 RPA2 Replication protein A2 SERPINB2 Serpin family B member 2 SERPINE1 Serpin family E member 1 SMUG1 Single-strand selective monofunctional uracil-dna glycosylase 1 SUMO1 Small ubiquitin-like modifier 1 TDG Thymine DNA glycosylase TERF2 Telomeric repeat binding factor 2 TERT Telomerase reverse transcriptase TNFRSF14 TNF receptor superfamily member 14 TNFRSF18 TNF receptor superfamily member 18 TP53 Tumor protein 53 TP53BP1 Tumor protein binding protein 1 TP73 Tumor protein p73 TREX1 Three prime repair exonuclease 1 UNG Uracil DNA glycosylase XAB2 XPA binding protein 2 XPA XPA, DNA damage recognition and repair factor XPC XPC complex subunit, DNA damage recognition and repair factor XRCC1 X-Ray repair cross complementing 1 XRCC2 X-Ray repair cross complementing 2 XRCC3 X-Ray repair cross complementing 3 XRCC4 X-Ray repair cross complementing 4 XRCC5 X-Ray repair cross complementing 5 XRCC6 X-Ray repair cross complementing 6

AARS Alanyl-TRNA Synthetase CYC1 Cytochrome C1 GUSB Glucuronidase beta HPRT1 Hypoxanthine phosphoribosyltransferase 1 RPL13 Ribosomal protein L13 TBP TATA-box binding protein UBE2D2 Ubiquitin conjugating enzyme E2 D2

Appendix 2: Mouse NanoString Neuroinflammation Panel

Gene Symbol Gene Name

Abcc3 ATP-binding cassette, sub-family C (CFTR/MRP), member 3 Abcc8 ATP-binding cassette, sub-family C (CFTR/MRP), member 8 Abl1 c-abl oncogene 1, non-receptor tyrosine kinase Adamts16 a disintegrin-like and metallopeptidase (reprolysin type) with thrombospondin type 1 motif, 16 Ago4 argonaute RISC catalytic subunit 4 Agt angiotensinogen (serpin peptidase inhibitor, clade A, member 8) AI464131 expressed sequence AI464131 Ak1 adenylate kinase 1 Akt1 thymoma viral proto-oncogene 1 Akt2 thymoma viral proto-oncogene 2 Aldh1l1 aldehyde dehydrogenase 1 family, member L1 Ambra1 autophagy/beclin 1 regulator 1 Amigo2 adhesion molecule with Ig like domain 2 Anapc15 anaphase prompoting complex C subunit 15 Anxa1 annexin A1 Apc adenomatosis polyposis coli Apex1 apurinic/apyrimidinic endonuclease 1 Apoe apolipoprotein E Arc activity regulated cytoskeletal-associated protein Arhgap24 Rho GTPase activating protein 24 Arid1a AT rich interactive domain 1A (SWI-like) Asb2 ankyrin repeat and SOCS box-containing 2 Ash2l ASH2 like histone lysine methyltransferase complex subunit Asph aspartate-beta-hydroxylase Atf3 activating transcription factor 3 Atg14 autophagy related 14 Atg3 autophagy related 3 Atg5 autophagy related 5 Atg7 autophagy related 7 Atg9a autophagy related 9A Atm ataxia telangiectasia mutated Atp6v0e ATPase, H+ transporting, lysosomal V0 subunit E Atp6v1a ATPase, H+ transporting, lysosomal V1 subunit A Atr ataxia telangiectasia and Rad3 related Axl AXL receptor tyrosine kinase B3gnt5 UDP-GlcNAc:betaGal beta-1,3-N-acetylglucosaminyltransferase 5 Bad BCL2-associated agonist of cell death Bag3 BCL2-associated athanogene 3 Bag4 BCL2-associated athanogene 4

Bak1 BCL2-antagonist/killer 1 Bard1 BRCA1 associated RING domain 1 Bax BCL2-associated X protein Bbc3 BCL2 binding component 3 Bcas1 breast carcinoma amplified sequence 1 Bcl10 B cell leukemia/lymphoma 10 Bcl2 B cell leukemia/lymphoma 2 Bcl2a1a B cell leukemia/lymphoma 2 related protein A1a Bcl2l1 BCL2-like 1 Bcl2l11 BCL2-like 11 (apoptosis facilitator) Bcl2l2 BCL2-like 2 Bdnf brain derived neurotrophic factor Becn1 beclin 1, autophagy related Bid BH3 interacting domain death agonist Bik BCL2-interacting killer Bin1 bridging integrator 1 Birc2 baculoviral IAP repeat-containing 2 Birc3 baculoviral IAP repeat-containing 3 Birc5 baculoviral IAP repeat-containing 5 Blk B lymphoid kinase Blm Bloom syndrome, RecQ like helicase Blnk B cell linker Bmi1 Bmi1 polycomb ring finger oncogene Bnip3 BCL2/adenovirus E1B interacting protein 3 Bnip3l BCL2/adenovirus E1B interacting protein 3-like Bok BCL2-related ovarian killer Bola2 bolA-like 2 (E. coli) Braf Braf transforming gene Brca1 breast cancer 1, early onset Brd2 bromodomain containing 2 Brd3 bromodomain containing 3 Brd4 bromodomain containing 4 Btk Bruton agammaglobulinemia tyrosine kinase C1qa complement component 1, q subcomponent, alpha polypeptide C1qb complement component 1, q subcomponent, beta polypeptide C1qc complement component 1, q subcomponent, C chain C3 complement component 3 C3ar1 complement component 3a receptor 1 C4a complement component 4A (Rodgers blood group) C5ar1 complement component 5a receptor 1 C6 complement component 6 Cables1 CDK5 and Abl enzyme substrate 1 Calcoco2 calcium binding and coiled-coil domain 2 Calr calreticulin

