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Alzheimer’s disease (AD) genes: Enrichment in cancer genes and those related to comorbid conditions, risk factors (pollution and pathogens) or beneficial agents (NSAIDs and statins). Endogenous compounds related to AD genes target immune and antimicrobial defence.

C.J.Carter

41C Marina, Saint Leonard’s on Sea, East Sussex, TN38 0BU, UK

Email [email protected]

Tel: 0044 (0)7854659602

Abstract

Alzheimer’s disease (AD) GWASdb genes (N=1591) were analysed for enrichment versus other disease genes or the host genes of 18 host/pathogen interactomes (viral, bacterial, fungal and protozoan). AD gene/Chemical enrichment was analysed using the Comparative Toxicogenomics Database. AD incidence inversely associates with cancer and AD genes are enriched in cancer genes and in genes affected by carcinogenic or antineoplastic agents. Host/pathogen interactomes were enriched in AD genes, which were also targeted by mycotoxins. Many cancers are pathogen-related. AD genes may convey resistance to pathogens and the Cancer/AD inversion may pivot around this effect. AD genes were enriched in genes for type 2 diabetes, cardiovascular diseases, lipid metabolism disorders, arteriosclerosis, obesity, mood disorders and immune system or infectious diseases. Genes affected by NSAID’s and statins or antidiabetic drugs (PPAR ligands) and dietary polyphenols (all with antimicrobial activity) were also enriched in AD genes. Other drugs targeting AD genes affect sex steroids, retinoid and thyroid hormones and include immunosuppressants and anticonvulsants. AD genes were enriched in genes related to 28 endogenous compounds (retinoids, estrogens, progesterone, corticosterone, calcitriol, vitamins C and D3, folate, methionine and choline, an endogenous aryl hydrocarbon receptor ligand (ITE) and compounds related to oxidative stress. Most could be linked to immune regulation and many, like beta-amyloid, have antimicrobial properties (N-acetyl cysteine, Glutathione, Lithocholic acid, melatonin, Nitric oxide, iron/ascorbic acid, iron/O2 , H2O2, arachidonic and hypochlorous acids) These compounds selectively target immune and pathogen pathways. AD genes were also enriched in genes affected by AD risk factors (dietary fats/sucrose, pesticides, metals, vehicle emissions or smoking and other pollutants. The analysis highlights AD gene subsets related to AD comorbidities, risk factors or beneficial agents. Endogenous chemicals targeted by the AD genes are dedicated to the immune system and 2 specifically to antimicrobial defence. Antimicrobial drugs may aid these endogenous agents and could also be of benefit in AD.

Key words: Alzheimer’s disease; gene/environment; pathogens; microbes; pesticides; pollution; heavy metals, anti-inflammatory agents; cancer; type 2 diabetes; cardiovascular disease; antimicrobial

Introduction

Alzheimer’s disease (AD) has been associated with multiple pathogens (Itzhaki et al. 2016) and bacteria including chlamydia pneumoniae (Gerard et al. 2006) , Treponema’s and spirochetes (Miklossy 2011) the oral pathogen Porphyromonas gingivalis (Dominy et al. 2019) and many other bacteria (Emery et al. 2017) have been detected in the AD brain. Diverse fungi (Pisa et al. 2017;Pisa et al. 2015) or viruses (herpes viruses HSV-1, HSV-6, HSV-7 ) (Readhead et al. 2018;Itzhaki 2017) and hepatitis (MastroeniB et al. 2018) have also been detected in post-mortem AD brains. Many of these pathogens promote beta-amyloid (Aβ) deposition as well as tau phosphorylation (Carter 2017). Aβ is a potent antimicrobial agent with broad-spectrum activity against bacteria, fungi and viruses (Soscia et al. 2010;Bourgade et al. 2016) and its deposition in AD is likely to be a response to cerebral pathogen invasion. Previous studies have shown that AD genes, as well as the proteins found in AD plaques and tangles are enriched in genes used by multiple bacterial, fungal and viral pathogens. They are also enriched in genes related to global pathogen diversity. Other AD risk factors (age, alcohol, aluminium, concussion, cerebral hypoperfusion, diabetes, homocysteine, hypercholesterolemia, hypertension, obesity, pesticides, pollution, physical inactivity, sleep disruption, smoking) promote blood-brain barrier disruption) while the BBB benefits from statins, non-steroidal anti-inflammatory agents (NSAIDs), estrogen, melatonin, memantine, and the Mediterranean diet, each of which have been reported to be of benefit or to reduce the incidence of AD. Many AD genes are localised in immune cells and tissues and converge on processes related to Aβ production. It has been suggested that the AD genes convey resistance to pathogens, as supported by the old age of AD patients, but the benefit they afford becomes detrimental if pathogens are allowed to reach the brain. Essentially, a combination of immunosenescence, which leads to diminished immune capacity and to heightened innate immune/inflammatory mechanisms (Martorana et al. 2012) and a hyperefficient antimicrobial effect of the AD genes promotes excessive Aβ production and associated collateral inflammatory damage (Carter 2017).

Alzheimer’s disease has been associated with Type 2 diabetes mellitus (Shinohara and Sato 2017), periodontal disease (Pritchard et al. 2017;Carter et al. 2017) and with atherosclerosis of the carotid or circle of Willis and other cerebral arteries (Xiang 2017;Xu et al. 2015;Beach et al. 2007;Kalback et 3 al. 2004) and with other cardiovascular disorders and their associated conditions (Love and Miners 2016;Attems and Jellinger 2014).

In contrast, the incidences of cancer and Alzheimer’s disease are inversely related (Shafi 2016;Snyder et al. 2017). Rheumatoid arthritis has also been inversely associated with Alzheimer’s disease incidence (Policicchio et al. 2017) .

Several studies have shown that anti-rheumatic agents and non-steroidal anti-inflammatory drugs (NSAIDS) can delay the progression or reduce the incidence of Alzheimer’s disease (McGeer et al. 2018;McGeer et al. 2016;White et al. 2017;Heneka et al. 2015;Hoozemans et al. 2011). Two meta- analyses have supported these effects in observational studies but not in randomly controlled trials (Zhang et al. 2018a;Wang et al. 2015b)

There is some evidence that statins (HMG Co a reductase inhibitors and cholesterol lowering agents) may reduce the incidence or slow the progression of Alzheimer’s disease (Haag et al. 2009;Williams 2015;Wong et al. 2013), although large meta-analyses have cast some doubt on their effectiveness and their benefit may be slight (McGuinness et al. 2016;Mejias-Trueba et al. 2018). These effects may be gene-dependent and simvastatin was more effective in APOE4 carriers (Geifman et al. 2017).

A number of studies have linked metals to AD. Arsenic levels in topsoil have been related to the prevalence and mortality of Alzheimer's disease and other dementias in Europe (Dani 2010). A recent meta-analysis has reported that blood levels of aluminium, mercury, and cadmium are significantly higher while levels of lead were reduced in AD patients (Xu et al. 2018b). High levels of cerebral iron, particularly in myelin areas and disrupted iron homoeostasis have also been reported in AD (Liu et al. 2018;Bulk et al. 2018). Air pollution has also been linked to a higher risk of dementia (Carey et al. 2018) A meta-analysis has also supported an association of pesticides with the incidence of Alzheimer’s disease (Yan et al. 2016).

In this study, the relationship between AD genes and these various comorbid conditions, pathogens or environmental risk factors was examined using AD susceptibility genes and three extensive databases. The genome-wide association database (GWASdb) contains over ten thousand significant trait/disease associated SNP’s from 435 diseases as classified by disease ontology (P-values < 1.0 × 10-3 ) (Li et al. 2012) http://jjwanglab.org/ gwasdb . The comparative toxicogenomics database currently contains over 40 million chemical/gene interactions (Davis et al. 2017) (CTD; http://ctdbase.org/ ). The manually curated host/pathogen interactomes (HPI) for 18 diverse bacterial (Chlamydia pneumoniae (C.Pneumoniae), Helicobacter pylori (H.Pylori), Borrelia burgdorferi, (Borrelia), Porphyromonas gingivalis (P.Ging), viral (Bornavirus , Dengue virus; Ebola 4 virus, herpes simplex (HSV-1); Human cytomegalovirus (HCMV) ,Epstein barr (EBV), influenza A (INF), hepatitis C (HepC) viruses , HERV-W and human immunodeficiency (HIV-1) retro viruses, fungi (Cryptococcus Neoformans (C.neo), Candida albicans (C.Alb), and others (Toxoplasma Gondii (T.Gondii) and Trypanosoma Cruzi (T.cruzi) are available at http://www.polygenicpathways.co.uk/hpi.htm. GWASdb contains 1591 AD genes and these were cross-referenced with genes associated with other diseases (GWASdb), chemicals and drugs (CTD) and host/pathogen interactomes (HPI). Any over-representation of other disease genes, chemicals of pathogen interactomes with the AD gene dataset was subjected to statistical analysis.

Methods

The GWASdb database contains curated data for multiple diseases, with a P value cut-off of P < 1.0 x 10-3 (Li et al. 2012) and this was downloaded for analysis. GWASdb contains 1591 Alzheimer’s disease (AD) genes, and AD gene overlaps with other disease gene sets were identified. GWASdb can be downloaded from http://jjwanglab.org/gwasdb or from the Harmonizome database http://amp.pharm.mssm.edu/Harmonizome/ (Rouillard et al. 2016) .

This list of 1591 Alzheimer’s disease genes was uploaded to the comparative toxicogenomics database (Davis et al. 2017) (CTD; http://ctdbase.org/ ) and curated gene/chemical interactions were downloaded in batch. The output provides a list of chemicals associated with each gene and was restricted to human, rat and mouse data. The number of AD genes affected by each chemical was assessed and the total number of genes affected by each compound re-interrogated at CTD. Chemicals were grouped into families (e.g. pesticides, metals, pollutants, hormones, drug type) using diverse internet resources as previously described (Carter and Blizard 2016).

The manually curated host/pathogen datasets for diverse bacteria, viruses, fungi and protozoa are available at http://www.polygenicpathways.co.uk/hpi.htm The distribution of the autism genes in the cortex and hippocampus, immune organs and cell types was analysed using Funrich which accesses genomic and proteomic expression data from > 1.5 million annotations (Pathan et al. 2015) http://www.funrich.org/ ). The genes expressed in aged microglia are from a recent transcriptome analysis of microglia isolated from the human brain (Olah et al. 2018). Blood brain barrier genes are from a proteomics study of mouse cerebral arteries from the Circle of Willis (Badhwar et al. 2014).

