scholarly journals Genome-Wide Association Studies of Schizophrenia and Bipolar Disorder in a Diverse Cohort of US Veterans

2020 ◽  
Author(s):  
Tim B Bigdeli ◽  
Ayman H Fanous ◽  
Yuli Li ◽  
Nallakkandi Rajeevan ◽  
Frederick Sayward ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Susceptibility Loci ◽  
New Associations ◽  
Genome Wide ◽  
Us Veterans

Abstract Background Schizophrenia (SCZ) and bipolar disorder (BIP) are debilitating neuropsychiatric disorders, collectively affecting 2% of the world’s population. Recognizing the major impact of these psychiatric disorders on the psychosocial function of more than 200 000 US Veterans, the Department of Veterans Affairs (VA) recently completed genotyping of more than 8000 veterans with SCZ and BIP in the Cooperative Studies Program (CSP) #572. Methods We performed genome-wide association studies (GWAS) in CSP #572 and benchmarked the predictive value of polygenic risk scores (PRS) constructed from published findings. We combined our results with available summary statistics from several recent GWAS, realizing the largest and most diverse studies of these disorders to date. Results Our primary GWAS uncovered new associations between CHD7 variants and SCZ, and novel BIP associations with variants in Sortilin Related VPS10 Domain Containing Receptor 3 (SORCS3) and downstream of PCDH11X. Combining our results with published summary statistics for SCZ yielded 39 novel susceptibility loci including CRHR1, and we identified 10 additional findings for BIP (28 326 cases and 90 570 controls). PRS trained on published GWAS were significantly associated with case-control status among European American (P < 10–30) and African American (P < .0005) participants in CSP #572. Conclusions We have demonstrated that published findings for SCZ and BIP are robustly generalizable to a diverse cohort of US veterans. Leveraging available summary statistics from GWAS of global populations, we report 52 new susceptibility loci and improved fine-mapping resolution for dozens of previously reported associations.

scholarly journals S173. GENOME-WIDE ASSOCIATION STUDIES OF SCHIZOPHRENIA AND BIPOLAR DISORDER IN A DIVERSE COHORT OF US VETERANS

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S103-S103
Author(s):  
Tim Bigdeli ◽  
Ayman Fanous ◽  
Nallakkandi Rajeevan ◽  
Frederick Sayward ◽  
Yuli Li ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Us Veterans

Abstract Background Schizophrenia and bipolar disorder are debilitating neuropsychiatric illnesses collectively affecting 2% of the world’s population, and which cause tremendous human suffering that impacts patients, their families and their communities. Recognizing the major impact of these disorders on the psychosocial function of more than 200,000 US Veterans, the Department of Veterans Affairs (VA) recently genotyping of nearly 9,000 veterans with schizophrenia or bipolar I disorder in Cooperative Studies Program (CSP) #572: “Genetics of Functional Disability in Schizophrenia and Bipolar Illness”, all of whom were extensively assessed for neurocognitive function and disability, and genotyped using a custom Affymetrix Axiom Biobank array. Methods Primary genome-wide association studies (GWAS) of schizophrenia and bipolar disorder were performed across and within ancestry goups, with attempted replication in matched subjects from the PGC and Genomic Psychiatry Cohort (GPC). We combined results for CSP#572 with available summary statistics from the PGC, Indonesia Schizophrenia Consortium and Genetic REsearch on schizophreniA neTwork-China and Netherland (GREAT-CN) study, and multi-ethnic GPC cohorts, achieving among the largest and most diverse studies of these disorders to date. Results Polygenic risk scores based on published PGC summary statistics for schizophrenia or bipolar disorder were significantly associated with case status among EA (P<10–30) and AA (P<0.0005) participants in CSP#572. Our primary analyses of schizophrenia yielded a single genome-wide significant association with variants in CHD7 at 8q12.2 for European-American (EA) participants, which remained significant in a joint analysis of EA and African-American (AA) subjects (P=4.62e-08). While no genome-wide significant associations were detected by our within-ancestry analyses of bipolar disorder, a cross-ancestry meta-analysis of CSP#572 participants yielded a significant finding at 10q25 with variants in SORCS3 (P=2.62e-08). Among loci attaining P<0.0001 in our within-ancestry analyses, 4 and 8 subsequently achieved genome-wide significance, respectively, when jointly analyzed with matched subjects from the PGC and GPC. Combining our results with published summary statistics, we performed a cross-ancestry GWAS meta-analysis of 69,280 schizophrenia cases and 138,379 controls, identifying 200 genome-wide significant loci of which 76 are newly reported here. Cross-ancestry analysis of 28,326 bipolar cases and 90,570 controls identified 24 genome-wide significant loci, including novel associations with common variants in PAX5, DOCK2, MACROD2, BRE, KCNG1, and LINC01378. Discussion We newly describe genome-wide analyses in a diverse cohort of US Veterans with schizophrenia or bipolar disorder, benchmarking the predictive value of polygenic risk scores based on published GWAS findings. Leveraging available summary statistics from studies of global populations, we add to burgeoning lists of genomic loci implicated in the etiologies of these disorders.