Camk4 calcium/calmodulin-dependent protein kinase IV Casp1 caspase 1 Casp2 caspase 2 Casp3 caspase 3 Casp4 caspase 4, apoptosis-related cysteine peptidase Casp6 caspase 6 Casp7 caspase 7 Casp8 caspase 8 Casp9 caspase 9 Cass4 Cas scaffolding protein family member 4 Ccl2 chemokine (C-C motif) ligand 2 Ccl3 chemokine (C-C motif) ligand 3 Ccl4 chemokine (C-C motif) ligand 4 Ccl5 chemokine (C-C motif) ligand 5 Ccl7 chemokine (C-C motif) ligand 7 Ccng2 cyclin G2 Ccni cyclin I Ccr2 chemokine (C-C motif) receptor 2 Ccr5 chemokine (C-C motif) receptor 5 Cd109 CD109 antigen Cd14 CD14 antigen Cd163 CD163 antigen Cd19 CD19 antigen Cd209e CD209e antigen Cd244 CD244 natural killer cell receptor 2B4 Cd24a CD24a antigen Cd300lf CD300 molecule like family member F Cd33 CD33 antigen Cd36 CD36 molecule Cd3d CD3 antigen, delta polypeptide Cd3e CD3 antigen, epsilon polypeptide Cd3g CD3 antigen, gamma polypeptide Cd40 CD40 antigen Cd44 CD44 antigen Cd47 CD47 antigen (Rh-related antigen, integrin-associated signal transducer) Cd6 CD6 antigen Cd68 CD68 antigen Cd69 CD69 antigen Cd70 CD70 antigen Cd72 CD72 antigen Cd74 CD74 antigen (invariant polypeptide of major histocompatibility complex, class II antigen- Cd83 CD83 antigen Cd84 CD84 antigen Cd86 CD86 antigen

Cd8a CD8 antigen, alpha chain Cd8b1 CD8 antigen, beta chain 1 Cdc25a cell division cycle 25A Cdc7 cell division cycle 7 (S. cerevisiae) Cdk20 cyclin-dependent kinase 20 Cdkn1a cyclin-dependent kinase inhibitor 1A (P21) Cdkn1c cyclin-dependent kinase inhibitor 1C (P57) Ceacam3 carcinoembryonic antigen-related cell adhesion molecule 3 Cflar CASP8 and FADD-like apoptosis regulator Ch25h cholesterol 25-hydroxylase Chek1 checkpoint kinase 1 Chek2 checkpoint kinase 2 Chn2 chimerin 2 Chst8 carbohydrate (N-acetylgalactosamine 4-0) sulfotransferase 8 Chuk conserved helix-loop-helix ubiquitous kinase Cidea cell death-inducing DNA fragmentation factor, alpha subunit-like effector A Cideb cell death-inducing DNA fragmentation factor, alpha subunit-like effector B Cks1b CDC28 protein kinase 1b Clcf1 cardiotrophin-like cytokine factor 1 Cldn5 claudin 5 Clec7a C-type lectin domain family 7, member a Clic4 chloride intracellular channel 4 (mitochondrial) Cln3 ceroid lipofuscinosis, neuronal 3, juvenile (Batten, Spielmeyer-Vogt disease) Clstn1 calsyntenin 1 Cnn2 calponin 2 Cnp 2',3'-cyclic nucleotide 3' phosphodiesterase Cntnap2 contactin associated protein-like 2 Coa5 cytochrome C oxidase assembly factor 5 Col6a3 collagen, type VI, alpha 3 Cotl1 coactosin-like 1 (Dictyostelium) Cox5b cytochrome c oxidase subunit Vb Cp ceruloplasmin Cpa3 carboxypeptidase A3, mast cell Creb1 cAMP responsive element binding protein 1 Crebbp CREB binding protein Crem cAMP responsive element modulator Crip1 cysteine-rich protein 1 (intestinal) Cryba4 crystallin, beta A4 Csf1 colony stimulating factor 1 (macrophage) Csf1r colony stimulating factor 1 receptor Csf2rb colony stimulating factor 2 receptor, beta, low-affinity (granulocyte-macrophage) Csf3r colony stimulating factor 3 receptor (granulocyte) Csk c-src tyrosine kinase Cst7 cystatin F (leukocystatin)