Pathway enrichment analysis was performed using the Consensus path database (CPDB) (Kamburov et al. 2009). (http://cpdb.molgen.mpg.de/CPDB ) 5

Statistics

Assuming 26846 total human genes and 1591 Alzheimer’s disease genes, one would expect 1591 /26846 (5.9%) to be present in any other dataset (e.g. other disease susceptibility genes, host genes of the pathogen interactomes or the genes affected by each chemical). The expected number of genes = 5.9% of the total number of genes affected by the pathogen or compound. Observed/expected (O/E) ratios were calculated and the significance of enrichment assessed using the hypergeometric test. P values were corrected for false discovery (FDR) to give q values (Benjamini and Hochberg 1995) .

The statistical analysis for pathway enrichment is provided in the files downloaded from CPDB and uses the same hypergeometric test corrected for false discovery.

Results

The distribution of the Alzheimer’s disease genes.

While a large number of AD genes are expressed in the hippocampus and cortex, similar numbers are expressed in immune-related organs (spleen, bone marrow, tonsils, appendix, nasopharynx salivary glands, lymph nodes and to a lesser extent the thymus) as well as in barrier systems (skin and blood-brain barrier).They were also expressed in a number of immunocompetent blood cells (Leukocytes, lymphocytes, monocytes, B and T cells, neutrophils, dendritic cells and macrophages). A similar number, in relation to these blood cells, are also expressed in aged human microglia. This confirms and extends previous data from a smaller GWAS dataset of 78 AD genes with more stringent genome-wide significance (Carter 2017).

Fig 1. The distribution of the AD genes (of 1591) in diverse regions and immunocompetent cells. The data are from Funrich, or from a proteomic analysis of Circle of Willis arteries (BB- barrier = Blood brain barrier) and a transcriptome analysis of aged human microglia. Blood brain barrier and microglial sets are highlighted in black.

Figure 1 6

GWASdb: Other disease susceptibility genes within the Alzheimer’s disease gene dataset.

The 1591 AD genes were significantly over-represented in cancer, type 2 diabetes and cardiovascular disease (CVD) genes (q = zero), and in genes related to hypertension, coronary artery disease, arteriosclerosis and lipid metabolism disorders (q< 1E-70). Almost half of the AD GWASdb genes (744/1591= 46.7%) have also been associated with cancer. As noted above, there is an inverse correlation between cancer and AD and associations between AD, T2DM and cardiovascular disorders. The individual cancers significantly over-represented in this dataset included, breast, lung, prostate, head and neck, intestinal and testicular cancer as well as leukaemias and lymphoma (q < 7E-30). There are also clear inter-relations between AD, T2DM, CVD and lipid metabolism (Chornenkyy et al. 2019). Other over-represented disorders in Fig 2 have also been associated with AD, including obesity (Alford et al. 2018;Pugazhenthi et al. 2017), kidney disease (Shi et al. 2018). Connective tissue contains collagen and other fibres, as well as immune cells (fibroblasts, adipocytes, macrophages, mast cells and leucocytes). It is found in many areas including the meninges and choroid plexus which play an important role in blood brain and blood cerebrospinal fluid barrier formation (Patel and Kirmi 2009;Marques and Sousa 2015) . Blood brain barrier breakdown is observed in AD and precedes dementia and neurodegeneration (Montagne et al. 2017). The 7 incidence of rheumatoid arthritis has been inversely correlated with AD incidence (Ferraccioli et al. 2012;Policicchio et al. 2017), while osteoarthritis has been reported as a risk factor (Wang et al. 2018) . The use of anti-inflammatory drugs in rheumatoid arthritis may contribute to the inverse association (McGeer et al. 2016). Asthma has also been associated with an increased risk of developing dementia or AD (Chen et al. 2014). Psychiatric disorders, including bipolar disorder, depression and schizophrenia are also relatively frequent comorbidities in AD (Garcez et al. 2015). Immune and infection related diseases were also enriched in AD genes.

Within this large dataset of AD genes there thus exist subsets of genes associated with known AD risk factors and comorbidities, as well as with genes for diseases inversely associated with AD. The inverse association between cancer and AD in particular would thus appear to be gene-related rather than due to early death precluding the subsequent development of AD in old age. (i.e. Certain AD genes may exert a protective effect in some types of cancer).

Fig 2. The number of GWASdb genes for various diseases significantly overlapping with 1591 AD genes. The bars represent the number of overlapping genes (left Y axis) and the dotted line the FDR corrected q values (right Y axis) Each disease label is followed by the observed/expected ratio for the overlap with AD genes, then by the total number of GWASdb genes for that disease (e.g. Cancer| 7.9 | 3403). T2DM = type 2 diabetes mellitus; CVD = cardiovascular system disease; CAD = coronary artery Disease; MSKD = musculoskeletal system Disease; ConTisD = connective tissue disease; Lipid MD = lipid metabolism disorders.GI = gastrointestinal; Dis = disease. The first 3 diseases (cancer T2DM and CVD) returned a significance q value of zero and the logarithmic q value minimum is set to 1E-250.

Figure 2 8

3.3 Pathogens and mycotoxins targeting Alzheimer’s disease genes

All of the pathogen interactomes tested (viruses, bacteria, fungi and protozoans), with the exception of the Ebola virus, targeted the Alzheimer’s disease genes, extending previous data that used a smaller set of 78 highly significant GWAS AD genes (Carter 2017). The Epstein-Barr virus, P. gingivalis and the cytomegalovirus were the three most significant overlaps. In the light of the above data linking AD and cancer genes, cancer genes within the genes common to host/pathogen interactomes and AD are also shown in Fig 2. Cancer genes are present in 744/1591 AD genes (46.7%) and one would expect a similar percentage within the AD/pathogen overlaps. This figure was significantly exceeded for the Epstein - Barr virus (O/E = 1.21; q =1.9E-05), H. pylori (O/E= 1.2: q = 0.03) , P.gingivalis (O/E= 1.15; q = 0.0016); C.neoformans (O/E= 1.13 q = 0.03) and HCMV (O/E= 1.09, q= 0.003 but not for others. A number of these pathogens, including the Epstein Barr virus, hepatitis C, HIV-1 and Helicobacter pylori are classified as oncogenic by the International Agency for Research on Cancer (Yasunaga and Matsuoka 2018). Other pathogens, not generally considered as oncogenic have nevertheless been associated with cancers, or are considered as oncomodulatory including P. gingivalis (Oral, digestive tract and pancreatic cancers ) (Olsen and Yilmaz 2019), HCMV (Breast and 9 colorectal cancer) (Herbein 2018;Pasquereau et al. 2017;Bai et al. 2016). Gondii infections have been described as a risk factor in brain and oral cancers as well as in leukaemia (Thomas et al. 2012;Zhou et al. 2018b;Huang et al. 2016;Vittecoq et al. 2012) , but and oncogenic potential has been little studied. The influenza virus is not considered as oncogenic, but influenza and other pathogens can enhance tumour growth and increase host mortality in cancer-bearing mice (Kohlhapp et al. 2016).

If, as suggested (Carter 2017), the AD genes initially convey resistance to pathogens, it is conceivable that the inverse correlation between cancer and AD pivots around an ability to also counter infection by oncogenic pathogens.

Several mycotoxins including ochratoxin (from aspergillus and penicillium species), zearalenone (from Giberella and fusarium species) and particularly Aflatoxin B1 (from aspergillus)( which also possesses carcinogenic properties (Marchese et al. 2018) ) , as well as ciguatoxins (from dinoflagellates), incobotulinumtoxin A (from Clostridium botulinum) and cylindrospermopsin (from cyanobacteria) targeted the AD genes. There has been little work on these toxins in relation to Alzheimer’s disease. However, the effects of these mycotoxins concords with the recent description of inhalational Alzheimer’s disease, a phenotypic manifestation of chronic inflammatory response syndrome (CIRS). A number of patients fulfilling diagnostic criteria for both Alzheimer's disease and CIRS were found to have been exposed to Aspergillus, penicillium and other fungal species, in the home (Bredesen 2016). Penicillium varieties are one of many fungal species that have been detected in the AD brain (Alonso et al. 2014). Aflatoxin B1

Fig 3: The number of host genes of diverse host/pathogen interactomes significantly overlapping with 1591 AD genes. The number of overlapping genes affected by Mycotoxins and ciguatoxins are also shown on the right (from CTD data). The bars represent the number of overlapping genes (left Y axis) and the dashed line the FDR corrected q values (right Y axis). The overlaps for cancer genes common to both the pathogen interactomes and the AD genes are also shown by the dotted line. Each pathogen label is followed by the observed/expected ratio for the overlap with AD genes, then by the total number of interactome genes for that pathogen EBV = Epstein-Barr virus; P.ging = Porphyromonas gingivalis; HCMV = human cytomegalovirus; T.Cruzi = Trypanosoma cruzi; C.neoformans = Cryptococcus Neoformans; HSV-1 = herpes simplex virus 1; Dengue = Dengue virus; HepC = hepatitis C virus; Borrelia = Borrelia burgdorferi; HIV = human immunodeficiency virus; T. Gondii = Toxoplasma Gondii; HERV-W = human endogenous retrovirus W ; Influenza = Influenza A virus; C. albicans = Candida albicans; H. pylori = Helicobacter pylori; C.Pneumoniae = Chlamydia pneumoniae. IncoBotox = incobotulinumtoxin A; Deoxyniv = deoxynivalenol; cylindroSP = 10 cylindrospermopsin. Aflatoxin B1 affected 937/1591 AD genes and the left Y axis has been cut to better illustrate the effects of others.

Figure 3

3.4 Immune and antimicrobial properties of Endogenous compounds targeting Alzheimer’s disease genes.

The relationships between diverse endogenous hormones and other compounds are shown in Fig 4, which is restricted to compounds affecting > 20 AD genes. 11

Several of these compounds are relevant to the immune system and possess or control antimicrobial defences. For example, glutathione is a potent antioxidant, derived from N-acetyl cysteine, and also has antiviral effects (Fraternale et al. 2009). N-acetylcysteine also possesses antimicrobial properties against biofilm phenotypes of Gram-positive and Gram-negative bacteria (Dinicola et al. 2014). Reduced brain levels of glutathione have been reported in the AD frontal cortex and hippocampus (Mandal et al. 2015). A compound that increases cellular glutathione levels (Shah et al. 2015) (1-(2-cyano-3,12-dioxooleana-1,9-dien-28-oyl) imidazole) also targeted the AD genes (O/E = 2.7; q =0.0001).

