scholarly journals Genome-wide Association Study of Alcohol Consumption and Use Disorder in Multiple Populations (N = 274,424)

2019 ◽  
Author(s):  
Henry R. Kranzler ◽  
Hang Zhou ◽  
Rachel L. Kember ◽  
Rachel Vickers Smith ◽  
Amy C. Justice ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Alcohol Use ◽  
Alcohol Use Disorder ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Cell Type ◽  
Polygenic Risk ◽  
Consumption Level ◽  
Genome Wide

SummaryAlthough alcohol consumption level and alcohol use disorder (AUD) diagnosis are both moderately heritable, their genetic risks and overlap are not well understood. We conducted genome-wide association studies of these traits using longitudinal Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) scores (reflecting alcohol consumption) and AUD diagnoses from electronic health records (EHRs) in a single, large multi-ancestry Million Veteran Program sample. Meta-analysis across population groups (N = 274,424) identified 18 genome-wide significant loci, 5 of which were associated with both traits and 13 with either AUDIT-C (N = 8) or AUD (N = 5). A significant genetic correlation between the traits reflects this overlap. However, downstream analyses revealed biologically meaningful points of divergence. Cell-type group partitioning heritability enrichment analyses indicated that central nervous system was the most significant cell type for AUDIT-C and the only significant cell type for AUD. Polygenic risk scores (PRS) for both traits were associated with alcohol-related disorders in two independent samples. Genetic correlations for 188 non-alcohol-related traits were significantly different for the two traits, as were the phenotypes associated with the traits’ polygenic risk scores. We conclude that EHR-derived, longitudinal, repeated measures of alcohol consumption level and AUD diagnosis can facilitate genetic discovery and help to elucidate the relationship between drinking level and AUD risk. Finally, although heavy drinking is a key risk factor for AUD, it is not a sufficient cause of the disorder.

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.

scholarly journals Polygenic transcriptome risk scores (PTRS) can improve portability of polygenic risk scores across ancestries

2022 ◽  
Vol 23 (1) ◽  
Author(s):  
Yanyu Liang ◽  
Milton Pividori ◽  
Ani Manichaikul ◽  
Abraham A. Palmer ◽  
Nancy J. Cox ◽  
...  
Keyword(s):  
Association Studies ◽  
Poor Performance ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Transcript Levels ◽  
Polygenic Risk ◽  
Genome Wide

Abstract Background Polygenic risk scores (PRS) are valuable to translate the results of genome-wide association studies (GWAS) into clinical practice. To date, most GWAS have been based on individuals of European-ancestry leading to poor performance in populations of non-European ancestry. Results We introduce the polygenic transcriptome risk score (PTRS), which is based on predicted transcript levels (rather than SNPs), and explore the portability of PTRS across populations using UK Biobank data. Conclusions We show that PTRS has a significantly higher portability (Wilcoxon p=0.013) in the African-descent samples where the loss of performance is most acute with better performance than PRS when used in combination.

scholarly journals Evidence of shared genetic influences underlying schizophrenia and alcohol use disorder, but not alcohol consumption

2020 ◽  
Author(s):  
Emma C. Johnson ◽  
Manav Kapoor ◽  
Alexander S. Hatoum ◽  
Hang Zhou ◽  
Renato Polimanti ◽  
...  
Keyword(s):  
Alcohol Consumption ◽  
Alcohol Use ◽  
Genetic Variants ◽  
Alcohol Use Disorder ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Genetic Covariance ◽  
Genome Wide ◽  
Brain Tissues

AbstractBackgroundAlcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and recent genome-wide association studies (GWAS) have identified significant genetic correlations between them. In parallel, mounting evidence from GWAS suggests that alcohol consumption is only weakly genetically correlated with SCZ, but this has not yet been systematically investigated.MethodsWe used the largest published GWAS for AUD (total cases = 77,822) and SCZ (total cases = 46,827) to systematically identify genetic variants that influence both disorders (in either the same or opposite direction of effect) as well as disorder-specific loci, and contrast our findings with GWAS data for drinks per week (DPW; N = 537,349) as a measure of alcohol consumption.ResultsWe identified 55 independent genome-wide significant SNPs with the same direction of effect on AUD and SCZ, 9 with robust opposite effects, and 99 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001). The genetic correlation between DPW and SCZ (rg = 0.102, SE = 0.022) was significantly lower than that for AUD and SCZ (rg = 0.392, SE = 0.029; p-value of the difference = 9.3e-18), and the genetic covariance between DPW and SCZ was not enriched for any meaningful tissue-specific categories.ConclusionsOur findings provide a detailed view of genetic loci that influence risk of both AUD and SCZ, suggest that biological commonalities underlying genetic variants with an effect on both disorders are manifested in brain tissues, and provide further evidence that SCZ shares meaningful genetic overlap with AUD and not merely alcohol consumption.

scholarly journals Evaluating the Utility of Polygenic Risk Scores in Identifying High-Risk Individuals for Eight Common Cancers

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Guochong Jia ◽  
Yingchang Lu ◽  
Wanqing Wen ◽  
Jirong Long ◽  
Ying Liu ◽  
...  
Keyword(s):  
Cancer Risk ◽  
Association Studies ◽  
Elevated Risk ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cancer Case ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Risk Variants ◽  
Genome Wide