Ctse cathepsin E Ctsf cathepsin F Ctss cathepsin S Ctsw cathepsin W Cx3cl1 chemokine (C-X3-C motif) ligand 1 Cx3cr1 chemokine (C-X3-C motif) receptor 1 Cxcl10 chemokine (C-X-C motif) ligand 10 Cxcl9 chemokine (C-X-C motif) ligand 9 Cycs cytochrome c, somatic Cyp27a1 cytochrome P450, family 27, subfamily a, polypeptide 1 Cyp7b1 cytochrome P450, family 7, subfamily b, polypeptide 1 Cytip cytohesin 1 interacting protein Dab2 disabled 2, mitogen-responsive phosphoprotein Dapk1 death associated protein kinase 1 Ddb2 damage specific DNA binding protein 2 Ddx58 DEAD (Asp-Glu-Ala-Asp) box polypeptide 58 Dicer1 dicer 1, ribonuclease type III Dlg1 discs large MAGUK scaffold protein 1 Dlg4 discs large MAGUK scaffold protein 4 Dlx1 distal-less homeobox 1 Dlx2 distal-less homeobox 2 Dna2 DNA replication helicase/nuclease 2 Dnmt1 DNA methyltransferase (cytosine-5) 1 Dnmt3a DNA methyltransferase 3A Dnmt3b DNA methyltransferase 3B Dock1 dedicator of cytokinesis 1 Dock2 dedicator of cyto-kinesis 2 Dot1l DOT1-like, histone H3 methyltransferase (S. cerevisiae) Dst dystonin Duoxa1 dual oxidase maturation factor 1 Dusp7 dual specificity phosphatase 7 E2f1 E2F transcription factor 1 Eed embryonic ectoderm development Eef2k eukaryotic elongation factor-2 kinase Egfr epidermal growth factor receptor Egr1 early growth response 1 Ehmt2 euchromatic histone lysine N-methyltransferase 2 Eif1 eukaryotic translation initiation factor 1 Emcn endomucin Emp1 epithelial membrane protein 1 Enpp6 ectonucleotide pyrophosphatase/phosphodiesterase 6 Entpd2 ectonucleoside triphosphate diphosphohydrolase 2 Eomes eomesodermin Ep300 E1A binding protein p300

Epcam epithelial cell adhesion molecule Epg5 ectopic P-granules autophagy protein 5 homolog (C. elegans) Epsti1 epithelial stromal interaction 1 (breast) Erbb3 erb-b2 receptor tyrosine kinase 3 Ercc2 excision repair cross-complementing rodent repair deficiency, complementation group 2 Esam endothelial cell-specific adhesion molecule Ets2 E26 avian leukemia oncogene 2, 3' domain Exo1 exonuclease 1 Ezh1 enhancer of zeste 1 polycomb repressive complex 2 subunit Ezh2 enhancer of zeste 2 polycomb repressive complex 2 subunit F3 coagulation factor III Fa2h fatty acid 2-hydroxylase Fabp5 fatty acid binding protein 5, epidermal Fadd Fas (TNFRSF6)-associated via death domain Fancc Fanconi anemia, complementation group C Fancd2 Fanconi anemia, complementation group D2 Fancg Fanconi anemia, complementation group G Fas Fas (TNF receptor superfamily member 6) Fasl Fas ligand (TNF superfamily, member 6) Fbln5 fibulin 5 Fcer1g Fc receptor, IgE, high affinity I, gamma polypeptide Fcgr1 Fc receptor, IgG, high affinity I Fcgr2b Fc receptor, IgG, low affinity IIb Fcgr3 Fc receptor, IgG, low affinity III Fcrla Fc receptor-like A Fcrlb Fc receptor-like B Fcrls Fc receptor-like S, scavenger receptor Fdxr ferredoxin reductase Fen1 flap structure specific endonuclease 1 Fgd2 FYVE, RhoGEF and PH domain containing 2 Fgf13 fibroblast growth factor 13 Fgl2 fibrinogen-like protein 2 Fkbp5 FK506 binding protein 5 Flt1 FMS-like tyrosine kinase 1 Fos FBJ osteosarcoma oncogene Foxp3 forkhead box P3 Fpr1 formyl peptide receptor 1 Fscn1 fascin actin-bundling protein 1 Fyn Fyn proto-oncogene Gadd45a growth arrest and DNA-damage-inducible 45 alpha Gadd45g growth arrest and DNA-damage-inducible 45 gamma Gal3st1 galactose-3-O-sulfotransferase 1 Gba glucosidase, beta, acid Gbp2 guanylate binding protein 2