Tretinoin (all-trans retinoic acid), a component of vitamin A, also targets viruses via its ability to increase the expression of interferon-stimulated genes (ISGS), many of which have antiviral activity . Tretinoin enhances the production of ISGS in response to viral infection and also potentiates the effects of interferon (Cho et al. 2016).Tretinoin also controls the expression of retinoic acid-inducible gene-I-like receptors (RLRs). These are intracellular pattern recognition receptors reacting to viral DNA or RNA by activation of proinflammatory agents and appropriate immune defence (Matsumiya et al. 2011). Two studies have noted a significant reduction of Vitamin A levels in in Alzheimer’s disease serum (Jimenez-Jimenez et al. 1999;Zaman et al. 1992). Retinoids possess several properties relevant to AD, including beneficial effects in relation to the cholinergic system or on amyloidogenesis, and their therapeutic use has been suggested but not yet tested (Szutowicz et al. 2015;Lerner et al. 2012).

Calcitriol (1,25-dihydroxyvitamin D3), the active form of vitamin D, acting via its receptor (VDR) stimulates the innate immune response by enhancing the chemotactic and phagocytic activity of macrophages and the production of antimicrobial peptides (Miraglia et al. 2018). Low serum levels of vitamin D are associated with diminished cognition in the elderly and in Alzheimer’s disease (Lu'o'ng and Nguyen 2013;Lu'o'ng and Nguyen 2011;Dickens et al. 2011).

Lithocholic acid is a bile acid which also acts as a Vitamin D receptor ligand. It stimulates the production of the antimicrobial peptide Cathelicidin in epithelial cells via VDR activation (Peric et al. 2009). Lithocholic acid also activates the Pregnane-X-Receptor (PXR, NR1I2), the G-protein bile acid receptor 1 (GPBAR1), Sphingosine-1-phosphate receptor 2 (S1PR2) and muscarinic acetylcholine receptors (CHRM2, CHRM3). It is a weak ligand for the Farnesoid-X-Receptor (NR1H4/FXR). GPBAR1 or FXR activation blunts the inflammatory activity of macrophages and also inhibits the NLRP3 inflammasome (Fiorucci et al. 2018). Lithocholic acid also has antibacterial (do Nascimento et al. 2015) and antifungal effects and inhibits the growth of Candida albicans in vitro (Guinan et al. 12

2018).Lithocholic acid plasma levels are increased in Alzheimer’s disease patients and this has been suggested as a reliable biomarker(Marksteiner et al. 2018) .

ITE = 2-(1'H-indolo-3'-carbonyl)thiazole-4-carboxylic acid methyl ester) is an endogenous nontoxic aryl hydrocarbon receptor (AHR) ligand (Zamali et al. 2018). AHR is a target of many of the pollutants that also target the AD genes (see below). An exogenous AHR ligand, Indole-3-carbinol, a breakdown product from cruciferous vegetables (Marconett et al. 2010) also targeted the AD genes ( O/E= 1.19; q = 0.01).The aryl hydrocarbon receptor is involved in xenobiotic detoxification, but also plays an important role in the immune system and in pathogen defence. Activation by endogenous ligands regulates the activity of macrophages, dendritic cells and neutrophils in response to bacterial lipopolysaccharide or influenza virus infection. AHR is also involved in B cell maturation and for the postnatal maintenance of intestinal intraepithelial lymphocytes and skin-resident dendritic epidermal gamma delta T cells (Hao and Whitelaw 2013). In the brain, astrocytic AHR activation by endogenous ligands plays an anti-inflammatory role (Rothhammer et al. 2016) .Estradiol also controls the innate immune system and can exert pro- or anti-inflammatory effects, depending on concentration. It has been suggested that declining estradiol levels post-menopause contribute to immunosenescence in women (Giefing-Kroll et al. 2015). Estradiol increases the production of antimicrobial peptides in epithelial cells an effect that counters bacterial infection (Medina-Estrada et al. 2018). In the brain, estrogen and progesterone are generally neuroprotective and anti- inflammatory with the potential to reduce inflammasome activity in pro-inflammatory conditions (Slowik and Beyer 2015;Lammerding et al. 2016;Slowik et al. 2018). They are also able to switch microglia from a pro-inflammatory M1 to a neuroprotective M2 phenotype (Habib and Beyer 2015). The neuroprotective potential of Estradiol is well recognised and Estradiol therapy in Alzheimer’s disease may be of some benefit, particularly in menopausal women (Lan et al. 2016).

The glucocorticoid stress hormone corticosterone plays an important role in the immune system. Corticosterone impairs the dendritic cell maturation and function as well as the efficiency with which antigen is presented by dendritic cells to cytotoxic T-lymphocytes in the circulation. These lymphocytes are an essential defence against invading pathogens. These effects lead to increased mortality due to viral infection in corticosterone treated mice(Truckenmiller et al. 2006;Elftman et al. 2007). With regard to the brain/hypothalamic–pituitary–adrenal (HPA) axis, pro-inflammatory cytokines stimulate the release of glucocorticoids which in turn reduces the production of pro- inflammatory cytokines (Silverman and Sternberg 2012)

Melatonin also has immunomodulatory effects and also possesses antimicrobial effects in relation to viruses, bacteria and protozoan parasites (Srinivasan et al. 2012;Daryani et al. 2018) .Melatonin 13 serum levels decline with age, an effect that is amplified in Alzheimer’s disease. It possesses many potential benefits in relation to AD pathology (Shukla et al. 2017) . A small number of clinical trials with melatonin have reported improvements in cognitive function in AD, although the effects on the overall pathologies are slight (Wade et al. 2014;Asayama et al. 2003).

Choline is a precursor for acetylcholine, but also an essential nutrient providing the substrate for the phospholipid phosphatidylcholine and , via betaine, to methionine (also targeted by the AD genes) and subsequently the methyl group donor S-adenosylmethionine (SAM) (Blusztajn et al. 2017). However acetylcholine, betaine and SAM only affected 8 AD genes and Phosphatidylcholines only 3 AD genes, with no significant enrichment. Choline has recently been identified as an endogenous intracellular agonist at Sigma-1 receptors (SIGMAR1), potentiating the calcium signals evoked by inositol 1,4,5-trisphosphate receptors (Brailoiu et al. 2019). Other Sigma-1 agonists or allosteric modulators can inhibit neuroinflammation and, in microglial cells, have been shown to inhibit the lipopolysaccharide induced release of pro-inflammatory cytokines (TNF and IL1B) and the generation of reactive oxygen species (Wu et al. 2015b).Other sigma-1 receptor agonists N,N- dimethyltryptamine (NN-DMT) and its derivative 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT) also inhibit the inflammatory effects of bacterial lipopolysaccharide (LPS) or the viral mimic polyinosinic: polycytidylic acid (polyI:C) producing a reduction in interleukins (IL1beta and IL6) and TNF, and an increase in anti-inflammatory IL10 levels (Szabo et al. 2014). Activation of SIGMAR1 provides neuroprotection in cellular and animal models of neurodegenerative diseases or brain ischaemia. Neuroprotection is believed to be due to inhibition of cellular calcium toxicity and inflammation (Ruscher and Wieloch 2015) .Choline is an essential nutrient and also has neuroprotective effects (Blusztajn et al. 2017) .

Choline or methionine deficiency both produce natural killer cell (NKC) loss or reduced NKC cytotoxicity (Sagami et al. 2017;Li et al. 2016) Methionine levels have been reported to be reduced in AD serum and cerebrospinal fluid (Gonzalez-Dominguez et al. 2014;Molina et al. 1998). Methionine can also be converted to cysteine and thence to glutathione in hepatocytes (Martinez et al. 2017).

Oxidative stress is a feature of AD and other degenerative conditions (Tonnies and Trushina 2017) and a number of the endogenous compounds targeting the AD genes relate to this area. The respiratory burst stimulated by phagocytosis and increased oxygen uptake in macrophages and neutrophils generates potent antimicrobial agents including hydroxyl radicals (HO•) and 14 hypochlorous acid. Nitric oxide and hydrogen peroxide are also released, both of which are antimicrobial agents (Knight 2000;Aribi 2018) . The Fenton reaction involving iron and hydrogen

2+ 3+ peroxide ( Fe + H2O2 → Fe + HO• + OH−) also contributes to the generation of antimicrobial hydroxyl radicals. Antioxidant compounds (ascorbic acid and selenium) are able to scavenge free radicals. 4-hydroxy-2-nonenal (HNE), also targeted by the AD genes, is a product of lipid peroxidation by free radicals. It is a toxic compound acting by covalent binding to proteins. Increased brain levels of HNE-adducts have been observed in a number of degenerative diseases, including Alzheimer’s disease (Di Domenico et al. 2017).HNE or reduced levels of glutathione are able to increase blood brain barrier permeability in a rat in vitro model (Mertsch et al. 2001). Ascorbic acid also possesses antiviral activity against HSV-1, influenza and the poliovirus , particularly in the presence of ferric Fe++ + ions, suggesting that this is due to hydroxyl radical generation (Furuya et al. 2008) .

Lower selenium levels have been reported in the AD temporal, hippocampal, and cortex regions (Varikasuvu et al. 2018), and selenium supplementation may have beneficial effects on cognitive and metabolic function in AD (Cardoso et al. 2018;Tamtaji et al. 2018). Selenium plays an important role in the immune system, particularly in relation to infection, where its effects combine to favour antiviral activity (Wrobel et al. 2016). Selenium supplementation promotes the proliferation of naive CD4-positive T lymphocytes and their development toward T helper 1 cells, thus supporting the acute cellular immune response. In contrast excessive activation of the immune system and collateral tissue damage are dampened by directing macrophages toward the M2 phenotype . These are involved in the resolution of inflammation and tissue repair(Steinbrenner et al. 2015).In the brain, selenium inhibits the stress-related migration of microglial cells (Dalla et al. 2007). In the triple transgenic AD mouse model, selenium improved spatial learning and memory retention. It also attenuated the activation of astrocytes and microglia, improved synaptic deficits, and reduced the levels tau phosphorylation (Zhang et al. 2017).

Arachidonic acid plays an important role in inflammatory processes, but it is also an effective antimicrobial agent with activity against gram-positive and negative bacteria, fungi, and enveloped viruses, including influenza and herpes simplex (Das 2018)..

