Participants Of African Ancestry Research Articles

Genome-Wide Association Study Meta-Analysis Uncovers Novel Genetic Variants Associated with Olfactory Dysfunction.

Olfactory dysfunction is among the earliest signs of many age-related neurodegenerative diseases and has been associated with increased mortality in older adults; however, its genetic basis remains largely unknown. To identify the genetic loci associated with olfactory dysfunction in the general population. This genome-wide association study meta-analysis (GWMA) included participants of European ancestry (N = 22,730) enrolled in four different large population-based studies, followed by a multi-ancestry GWMA including participants of African ancestry (N = 1,030). The data analysis was performed from March 2023 through June 2024. Genome-wide single nucleotide polymorphisms. Olfactory dysfunction was the outcome and assessed using a 12-item smell identification test. GWMA revealed a novel genome-wide significant locus (tagged by rs11228623 at 11q12) associated with olfactory dysfunction. Gene-based analysis revealed a high enrichment for olfactory receptor genes in this region. Phenome-wide association studies demonstrated associations between genetic variants related to olfactory dysfunction and blood cell counts, kidney function, skeletal muscle mass, cholesterol levels and cardiovascular disease. Using individual-level data, we also confirmed and quantified the strength of these associations on a phenotypic level. Moreover, employing two-sample Mendelian Randomization analyses, we found evidence for causal associations between olfactory dysfunction and these phenotypes. These findings provide novel insights into the genetic architecture of the sense of smell and highlight its importance for many aspects of human health.

Application of polygenic scores to a deeply phenotyped sample enriched for substance use disorders reveals extensive pleiotropy with psychiatric and somatic traits

Co-occurring psychiatric, medical, and substance use disorders (SUDs) are common, but the complex pathways leading to such comorbidities are poorly understood. A greater understanding of genetic influences on this phenomenon could inform precision medicine efforts. We used the Yale-Penn dataset, a cross-sectional sample enriched for individuals with SUDs, to examine pleiotropic effects of genetic liability for psychiatric and somatic traits. Participants completed an in-depth interview that provides information on demographics, environment, medical illnesses, and psychiatric and SUDs. Polygenic scores (PGS) for psychiatric disorders and somatic traits were calculated in European-ancestry (EUR; n = 5691) participants and, when discovery datasets were available, for African-ancestry (AFR; n = 4918) participants. Phenome-wide association studies (PheWAS) were then conducted. In AFR participants, the only PGS with significant associations was bipolar disorder (BD), all of which were with substance use phenotypes. In EUR participants, PGS for major depressive disorder (MDD), generalized anxiety disorder (GAD), post-traumatic stress disorder (PTSD), schizophrenia (SCZ), body mass index (BMI), coronary artery disease (CAD), and type 2 diabetes (T2D) all showed significant associations, the majority of which were with phenotypes in the substance use categories. For instance, PGSMDD was associated with over 200 phenotypes, 15 of which were depression-related (e.g., depression criterion count), 55 of which were other psychiatric phenotypes, and 126 of which were substance use phenotypes; and PGSBMI was associated with 138 phenotypes, 105 of which were substance related. Genetic liability for psychiatric and somatic traits is associated with numerous phenotypes across multiple categories, indicative of the broad genetic liability of these traits.

Polygenic prediction of major depressive disorder and related traits in African ancestries UK Biobank participants.

Genome-Wide Association Studies (GWAS) over-represent European ancestries, neglecting all other ancestry groups and low-income nations. Consequently, polygenic risk scores (PRS) more accurately predict complex traits in Europeans than African Ancestries groups. Very few studies have looked at the transferability of European-derived PRS for behavioural and mental health phenotypes to Africans. We assessed the comparative accuracy of depression PRS trained on European and African Ancestries GWAS studies to predict major depressive disorder (MDD) and related traits in African ancestry participants from the UK Biobank. UK Biobank participants were selected based on Principal component analysis clustering with an African genetic similarity reference population, MDD was assessed with the Composite International Diagnostic Interview (CIDI). PRS were computed using PRSice2 software using either European or African Ancestries GWAS summary statistics. PRS trained on European ancestry samples (246,363 cases) predicted case control status in Africans of the UK Biobank with similar accuracies (R2 = 2%, β = 0.32, empirical p-value = 0.002) to PRS trained on far much smaller samples of African Ancestries participants from 23andMe, Inc. (5045 cases, R² = 1.8%, β = 0.28, empirical p-value = 0.008). This suggests that prediction of MDD status from Africans to Africans had greater efficiency relative to discovery sample size than prediction of MDD from Europeans to Africans. Prediction of MDD status in African UK Biobank participants using GWAS findings of likely causal risk factors from European ancestries was non-significant. GWAS of MDD in European ancestries are inefficient for improving polygenic prediction in African samples; urgent MDD studies in Africa are needed.

