Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk.
ABSTRACT: Alzheimer's disease (AD) is highly heritable and recent studies have identified over 20 disease-associated genomic loci. Yet these only explain a small proportion of the genetic variance, indicating that undiscovered loci remain. Here, we performed a large genome-wide association study of clinically diagnosed AD and AD-by-proxy (71,880 cases, 383,378 controls). AD-by-proxy, based on parental diagnoses, showed strong genetic correlation with AD (rg?=?0.81). Meta-analysis identified 29 risk loci, implicating 215 potential causative genes. Associated genes are strongly expressed in immune-related tissues and cell types (spleen, liver, and microglia). Gene-set analyses indicate biological mechanisms involved in lipid-related processes and degradation of amyloid precursor proteins. We show strong genetic correlations with multiple health-related outcomes, and Mendelian randomization results suggest a protective effect of cognitive ability on AD risk. These results are a step forward in identifying the genetic factors that contribute to AD risk and add novel insights into the neurobiology of AD.
Project description:Alcohol consumption has been linked to over 200 diseases and is responsible for over 5% of the global disease burden. Well-known genetic variants in alcohol metabolizing genes, for example, ALDH2 and ADH1B, are strongly associated with alcohol consumption but have limited impact in European populations where they are found at low frequency. We performed a genome-wide association study (GWAS) of self-reported alcohol consumption in 112 117 individuals in the UK Biobank (UKB) sample of white British individuals. We report significant genome-wide associations at 14 loci. These include single-nucleotide polymorphisms (SNPs) in alcohol metabolizing genes (ADH1B/ADH1C/ADH5) and two loci in KLB, a gene recently associated with alcohol consumption. We also identify SNPs at novel loci including GCKR, CADM2 and FAM69C. Gene-based analyses found significant associations with genes implicated in the neurobiology of substance use (DRD2, PDE4B). GCTA analyses found a significant SNP-based heritability of self-reported alcohol consumption of 13% (se=0.01). Sex-specific analyses found largely overlapping GWAS loci and the genetic correlation (rG) between male and female alcohol consumption was 0.90 (s.e.=0.09, P-value=7.16 × 10-23). Using LD score regression, genetic overlap was found between alcohol consumption and years of schooling (rG=0.18, s.e.=0.03), high-density lipoprotein cholesterol (rG=0.28, s.e.=0.05), smoking (rG=0.40, s.e.=0.06) and various anthropometric traits (for example, overweight, rG=-0.19, s.e.=0.05). This study replicates the association between alcohol consumption and alcohol metabolizing genes and KLB, and identifies novel gene associations that should be the focus of future studies investigating the neurobiology of alcohol consumption.
Project description:Recent advances toward the characterization of Alzheimer's disease (AD) have permitted the identification of a dozen of genetic risk factors, although many more remain undiscovered. In parallel, works in the field of network biology have shown a strong link between protein connectivity and disease. In this manuscript, we demonstrate that AD-related genes are indeed highly interconnected and, based on this observation, we set up an interaction discovery strategy to unveil novel AD causative and susceptibility genes. In total, we report 200 high-confidence protein-protein interactions between eight confirmed AD-related genes and 66 candidates. Of these, 31 are located in chromosomal regions containing susceptibility loci related to the etiology of late-onset AD, and 17 show dysregulated expression patterns in AD patients, which makes them very good candidates for further functional studies. Interestingly, we also identified four novel direct interactions among well-characterized AD causative/susceptibility genes (i.e., APP, A2M, APOE, PSEN1, and PSEN2), which support the suggested link between plaque formation and inflammatory processes and provide insights into the intracellular regulation of APP cleavage. Finally, we contextualize the discovered relationships, integrating them with all the interaction data reported in the literature, building the most complete interactome associated to AD. This general view facilitates the analyses of global properties of the network, such as its functional modularity, and triggers many hypotheses on the molecular mechanisms implicated in AD. For instance, our analyses suggest a putative role for PDCD4 as a neuronal death regulator and ECSIT as a molecular link between oxidative stress, inflammation, and mitochondrial dysfunction in AD.
Project description:The risk of APOE for Alzheimer's disease (AD) is modified by age. Beyond APOE, the polygenic architecture may also be heterogeneous across age. We aim to investigate age-related genetic heterogeneity of AD and identify genomic loci with differential effects across age. Stratified gene-based genome-wide association studies and polygenic variation analyses were performed in the younger (60-79 years, N = 14,895) and older (?80 years, N = 6559) age-at-onset groups using Alzheimer's Disease Genetics Consortium data. We showed a moderate genetic correlation (rg = 0.64) between the two age groups, supporting genetic heterogeneity. Heritability explained by variants on chromosome 19 (harboring APOE) was significantly larger in younger than in older onset group (p < 0.05). APOE region, BIN1, OR2S2, MS4A4E, and PICALM were identified at the gene-based genome-wide significance (p < 2.73 × 10-6) with larger effects at younger age (except MS4A4E). For the novel gene OR2S2, we further performed leave-one-out analyses, which showed consistent effects across subsamples. Our results suggest using genetically more homogeneous individuals may help detect additional susceptible loci.