Folate and other vitamins have many functions. In microglial cells, folic acid attenuates the release of proinflammatory cytokines in response to lipopolysaccharide (Cianciulli et al. 2016). In relation to immune defence, Vitamins A (Tretinoin) and C as well as zinc support the skin barrier, while vitamins A, B6, B12, C, D, E and folic acid and the trace elements iron, zinc, copper and selenium work together to support the protective activities of immune cells (Maggini et al. 2007). Vitamin C accumulates in phagocytic cells, (e.g. neutrophils and macrophages), and can enhance chemotaxis, 15 phagocytosis the generation of reactive oxygen species, and antimicrobial effects. It also augments the proliferation of both B- and T-cells (Carr and Maggini 2017). Zinc ions have also been shown to have antiviral effects against hepatitis C and E viruses and herpes simplex (Kaushik et al. 2018;Read et al. 2018;Hulisz 2004;Kumel et al. 1990) . Zinc supplementation has also been shown to promote protozoan, bacterial and fungal pathogen clearance in animal models. These effects may be related to promotion by zinc of macrophage phagocytic capacity (Stafford et al. 2013).

Ketone bodies also play an important role in the immune system. Beta-Hydroxybutyrate is a histone deacetylase inhibitor and upregulates gene involved in combatting oxidative stress and blocks the NLRP3 inflammasome, reducing the production of inflammatory cytokines and inflammation (Achanta and Rae 2017;Youm et al. 2015). In the brain it exerts anti-inflammatory actions by promoting microglial ramification (Huang et al. 2018).

Dopamine and noradrenaline were the only endogenous neurotransmitters significantly related to the AD genes, but their effects were relatively minor, each targeting fewer than 20 AD genes (not shown).

Fig 4: The number of 1591 AD genes that significantly overlap with the genes affected by endogenous compounds. The bars represent the number of overlapping genes (left Y axis) and the dotted line the FDR corrected q values (right Y axis). Each label (X axis) is followed by the observed/expected ratio for the overlap with AD genes, then by the total number of interactome genes affected by the compound. ITE = 2-(1'H-indolo-3'-carbonyl)thiazole-4-carboxylic acid methyl ester), a ligand for Ahr = aryl hydrocarbon receptor; 4-OH-2-nonenal = 4-hydroxy-2-nonenal; HClO = hypochlorous acid; H2O2 = hydrogen peroxide;

Figure 4 16

3.4.1 Endogenous AD gene-related compounds and the blood-brain barrier (BBB)

Endogenous compounds targeted by the AD genes are also concerned with BBB function. For example, ITE is an endogenous aryl hydrocarbon receptor (AHR) ligand. AHR is highly expressed in skin, intestinal, placental and blood brain barriers and plays an important role in maintaining their integrity (Esser and Rannug 2015;Juricek and Coumoul 2018). Glutathione also maintains BBB integrity (Agarwal and Shukla 1999). Retinoic acid is involved in the formation of the BBB (Mizee et al. 2013) and ameliorates BBB malfunction in stroke and spinal injury models (Mizee et al. 2013) . Estradiol also mitigates BBB disruption in cerebral ischaemia models (Xiao et al. 2018) and protects against BBB disruption produced by bacterial lipopolysaccharide or inflammatory cytokines (Maggioli et al. 2016) . Progesterone also ameliorates BBB malfunction in stroke and trauma models (Si et al. 2014;Wang et al. 2009) . Calcitriol prevents the decrease in brain endothelial barrier function produced by hypoxic injury in an in vitro BBB model (Won et al. 2015). Melatonin has been shown to alleviate BBB breakdown caused by lipopolysaccharide or glutamatergic excitotoxins (Wang et al. 2017b;Moretti et al. 2015). 17

3.4.1.1 Pathway analysis of the genes affected by the endogenous compounds targeted by the AD genes.

It is possible to upload a list of compounds to the Comparative toxicogenomics database. CTD recovers genes affected by each compound and subjects these to KEGG pathway enrichment analysis. This analysis is not restricted to AD genes and includes all other genes affected by the compounds. Each compound affects a number of genes within specific pathways and the significance of enrichment (q value) is provided by the output. For example, Tretinoin affects 71 genes in the KEGG Alzheimer’s disease pathway (enrichment q = 5.69E-29). From this table one can than calculate the number of endogenous compounds affecting each pathway and the median q values for the set of compounds. This provides an overall view of the pathways most commonly affected by the endogenous compounds.

The KEGG pathways common to most of the 28 endogenous chemicals identified from Fig 3 are shown in Tables 1(other disease pathways) and 2 (immune/inflammation and infection pathways). The disease pathways affected by these compounds were headed by “Pathways in cancer”. 23 other cancer pathways, including breast, lung, prostate, bladder, renal, thyroid, colorectal, endometrial cancers, glioma, melanoma and leukaemias (all q values < 2.85E-07). This concurs with the connection between cancer and AD genes described above. Rheumatoid arthritis has also been inversely associated with Alzheimer’s disease (Policicchio et al. 2017) and many endogenous compounds targeted this pathway (Table 1) .

Alzheimer’s disease has been associated with diabetes and atherosclerosis and these endogenous compounds target pathways related to these conditions. Age is the most prominent risk factor in Alzheimer’s disease and the longevity pathway was also targeted by many of these compounds. The processes in diabetes, the metabolic syndrome and Non-alcoholic fatty liver disease (NAFLD) have been associated with Alzheimer’s disease (de la Monte 2017;de la Monte and Tong 2014) and in mice peripheral inflammation caused by Chronic NAFLD induces advanced pathological signs of Alzheimer’s disease in wild-type or APP-Transgenic mice (Kim et al. 2016). Cardiomyopathy has not been associated with AD, but a recent report has shown diastolic dysfunction and Aβ deposition in the hearts of AD patients, suggesting cardiac involvement in AD(Troncone et al. 2016). The risk of developing dementia is increased by mid- or late-life asthma (Chen et al. 2014) and also by inflammatory bowel disease (Caini et al. 2016) and by a number of autoimmune diseases, including Systemic lupus erythematosus (Wotton and Goldacre 2017), which was also targeted by these endogenous compounds. Anaemia has also been associated with AD and contributes to cognitive dysfunction (Faux et al. 2014).The number of AD/endogenous chemicals related to these disorders 18 are shown in Table x. This includes other neurodegenerative disorders which share some of the features of Alzheimer’s disease processes.

Table 1: Enrichment analysis of the disease-related pathways affected by 28 endogenous compounds significantly related to the AD genes (from Fig 3). N = number of endogenous compounds involved (of 28); Q value = significance of enrichment.

Pathway N Q value

Pathways in Cancer 26 2.57E-59

Rheumatoid arthritis 25 1.21E-18

Diabetes

AGE-RAGE signalling pathway in diabetic 26 6.00E-35 complications

Insulin signalling pathway 24 3.65E-17

Insulin resistance 22 3.94E-23

Type II diabetes mellitus 20 1.24E-11

Type I diabetes mellitus 17 1.39E-06

Glucagon signalling pathway 16 1.32E-11

Insulin secretion 13 2.09E-06

Pancreatic secretion 12 6.52E-06

Maturity onset diabetes of the young 5 1.36E-03

Atherosclerosis

Fluid shear stress and atherosclerosis 25 6.88E-40

Other neurodegenerative conditions

Amyotrophic lateral sclerosis (ALS) 24 2.72E-13

Prion diseases 24 3.13E-09

Alzheimer's disease 23 7.67E-16

Huntington's disease 21 4.53E-14

Parkinson's disease 11 3.27E-11 19

Others

Non-alcoholic fatty liver disease (NAFLD) 25 7.42E-25

Longevity regulating pathway 23 1.83E-16

Inflammatory bowel disease (IBD) 23 4.32E-13

Antifolate resistance 20 7.50E-09

Hypertrophic cardiomyopathy (HCM) 18 1.53E-09

Alcoholism 17 2.35E-09

Dilated cardiomyopathy 15 4.32E-12

Graft-versus-host disease 14 3.34E-06

Arrhythmogenic right ventricular 12 1.42E-09 cardiomyopathy (ARVC)

Systemic lupus erythematosus 9 7.82E-09

Autoimmune thyroid disease 9 4.98E-06

Asthma 7 5.93E-04

Fanconi anaemia pathway 6 5.15E-05

Many different types of immune/inflammation or infection pathways (viruses, bacteria, amoeba and protozoa) were targeted by most of these endogenous compounds as shown in Table 2. Tumor necrosis factor alpha (TNF) signalling headed this list and cytokine and chemokine receptor signalling pathways were significantly enriched. TNF plays a key role in AD pathology and clinical trials with a TNF antagonist, etanercept, are in progress, following initial promising results in a small number of patients (Decourt et al. 2017). Toll-like, NOD-like and RIG-1-like receptors as well as cytosolic DNA sensing are adapted to recognise diverse pathogens or foreign pathogen’s DNA and launch the appropriate immune and inflammatory defence responses (Fukata et al. 2009;Takeuchi and Akira 2010;Patrick et al. 2016) .

Table 2: Enrichment analysis of the immune and infection-related pathways affected by endogenous compounds significantly related to the AD genes (from Fig 3). N = number of endogenous compounds involved (of 28); Q value = significance of enrichment.

Immune pathways N Q value 20

TNF Signalling 24 1.19E-32

IL-17 Signalling 24 5.46E-29

Cytokine-cytokine receptor interaction 22 5.98E-26

Th17 cell differentiation 25 3.33E-22

Toll-like receptor signalling 24 1.09E-21

NOD-Like Receptor Signalling 26 2.98E-20

Chemokine Signalling 24 5.26E-19

T cell receptor Signalling 24 2.46E-17

Adipocytokine Signalling 23 8.44E-17

Th1/Th2 cell differentiation 24 2.68E-15

Leukocyte transendothelial migration 18 3.85E-13

Natural killer cell mediated cytotoxicity 21 1.73E-11

Fc epsilon RI Signalling 20 1.98E-11

Complement and coagulation cascades 12 2.08E-11

B cell receptor Signalling 23 2.96E-11

Platelet activation 21 1.59E-10

Inflammatory mediator regulation of TRP channels 19 1.64E-10

Hematopoietic cell lineage 20 4.02E-09

Fc γ R-mediated phagocytosis 18 6.16E-09

RIG-I-like receptor Signalling 18 3.65E-08

Allograft rejection 14 1.95E-07

Intestinal network for IgA production 12 5.59E-07

Cytosolic DNA-sensing 13 5.50E-06

Antigen processing/presentation 24 1.18E-04

Infection pathways

Hepatitis B 25 1.35E-36

HTLV-I infection 25 5.45E-30

Chagas disease (American trypanosomiasis) 25 6.24E-29 21

Toxoplasmosis 25 2.13E-25

Tuberculosis 23 1.44E-23

Influenza A 24 7.86E-23

Pertussis 24 5.89E-19

Amoebiasis 24 1.46E-18

Epstein-Barr virus infection 24 4.36E-18

Leishmaniasis 25 6.79E-18

Viral carcinogenesis 24 8.86E-18

Legionellosis 24 1.51E-17

Hepatitis C 25 2.02E-17

Measles 23 2.25E-17

Herpes simplex infection 24 3.47E-15

Salmonella infection 24 9.50E-15

Malaria 24 4.33E-11

African trypanosomiasis 22 1.48E-08

Epithelial cell signalling in Helicobacter pylori infection 22 2.26E-08

Shigellosis 21 3.45E-07

Viral myocarditis 19 3.91E-07

Bacterial invasion of epithelial cells 12 1.21E-06

Pathogenic Escherichia coli infection 13 8.35E-06

Vibrio cholerae infection 8 0.001

Numerous other pathways were significantly targeted by these endogenous compounds including apoptosis, ferroptosis and autophagy (cell death pathways that all play a role in Alzheimer’s disease) 22