Fish oil supplementation modifies the associations between genetically predicted and observed concentrations of blood lipids: a cross-sectional gene-diet interaction study in UK Biobank

BackgroundDyslipidemia is a well-known risk factor for cardiovascular disease, the leading cause of mortality worldwide. Although habitual intake of fish oil is associated with cardioprotective effects through triglyceride reduction, the interactions of fish oil with the genetic predisposition to dysregulated lipids remain elusive. ObjectivesWe examined whether fish oil supplementation modifies the association between genetically predicted and observed concentrations of total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides. MethodsA total of 441,985 participants with complete genetic and phenotypic data from the UK Biobank were included. Polygenic scores (PGS) of the 4 lipids were calculated in participants of diverse ancestries. For each lipid, multivariable linear regression models were used to assess if fish oil supplementation modified the association between PGS and the observed circulating concentration, with adjustment for relevant covariates. ResultsFish oil supplementation attenuates the associations between genetically predicted and observed circulating concentrations of total cholesterol, LDL cholesterol, and triglycerides while accentuating the corresponding association for HDL cholesterol among 424,090 participants of European ancestry. Consistent significant findings were obtained using PGS calculated based on multiple genome-wide association studies or alternative PGS methods. For triglycerides, each standard deviation (SD) increment in PGS is associated with 0.254 [95% confidence interval (CI): 0.248, 0.259] SD increase in the observed concentration among European-ancestry participants who reported fish oil usage. In contrast, a stronger association was observed in nonusers (0.267; 95% CI: 0.263, 0.270). Consistently, we showed that fish oil significantly attenuates the association between genetically predicted and observed concentrations of triglycerides in African-ancestry participants. ConclusionsFish oil supplementation attenuates the association between genetically predicted and observed circulating concentrations of total cholesterol, LDL cholesterol, and triglycerides while accentuating the corresponding association for HDL cholesterol in individuals of European ancestry. Further research is needed to understand the clinical implications of these findings.

Association of PHACTR1 with Coronary Artery Calcium Differs by Sex and Cigarette Smoking.

Background: Coronary artery calcium (CAC) is a marker of subclinical atherosclerosis and is a complex heritable trait with both genetic and environmental risk factors, including sex and smoking. Methods: We performed genome-wide association (GWA) analyses for CAC among all participants and stratified by sex in the COPDGene study (n = 6144 participants of European ancestry and n = 2589 participants of African ancestry) with replication in the Diabetes Heart Study (DHS). We adjusted for age, sex, current smoking status, BMI, diabetes, self-reported high blood pressure, self-reported high cholesterol, and genetic ancestry (as summarized by principal components computed within each racial group). For the significant signals from the GWA analyses, we examined the single nucleotide polymorphism (SNP) by sex interactions, stratified by smoking status (current vs. former), and tested for a SNP by smoking status interaction on CAC. Results: We identified genome-wide significant associations for CAC in the chromosome 9p21 region [CDKN2B-AS1] among all COPDGene participants (p = 7.1 × 10-14) and among males (p = 1.0 × 10-9), but the signal was not genome-wide significant among females (p = 6.4 × 10-6). For the sex stratified GWA analyses among females, the chromosome 6p24 region [PHACTR1] had a genome-wide significant association (p = 4.4 × 10-8) with CAC, but this signal was not genome-wide significant among all COPDGene participants (p = 1.7 × 10-7) or males (p = 0.03). There was a significant interaction for the SNP rs9349379 in PHACTR1 with sex (p = 0.02), but the interaction was not significant for the SNP rs10757272 in CDKN2B-AS1 with sex (p = 0.21). In addition, PHACTR1 had a stronger association with CAC among current smokers (p = 6.2 × 10-7) than former smokers (p = 7.5 × 10-3) and the SNP by smoking status interaction was marginally significant (p = 0.03). CDKN2B-AS1 had a strong association with CAC among both former (p = 7.7 × 10-8) and current smokers (p = 1.7 × 10-7) and the SNP by smoking status interaction was not significant (p = 0.40). Conclusions: Among current and former smokers of European ancestry in the COPDGene study, we identified a genome-wide significant association in the chromosome 6p24 region [PHACTR1] with CAC among females, but not among males. This region had a significant SNP by sex and SNP by smoking interaction on CAC.