Project description:OBJECTIVE:Increasing evidence suggests epidemiological and pathological links between Alzheimer's disease (AD) and Ischaemic Stroke (IS). We investigated the evidence that shared genetic factors underpin the two diseases. METHODS:Using genome wide association study (GWAS) data from METASTROKE+ (15,916 IS cases and 68,826 controls) and IGAP (17,008 AD cases and 37,154 controls), we evaluated known associations with AD and IS. On the subset of data for which we could obtain compatible genotype-level data (4,610 IS cases, 1,281 AD cases and 14,320 controls), we estimated the genome-wide genetic correlation (rG) between AD and IS, and the three subtypes (cardioembolic, small vessel, large vessel), using genome-wide SNP data. We then performed a meta-analysis and pathway analysis in the combined AD and small vessel stroke datasets to identify the SNPs and molecular pathways through which disease risk may be conferred. RESULTS:We found evidence of a shared genetic contribution between AD and small vessel stroke (rG(SE)=0.37(0.17); p=0.011). Conversely, there was no evidence to support shared genetic factors in AD and IS overall, or with the other stroke subtypes. Of the known GWAS associations with IS or AD, none reached significance for association with the other trait (or stroke subtypes). A meta-analysis of AD IGAP and METASTROKE+ small vessel stroke GWAS data highlighted a region (ATP5H/KCTD2/ICT1), associated with both diseases (p=1.8x10-8 ). A pathway analysis identified four associated pathways, involving cholesterol transport and immune response. INTERPRETATION:Our findings indicate shared genetic susceptibility to AD and small vessel stroke and highlight potential causal pathways and loci. This article is protected by copyright. All rights reserved.
Project description:OBJECTIVE:Alcohol use disorders are common conditions that have enormous social and economic consequences. Genome-wide association analyses were performed to identify genetic variants associated with a proxy measure of alcohol consumption and alcohol misuse and to explore the shared genetic basis between these measures and other substance use, psychiatric, and behavioral traits. METHOD:This study used quantitative measures from the Alcohol Use Disorders Identification Test (AUDIT) from two population-based cohorts of European ancestry (UK Biobank [N=121,604] and 23andMe [N=20,328]) and performed a genome-wide association study (GWAS) meta-analysis. Two additional GWAS analyses were performed, a GWAS for AUDIT scores on items 1-3, which focus on consumption (AUDIT-C), and for scores on items 4-10, which focus on the problematic consequences of drinking (AUDIT-P). RESULTS:The GWAS meta-analysis of AUDIT total score identified 10 associated risk loci. Novel associations localized to genes including JCAD and SLC39A13; this study also replicated previously identified signals in the genes ADH1B, ADH1C, KLB, and GCKR. The dimensions of AUDIT showed positive genetic correlations with alcohol consumption (rg=0.76-0.92) and DSM-IV alcohol dependence (rg=0.33-0.63). AUDIT-P and AUDIT-C scores showed significantly different patterns of association across a number of traits, including psychiatric disorders. AUDIT-P score was significantly positively genetically correlated with schizophrenia (rg=0.22), major depressive disorder (rg=0.26), and attention deficit hyperactivity disorder (rg=0.23), whereas AUDIT-C score was significantly negatively genetically correlated with major depressive disorder (rg=-0.24) and ADHD (rg=-0.10). This study also used the AUDIT data in the UK Biobank to identify thresholds for dichotomizing AUDIT total score that optimize genetic correlations with DSM-IV alcohol dependence. Coding individuals with AUDIT total scores ?4 as control subjects and those with scores ?12 as case subjects produced a significant high genetic correlation with DSM-IV alcohol dependence (rg=0.82) while retaining most subjects. CONCLUSIONS:AUDIT scores ascertained in population-based cohorts can be used to explore the genetic basis of both alcohol consumption and alcohol use disorders.
Project description:A growing number of studies clearly demonstrate a substantial link between metabolic dysfunction and the risk of Alzheimer's disease (AD), especially glucose-related dysfunction; one hypothesis for this comorbidity is the presence of a common genetic etiology. We conducted a large-scale cross-trait GWAS to investigate the genetic overlap between AD and ten metabolic traits. Among all the metabolic traits, fasting glucose, fasting insulin and HDL were found to be genetically associated with AD. Local genetic covariance analysis found that 19q13 region had strong local genetic correlation between AD and T2D (P?=?6.78?×?10-?22), LDL (P?=?1.74?×?10-?253) and HDL (P?=?7.94?×?10-?18). Cross-trait meta-analysis identified 4 loci that were associated with AD and fasting glucose, 3 loci that were associated with AD and fasting insulin, and 20 loci that were associated with AD and HDL (Pmeta?<?1.6?×?10-?8, single trait P?<?0.05). Functional analysis revealed that the shared genes are enriched in amyloid metabolic process, lipoprotein remodeling and other related biological pathways; also in pancreas, liver, blood and other tissues. Our work identifies common genetic architectures shared between AD and fasting glucose, fasting insulin and HDL, and sheds light on molecular mechanisms underlying the association between metabolic dysregulation and AD.