Abstract Background Genome-wide association studies have identified common genetic risk variants in many loci associated with multiple cancers. We sought to systematically evaluate the utility of these risk variants in identifying high-risk individuals for eight common cancers. Methods We constructed polygenic risk scores (PRS) using genome-wide association studies–identified risk variants for each cancer. Using data from 400 812 participants of European descent in a population-based cohort study, UK Biobank, we estimated hazard ratios associated with PRS using Cox proportional hazard models and evaluated the performance of the PRS in cancer risk prediction and their ability to identify individuals at more than a twofold elevated risk, a risk level comparable to a moderate-penetrance mutation in known cancer predisposition genes. Results During a median follow-up of 5.8 years, 14 584 incident case patients of cancers were identified (ranging from 358 epithelial ovarian cancer case patients to 4430 prostate cancer case patients). Compared with those at an average risk, individuals among the highest 5% of the PRS had a two- to threefold elevated risk for cancer of the prostate, breast, pancreas, colorectal, or ovary, and an approximately 1.5-fold elevated risk of cancer of the lung, bladder, or kidney. The areas under the curve ranged from 0.567 to 0.662. Using PRS, 40.4% of the study participants can be classified as having more than a twofold elevated risk for at least one site-specific cancer. Conclusions A large proportion of the general population can be identified at an elevated cancer risk by PRS, supporting the potential clinical utility of PRS for personalized cancer risk prediction.

Genome-wide investigation of alcohol response : a meta-analytic review and polygenic associations with alcohol use disorder

2020 ◽  
Author(s):  
◽  
Joseph D. Deak
Keyword(s):  
Alcohol Use ◽  
Alcohol Use Disorder ◽  
Meta Analysis ◽  
Genotype Imputation ◽  
Genetic Influences ◽  
Risk Scores ◽  
Individual Study ◽  
Polygenic Risk ◽  
Gene Set ◽  
Genome Wide

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI-COLUMBIA AT REQUEST OF AUTHOR.] The current study aimed to extend previous genetic studies of level of response (LR) to alcohol by conducting the largest genome-wide association study (GWAS) of LR to date through the meta-analysis of multiple samples with extant SRE (Self-rating of the Effects of Alcohol) and GWAS data. A second aim was to use summary data from the described GWAS of LR to create polygenic risk scores (PRS) in an independent sample in order to determine whether, and to what extent, the genetic influences underlying LR to alcohol serve as a risk factor for alcohol use disorder (AUD). Towards these aims, datasets were processed according to standard quality control (QC) procedures allowing for genotype imputation and GWA analysis using methods appropriate for the individual study designs. Following individual study-level GWAS analysis, results were meta-analyzed utilizing an inverse-variance weighted fixed-effects model in METAL resulting in a final sample size of N=10,635. GWAS summary statistics from the SRE meta-analysis were then used to conduct gene-based and gene-set analyses, as well as compute polygenic risk scores (PRS) in an independent target sample to examine the predictive ability of the LR to alcohol PRS for DSM-IV AD symptom counts. No individual variants, genes, or gene-sets achieved study-level significance, although multiple genetic loci of interest achieved suggestive significance. The top single variant association was in an intergenic region on chromosome 2 located near the FUNDC2P2 gene (rs12463481; p=6.35x10[superscript -8]), the top gene-based association was with the PRR16 gene on chromosome 5 (p=6.72x10 [superscript -6]), and the top gene-set was with a set of genes associated with NFE2L2 targets (p=1.21 x10 [superscript -5]). No results from the PRS analysis approached significance. These findings suggest that, similar to other alcohol use outcomes, larger sample sizes will be required for the robust detection of genetic influences contributing to level of response to alcohol.

scholarly journals Age varying polygenic effects on alcohol use in African Americans and European Americans from adolescence to adulthood

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kit K. Elam ◽  
Thao Ha ◽  
Zoe Neale ◽  
Fazil Aliev ◽  
Danielle Dick ◽  
...  
Keyword(s):  
Alcohol Use ◽  
Association Studies ◽  
Genetic Effects ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Longitudinal Models ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Polygenic Scores ◽  
Distal Outcome

AbstractGenetic effects on alcohol use can vary over time but are often examined using longitudinal models that predict a distal outcome at a single time point. The vast majority of these studies predominately examine effects using White, European American (EA) samples or examine the etiology of genetic variants identified from EA samples in other racial/ethnic populations, leading to inconclusive findings about genetic effects on alcohol use. The current study examined how genetic influences on alcohol use varied by age across a 15 year period within a diverse ethnic/racial sample of adolescents. Using a multi-ethnic approach, polygenic risk scores were created for African American (AA, n = 192) and EA samples (n = 271) based on racially/ethnically aligned genome wide association studies. Age-varying associations between polygenic scores and alcohol use were examined from age 16 to 30 using time-varying effect models separately for AA and EA samples. Polygenic risk for alcohol use was found to be associated with alcohol use from age 22–27 in the AA sample and from age 24.50 to 29 in the EA sample. Results are discussed relative to the intersection of alcohol use and developmental genetic effects in diverse populations.

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.

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