Adaptive selection at G6PD and disparities in diabetes complications.

Diabetes complications occur at higher rates in individuals of African ancestry. Glucose-6-phosphate dehydrogenase deficiency (G6PDdef), common in some African populations, confers malaria resistance, and reduces hemoglobin A1c (HbA1c) levels by shortening erythrocyte lifespan. In a combined-ancestry genome-wide association study of diabetic retinopathy, we identified nine loci including a G6PDdef causal variant, rs1050828 -T (Val98Met), which was also associated with increased risk of other diabetes complications. The effect of rs1050828 -T on retinopathy was fully mediated by glucose levels. In the years preceding diabetes diagnosis and insulin prescription, glucose levels were significantly higher and HbA1c significantly lower in those with versus without G6PDdef. In the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, participants with G6PDdef had significantly higher hazards of incident retinopathy and neuropathy. At the same HbA1c levels, G6PDdef participants in both ACCORD and the Million Veteran Program had significantly increased risk of retinopathy. We estimate that 12% and 9% of diabetic retinopathy and neuropathy cases, respectively, in participants of African ancestry are due to this exposure. Across continentally defined ancestral populations, the differences in frequency of rs1050828 -T and other G6PDdef alleles contribute to disparities in diabetes complications. Diabetes management guided by glucose or potentially genotype-adjusted HbA1c levels could lead to more timely diagnoses and appropriate intensification of therapy, decreasing the risk of diabetes complications in patients with G6PDdef alleles.

Genotype-based "virtual" metabolomics in a clinical biobank identifies novel metabolite-disease associations.

Introduction: Circulating metabolites act as biomarkers of dysregulated metabolism and may inform disease pathophysiology. A portion of the inter-individual variability in circulating metabolites is influenced by common genetic variation. We evaluated whether a genetics-based "virtual" metabolomics approach can identify novel metabolite-disease associations. Methods: We examined the association between polygenic scores for 724 metabolites with 1,247 clinical phenotypes in the BioVU DNA biobank, comprising 57,735 European ancestry and 15,754 African ancestry participants. We applied Mendelian randomization (MR) to probe significant relationships and validated significant MR associations using independent GWAS of candidate phenotypes. Results and Discussion: We found significant associations between 336 metabolites and 168 phenotypes in European ancestry and 107 metabolites and 56 phenotypes in African ancestry. Of these metabolite-disease pairs, MR analyses confirmed associations between 73 metabolites and 53 phenotypes in European ancestry. Of 22 metabolitephenotype pairs evaluated for replication in independent GWAS, 16 were significant (false discovery rate p < 0.05). These included associations between bilirubin and X-21796 with cholelithiasis, phosphatidylcholine (16:0/22:5n3,18:1/20:4) and arachidonate with inflammatory bowel disease and Crohn's disease, and campesterol with coronary artery disease and myocardial infarction. These associations may represent biomarkers or potentially targetable mediators of disease risk.

Using genome and transcriptome data from African-ancestry female participants to identify putative breast cancer susceptibility genes

African-ancestry (AA) participants are underrepresented in genetics research. Here, we conducted a transcriptome-wide association study (TWAS) in AA female participants to identify putative breast cancer susceptibility genes. We built genetic models to predict levels of gene expression, exon junction, and 3′ UTR alternative polyadenylation using genomic and transcriptomic data generated in normal breast tissues from 150 AA participants and then used these models to perform association analyses using genomic data from 18,034 cases and 22,104 controls. At Bonferroni-corrected P < 0.05, we identified six genes associated with breast cancer risk, including four genes not previously reported (CTD-3080P12.3, EN1, LINC01956 and NUP210L). Most of these genes showed a stronger association with risk of estrogen-receptor (ER) negative or triple-negative than ER-positive breast cancer. We also replicated the associations with 29 genes reported in previous TWAS at P < 0.05 (one-sided), providing further support for an association of these genes with breast cancer risk. Our study sheds new light on the genetic basis of breast cancer and highlights the value of conducting research in AA populations.