(Wu et al. 2018;Ghavami et al. 2014), adhesion, junction and extracellular matrix pathways that are involved in blood-brain barrier control (Willis et al. 2013) , neurotrophin and growth factor signalling (EGF, VEGF and ERBB) that are all relevant to Alzheimer’s disease (Sopova et al. 2014;Lim et al. 2016;Lazarov and Marr 2010) . In addition, several hormonal pathways (thyroid, estrogen, progesterone, prolactin, gonadotrophin releasing hormone, oxytocin) were targeted by these endogenous compounds (see below) as were Glutathione metabolism and Hypoxia-inducible factor HIF-1 signalling that play a key role in oxidative stress seen in many neuro degenerative conditions (Islam 2017). Diverse kinase pathways were also targeted by these compounds. Many of these pathways respond to a variety of ligands and control multiple functions. They include PI3K-Akt, FoxO, MAPK, Jak-stat, p53, AMPK and cyclic AMP, cyclic GMP/PKG, rap1 and ras signalling, NF- kappa B, sphingolipid pathway, apelin , mTor, TGF-beta, PPAR, and phospholipase d signalling. (Not shown)

Hormonal drugs targeting the AD genes

The data above showed that endogenous retinoid and steroid hormones target the AD genes. Several drugs relate to these hormones and these also targeted the AD genes as shown in Table 1. These included androgen antagonists as well as agonists (testosterones and metribolone), pro- and anti-progestogens as well as several estrogenic compounds and the anticancer-related antiestrogenic compounds tamoxifen and its metabolite afimoxifene. Tamibarotene is a synthetic retinoid with anticarcinogenic potential. It also has anti-inflammatory effects, decreases beta- amyloid production in Alzheimer’s transgenic mice and has beneficial effects on acetylcholine levels and memory in laboratory models. It has been proposed as a potential treatment for Alzheimer’s disease (Fukasawa et al. 2012) but there is no clinical data.

The potential effects of estrogens have been mentioned above. A recent large Finnish study has investigated the relationship between postmenopausal hormone therapy and Alzheimer’s disease. It showed that the use of systemic estrogen and progestogen was associated with an increased risk of AD, while the use of systemic estrogen for >10years was protective against AD. Long-term (>10years) use of progestogen or estrogen + progestogen was not related to AD risk. However these effects were slight and the authors concluded that hormone replacement therapy is not an important risk determinant(Imtiaz et al. 2017) A meta-analysis has shown that low testosterone levels in elder men are associated with an increased risk of Alzheimer’s disease (Lv et al. 2016). Testosterone has also been shown to improve cognitive function in elderly men, possibly via the conversion of testosterone to estrogen (Mohamad et al. 2018). 23

Propylthiouracil inhibits the synthesis of thyroxine and Triiodothyronine. Thyroid hormones have been associated with an increased risk of Alzheimer’s disease as have low serum concentrations of Triiodothyronine (Quinlan et al. 2019)

Table 3: Enrichment analysis of hormone-related drugs that significantly target the AD genes N = number of overlapping genes (AD genes within all genes affected by each compound); Each compound also shows the enrichment value (O/E) followed by the total number of genes affected by the compound. Q value = significance of enrichment.

N Q value

Androgen-antagonists

Androgen Antagonists| 4.21| 95 24 4.11E-09

bicalutamide| 1.81 | 193 21 0.002835

Flutamide| 1.04 | 4030 252 0.025

Androgen agonists

testosterone enanthate| 1.82| 587 64 3.62E-06

testosterone undecanoate| 2.16| 200 26 0.0002

Metribolone| 1.61| 424 41 0.001

Pro and antiprogestogen

Mifepristone| 1.74| 585 (anti progestogen) 61 2.15E-05

Medroxyprogesterone Acetate| 1.44| 393 (progestogen) 34 0.01

Pregnenolone Carbonitrile| 1.34| 1695 136 0.0002

Estrogenic

Coumestrol| 1.3| 1819 142 0.0003

Levonorgestrel| 2.05| 219 27 0.0004

Raloxifene Hydrochloride| 1.39 | 992 83 0.0008

Diethylstilbestrol| 1.23 | 1407 104 0.005

estradiol 3-benzoate| 1.63| 204 20 0.014

Anti-estrogen

Tamoxifen| 1.1| 3802 251 0.008 24

afimoxifene| 1.36| 491 40 0.014

Fulvestrant| 1.33| 540 43 0.015

Retinoid

tamibarotene| 1.3| 602 47 0.015

Thyroid related

Propylthiouracil| 1.69 | 4949 503 1.02E-37

Pesticides targeting Alzheimer’s disease genes.

A number of diverse classes of insecticides including organochlorines and organophosphates , rotenone, cinnamic aldehyde (a cinnamon component) and the pyrethroid momflurin selectively targeted a number of AD genes, as did fungicides and herbicides , including 2,4,5-T (2,4,5- Trichlorophenoxyacetic acid), a component of agent orange, a defoliant used in the Vietnam war. The use of agent orange, which also contained 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), has been associated with an increased incidence of a number of diseases, including Alzheimer’s disease (Yi et al. 2014). In an American study, high levels of the DDT metabolite DDE were found in AD patients and increase DDE levels were associated with an increased risk for AD. Both DDT and DDE increased amyloid precursor protein (APP) levels in neuroblastoma cells (Richardson et al. 2014). These data show that a number of pesticides target the AD genes and supports the meta-analysis showing that pesticide exposure is associated with AD risk (Yan et al. 2016).

Fig 5: The number of 1591 AD genes (bars , left Y axis) affected by diverse pesticides, together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data). DDE = Dichlorodiphenyl Dichloroethylene, a metabolite of DDT.

Figure 5 25

Metals targeting Alzheimer’s disease genes

The most significant groups affecting AD genes were arsenic, mercury, chromium, vanadate, nickel, lead, cobalt and asbestos related metals, their salts or compounds containing metals, (Cacodylic acid contains arsenic = (CH3)2AsO2H; Thimerosal contains alkyl mercury= C9H9HgNaO2S.) (Fig 5). Aluminium compounds did not significantly target the AD genes. However if all species were included (as well as rat mouse or human data) aluminium-related genes were significantly over- represented in the AD dataset (O/E =1.45 q = 8.2E-08).The high significance of arsenic is supported by a European study linking arsenic levels in topsoil to the prevalence and mortality of AD and other dementias (Dani 2010).

AD risk has also been linked to aluminium, mercury, cadmium and iron (see introduction). There has been little work in relation to any relationship between chromium and AD. There is no consistent evidence linking nickel to AD, although the exposure of mice to nickel nanoparticles as a model of atmospheric pollution leads to a marked increase in brain beta-amyloid levels (Kim et al. 2012).

Vanadium (as sodium orthovanadate) has been shown to increase tau phosphorylation in rat hippocampal slices (Jhang et al. 2017). Vanadium and vanadyl (IV) acetylacetonate (VAC) also have 26 antidiabetic properties. In APP/PS1 transgenic mice, VAC treatment preserved cognitive function and attenuated neuron loss, but did not reduce brain Aβ plaques. Its protective effects were related to activation of the PPARγ-AMPK signal transduction pathway, leading to improved glucose and energy metabolism, suppression of apoptosis and a decrease in toxic soluble Aβ peptide levels (Dong et al. 2019).

Serum lead levels do not appear to correlate with the incidence of AD. However lead exposure has been linked to an increased cerebral beta-amyloid deposition in rodents and primates (Zhou et al. 2018a;Li et al. 2017) . Cobalt or asbestos do not appear to have been linked to AD, nor has titanium dioxide although TiO2 nanoparticles have been shown to promote beta amyloid fibrillation in vitro (Wu et al. 2008) . Silica nanoparticles have also been shown to increase intracellular beta-amyloid as well as tau phosphorylation in human SK-N-SH and mouse neuro2a neuroblastoma cells (Yang et al. 2014). There effects may be related to nanoparticles as well as to the metals involved.

High levels of copper have been found in amyloid plaques in AD, although overall brain levels may be lower. Copper has high affinity for beta-amyloid and promotes its fibrillation. Copper also enhances tau phosphorylation. Its toxic effects may be related to free radical formation (reviewed in) (Li et al. 2017). Other metals or succimer (metal chelator) had relatively minor effects in relation to the AD genes. However, cuprizone, a demyelinating copper chelator targeted 345 AD genes with high significance (O/E = 1.68; q =8.18E-24).

Fig 6: The number of 1591 AD genes (bars , left Y axis) affected by diverse metals and their salts together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data). NaAsO2 = sodium arsenite; As2O3 = arsenic trioxide; MMAsA = monomethylarsonous acid; PMA = Phenylmercuric Acetate; HgBr2 = mercuric bromide; K2Cr04 = potassium chromate(VI); K2Cr2O7 = Potassium dichromate; Chromium6 = chromium hexavalent ion; Na2Cr2O7 = sodium bichromate; NiSO4 = Nickel sulphate; NiO = nickel monoxide; CoCl2 = cobaltous chloride; Asbest, serp = serpentine asbestos; Asbest, croc = crocidolite asbestos (blue asbestos)

Figure 6 27

3.8 Pollutants targeting the Alzheimer’s disease genes

Polycyclic aromatic hydrocarbons (PAH) and persistent organic pollutants (POPs)

A number of these toxic compounds selectively targeted AD genes, the most significant being the PAH’s benzo[a]pyrene and its derivative , 7,8-Dihydro-7,8-dihydroxybenzo(a)pyrene 9,10-oxide (BPDE) and 2,3,7,8-tetrachlorodibenzo-p-dioxin, a component of agent orange which has been associated with an increase in the incidence of Alzheimer’s disease in Korean veterans (Yi et al. 2014). A number of polychlorinated (PCB), polybrominated biphenyls (PBB) or fluorocarbons and diverse PAH and POP’s were also included, as were flame retardants. Blood levels of PCB’s were unrelated to dementia or Alzheimer’s disease in a Canadian study (Medehouenou et al. 2014) . However, they have been shown to disrupt the blood-brain barrier in animal studies (Selvakumar et al. 2013).