Gclc glutamate-cysteine ligase, catalytic subunit Gdpd2 glycerophosphodiester phosphodiesterase domain containing 2 Gja1 gap junction protein, alpha 1 Gjb1 gap junction protein, beta 1 Gna15 guanine nucleotide binding protein, alpha 15 Gpr183 G protein-coupled receptor 183 Gpr34 G protein-coupled receptor 34 Gpr62 G protein-coupled receptor 62 Gpr84 G protein-coupled receptor 84 Grap GRB2-related adaptor protein Gria1 glutamate receptor, ionotropic, AMPA1 (alpha 1) Gria2 glutamate receptor, ionotropic, AMPA2 (alpha 2) Gria4 glutamate receptor, ionotropic, AMPA4 (alpha 4) Grin2a glutamate receptor, ionotropic, NMDA2A (epsilon 1) Grin2b glutamate receptor, ionotropic, NMDA2B (epsilon 2) Grm2 glutamate receptor, metabotropic 2 Grm3 glutamate receptor, metabotropic 3 Grn granulin Gsn gelsolin Gstm1 glutathione S-transferase, mu 1 Gzma granzyme A Gzmb granzyme B H2afx H2A histone family, member X H2-T23 histocompatibility 2, T region locus 23 Hat1 histone aminotransferase 1 Hcar2 hydroxycarboxylic acid receptor 2 Hdac1 histone deacetylase 1 Hdac2 histone deacetylase 2 Hdac4 histone deacetylase 4 Hdac6 histone deacetylase 6 Hdc histidine decarboxylase Hells helicase, lymphoid specific Hif1a hypoxia inducible factor 1, alpha subunit Hilpda hypoxia inducible lipid droplet associated Hira histone cell cycle regulator Hist1h1d histone cluster 1, H1d Hmgb1 high mobility group box 1 Hmox1 heme oxygenase 1 Homer1 homer scaffolding protein 1 Hpgds hematopoietic prostaglandin D synthase Hprt hypoxanthine guanine phosphoribosyl transferase Hps4 HPS4, biogenesis of lysosomal organelles complex 3 subunit 2 Hrk harakiri, BCL2 interacting protein (contains only BH3 domain) Hsd11b1 hydroxysteroid 11-beta dehydrogenase 1

Hspb1 heat shock protein 1 Hus1 HUS1 checkpoint clamp component Icam2 intercellular adhesion molecule 2 Ifi30 interferon gamma inducible protein 30 Ifih1 interferon induced with helicase C domain 1 Ifitm2 interferon induced transmembrane protein 2 Ifitm3 interferon induced transmembrane protein 3 Ifnar1 interferon (alpha and beta) receptor 1 Ifnar2 interferon (alpha and beta) receptor 2 Igf1 insulin-like growth factor 1 Igf1r insulin-like growth factor I receptor Igf2r insulin-like growth factor 2 receptor Igsf10 immunoglobulin superfamily, member 10 Igsf6 immunoglobulin superfamily, member 6 Ikbkb inhibitor of kappaB kinase beta Ikbke inhibitor of kappaB kinase epsilon Ikbkg inhibitor of kappaB kinase gamma Il10rb interleukin 10 receptor, beta Il15ra interleukin 15 receptor, alpha chain Il1a interleukin 1 alpha Il1b interleukin 1 beta Il1r1 interleukin 1 receptor, type I Il1r2 interleukin 1 receptor, type II Il1rap interleukin 1 receptor accessory protein Il1rl2 interleukin 1 receptor-like 2 Il1rn interleukin 1 receptor antagonist Il21r interleukin 21 receptor Il2rg interleukin 2 receptor, gamma chain Il3 interleukin 3 Il3ra interleukin 3 receptor, alpha chain Il6ra interleukin 6 receptor, alpha Inpp5d inositol polyphosphate-5-phosphatase D Iqsec1 IQ motif and Sec7 domain 1 Irak1 interleukin-1 receptor-associated kinase 1 Irak2 interleukin-1 receptor-associated kinase 2 Irak3 interleukin-1 receptor-associated kinase 3 Irak4 interleukin-1 receptor-associated kinase 4 Irf1 interferon regulatory factor 1 Irf2 interferon regulatory factor 2 Irf3 interferon regulatory factor 3 Irf4 interferon regulatory factor 4 Irf6 interferon regulatory factor 6 Irf7 interferon regulatory factor 7 Irf8 interferon regulatory factor 8

Islr2 immunoglobulin superfamily containing leucine-rich repeat 2 Itga6 integrin alpha 6 Itga7 integrin alpha 7 Itgam integrin alpha M Itgav integrin alpha V Itgax integrin alpha X Itgb5 integrin beta 5 Jag1 jagged 1 Jam2 junction adhesion molecule 2 Jarid2 jumonji, AT rich interactive domain 2 Jun jun proto-oncogene Kat2a K(lysine) acetyltransferase 2A Kat2b K(lysine) acetyltransferase 2B Kcnd1 potassium voltage-gated channel, Shal-related family, member 1 Kcnj10 potassium inwardly-rectifying channel, subfamily J, member 10 Kcnk13 potassium channel, subfamily K, member 13 Kdm1a lysine (K)-specific demethylase 1A Kdm1b lysine (K)-specific demethylase 1B Kdm2a lysine (K)-specific demethylase 2A Kdm2b lysine (K)-specific demethylase 2B Kdm3a lysine (K)-specific demethylase 3A Kdm3b KDM3B lysine (K)-specific demethylase 3B Kdm4a lysine (K)-specific demethylase 4A Kdm4b lysine (K)-specific demethylase 4B Kdm4c lysine (K)-specific demethylase 4C Kdm4d lysine (K)-specific demethylase 4D Kdm5a lysine (K)-specific demethylase 5A Kdm5b lysine (K)-specific demethylase 5B Kdm5c lysine (K)-specific demethylase 5C Kdm5d lysine (K)-specific demethylase 5D Kdm6a lysine (K)-specific demethylase 6A Kif2c kinesin family member 2C Kir3dl1 killer cell immunoglobulin-like receptor, three domains, long cytoplasmic tail, 1 Kir3dl2 killer cell immunoglobulin-like receptor, three domains, long cytoplasmic tail, 2 Kit KIT proto-oncogene receptor tyrosine kinase Klrb1 killer cell lectin-like receptor subfamily B member 1 Klrd1 killer cell lectin-like receptor, subfamily D, member 1 Klrk1 killer cell lectin-like receptor subfamily K, member 1 Kmt2a lysine (K)-specific methyltransferase 2A Kmt2c lysine (K)-specific methyltransferase 2C Lacc1 laccase (multicopper oxidoreductase) domain containing 1 Lag3 lymphocyte-activation gene 3 Lair1 leukocyte-associated Ig-like receptor 1 Lamp1 lysosomal-associated membrane protein 1