430 Genome-wide meta-analysis identifies novel risk loci for uterine fibroids across multiple ancestry groups

OBJECTIVES/GOALS: Uterine fibroids are benign tumors of the uterus with a high disease prevalence and burden, yet there are few multi-ancestry genetic studies. This is the largest and most diverse fibroid GWAS to-date. Our goal is to identify novel genetic variants and gene expression pathways associated with fibroids and characterize their biological relevance. METHODS/STUDY POPULATION: We performed a cross-ancestry meta-analysis of GWAS summary statistics from eight datasets. The total sample size was 74,294 cases and 465,810 controls with participants of European (80% of sample), African (4%), East Asian, and Central South Asian (16%) ancestry. We mapped variants to genes with OpenTarget Genetics and used Functional Mapping and Annotation to conduct tissue expression gene-set enrichment and identify lead variants. We used S-PrediXcan to estimate genetically predicted gene expression (GPGE) associated with fibroid risk. This was with models that predicted gene expression across 49 different tissue types. Ingenuity Pathway Analysis compiled significant GPGE genes and their weights with a scientific literature database to identify overlapping pathways. RESULTS/ANTICIPATED RESULTS: We identified 370 independent significant variants. Among these, we identified variants mapped to three novel genes (PAX2, VIP, FOXO3) and eight genes not previously validated (TEKT1, SLC16A11, RPEL1, RASL11B, ASGR1, SLC12A7, TTC28, POLR2A). Many loci have roles in cell cycle regulation or are associated with fibroid risk factors like blood pressure, BMI, and vitamin D levels. Loci were significantly enriched in DNA damage and cell cycle pathways. Of 588 significant predicted expression gene-tissue pairs, 173 unique genes were novel fibroid associations. These genes are also associated with cancers, estradiol, and endometriosis. Top enriched pathways included p53 signaling, HOTAIR, BRCA1DNA damage response, and pulmonary fibrosis signaling. In uterine tissue there were 15 novel GPGE associations. DISCUSSION/SIGNIFICANCE: Using this large and diverse data, we identified novel loci associated with fibroids that are enriched in hormone-response, DNA damage, and cell-cycle pathways. GPGE loci were in tumorigenesis and fibrosis pathways. These novel genetic loci and uterine gene expression findings may provide translational opportunities for novel fibroid treatments.

Abstract 4801: Clinical polygenic model to stratify risk of any, metastatic, and fatal prostate cancer in a randomized controlled trial of precision screening

Abstract Introduction: Lifetime risk of prostate cancer (PCa) is strongly associated with three factors: ancestry, family history, and genetics. We previously developed a polygenic hazard score (PHS) for PCa comprised of 290 common genetic variants (PHS290). When accounting for family history and ancestry (self-reported or genetically determined), PHS290 remained a powerful independent predictor of age at PCa diagnosis, metastatic PCa diagnosis, and PCa death. Additional variants associated with PCa susceptibility or benign elevation of prostate-specific antigen (PSA) have since been published. Here, we evaluate their impact on lifetime risk predictions for metastatic and fatal PCa and develop an updated polygenic score. This score will inform the design of the Prostate Cancer, Genetic Risk, and Equitable Screening Study (ProGRESS, ClinicalTrials.gov ID NCT05926102), a nationwide randomized controlled trial evaluating precision PCa screening in the VA healthcare system. Methods: We utilized a machine learning approach to update the PHS. Over 450 variants associated with PCa, aggressive PCa, benign prostatic hyperplasia, or benign PSA elevation were evaluated for inclusion. First, we identified pairs of variants with highly correlated genotype (defined as R2 &amp;gt; 0.95) and utilized univariable Cox proportional hazards models (using age at diagnosis of PCa) to exclude one variant from each pair. We then evaluated all remaining candidate variants for inclusion in a new PHS using a LASSO-regularized Cox proportional hazards model. We combined the new PHS with clinical predictors (ancestry and family history) to create a comprehensive, quantitative polygenic score in a diverse, population-based cohort of n=590,750 (Million Veteran Program). Both self-reported and genetic ancestry (based on 2,309 ancestry informative markers) were assessed. We estimated hazard ratios (HRs) to compare men with high versus low polygenic score and evaluated absolute predictions of any, metastatic, and fatal PCa. Results: The updated polygenic score included 356 variants, as well as family history and genetic ancestry. When comparing the highest to the lowest quintile of the population for polygenic score, the HRs for any PCa, metastatic PCa, and fatal PCa were 5.6, 5.8, and 5.2 respectively. These HRs are all greater than those achieved with PHS290, which yielded 5.2, 4.9, and 4.4 respectively. Risk stratification improved within each ancestry group, including within the &amp;gt;100,000 participants of African ancestry—a group known to have elevated risk of fatal PCa. Absolute risk prediction was accurate for both metastatic and fatal PCa. Conclusion: The polygenic score accurately predicts risk of metastatic and fatal PCa in multiple ancestry groups. A clinical polygenic model has potential utility for precision PCa screening and will now be evaluated prospectively in the ProGRESS trial. Citation Format: Anna M. Dornisch, Roshan Karunamuni, Kara N. Maxwell, Julie Lynch, Isla P. Garraway, Adam Kibel, Charles A. Brunette, Morgan E. Danowski, Kyung M. Lee, Scott L. DuVall, J M. Gaziano, Brent S. Rose, Richard L. Hauger, Jason L. Vassy, Tyler M. Seibert. Clinical polygenic model to stratify risk of any, metastatic, and fatal prostate cancer in a randomized controlled trial of precision screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4801.