Project description:Anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) are often comorbid and likely to share genetic risk factors. Hence, we examine their shared genetic background using a cross-disorder GWAS meta-analysis of 3495 AN cases, 2688 OCD cases, and 18,013 controls. We confirmed a high genetic correlation between AN and OCD (rg?=?0.49?±?0.13, p?=?9.07?×?10-7) and a sizable SNP heritability (SNP h2?=?0.21?±?0.02) for the cross-disorder phenotype. Although no individual loci reached genome-wide significance, the cross-disorder phenotype showed strong positive genetic correlations with other psychiatric phenotypes (e.g., rg?=?0.36 with bipolar disorder and 0.34 with neuroticism) and negative genetic correlations with metabolic phenotypes (e.g., rg?=?-0.25 with body mass index and -0.20 with triglycerides). Follow-up analyses revealed that although AN and OCD overlap heavily in their shared risk with other psychiatric phenotypes, the relationship with metabolic and anthropometric traits is markedly stronger for AN than for OCD. We further tested whether shared genetic risk for AN/OCD was associated with particular tissue or cell-type gene expression patterns and found that the basal ganglia and medium spiny neurons were most enriched for AN-OCD risk, consistent with neurobiological findings for both disorders. Our results confirm and extend genetic epidemiological findings of shared risk between AN and OCD and suggest that larger GWASs are warranted.
Project description:There is a strong genetic basis for late-onset of Alzheimer’s disease (LOAD), and thus far >20 genes/loci have been identified that affect the risk of LOAD. In addition to disease risk, genetic variation at these loci may also affect components of the natural history of AD, such as survival in AD. In this study, we first examined the role of known LOAD genes with survival time in 983 AD patients. We then performed genome-wide single-nucleotide polymorphism (SNP) and gene-based association analyses to identify novel loci that may influence survival of AD. Survival analysis was conducted using Cox proportional hazards regression under an additive genetics model. We found multiple nominally significant associations (p < 0.01) either within or adjacent to known LOAD genes. Genome-wide SNP analysis identified multiple suggestive novel loci and two of them were also significant in gene-based analysis (CCDC85C and NARS2) that survived after controlling for false-discovery rate at 0.05. In summary, we have identified two novel genes for survival in AD that need to be replicated in independent samples. Our findings highlight the importance of focusing on AD-related phenotypes that may help to identify additional genes relevant toAD.
Project description:Insomnia is one of the most prevalent and burdensome mental disorders worldwide, affecting between 10-20% of adults and up to 48% of the geriatric population. It is further associated with substance usage and dependence, as well other psychiatric disorders. In this study, we combined electronic health record (EHR) derived phenotypes and genotype information to conduct a genome wide analysis of insomnia in a 18,055 patient cohort. Diagnostic codes were used to identify 3,135 patients with insomnia. Our genome-wide association study (GWAS) identified one novel genomic risk locus on chromosome 8 (lead SNP rs17052966, p?=?4.53 × 10-9, odds ratio = 1.28, se = 0.04). The heritability analysis indicated that common SNPs accounts for 7% (se?=?0.02, p?=?0.015) of phenotypic variation. We further conducted a large-scale meta-analysis of our results and summary statistics of two recent insomnia GWAS and 13 significant loci were identified. The genetic correlation analysis yielded a strong positive genetic correlation between insomnia and alcohol use (rG?=?0.56, se = 0.14, p?<?0.001), nicotine use (rG?=?0.50, se = 0.12, p?<?0.001) and opioid use (rG?=?0.43, se = 0.18, p?=?0.02) disorders, suggesting a significant common genetic risk factors between insomnia and substance use.
Project description:Neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD) suffer from the lack of risk-predictive circulating biomarkers, and clinical diagnosis occurs only when symptoms are evident. Among potential biomarkers, platelet parameters have been associated with both disorders. However, these associations have been scarcely investigated at the genetic level. Here, we tested genome-wide coheritability based on common genetic variants between platelet parameters and PD/AD risk, through Linkage Disequilibrium Score Regression. This revealed a significant genetic correlation between platelet distribution width (PDW), an index of platelet size variability, and PD risk (rg [SE] = 0.080 [0.034]; p = 0.019), which was confirmed by a summary-summary polygenic score analysis, where PDW explained a small but significant proportion PD risk (<1%). AD risk showed no significant correlations, although a negative trend was observed with PDW (rg [SE] =-0.088 [0.053]; p=0.096), in line with previous epidemiological reports. These findings suggest the existence of limited shared genetic bases between PDW and PD and warrant further investigations to clarify the genes involved in this relation. Additionally, they suggest that the association between platelet parameters and AD risk is more environmental in nature, prompting an investigation into which factors may influence these traits.