Benzo[a]pyrene has been shown to reduce the degradation of beta-amyloid by insulin degrading enzyme in rat neuroglial cells (Zhang et al. 2018b) and to increase beta-amyloid levels and apoptosis in the adult zebrafish brain (Gao et al. 2017). TCDD and Benzo[a]pyrene were clearly the most 28 influential of these compounds, although the effects of some of the more common PCB and related toxins are likely to be cumulative.

Fig 7: The number of AD genes (bars , left Y axis) affected polycyclic aromatic hydrocarbons (PAH) or persistent organic pollutants (POP’s) together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data). 4-OH-PeCB2 =4-hydroxy-2,3,5,3',4'- pentachlorobiphenyl ; BBFA= benzo(b)fluoranthene; BPDE = 7,8-Dihydro-7,8- dihydroxybenzo(a)pyrene 9,10-oxide| 1.76| 3393DHDBP = 9,10-dihydro-9,10- dihydroxybenzo(a)pyrene ; PBDE = pentabromodiphenyl ether; PCB = polychlorinated biphenyl; PFOA = perfluorooctanoic acid PFOSA= perfluorooctane sulfonic acid| 1.26| 1997 TCDD= 2,3,7,8- tetrachlorodibenzo-p-dioxin Flame = flame retardants.

Figure 7 29

3.9 Diesel, smoking and other airborne pollutants.

A number of studies have linked living close to busy roads and traffic or wood-burning stove airborne pollution to the incidence of dementia or Alzheimer’s disease (Chen et al. 2017;Kilian and Kitazawa 2018;Andersson et al. 2018;Carey et al. 2018;Oudin et al. 2016;Oudin et al. 2018). These effects are accompanied by Alzheimer’s–like pathological changes and neuroinflammation in the brain and also related to blood-brain barrier breakdown (Calderon-Garciduenas et al. 2004;Calderon-Garciduenas et al. 2008;Calderon-Garciduenas et al. 2015). Smoking has also been associated with an increased risk of developing Alzheimer’s disease (Durazzo et al. 2014;Calderon-Garciduenas 2016) .

As can be seen in Fig 7, a number of the components of diesel are also contained in cigarette smoke. Many of these compounds, from diesel fuel or other airborne components (magnetite nanoparticles, JP8 aviation fuel, gasoline and soot) selectively targeted the AD genes. Particulate matter affected 224/1591 AD genes, but this was not more than expected under the criteria used.

Magnetite nanoparticles are derived from coal burning and other combustion sources and have been found in the human brain (Kirschvink et al. 1992;Maher et al. 2016). In Alzheimer’s disease brains they are localised in amyloid plaques (Plascencia-Villa et al. 2016)

Fig 8: The number of AD genes (bars , left Y axis) affected by diesel or smoking (marked by *) constituents and other airborne pollutants together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data): DENitro = Diethylnitrosamine

Figure 8 30

3.10 Bisphenols, phthalates and Other pollutants (Fig 9)

Several bisphenols and mono-(2-ethylhexyl) phthalate, but no other phthalates significantly targeted the AD genes. Bisphenol A increases Aβ 1-42 and phosphorylated tau proteins in SH-SY5Y cells and these effects were blocked by insulin and the antidiabetic drug, rosiglitazone (peroxisome proliferator-activated receptor agonist (PPARG)) (Wang et al. 2017a). No AD-related data were found for mono-(2-ethylhexyl)phthalate, but a related compound, Di-(2-ethylhexyl)-Phthalate, when given prenatally can lead to increased hippocampal tau phosphorylation in the offspring, again related to insulin disturbances (Sun et al. 2014). The mildly acidic NH4Cl reduces beta-amyloid secretion in SY5Y cells, an effect related to acidification of intracellular compartments (Fuller et al. 1995). It seems unlikely this is relevant to any environmental effects of NH4CL. The effects of other diverse pollutants were relatively minor in relation to other noxious agents and are not further discussed, although, as with other pollutants, their effects are likely to be cumulative. 31

Fig 9: The number of AD genes (bars, left Y axis) affected by bisphenols, phthalates and other pollutants together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data). 2-A2MP = 2-amino-2-methyl-1-propanol;TBr bisphenol A = tetrabromobisphenol A; MEH phthalate = mono-(2-ethylhexyl)phthalate; 4-VCD = 4-vinyl-1- cyclohexene dioxide; 4-A-Dinitrotoluene= 4-amino-2,6-dinitrotoluene; Cl-diphenyl (54% Cl) = Chlorodiphenyl (54% Chlorine). Bisphenol A affected 1387 of the 1591 AD genes and the left Y axis has been cut to better illustrate the effects of other compounds

Figure 9

3.11Dietary compounds related to the AD genes

Dietary fats have been associated with Alzheimer’s disease and dementia (meta-analysis) (Ruan et al. 2018) and dietary sugar has been linked to both type 2 diabetes and AD (Moreira 2013) . Dietary fats 32 affected 463 AD genes (O/E= 1.2; enrichment q = 1.68E-06) and dietary sucrose 122 AD genes (O/E = 1.5; enrichment q = 2.06E-06). Palm oil affected 157 AD genes (O/E= 1.45; enrichment q = 1.07E- 06) .Palm oil supplementation has been associated with both beneficial and deleterious effects in cardiovascular disease, depending on the type of dietary fats it replaced (Fattore et al. 2014). . LDL, VLDL or HDL cholesterol affected fewer than 5 AD genes and dietary cholesterol only 8. LDL or HDL have not proved to be reliable predictors of AD development (Benn et al. 2017;Tynkkynen et al. 2016)

3.12 Carcinogenic and antineoplastic agents

Several studies have noted an inverse relationship between the incidence of cancer and Alzheimer’s disease and understanding the processes involved may be useful to both diseases (Snyder et al. 2017;Shafi 2016). This relationship may partly be explained by cancer mortality in early life which evidently precludes the development of Alzheimer’s disease in old age, but as noted above, many AD genes have been implicated in cancer and may play a role in its prevention. AD and cancer are also diametrically opposed in terms of cell growth/cell death and the processes controlling these events. 43 antineoplastic drugs and 22 carcinogens significantly targeted the Alzheimer’s disease genes, the most significant of which are illustrated in Fig 10. Other antineoplastic drugs targeting the AD genes (q < 0.05), not included in the figure included Vincristine, Demecolcine, Irinotecan, Geldanamycin, NSC 689534, 1,2-dithiol-3-thione, Paclitaxel, Mitomycin, Fluorouracil, Gemcitabine, sulforafan, MRK-003, , Dasatinib, Pictilisib, Melphalan, XL-147, tamoxifen and its metabolite afimoxifene, fulvestrant, Tamibarotene , dactinomycin and casticin, while other carcinogens include Bortezomib, PCI 5002, Seocalcitol, Temozolomide, Lucanthone, Mitoxantrone, BA-TPQ, Bexarotene, Me-IQX and Methylcholanthrene

Among the antineoplastic drugs (including research agents with laboratory evidence) are dorsomorphin, a bone morphogenic protein (BMP) inhibitor (Zhou et al. 2017) and SB 431542 , a Transforming growth factor beta (TGFB) receptor kinase inhibitor (Halder et al. 2005) . The gliotrophic/neurotrophic soluble APPalpha (sAPPα) induces gliogenesis via BMP4 signalling (Kwak et al. 2014) while BMP9 has been shown to reduce cholinergic neuronal cell loss in septal nuclei following axotomy (Lopez-Coviella et al. 2011). BMP6 levels are increased in the AD hippocampus. Aβ increases BMP6 expression and it was suggested that Aβ-associated increases in BMP6 expression in AD may have deleterious effects on hippocampal neurogenesis (Crews et al. 2010). TGFB1 levels are increased in the brains of AD patients, correlating with neuroinflammation. Transgenic mice overexpressing TGFB1 show neurovascular pathology similar to that observed in AD (Zhang et al. 2016) . However reduced TGFB1 signalling is also associated with Aβ deposition and 33 neurofibrillary tangle formation and with neurodegeneration and a neuroprotective role for TGFB has been suggested (Estrada et al. 2018). The diverse and contrary effects of BMP’s and TGF would seem to preclude the use of such antagonists. A number of histone deacetylase (HDAC) inhibitors also targeted the AD genes, (valproate, trichostatin A, entinostat, Vorinostat, and Panobinostat belinostat (De Souza and Chatterji 2015)) and sulfofuran which is produced after ingestion of cruciferous vegetables, particularly broccoli (Tortorella et al. 2015) . However, while there are some theoretical arguments for the use of HDAC inhibitors in Alzheimer’s disease (Yang et al. 2017;Millard et al. 2017), there is as yet no evidence that they affect the incidence or progression of the disease .

These data suggest that the inverse relationship between cancer and Alzheimer’s disease is in some way related to the processes governed by the Alzheimer’s disease genes. Many antineoplastic drugs are cytotoxic by design and the use of carcinogens is evidently precluded in medicine. It is difficult to imagine how this relationship could be harnessed to Alzheimer’s disease treatment, although understanding the mechanisms involved could be of use.

Fig 10: The number of AD genes (bars, left Y axis) affected by Antineoplastic agents or carcinogens, together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data). (+)-JQ1 cmpd = (+)-JQI compound; Mtrexate = methotrexate; vinylidine Cl = vinylidene chloride EMS = Ethyl Methanesulfonate; CAPE = caffeic acid phenethyl ester; NNTCU =N- nitroso-tris-chloroethylurea; 4,4DDM= 4,4'-diaminodiphenylmethane; Thioacet = Thioacetamide; DM4T= dimethyl-4-toluidine; ECl2 =ethylene dichloride; EN-urea = Ethylnitrosourea; MN-urea= Methylnitrosourea

Figure 10 34

3.13 Anti-inflammatory, cholesterol-lowering and antidiabetic drugs

Neuroinflammation is a prominent feature in Alzheimer’s disease and several studies have shown that anti-rheumatic agents and non-steroidal anti-inflammatory drugs (NSAIDS) can delay the progression or reduce the incidence of Alzheimer’s disease. Cholesterol lowering agents (statins) have also shown some benefit (see introduction).