Abstract P493: A Multivariate Analysis of Genetic Risk Scores for Heart Failure and Left Ventricular Mass Derived From Multi-Ancestry Populations and Left Ventricular Mass Amongst African Americans: The Jackson Heart Study

Background: Increased left ventricular (LV) mass is an outcome of LV remodeling that can result in development of left ventricular hypertrophy (LVH), a maladaptive disorder that increases the risk of heart failure. Elevated LV mass is a sensitive predictor of adverse cardiovascular events. African Americans experience a disproportionate burden of heart failure risk and development of LVH. The influence of genetics on this health disparity is unclear and a topic of interest. Genome-wide association studies (GWAS) have uncovered many variants associated with numerous adverse cardiovascular outcomes, such as heart failure and LV phenotypes. However, the relevance of these studies for African Americans may be limited as these analyses have been conducted in multi-ancestry populations with limited representation of African heritage. The question of whether these genetic risk variants can be used to predict LV phenotypes in an independent African American population remains unanswered. Hypothesis: Variant loci that have been associated with heart failure and LV mass in multi-ancestry populations will be associated with LV mass amongst African Americans in the Jackson Heart Study (JHS). Methods: Thirty-nine (39) SNPs associated with heart failure and ten (10) SNPs associated with LV mass were identified from two published studies in which participants of African ancestry or Black individuals comprised less than 15% and 2%, respectively. Using the published effect size estimates, genetic risk scores (GRSs) for heart failure and LV mass were computed for 2,175 African American participants (mean age 55, 63% female) in the JHS with complete data and consent for genetic research. We assessed the linear association of heart failure and LV mass GRSs with LV mass indexed to height (LVM h ) and indexed to body surface area (LVM bsa ). A multivariate general linear model was fit to both LVM h and LVM bsa containing both GRS predictors and accounting for age, sex, BMI (mean 31.5), diabetes (22%), and hypertension (52%). No multicollinearity was noted among these explanatory variables using variance inflation factors. Due to non-constant error variance, a log transformation was conducted on both LV mass response variables. Type III MANOVA Pillai tests were run to assess the effects of the GRSs on the log LVM bsa and log LVM h values. Conclusion: When accounting for age, BMI, sex, diabetes, and hypertension, we found that neither the heart failure GRS (p-val = 0.4012) nor the LV mass GRS (p-val = 0.8332) had an effect on both log LVM bsa and log LVM h . There is insufficient evidence to suggest that heart failure and LV mass variants derived from predominantly European multi-ancestry populations are linearly associated with log LV mass amongst African Americans in the Jackson Heart Study. Our work highlights the need for greater recruitment and targeted studies of populations with African ancestry for GWAS of LV phenotypes.

Genomic data in the All of Us Research Program

Comprehensively mapping the genetic basis of human disease across diverse individuals is a long-standing goal for the field of human genetics1–4. The All of Us Research Program is a longitudinal cohort study aiming to enrol a diverse group of at least one million individuals across the USA to accelerate biomedical research and improve human health5,6. Here we describe the programme’s genomics data release of 245,388 clinical-grade genome sequences. This resource is unique in its diversity as 77% of participants are from communities that are historically under-represented in biomedical research and 46% are individuals from under-represented racial and ethnic minorities. All of Us identified more than 1 billion genetic variants, including more than 275 million previously unreported genetic variants, more than 3.9 million of which had coding consequences. Leveraging linkage between genomic data and the longitudinal electronic health record, we evaluated 3,724 genetic variants associated with 117 diseases and found high replication rates across both participants of European ancestry and participants of African ancestry. Summary-level data are publicly available, and individual-level data can be accessed by researchers through the All of Us Researcher Workbench using a unique data passport model with a median time from initial researcher registration to data access of 29 hours. We anticipate that this diverse dataset will advance the promise of genomic medicine for all.