Lamp2 lysosomal-associated membrane protein 2 Lcn2 lipocalin 2 Ldha lactate dehydrogenase A Ldlrad3 low density lipoprotein receptor class A domain containing 3 Lfng LFNG O-fucosylpeptide 3-beta-N-acetylglucosaminyltransferase Lgmn legumain Lig1 ligase I, DNA, ATP-dependent Lilrb4a leukocyte immunoglobulin-like receptor, subfamily B, member 4A Lingo1 leucine rich repeat and Ig domain containing 1 Lmna lamin A Lmnb1 lamin B1 Lrg1 leucine-rich alpha-2-glycoprotein 1 Lrrc25 leucine rich repeat containing 25 Lrrc3 leucine rich repeat containing 3 Lsr lipolysis stimulated lipoprotein receptor Lst1 leukocyte specific transcript 1 Lta lymphotoxin A Ltb lymphotoxin B Ltbr lymphotoxin B receptor Ltc4s leukotriene C4 synthase Ly6a lymphocyte antigen 6 complex, locus A Ly6g lymphocyte antigen 6 complex, locus G Ly9 lymphocyte antigen 9 Lyn LYN proto-oncogene, Src family tyrosine kinase Mafb v-maf musculoaponeurotic fibrosarcoma oncogene family, protein B (avian) Maff v-maf musculoaponeurotic fibrosarcoma oncogene family, protein F (avian) Mag myelin-associated glycoprotein Mal myelin and lymphocyte protein, T cell differentiation protein Man2b1 mannosidase 2, alpha B1 Map1lc3a microtubule-associated protein 1 light chain 3 alpha Map2k1 mitogen-activated protein kinase kinase 1 Map2k4 mitogen-activated protein kinase kinase 4 Map3k1 mitogen-activated protein kinase kinase kinase 1 Map3k14 mitogen-activated protein kinase kinase kinase 14 Mapk10 mitogen-activated protein kinase 10 Mapk12 mitogen-activated protein kinase 12 Mapk14 mitogen-activated protein kinase 14 Mapt microtubule-associated protein tau Marco macrophage receptor with collagenous structure Mavs mitochondrial antiviral signaling protein Mb21d1 Mab-21 domain containing 1 Mbd2 methyl-CpG binding domain protein 2 Mbd3 methyl-CpG binding domain protein 3 Mcm2 minichromosome maintenance complex component 2

Mcm5 minichromosome maintenance complex component 5 Mcm6 minichromosome maintenance complex component 6 Mdc1 mediator of DNA damage checkpoint 1 Mdm2 transformed mouse 3T3 cell double minute 2 Mef2c myocyte enhancer factor 2C Mertk c-mer proto-oncogene tyrosine kinase Mfge8 milk fat globule-EGF factor 8 protein Mgmt O-6-methylguanine-DNA methyltransferase Mmp12 matrix metallopeptidase 12 Mmp14 matrix metallopeptidase 14 (membrane-inserted) Mobp myelin-associated oligodendrocytic basic protein Mog myelin oligodendrocyte glycoprotein Mpeg1 macrophage expressed gene 1 Mpg N-methylpurine-DNA glycosylase Mr1 major histocompatibility complex, class I-related Mre11a MRE11A homolog A, double strand break repair nuclease Ms4a1 membrane-spanning 4-domains, subfamily A, member 1 Ms4a2 membrane-spanning 4-domains, subfamily A, member 2 Ms4a4a membrane-spanning 4-domains, subfamily A, member 4A Msh2 mutS homolog 2 Msn moesin Msr1 macrophage scavenger receptor 1 Mvp major vault protein Myc myelocytomatosis oncogene Myct1 myc target 1 Myd88 myeloid differentiation primary response gene 88 Myrf myelin regulatory factor Nbn nibrin Ncaph non-SMC condensin I complex, subunit H Ncf1 neutrophil cytosolic factor 1 Ncor1 nuclear receptor co-repressor 1 Ncor2 nuclear receptor co-repressor 2 Ncr1 natural cytotoxicity triggering receptor 1 Nefl neurofilament, light polypeptide Nfe2l2 nuclear factor, erythroid derived 2, like 2 Nfkb1 nuclear factor of kappa light polypeptide gene enhancer in B cells 1, p105 Nfkb2 nuclear factor of kappa light polypeptide gene enhancer in B cells 2, p49/p100 Nfkbia nuclear factor of kappa light polypeptide gene enhancer in B cells inhibitor, alpha Nfkbie nuclear factor of kappa light polypeptide gene enhancer in B cells inhibitor, epsilon Ngf nerve growth factor Ngfr nerve growth factor receptor (TNFR superfamily, member 16) Ninj2 ninjurin 2 Nkg7 natural killer cell group 7 sequence Nlgn1 neuroligin 1