A number of NSAIDS and anti-rheumatic agents significantly targeted a large number of AD genes. Pravastatin , simvastatin and other cholesterol lowering agents, torcetrapib (cholesterol ester transfer protein inhibitor) and the lipid-lowering agent bezafibrate also targeted AD genes, but both the number of genes and the significance of enrichment were lower than that of the anti- inflammatory agents. Torcetrapib failed in clinical trials related to atherosclerosis (Joy and Hegele 2008) .

Diabetes is associated with Alzheimer’s disease (Vieira et al. 2018;Shinohara and Sato 2017) and there has been much interest in the potential use of anti-diabetic drugs, including the peroxisome proliferator-activated receptor gamma (PPARG) agonists. 35

The AD genes were significantly targeted by a number of PPAR agonists, including Pirinixic acid (PPARA) (Wolkart et al. 2012), Troglitazone , Rosiglitazone, Piaglitazone (all PPARG) (Stumvoll and Haring 2002) , muraglitazar and tesaglitazar (both PPARA/PPARG). Bezafibrate is also a pan-PPAR ligand(Tenenbaum et al. 2005).

Piaglitazone therapy in AD patients has shown promising effects in patients with diabetes but Rosiglitazone monotherapy was shown to be ineffective in mild-to-moderate Alzheimer’s disease (Gold et al. 2010;Liu et al. 2015) . Streptozotocin is included on this figure as a diabetes inducing agent, derived from bacteria, that has also been used to model some of the aspects of Alzheimer’s disease (Grieb 2016) .

Dietary plant and red wine-derived polyphenols have attracted much attention in relation to their potential health benefits, particularly in the cardiovascular field. There are associated with multiple mechanisms including antioxidant, anti-inflammatory, anti-allergic, anti-atherogenic, anti- thrombotic, and anti-mutagenic effects (Gorzynik-Debicka et al. 2018). Red wine polyphenols have also been shown to reduce beta-amyloid and tau pathology in Alzheimer’s disease models (Pasinetti 2012) . A prospective study has indicated that moderate consumption of red wine may reduce the incidence of AD in men, but not in women, where the effect was deleterious (Fischer et al. 2018).

The AD genes were significantly targeted by a number of these compounds including epigallocatechin gallate (a tea polyphenol), genistein (from fava beans and soybeans), quercetin and its glycoside derivative quercitrin (from fruits, vegetables, leaves, and grains; red onions and kale); curcumin (turmeric), daidzein (from soybeans and other legumes), resveratrol (skins of grapes, blueberries, raspberries, mulberries, and peanuts) and Grape Seed Proanthocyanidins. Several plant polyphenols (Fig 10) show both antiviral and antibacterial properties including genistein (Andres et al. 2009;Ulanowska et al. 2006), epigallocatechin gallate (Vazquez-Calvo et al. 2017), quercetin (Wu et al. 2015a;Chembili et al. 2019), daidzein (Seo and Choi 2017;Chin et al. 2012), resveratrol (Abba et al. 2015;Taylor et al. 2014) , quercitrin (Chiow et al. 2016;Gomez-Florit et al. 2014)and Grape Seed Proanthocyanidins (Lee et al. 2017;Mayer et al. 2008). Curcumin (Moghadamtousi et al. 2014) and resveratrol (Abba et al. 2015;Taylor et al. 2014;Lee and Lee 2015) have broad spectrum activity against bacteria, fungi and viruses and Allylpyrocatechol kills Staphylococcus aureus (Hussain et al. 2016).

Dietary polyphenols are components of the Mediterranean diet, which has been shown to exert beneficial effects with respect to the incidence or inflammatory markers of a number of diseases 36 including atherosclerosis (Medina-Remon et al. 2017), diabetes (Guasch-Ferre et al. 2017) and Alzheimer’s disease (Yusufov et al. 2017;Morris et al. 2015;Miranda et al. 2017) .

Fig 11: The number of AD genes (bars, left Y axis) affected by non-steroidal anti-inflammatory (NSAID’s) , cholesterol-lowering, antidiabetic drugs and plant polyphenols, together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data). Acetamin = acetaminophen; EGC gallate = epigallocatechin gallate. PPAR = peroxisome proliferator- activated receptor.

Figure 11

3.14 Other drugs targeting AD genes (Fig 12) .

Other drugs affecting the AD genes included drugs used in epilepsy (pentobarbital, ketamine, phenytoin and pantogab) and the antiarrhythmic agent amiodarone (affecting sodium/calcium channels). Epilepsy has been frequently associated with AD(Sawikr et al. 2017;Pasinetti et al. 37

2015;Vossel et al. 2017;Nicastro et al. 2016). The immunosuppressants cyclosporine, leflunomide and azathioprine also targeted the AD genes. However, despite a clear role for immune and inflammatory processes in AD, immunosuppressive strategies have not been of benefit (Regen et al. 2017), although cyclosporine does not appear to have been tested. Several antibiotics targeted the AD genes, an affect that is likely unrelated to their primary effects on pathogens.

Tunicamycin activates the unfolded protein response which plays a role in many neurodegenerative diseases (Wang et al. 2015a). Cycloheximide inhibits protein synthesis . MG132 is a proteasome inhibitor that stimulates hippocampal beta-amyloid aggregation in mice (Sunkaria et al. 2017). Bromfenacoum is a Vitamin K antagonist and anticoagulant rodent poison (Mosterd and Thijssen 1991) .Clinical vitamin K antagonists have been associated with a decline executive function in the elderly and vitamin K levels may be reduced in AD patients (Brangier et al. 2018;Presse et al. 2008). Vitamin K3 (menadione) also targeted the AD genes.

Linsidomine is a nitric oxide releasing vasodilator. Other compounds have diverse effects on phospholipase C (U73122), histone demethylase (GSK-J4) , the Farnesoid X receptor (obeticholic acid), tyrosinase inhibition (arbutin). Zidovudine is an antiretroviral agent. In general there appears to be no common thread linking many of the diverse compounds in Figs x and y.

Fig 12: The number of AD genes (bars, left Y axis) affected by anticonvulsants, immunosuppressants, antibiotics and diverse compounds, together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data). StThom = St. Thomas' Hospital cardioplegic solution; BCLA = benzyloxycarbonylleucyl-leucyl-leucine aldehyde (proteasome inhibitor).

Figure 12 38

3.15 Diverse compounds targeting AD genes (Fig 13)

Among these were 8-bromo cyclic AMP, a potent analogue of cyclic AMP (cAMP) and the cAMP synthesis activator, forskolin. cAMP is involved in multiple signalling networks. Pentanal inhibits cAMP-dependent protein kinase catalytic subunit alpha (PRKACA), which is stimulated by cAMP. Interestingly, a number of NSAIDs including aspirin and nimesulide inhibit this cAMP-dependent kinase (Zentella et al. 2007). AG1879 is a selective inhibitor of Src family kinases with selectivity for Lck and Fyn (Hanke et al. 1996), both of which phosphorylate the microtubule component tau (Scales et al. 2011). U0126 is a Mek 1 and 2 map kinase (MAP2K1/MAP2K2) inhibitor (Duncia et al. 1998). PD98059 also inhibits Mek1 (Boyd and Mathie 2002). Pyrazolanthrone/SP600125 is a c-Jun N-terminal kinases (JNK) inhibitor (Bogoyevitch and Arthur 2008). JNK’s are activated by various stressors including cytokines, growth factors, oxidative stress, unfolded protein response signals or beta-amyloid peptides and JNK inhibitors have been suggested as therapeutic targets in Alzheimer’s disease (Yarza et al. 2015) 39

The AD genes were also targeted by a diverse range of compound including drugs of abuse (MDMA/ ecstasy (3,4-methylenedioxymethamphetamine), cocaine, morphine and dronabinol). The antidepressants Venlaflaxine (serotonin-noradrenaline reuptake inhibitor) and fluoxetine (selective for serotonin uptake) and nefadozone (no longer marketed) also targeted the AD genes as did isoproterenol (β adrenoceptor agonist) and phenylephrine (α-adrenoceptor agonist), the muscarinic agonists beta-methylcholine and pilocarpine, and the muscarinic antagonist orphenadrine.

In general, other drugs in the same class (e.g. muscarinic drugs, antidepressants etc.) many of which exist in CTD did not target the AD genes and their effects may be unrelated to their primary actions.

Fig 13 The number of AD genes (bars, left Y axis) affected by other diverse drugs together with the significance of enrichment ( dotted line , right Y axis). The X axis gives the compound name, followed by observed/expected values and the total number of genes affected by the compound (CTD data). cAMP = cyclic adenosine monophosphate; MDMA = 3,4 methylenedioxymethamphetamine; AG 1879 = SRC kinase inhibitor ; U0126 = MEK kinase inhibitor; PD98059 = MEK/ERK kinase inhibitor;

Figure 13

3.16 Comparison of compounds affecting autism and Alzheimer’s disease genes. 40

For this exercise, the data were normalised to the number of compounds significantly targeting > 5% of each gene set (206 autism genes, 1591 AD genes). Despite the greater number of Alzheimer’s disease genes tested (7.7 fold more than autism) many more compounds affected the autism gene set. (Autism = 411 compounds/206 genes: Alzheimer’s = 184/1591), suggesting a much greater environmental influence in autism. Of the 411 compounds affecting autism and the 184 compounds affecting AD, 363 were specific to autism and 136 specific to AD. 48 compounds were common to both disorders. Those compounds common to both diseases included metals, pollutants, pesticides, steroid and retinoid hormones, anti-inflammatory agents, plant polyphenols and toxins. Many of these, particularly the pollutants and pesticides are highly toxic and affect multiple processes. These common compounds are listed below.

Compounds affecting both autism and AD genes:

Metals: Arsenic; Arsenite; Asbestos, Crocidolite ;Asbestos, Potassium Dichromate; Potassium Dichromate; Serpentine; cobaltous chloride; lead acetate; Cisplatin; sodium arsenite; Silver; Zinc; Pollutants: Ammonium Chloride; ; Benzo(a)pyrene; 2,4,5,2',4',5'-hexachlorobiphenyl; 8-Dihydro-7,8- dihydroxybenzo(a)pyrene 9,10-oxide; Carbon Tetrachloride; 2,4,4'-trichlorobiphenyl; Diethylnitrosamine; PCB 180; perfluorooctanoic acid

Pesticides Chlorpyrifos; Endosulfan; Mustard Gas; Parathion; Rotenone;

Hormones: Diethylstilbestrol; Estradiol; Progesterone; Tretinoin; Vitamins; Calcitriol; Folic Acid; Methionine;

Anti-inflammatory: Acetaminophen; Nimesulide;

Drugs: Carbamazepine; Cocaine; Cytarabine; Dronabinol; Isoproterenol; Nicotine; Valproic Acid; pirinixic acid;

Plant polyphenols: epigallocatechin gallate; Genistein; Toxins: 1-Methyl-4-phenylpyridinium; Hydrogen Peroxide; Cuprizone; Aflatoxin B1; 41

4.Discussion

This three way analysis has compared 1591 AD genes from genome wide association studies (GWASdb) with GWASdb genes from over 400 other disorders, with the host/pathogen interactomes from 18 bacterial, viral and fungal pathogens (HPI) and with toxicogenomics data from several million chemical/gene interactions (CTD).