TRANSETHNIC META-ANALYSIS OF INTERACTIONS BETWEEN GENETICS AND EARLY-LIFE SOCIOECONOMIC CONTEXT ON COGNITION

Abstract Later-life cognitive function is influenced by genetics as well as early- and later-life socioeconomic context. However, few studies have examined the interaction between genetics and early childhood factors. Using gene-based tests (interaction sequence kernel association test [iSKAT]/iSKAT optimal unified test), we examined whether common and rare variants in 39 gene regions previously associated with cognitive performance, dementia, and related traits had an interaction with childhood socioeconomic context (parental education and financial strain) on memory performance or decline in European ancestry (EA, N = 10,468) and African ancestry (AA, N = 2,252) participants from the Health and Retirement Study. Of the 39 genes, 22 in EA and 19 in AA had nominally significant interactions with at least one childhood socioeconomic measure on memory performance and/or decline; however, only one, SLC24A4 x father’s education, remained significant after multiple testing correction (false discovery rate [FDR] &amp;lt; .05). In trans-ethnic meta-analysis, 2 genes interacted with childhood socioeconomic context: MS4A4A x mother’s education on memory performance, and SLC24A4 x father’s education on memory decline. Both interactions remained significant after adjusting for respondent’s own education, apolipoprotein-ε4 allele status, lifestyle factors, body mass index, and comorbidities. For both interactions in EA and AA, the genetic effect was stronger in participants with low parental education. Examination of common and rare variants in genes discovered through genome-wide association studies shows that childhood context may interact with gene regions to jointly impact later-life memory function and decline. Genetic effects may be more salient for those with lower childhood socioeconomic status.

Abstract 16950: The Genetic Basis of Atrial Fibrillation in a Large-Scale Multi-Ancestry Sample

Introduction: Atrial fibrillation (AF) is a heritable arrhythmia and associated with substantial morbidity. Hypothesis/Aims: We sought to expand our understanding of the genetic basis of AF by examining a large and ancestrally diverse sample. Methods: We performed a meta-analysis of ancestry-specific GWAS results from 600K unrelated individuals (85K with AF) in the Million Veteran Program (MVP) with GWAS results from nearly 2.25 million individuals (267K with AF) in the Atrial Fibrillation Consortium (AFGen). We estimated genetic correlations across ancestry groups and traits in MVP. To evaluate GWAS loci, we examined possible gene functions, prioritized relevant genes and pathways, and explored potential drug targets. We derived a multi-ancestry polygenic risk score (PRS) and independently evaluated associations with AF in the All of Us cohort (nearly 100K individuals; 3K with AF). Results: We identified 376 loci associated with AF, including 63 that have not been reported. We observed closer genetic correlation of AF between individuals of European and Hispanic (r2=1.0) than with African ancestry (r2=0.6). AF is highly correlated genetically with multiple cardiovascular traits, especially coronary artery disease, heart failure, and hypertension. GWAS loci implicate 15 genetic regulators of the cardiac action potential, including targets of commonly used AF drugs and 2 potential therapeutic targets whose predicted cardiac expression is positively associated with AF risk (KCNJ5 and KCND3). A PRS derived from the meta-analysis outperforms all previously reported PRSs in European, African and Hispanic ancestry participants and is strongly associated with multiple cardiovascular outcomes. Conclusions: In the largest genetic study of AF to date, we identify disease-relevant pathways and improve polygenic prediction for AF. We demonstrate the importance of ancestry-specific analyses in assessing AF risk and suggest that further inclusion of participants from more diverse ancestries is likely to accelerate genetic discoveries.

A Protective Role of Low Polygenic Risk Score in Healthy Individuals Carrying Attention-Deficit/Hyperactivity Disorder–Associated Copy Number Variations

BackgroundPrevious studies have implicated both rare copy number variations (CNVs) and common variants in liability for attention-deficit/hyperactivity disorder (ADHD). However, how common and rare genetic variants jointly contribute to individual liability requires further investigation in larger cohorts. MethodsThis study comprises 9385 participants of European descent and 7810 participants of African American ancestry who were recruited from the greater Philadelphia area by the Children’s Hospital of Philadelphia. The polygenic risk score (PRS) of each participant was estimated by linkage disequilibrium pruning and p-value thresholding (P + T) methods using PRSice-2. We investigated whether the risk of ADHD follows a polygenic liability threshold model wherein 1) the risk of ADHD requires less contribution from common variants in the presence of a rare CNV, and 2) control carriers of ADHD-associated CNVs have lower common risk allele burden than noncarriers. ResultsCNVs previously reported in ADHD cases were significantly associated with ADHD risk in both the European American cohort and the African American cohort. Healthy control participants carrying those same risk CNVs had lower PRSs than those without risk CNVs in the European American cohort. This result was replicated in the African American cohort. However, PRSs were not significantly different in case participants carrying risk CNVs versus those without risk CNVs. ConclusionsThese findings provide evidence in support of interactive effects of PRS and ADHD-associated CNVs on disease risk and add novel insights into the genetic basis of ADHD by highlighting a protective role of low PRS in ADHD.