Nlgn2 neuroligin 2 Nlrp3 NLR family, pyrin domain containing 3 Nod1 nucleotide-binding oligomerization domain containing 1 Nostrin nitric oxide synthase trafficker Npl N-acetylneuraminate pyruvate lyase Npnt nephronectin Nptx1 neuronal pentraxin 1 Nqo1 NAD(P)H dehydrogenase, quinone 1 Nrgn neurogranin Nrm nurim (nuclear envelope membrane protein) Nrp2 neuropilin 2 Nthl1 nth (endonuclease III)-like 1 (E.coli) Nwd1 NACHT and WD repeat domain containing 1 Oas1g 2'-5' oligoadenylate synthetase 1G Ogg1 8-oxoguanine DNA-glycosylase 1 Olfml3 olfactomedin-like 3 Opalin oligodendrocytic myelin paranodal and inner loop protein Optn optineurin Osgin1 oxidative stress induced growth inhibitor 1 Osmr oncostatin M receptor P2rx7 purinergic receptor P2X, ligand-gated ion channel, 7 P2ry12 purinergic receptor P2Y, G-protein coupled 12 Pacsin1 protein kinase C and casein kinase substrate in neurons 1 Padi2 peptidyl arginine deiminase, type II Pak1 p21 protein (Cdc42/Rac)-activated kinase 1 Parp1 poly (ADP-ribose) polymerase family, member 1 Parp2 poly (ADP-ribose) polymerase family, member 2 Pcna proliferating cell nuclear antigen Pdpn podoplanin Pecam1 platelet/endothelial cell adhesion molecule 1 Pex14 peroxisomal biogenesis factor 14 Pik3ca phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha Pik3cb phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit beta Pik3cd phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit delta Pik3cg phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit gamma Pik3r1 phosphoinositide-3-kinase regulatory subunit 1 Pik3r2 phosphoinositide-3-kinase regulatory subunit 2 Pik3r5 phosphoinositide-3-kinase regulatory subunit 5 Pilra paired immunoglobin-like type 2 receptor alpha Pilrb1 paired immunoglobin-like type 2 receptor beta 1 Pink1 PTEN induced putative kinase 1 Pla2g4a phospholipase A2, group IVA (cytosolic, calcium-dependent) Pla2g5 phospholipase A2, group V Plcg2 phospholipase C, gamma 2

Pld1 phospholipase D1 Pld2 phospholipase D2 Plekhb1 pleckstrin homology domain containing, family B (evectins) member 1 Plekhm1 pleckstrin homology domain containing, family M (with RUN domain) member 1 Pllp plasma membrane proteolipid Plp1 proteolipid protein (myelin) 1 Plxdc2 plexin domain containing 2 Plxnb3 plexin B3 Pmp22 peripheral myelin protein 22 Pms2 PMS1 homolog2, mismatch repair system component Pnoc prepronociceptin Pole polymerase (DNA directed), epsilon Ppfia4 protein tyrosine phosphatase, receptor type, f polypeptide (PTPRF), interacting protein Ppp3ca protein phosphatase 3, catalytic subunit, alpha isoform Ppp3cb protein phosphatase 3, catalytic subunit, beta isoform Ppp3r1 protein phosphatase 3, regulatory subunit B, alpha isoform (calcineurin B, type I) Ppp3r2 protein phosphatase 3, regulatory subunit B, alpha isoform (calcineurin B, type II) Prdx1 peroxiredoxin 1 Prf1 perforin 1 (pore forming protein) Prkaca protein kinase, cAMP dependent, catalytic, alpha Prkacb protein kinase, cAMP dependent, catalytic, beta Prkar1a protein kinase, cAMP dependent regulatory, type I, alpha Prkar2a protein kinase, cAMP dependent regulatory, type II alpha Prkar2b protein kinase, cAMP dependent regulatory, type II beta Prkce protein kinase C, epsilon Prkcq protein kinase C, theta Prkdc protein kinase, DNA activated, catalytic polypeptide Pros1 protein S (alpha) Psen2 presenilin 2 Psmb8 proteasome (prosome, macropain) subunit, beta type 8 (large multifunctional peptidase 7) Pten phosphatase and tensin homolog Ptger3 prostaglandin E receptor 3 (subtype EP3) Ptger4 prostaglandin E receptor 4 (subtype EP4) Ptgs2 prostaglandin-endoperoxide synthase 2 Ptms parathymosin Ptpn6 protein tyrosine phosphatase, non-receptor type 6 Ptprc protein tyrosine phosphatase, receptor type, C Pttg1 pituitary tumor-transforming gene 1 Ptx3 pentraxin related gene Pycard PYD and CARD domain containing Rab6b RAB6B, member RAS oncogene family Rab7 RAB7, member RAS oncogene family Rac1 RAS-related C3 botulinum substrate 1 Rac2 RAS-related C3 botulinum substrate 2