The data highlight several themes, which are illustrated in Fig 14.

Fig 14: A summary of some of the relationships between the 1591 AD genes (black box) and environmental influences (hatched or squared boxes) all of which significantly target the AD genes. The effects of the endogenous compounds related to the AD genes are also shown (grey boxes). These exert beneficial effects on the blood brain barrier, possess anti-inflammatory effects, modulate natural killer cells, activate macrophages and increase the production of antimicrobial peptides or possess antimicrobial properties themselves. Tretinoin activates the RIG-1 antiviral defence pathway. ↑ = upregulated in AD; ↓= downregulated in AD.→ = Primary effects of compounds.T2DM = type 2 diabetes mellitus; CVD = cardiovascular disease. Lipid = lipid metabolism disorders. ITE = 2-(1'H-indole-3'-carbonyl)-thiazole-4-carboxylic acid methyl ester, an endogenous aryl hydrocarbon receptor (Ahr) ligand. δ receptor = Sigma 1 receptor (choline is an agonist). RIG-1 = DExD/H-box helicase 58 (gene symbol = DDX58; involved in viral double-stranded RNA recognition and the regulation of immune response)

Figure 14 42

Firstly, there is a clear relationship between cancer genes and AD genes and 744/1591 AD genes (46.7%) are also related to cancer. The cancer/AD link has also been reported in other comparisons of GWAS data using more selective datasets (Feng et al. 2017). Multiple host pathogen interactomes also target the AD genes, and several of these pathogens including the Epstein-Barr virus, HIV-1, hepatitis C, and helicobacter pylori are oncogenic, while others (HCMV, P. gingivalis) have also been associated with several cancers. Multiple exogenous drugs or compounds significantly targeting the AD genes are either antineoplastic or carcinogenic. Endogenous compounds targeting the AD genes also relate to multiple cancer pathways and several, like beta-amyloid, (glutathione, Lithocholic acid, melatonin, arachidonic acid, hydrogen peroxide, nitric oxide and hypochlorous acid) also possess antimicrobial properties or regulate the immune system, inflammation and pathogen resistance (Tretinoin, calcitriol, the endogenous AHR ligand (ITE), Estradiol ,corticosterone, choline, selenium, folic acid and ketone bodies). Many AD genes relate to the immune system (Jiang et al. 2017) . The AD hippocampal transcriptome is also enriched in tumor suppressor and immune-related pathways (Blalock et al. 2004) . The hippocampal genes upregulated in this AD study were significantly enriched in upregulated genes in infection datasets from multiple viral, bacterial, fungal and 43 protozoan species and responses to bacterial lipopolysaccharides and other Toll-like receptor ligands (TLR3,4,7,8,9) (Carter 2017). Aβ is a potent antimicrobial agent with broad-spectrum activity against bacteria, fungi and viruses (Soscia et al. 2010;Bourgade et al. 2016). AD GWAS genes also converge on beta-amyloid production (Camargo et al. 2015;Karch and Goate 2015) . It would appear that the AD genes as well as the endogenous compounds they target are primarily concerned with antimicrobial activity and immune defence. It has been estimated that infectious agents account for ~20% of all cancers worldwide (Vandeven and Nghiem 2014). The inverse relationship between cancer and AD may thus pivot around the antimicrobial activity of the endogenous compounds related to the AD genes.

Rheumatoid arthritis is also inversely associated with AD. This condition has also been associated with diverse infections (Mathew and Ravindran 2014) and a similar reasoning may apply.

Secondly, AD has been associated with type 2 diabetes and cardiovascular disease, including hypertension, coronary artery disease, and arteriosclerosis and lipid metabolism disorders as well as with obesity and kidney disease (see above). The AD genes were all enriched in other GWASdb datasets for these conditions and the endogenous compounds targeted by the AD genes were also enriched in numerous pathways related to diabetes, atherosclerosis or rheumatoid arthritis. In addition the drugs related to the AD genes included several non-steroidal anti-inflammatory agents (NSAID’s), antirheumatic agents, statins, antidiabetic PPAR ligands and dietary polyphenols. NSAIDs (McGeer et al. 2018) and statins (Haag et al. 2009) have both been associated with a reduction in AD risk. Dietary polyphenols have attracted much interest in relation to AD (Sawikr et al. 2017;Pasinetti et al. 2015) . Although not individually tested, polyphenols are components of the Mediterranean diet, which has been shown to be of benefit in relation to inflammation, diabetes, atherosclerosis and AD (Bonaccio et al. 2017;Martinez-Gonzalez et al. 2015;Medina-Remon et al. 2017;Singh et al. 2014). The relationship between all pathogens and all GWASdb diseases was not studied in this paper but previous studies with the P. gingivalis host interactome have highlighted relationships with GWADdb genes related to AD, atherosclerosis, hypertension, Type 2 diabetes and obesity (Carter et al. 2017). Other studies have linked infections to atherosclerosis or diabetes (Sawikr et al. 2017;Pasinetti et al. 2015;Hemmat et al. 2018;Campbell and Rosenfeld 2015;Chakraborty et al. 2017).

Thirdly, this analysis has identified several pollutants that have been implicated in AD, including pesticides (Yan et al. 2016), heavy metals (Chin-Chan et al. 2015;Li et al. 2017), particularly arsenic (Dani 2010), and two components of the agent orange defoliant (2,4,5-T and TCDD) which has been associated with increased AD incidence in Korean veterans (Yi et al. 2014). Components of Diesel , 44 vehicle emissions or cigarette smoke also significantly targeted numerous AD genes, concordant with several environmental studies linking air pollution to AD risk (Calderon-Garciduenas 2016;Calderon- Garciduenas et al. 2018;Alemany et al. 2018;Kilian and Kitazawa 2018;Andersson et al. 2018;Oudin et al. 2016).

Arsenic has deleterious effects on the immune system and is toxic to developing T cells (Xu et al. 2018a). Low level chronic arsenic exposure produces chronic systemic inflammation and suppresses the blood expression of phagocytic Fc-gamma and complement receptors (Prasad and Sinha 2017). Chronic arsenic exposure can also produce atherosclerosis or cancer and increases susceptibility to viral , bacterial and fungal infection (Zhang et al. 2018c;Hsu et al. 2016). TCDD, a ligand for the aryl hydrocarbon receptor also suppresses the immune system and increases susceptibility to many viral infections . It also increases latent infection with HIV1-1, the cytomegalovirus and the Epstein-Barr virus (Fiorito et al. 2017). Human exposure to air pollution, including diesel, has been associated with allergy , inflammation in the respiratory system and an increased susceptibility to respiratory infection (Sydbom et al. 2001;Kelly and Fussell 2011). In mice, diesel exhaust emissions suppress natural killer cells’ ability to kill virally infected cell (Muller et al. 2013) and reduce the ability to clear respiratory Pseudomonas aeruginosa infection (Harrod et al. 2005) . Several organochlorine pesticides also decrease human natural killer cell function in vitro (Reed et al. 2004). Organochlorine pesticides have been associated with immune suppression and increased susceptibility to infection in animals, and Endosulfan induces human T-cell apoptotic cell death in vitro (Kannan et al. 2000). Organophosphorus pesticides are also immunotoxic and impair the production of granzymes, which kill virally infected cells. They also inhibit the transcription of granzyme A, perforin and granulysin which also participate in this role. They impair the function of natural killer cells and produce apoptosis of immune cells (Li and Kawada 2006).

Of the other herbicides and fungicides targeting the AD genes, Rotenone impairs dendritic cell differentiation and the ability of dendritic cells to produce micobicidal hydrogen peroxide (Del Prete et al. 2008). There has been little research into the immune effects of vinclozocin but exposure of female rats to vinclozocin produced a significant increase in the numbers of splenocytes, B cells, T cells, helper T cells and cytotoxic T cells but a decrease in the percentage of natural killer cells (White, Jr. et al. 2004). APP and gamma-secretase components are highly expressed in dendritic and natural killer cells (Carter 2011)

Among the drugs selectively targeting the AD genes, several have been tested and found wanting in AD clinical trials, including immunosuppressants (Regen et al. 2017), and the PPAR ligand Rosiglitazone (Gold et al. 2010) although Pioglitazone therapy in AD patients has shown promising 45 effects in patients with diabetes (Liu et al. 2015). Nevertheless, the toxicogenomics/AD gene exercise agnostically identified two classes of drugs, as well as polyphenols, that are currently targets of interest in AD (HDAC inhibitors (Yang et al. 2017) and PPAR ligands (Liu et al. 2015;Govindarajulu et al. 2018;Agarwal et al. 2017)) . While the relationship with antineoplastic drugs or kinase inhibitors is of interest the toxicity of such agents or the involvement of kinases in multiple pathways does not seem promising in relation to therapeutic development in AD.

Perhaps the most interesting compounds from this study are the anti-inflammatory NSAID’s whose beneficial effects are already appreciated (see above). Retinoids are also of interest in relation to their anti-inflammatory effects (Shadfar et al. 2015). In addition, marginal Vitamin A deficiency has been associated with cognitive decline in the elderly and promotes Aβ production and neuritic plaque formation, and increases memory deficits in AD model mice (Zeng et al. 2017). Plasma or cerebrospinal fluid levels of vitamin A and β-carotene are reportedly reduced in AD patients, and these vitamins have been shown to slow the progression of dementia in the clinic (Ono and Yamada 2012) . An important role for inflammation in AD is now generally recognised and other inflammation targets including the use of the tumor necrosis factor alpha (TNF) antagonist etanercept are currently being considered (Decourt et al. 2017).

Finally, numerous studies have now implicated diverse pathogens in AD, and their close relationship with the AD genes and with beta-amyloid deposition continues to argue for their causal role, mediated both by the effects of beta-amyloid and by the collateral damage produced by cerebral inflammatory and pathogen defence processes. The use of antibiotics, antiviral or antifungal agents seem an evident solution that remains to be assessed in preventive clinical trials in AD.

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

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