Genetic Inhibition of APOL1 Pore-Forming Function Prevents APOL1-Mediated Kidney Disease.

African Americans are at increased risk of CKD in part due to high-risk (HR) variants in the apolipoprotein L1 ( APOL1 ) gene, termed G1/G2. A different APOL1 variant, p.N264K , reduced the risk of CKD and ESKD among carriers of APOL1 HR variants to levels comparable with individuals with APOL1 low-risk variants in an analysis of 121,492 participants of African ancestry from the Million Veteran Program (MVP). Functional genetic studies in cell models showed that APOL1 p.N264K blocked APOL1 pore-forming function and ion channel conduction and reduced toxicity of APOL1 HR mutations. Pharmacologic inhibitors that mimic this mutation blocking APOL1 -mediated pore formation may be able to prevent and/or treat APOL1 -associated kidney disease. African Americans are at increased risk for nondiabetic CKD in part due to HR variants in the APOL1 gene. We tested whether a different APOL1 variant, p.N264K , modified the association between APOL1 HR genotypes (two copies of G1/G2) and CKD in a cross-sectional analysis of 121,492 participants of African ancestry from the MVP. We replicated our findings in the Vanderbilt University Biobank ( n =14,386) and National Institutes of Health All of Us ( n =14,704). Primary outcome was CKD and secondary outcome was ESKD among nondiabetic patients. Primary analysis compared APOL1 HR genotypes with and without p.N264K . Secondary analyses included APOL1 low-risk genotypes and tested for interaction. In MVP, we performed sequential logistic regression models adjusting for demographics, comorbidities, medications, and ten principal components of ancestry. Functional genomic studies expressed APOL1 HR variants with and without APOL1 p.N264K in cell models. In the MVP cohort, 15,604 (12.8%) had two APOL1 HR variants, of which 582 (0.5%) also had APOL1 p.N264K . In MVP, 18,831 (15%) had CKD, 4177 (3%) had ESKD, and 34% had diabetes. MVP APOL1 HR, without p.N264K , was associated with increased odds of CKD (odds ratio [OR], 1.72; 95% confidence interval [CI], 1.60 to 1.85) and ESKD (OR, 3.94; 95% CI, 3.52 to 4.41). In MVP, APOL1 p.N264K mitigated the renal risk of APOL1 HR, in CKD (OR, 0.43; 95% CI, 0.28 to 0.65) and ESKD (OR, 0.19; CI 0.07 to 0.51). In the replication cohorts meta-analysis, APOL1 p.N264K mitigated the renal risk of APOL1 HR in CKD (OR, 0.40; 95% CI, 0.18 to 0.92) and ESKD (OR, 0.19; 95% CI, 0.05 to 0.79). In the mechanistic studies, APOL1 p.N264K blocked APOL1 pore-forming function and ion channel conduction and reduced toxicity of APOL1 HR variants. APOL1 p.N264K is associated with reduced risk of CKD and ESKD among carriers of APOL1 HR to levels comparable with individuals with APOL1 low-risk genotypes.

Resilience Phenotypes and Psychological Functioning among Individuals with Opioid Use Disorder

