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Common Factors in Neurodegeneration: a Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

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Common Factors in Neurodegeneration: a Meta-Study Revealing Shared Patterns on a Multi-Omics Scale cells Article Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale 1,2, 1, 1 1, Nicolas Ruffini y , Susanne Klingenberg y, Susann Schweiger and Susanne Gerber * 1 Institute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, Germany; Nicolas.Ruffi[email protected] (N.R.); [email protected] (S.K.); [email protected] (S.S.) 2 Leibniz Institute for Resilience Research, Leibniz Association, Wallstraße 7, 55122 Mainz, Germany * Correspondence: [email protected]; Tel./Fax: +49-(0)-6131-39-27331 These authors contributed equally to this work. y Received: 16 October 2020; Accepted: 4 December 2020; Published: 8 December 2020 Abstract: Neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources. Keywords: multi-omics; Alzheimer’s disease; Parkinson’s disease; Huntington’s disease; amyotrophic lateral sclerosis; neurodegeneration Cells 2020, 9, 2642; doi:10.3390/cells9122642 www.mdpi.com/journal/cells Cells 2020, 9, x 2 of 33 Cells 2020, 9, 2642 2 of 35 1. Introduction 1. Introduction Neurodegenerative diseases (NDDs), including Alzheimer’s disease, Parkinson’s disease, amyotrophicNeurodegenerative lateral sclerosis, diseases and (NDDs),Huntington’s including disease, Alzheimer’s are heterogeneous, disease, progressive Parkinson’s diseases disease, characterizedamyotrophic by lateral a loss sclerosis, of neurons, and Huntington’san accumulation disease, of aggregated are heterogeneous, and misfolded progressive proteins diseases [1–4], cognitivecharacterized decline by aand loss locomotive of neurons, dysfunction an accumulation [5–7]. Despite of aggregated decades andof research misfolded and proteins considerable [1–4], progresscognitive declinein identifying and locomotive risk genes, dysfunction potent bi [5–omarkers,7]. Despite and decades environmental of research risk and considerablefactors, this progressionprogress in identifying cannot be riskimpeded. genes, potentAs details biomarkers, regarding and the environmental various (patho-)physiological risk factors, this progression processes associatedcannot be impeded.with neurodegenerative As details regarding diseases the variousremain (patho-)physiologicalunclear, the diseases are processes still incurable. associated At with the sameneurodegenerative time, it has become diseases generally remain accepted unclear, thethat diseases the underlying are still incurable.mechanisms At are the polyfactorial same time, it and has dependbecome on generally the complex accepted interplay that theof multiple underlying (partly mechanisms unknown) aregenetic polyfactorial and non-genetic and depend variables on the[8– 14].complex interplay of multiple (partly unknown) genetic and non-genetic variables [8–14]. InfluencesInfluences onon thethe developmentdevelopment of of NDDs NDDs can can be be classified classified into into broader broader functional functional groups groups based based on ontheir their primary primary site orsite mode or mode of action of intoaction intracellular into intracellular mechanisms, mechanisms, local tissue local environment tissue environment influences, influences,and systemic and influences systemic influences [15]. These [15]. pathways These pathways and mechanisms and mechanisms are highly are highly related related and can and have can haveoverlapping overlapping or interacting or interacting components components that can that collectively can collectively modulate modulate neurodegenerative neurodegenerative processes. Weprocesses. slightly We adapted slightly this adapted categorization this categorizatio based onn Ramanan based on [Ramanan15], and depict [15], and the processesdepict the associatedprocesses withassociated each ofwith the each three of categories the three incategories Figure1. in Candidate Figure 1. pathways Candidate influencing pathways theinfluencing balance ofthe neuronal balance ofsurvival neuronal and degenerationsurvival and withindegeneration the cell arewithin misguided the cell apoptosis are misguided and autophagy apoptosis [16 ,17and], dysfunctionautophagy [16,17],in mitochondria dysfunction [18– 20in], mitochondria various forms [18–20], of cell stressvarious [15 ,21forms,22], defectiveof cell stress cytoskeletal [15,21,22], proteins defective and cytoskeletalimpaired protein proteins expression and impaired regulation protein [23– 26expre]. Withinssion regulation the local tissue [23–26]. environment, Within the impaired local tissue cell environment,adhesion pathways impaired lead tocell limited adhesion neurotransmission pathways lead and cellto proliferation,limited neurotransmission a permeable blood–brain and cell proliferation,barrier (BBB), anda permeable dysfunctional blood–brain extracellular barrier matrices (BBB), (ECMs) and dysfunctional [27–29]. Excessive extracellular immune responsematrices (ECMs)and inflammation [27–29]. Excessive [30–33] andimmune a dysregulated response and lipid inflammation and sugar metabolism [30–33] and lead a dysregulated to disturbances lipid in and the wholesugar metabolism systemic environment lead to disturbances [34–36]. in the whole systemic environment [34–36]. Figure 1. ClassificationClassification of candidate pathways contribu contributingting to neurodegeneration into three groups according to their cellular mechanisms or their primaryprimary site of action. The categorization is based on Ramanan’s pathways to neurodegeneration [[15]15] and aimsaims to help in classifying classifying the current current knowledge knowledge surrounding neurodegeneration. By far the most prevalent of NDDs, Alzheimer’s di diseasesease (AD) is an an inexorably inexorably progressive progressive brain disorder that aaffectsffects higherhigher cognitivecognitive functionsfunctions [[37–39].37–39]. The accumulation of abnormally folded extracellular β-amyloid (senile plaques) and intracellular phosphorylated tau (neurofibrillary Cells 2020, 9, 2642 3 of 35 extracellular β-amyloid (senile plaques) and intracellular phosphorylated tau (neurofibrillary tangles) proteins are the distinctive pathological hallmarks of the disease that might trigger synaptopathies, glial inflammation and eventually neuronal death in the cerebral cortex, subcortical regions, temporal and parietal lobes and cingulate gyrus [40–42] and even effects the gut microbiome [43]. Parkinson’s disease (PD) is the second most common neurodegenerative disorder, mainly affecting the motor system [44,45]. The aggregation of α-synuclein into Lewy bodies and Lewy neurites, primarily in the substantia nigra pars compacta, and the resulting loss of dopaminergic neurons leads to distinctive symptoms including resting tremors, bradykinesia, stooped posture and, in some cases, dementia [46–48]. Huntington’s disease (HD) is a progressive neurodegenerative disease that can lead to chorea, cognitive decline, psychiatric disorders
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