scholarly journals Genome-Wide Association Studies of Schizophrenia and Bipolar Disorder in a Diverse Cohort of US Veterans

2020 ◽  
Vol 87 (9) ◽  
pp. S178
Author(s):  
Tim Bigdeli ◽  
Ayman Fanous ◽  
Yuli Li ◽  
Nallakkandi Rajeevan ◽  
Frederick Sayward ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Us Veterans

Identification of six novel susceptibility loci for dyslipidemia by longitudinal exome-wide association studies in Japanese

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
M Oguri ◽  
K Kato ◽  
H Horibe ◽  
T Fujimaki ◽  
J Sakuma ◽  
...  
Keyword(s):  
Serum Lipid ◽  
Ldl Cholesterol ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Hdl Cholesterol ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Susceptibility Loci ◽  
Cross Sectional ◽  
Genome Wide

Abstract Background The circulating concentrations of triglycerides, high density lipoprotein (HDL)-cholesterol, and low density lipoprotein (LDL)-cholesterol have a substantial genetic component. Although previous genome-wide association studies identified various genes and loci related to plasma lipid levels, those studies were conducted in a cross-sectional manner. Purpose The purpose of the study was to identify genetic variants that confer susceptibility to hypertriglyceridemia, hypo-HDL-cholesterolemia, and hyper-LDL-cholesterolemia in Japanese. We have now performed longitudinal exome-wide association studies (EWASs) to identify novel loci for dyslipidemia by examining temporal changes in serum lipid profiles. Methods Longitudinal EWASs (mean follow-up period, 5 years) for hypertriglyceridemia (2056 case, 3966 controls), hypo-HDL-cholesterolemia (698 cases, 5324 controls), and hyper-LDL-cholesterolemia (2769 cases, 3251 controls) were performed with Illumina Human Exome arrays. The relation of genotypes of 24,691 single nucleotide polymorphisms (SNPs) that passed quality control to dyslipidemia-related traits was examined with the generalized estimating equation (GEE). To compensate for multiple comparisons of genotypes with each of the three conditions, we applied Bonferroni's correction for statistical significance of association. Replication studies with cross-sectional data were performed for hypertriglyceridemia (2685 cases, 4703 controls), hypo-HDL-cholesterolemia (1947 cases, 6146 controls), and hyper-LDL-cholesterolemia (1719 cases, 5833 controls). Results Longitudinal EWASs revealed that 30 SNPs were significantly (P<2.03 × 10–6 by GEE) associated with hypertriglyceridemia, 46 SNPs with hypo-HDL-cholesterolemia, and 25 SNPs with hyper-LDL-cholesterolemia. After examination of the relation of identified SNPs to serum lipid profiles, linkage disequilibrium, and results of the previous genome-wide association studies, we newly identified rs74416240 of TCHP, rs925368 of GIT2, rs7969300 of ATXN2, and rs12231744 of NAA25 as a susceptibility loci for hypo-HDL-cholesterolemia; and rs34902660 of SLC17A3 and rs1042127 of CDSN for hyper-LDL-cholesterolemia. These SNPs were not in linkage disequilibrium with those previously reported to be associated with dyslipidemia, indicating independent effects of the SNPs identified in the present study on serum concentrations of HDL-cholesterol or LDL-cholesterol in Japanese. According to allele frequency data from the 1000 Genomes project database, five of the six identified SNPs were monomorphic or rare variants in European populations. In the replication study, all six SNPs were associated with dyslipidemia-related phenotypes. Conclusion We have thus identified six novel loci that confer susceptibility to hypo-HDL-cholesterolemia or hyper-LDL-cholesterolemia. Determination of genotypes for these SNPs at these loci may prove informative for assessment of the genetic risk for dyslipidemia in Japanese. Funding Acknowledgement Type of funding source: None

scholarly journals CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

2019 ◽  
Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Genetic Variants ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genome Wide ◽  
Credible Sets ◽  
Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

scholarly journals Age-related late-onset disease heritability patterns and implications for genome-wide association studies

2018 ◽  
Author(s):  
Roman Teo Oliynyk
Keyword(s):  
Old Age ◽  
Cumulative Incidence ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cerebral Stroke ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

AbstractBackgroundGenome-wide association studies and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called “missing heritability” problem.MethodsComputer simulations of polygenic late-onset diseases in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes.ResultsThe incidence rate for late-onset diseases grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for genome-wide association studies overrepresent older individuals with lower polygenic risk scores, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and genome-wide association studies. It also explains the relatively constant-with-age heritability found for late-onset diseases of lower prevalence, exemplified by cancers.ConclusionsFor late-onset polygenic diseases showing high cumulative incidence together with high initial heritability, rather than using relatively old age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

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