Background Opioid use disorder (OUD) is a heterogeneous disorder. However, there is a lack of deep phenotyping investigations focusing on important psychological constructs such as resilience that may impact OUD. The present study aimed to investigate the relationship between trait resilience and the five-factor model of personality (FFM) among individuals with opioid use disorder (OUD). We also explored whether the FFM and trait resilience form specific phenotypes associated with psychological functioning. Methods This secondary analysis of an epigenetic study included participants of African ancestry (n = 72), an understudied population, who met DSM-5 criteria for OUD. Participants completed measures to assess personality traits, trait resilience, current and previous drug use, and psychological functioning (depression, anxiety, and stress). Results Linear regression revealed a significant relationship between resilience (CD-RISC-25 score) and the FFM, R 2 = 0.56, F(5,62) = 15.7, p<.001. Further, a two-cluster classification emerged as the optimal solution from the cluster analysis. Cluster 1 (n = 33, 45.8% of the sample) showed lower resilience (CD-RISC-25 score: M = 58.6, SD = 11.2) compared to Cluster 2 (n = 35, 48.6%; CD-RISC-25 score: M = 76.1, SD = 11.9). The “High-Resilience Cluster” (Cluster 2) was characterized by higher FFM traits of: Extraversion, Openness, Agreeableness, and Conscientiousness, and lower Neuroticism versus Cluster 1. Multivariate analysis of variance revealed statistically significant differences between the two resilience clusters concerning other psychological symptoms, Λ = 0.732, F(4, 50) = 7.05, p < 0.003. Conclusions These findings suggest associations between the FFM and trait resilience among individuals with OUD. Two distinct “resilience phenotypes” emerged, with high-resilience individuals displaying less stress, anxiety, and depressive symptoms. Results highlight the clinical importance of resilience as a potential target for intervention in people with OUD.

Prevalence of FH-Causing Variants and Impact on LDL-C Concentration in European, South Asian, and African Ancestry Groups of the UK Biobank-Brief Report.

Familial hypercholesterolemia (FH) is a monogenic disease that causes high low-density lipoprotein cholesterol (LDL-C) and higher risk of premature coronary heart disease. The prevalence of FH-causing variants and their association with LDL-C in non-European populations remains largely unknown. Using DNA diagnosis in a population-based cohort, we aimed to estimate the prevalence of FH across 3 major ancestry groups in the United Kingdom. Principal component analysis was used to distinguish genetic ancestry in UK Biobank participants. Whole exome sequencing data were analyzed to provide a genetic diagnosis of FH. LDL-C concentrations were adjusted for statin use. Principal component analysis distinguished 140 439 European, 4067 South Asian, and 3906 African participants with lipid and whole exome sequencing data. There were significant differences between the 3 groups, including total and LDL-C concentrations, and prevalence and incidence of coronary heart disease. We identified 488, 18, and 15 participants of European, South Asian, and African ancestry carrying a likely pathogenic or pathogenic FH-variant. No statistical difference in the prevalence of an FH-causing variant was observed: 1 out of 288 (95% CI, 1/316-1/264) in European, 1 out of 260 (95% CI, 1/526-1/173) in African, and 1 out of 226 (95% CI, 1/419-1/155) in South Asian. Carriers of an FH-causing variant had significantly higher LDL-C concentration than noncarriers in every ancestry group. There was no difference in median (statin-use adjusted) LDL-C concentration in FH-variant carriers depending on their ancestry background. Self-reported statin use was nonsignificantly highest in FH-variant carriers of South Asian ancestry (55.6%), followed by African (40.0%) and European (33.8%; P=0.15). The prevalence of FH-causing variants in the UK Biobank is similar across the ancestry groups analyzed. Despite overall differences in lipid concentrations, FH-variant carriers across the 3 ancestry groups had similar LDL-C levels. In all ancestry groups, the proportion of FH-variant carriers treated with lipid-lowering therapy should be improved to reduce future risk of premature coronary heart disease.

A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease

Identification of individuals at highest risk of coronary artery disease (CAD)—ideally before onset—remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPSMult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPSMult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10–2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPSMult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70–1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPSMult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPSMult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.

The collaborative study on the genetics of alcoholism: Genetics.

This review describes the genetic approaches and results from the family-based Collaborative Study on the Genetics of Alcoholism (COGA). COGA was designed during the linkage era to identify genes affecting the risk for alcohol use disorder (AUD) and related problems, and was among the first AUD-focused studies to subsequently adopt a genome-wide association (GWAS) approach. COGA's family-based structure, multimodal assessment with gold-standard clinical and neurophysiological data, and the availability of prospective longitudinal phenotyping continues to provide insights into the etiology of AUD and related disorders. These include investigations of genetic risk and trajectories of substance use and use disorders, phenome-wide association studies of loci of interest, and investigations of pleiotropy, social genomics, genetic nurture, and within-family comparisons. COGA is one of the few AUD genetics projects that includes a substantial number of participants of African ancestry. The sharing of data and biospecimens has been a cornerstone of the COGA project, and COGA is a key contributor to large-scale GWAS consortia. COGA's wealth of publicly available genetic and extensive phenotyping data continues to provide a unique and adaptable resource for our understanding of the genetic etiology of AUD and related traits.