Rad1 RAD1 checkpoint DNA exonuclease Rad17 RAD17 checkpoint clamp loader component Rad50 RAD50 double strand break repair protein Rad51 RAD51 recombinase Rad51b RAD51 paralog B Rad51c RAD51 paralog C Rad9a RAD9 checkpoint clamp component A Rag1 recombination activating gene 1 Rala v-ral simian leukemia viral oncogene A (ras related) Ralb v-ral simian leukemia viral oncogene B Rapgef3 Rap guanine nucleotide exchange factor (GEF) 3 Rb1cc1 RB1-inducible coiled-coil 1 Rbfox3 RNA binding protein, fox-1 homolog (C. elegans) 3 Rela v-rel reticuloendotheliosis viral oncogene homolog A (avian) Relb avian reticuloendotheliosis viral (v-rel) oncogene related B Reln reelin Rgl1 ral guanine nucleotide dissociation stimulator,-like 1 Rhoa ras homolog family member A Ripk1 receptor (TNFRSF)-interacting serine-threonine kinase 1 Ripk2 receptor (TNFRSF)-interacting serine-threonine kinase 2 Rnf8 ring finger protein 8 Rpa1 replication protein A1 Rpl28 ribosomal protein L28 Rpl29 ribosomal protein L29 Rpl36al ribosomal protein L36A-like Rpl9 ribosomal protein L9 Rps10 ribosomal protein S10 Rps2 ribosomal protein S2 Rps21 ribosomal protein S21 Rps3 ribosomal protein S3 Rps9 ribosomal protein S9 Rrm2 ribonucleotide reductase M2 Rsad2 radical S-adenosyl methionine domain containing 2 Rtn4rl1 reticulon 4 receptor-like 1 S100a10 S100 calcium binding protein A10 (calpactin) S100b S100 protein, beta polypeptide, neural S1pr3 sphingosine-1-phosphate receptor 3 S1pr4 sphingosine-1-phosphate receptor 4 S1pr5 sphingosine-1-phosphate receptor 5 Sall1 spalt like transcription factor 1 Sell selectin, lymphocyte Serpina3n serine (or cysteine) peptidase inhibitor, clade A, member 3N Serpine1 serine (or cysteine) peptidase inhibitor, clade E, member 1 Serpinf1 serine (or cysteine) peptidase inhibitor, clade F, member 1

Serping1 serine (or cysteine) peptidase inhibitor, clade G, member 1 Sesn1 sestrin 1 Sesn2 sestrin 2 Setd1a SET domain containing 1A Setd1b SET domain containing 1B Setd2 SET domain containing 2 Setd7 SET domain containing (lysine methyltransferase) 7 Setdb1 SET domain, bifurcated 1 Sftpd surfactant associated protein D Sh2d1a SH2 domain containing 1A Shank3 SH3 and multiple ankyrin repeat domains 3 Siglec1 sialic acid binding Ig-like lectin 1, sialoadhesin Siglecf sialic acid binding Ig-like lectin F Sin3a transcriptional regulator, SIN3A (yeast) Sirt1 sirtuin 1 Slamf8 SLAM family member 8 Slamf9 SLAM family member 9 Slc10a6 solute carrier family 10 (sodium/bile acid cotransporter family), member 6 Slc17a6 solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter), member 6 Slc17a7 solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter), member 7 Slc1a3 solute carrier family 1 (glial high affinity glutamate transporter), member 3 Slc2a1 solute carrier family 2 (facilitated glucose transporter), member 1 Slc2a5 solute carrier family 2 (facilitated glucose transporter), member 5 Slc44a1 solute carrier family 44, member 1 Slc6a1 solute carrier family 6 (neurotransmitter transporter, GABA), member 1 Slco2b1 solute carrier organic anion transporter family, member 2b1 Slfn8 schlafen 8 Smarca4 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 4 Smarca5 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily a, member 5 Smarcd1 SWI/SNF related, matrix associated, actin dependent regulator of chromatin, subfamily d, member 1 Smc1a structural maintenance of chromosomes 1A Snca synuclein, alpha Socs3 suppressor of cytokine signaling 3 Sod2 superoxide dismutase 2, mitochondrial Sox10 SRY (sex determining region Y)-box 10 Sox4 SRY (sex determining region Y)-box 4 Sox9 SRY (sex determining region Y)-box 9 Sphk1 sphingosine kinase 1 Spib Spi-B transcription factor (Spi-1/PU.1 related) Spint1 serine protease inhibitor, Kunitz type 1 Spp1 secreted phosphoprotein 1 Sqstm1 sequestosome 1 Srgn serglycin Srxn1 sulfiredoxin 1 homolog (S. cerevisiae)

St3gal6 ST3 beta-galactoside alpha-2,3-sialyltransferase 6 St8sia6 ST8 alpha-N-acetyl-neuraminide alpha-2,8-sialyltransferase 6 Stat1 signal transducer and activator of transcription 1 Steap4 STEAP family member 4 Stmn1 stathmin 1 Stx18 syntaxin 18 Sumo1 small ubiquitin-like modifier 1 Suv39h1 suppressor of variegation 3-9 1 Suv39h2 suppressor of variegation 3-9 2 Suz12 SUZ12 polycomb repressive complex 2 subunit Syk spleen tyrosine kinase Syn2 synapsin II Syp synaptophysin Tarbp2 TARBP2, RISC loading complex RNA binding subunit Tbc1d4 TBC1 domain family, member 4 Tbr1 T-box brain gene 1 Tbx21 T-box 21 Tcirg1 T cell, immune regulator 1, ATPase, H+ transporting, lysosomal V0 protein A3 Tcl1 T cell lymphoma breakpoint 1 Tet1 tet methylcytosine dioxygenase 1 Tfg Trk-fused gene Tgfa transforming growth factor alpha Tgfb1 transforming growth factor, beta 1 Tgfbr1 transforming growth factor, beta receptor I Tgm1 transglutaminase 1, K polypeptide Tgm2 transglutaminase 2, C polypeptide Tie1 tyrosine kinase with immunoglobulin-like and EGF-like domains 1 Timeless timeless circadian clock 1 Timp1 tissue inhibitor of metalloproteinase 1 Tle3 transducin-like enhancer of split 3 Tlr2 toll-like receptor 2 Tlr4 toll-like receptor 4 Tlr7 toll-like receptor 7 Tm4sf1 transmembrane 4 superfamily member 1 Tmc7 transmembrane channel-like gene family 7 Tmcc3 transmembrane and coiled coil domains 3 Tmem100 transmembrane protein 100 Tmem119 transmembrane protein 119 Tmem144 transmembrane protein 144 Tmem173 transmembrane protein 173 Tmem204 transmembrane protein 204 Tmem206 transmembrane protein 206 Tmem37 transmembrane protein 37 Tmem64 transmembrane protein 64

Tmem88b transmembrane protein 88B Tnf tumor necrosis factor Tnfrsf10b tumor necrosis factor receptor superfamily, member 10b Tnfrsf11b tumor necrosis factor receptor superfamily, member 11b (osteoprotegerin) Tnfrsf12a tumor necrosis factor receptor superfamily, member 12a Tnfrsf13c tumor necrosis factor receptor superfamily, member 13c Tnfrsf17 tumor necrosis factor receptor superfamily, member 17 Tnfrsf1a tumor necrosis factor receptor superfamily, member 1a Tnfrsf1b tumor necrosis factor receptor superfamily, member 1b Tnfrsf25 tumor necrosis factor receptor superfamily, member 25 Tnfrsf4 tumor necrosis factor receptor superfamily, member 4 Tnfsf10 tumor necrosis factor (ligand) superfamily, member 10 Tnfsf12 tumor necrosis factor (ligand) superfamily, member 12 Tnfsf13b tumor necrosis factor (ligand) superfamily, member 13b Tnfsf4 tumor necrosis factor (ligand) superfamily, member 4 Tnfsf8 tumor necrosis factor (ligand) superfamily, member 8 Top2a topoisomerase (DNA) II alpha Topbp1 topoisomerase (DNA) II binding protein 1 Tpd52 tumor protein D52 Tpsb2 tryptase beta 2 Tradd TNFRSF1A-associated via death domain Traf1 TNF receptor-associated factor 1 Traf2 TNF receptor-associated factor 2 Traf3 TNF receptor-associated factor 3 Traf6 TNF receptor-associated factor 6 Trat1 T cell receptor associated transmembrane adaptor 1 Trem1 triggering receptor expressed on myeloid cells 1 Trem2 triggering receptor expressed on myeloid cells 2 Trem3 triggering receptor expressed on myeloid cells 3 Trim47 tripartite motif-containing 47 Trp53 transformation related protein 53 Trp53bp2 transformation related protein 53 binding protein 2 Trp73 transformation related protein 73 Trpa1 transient receptor potential cation channel, subfamily A, member 1 Trpm4 transient receptor potential cation channel, subfamily M, member 4 Tspan18 tetraspanin 18 Ttr transthyretin Tubb3 tubulin, beta 3 class III Tubb4a tubulin, beta 4A class IVA Txnrd1 thioredoxin reductase 1 Tyrobp TYRO protein tyrosine kinase binding protein Ugt8a UDP galactosyltransferase 8A Ulk1 unc-51 like kinase 1 Ung uracil DNA glycosylase

Uty ubiquitously transcribed tetratricopeptide repeat gene, Y chromosome Vamp7 vesicle-associated membrane protein 7 Vav1 vav 1 oncogene Vegfa vascular endothelial growth factor A Vim vimentin Vps4a vacuolar protein sorting 4A Vps4b vacuolar protein sorting 4B Was Wiskott-Aldrich syndrome Wdr5 WD repeat domain 5 Xcl1 chemokine (C motif) ligand 1 Xiap X-linked inhibitor of apoptosis Xrcc6 X-ray repair complementing defective repair in Chinese hamster cells 6 Zbp1 Z-DNA binding protein 1 Zfp367 zinc finger protein 367

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