Ancestry Populations Research Articles

Mendelian randomization studies on coronary artery disease: a systematic review and meta-analysis

BackgroundCoronary artery disease (CAD) remains one of the leading causes of mortality worldwide. We aimed to summarize what is currently known with regard to causal modifiable risk factors associated with CAD in populations of diverse ancestries through conducting a systematic review and meta-analysis of Mendelian randomization (MR) studies on CAD.MethodsThe databases Embase, Medline, Cochrane Library and Web of Science were searched on the 19th and 20th of December 2022 for MR studies with CAD as a primary outcome; keywords of the search strategy included “coronary artery disease” and “mendelian randomization”. Studies were included if they were published in the English language, included only human participants, employed Mendelian randomization as the primary methodology and studied CAD as the outcome of interest. The exclusion criteria resulted in the removal of studies that did not align with the predefined inclusion criteria, as well as studies which were systematic reviews themselves, and used the same exposure and outcome source as another study.An ancestry-specific meta-analysis was subsequently conducted on studies which investigated either body mass index, lipid traits, blood pressure or type 2 diabetes as an exposure variable. Assessment of publication bias and sensitivity analyses was conducted for risk of bias assessment in the included studies.ResultsA total of 1781 studies were identified through the database searches after de-duplication was performed, with 47 studies included in the quantitative synthesis after eligibility screening. Approximately 80% of all included study participants for MR studies on CAD were of European descent irrespective of the exposure of interest, while no study included individuals of African ancestry. We found no evidence of differences in terms of direction of causation between ancestry groups; however, the strength of the respective relationships between each exposure and CAD were different, with this finding most evident when blood pressure was the exposure of interest.ConclusionsFindings from this review suggest that patterns regarding the causational relationship between modifiable risk factors and CAD do not differ in terms of direction when compared across diverse ancestry populations. Differences in the observed strengths of the respective relationships however are indicative of the value of increasing representation in non-European populations, as novel genetic pathways or functional SNPs relating to CAD may be uncovered through a more global analysis.Systematic review registrationThe protocol for this systematic review was registered to the International Prospective Register of Systematic Reviews (PROSPERO) and is publicly available online (CRD42021272726).

Addition of polygenic risk score to a risk calculator for prediction of breast cancer in US Black women

BackgroundPrevious work in European ancestry populations has shown that adding a polygenic risk score (PRS) to breast cancer risk prediction models based on epidemiologic factors results in better discriminatory performance as measured by the AUC (area under the curve). Following publication of the first PRS to perform well in women of African ancestry (AA-PRS), we conducted an external validation of the AA-PRS and then evaluated the addition of the AA-PRS to a risk calculator for incident breast cancer in Black women based on epidemiologic factors (BWHS model).MethodsData from the Black Women’s Health Study, an ongoing prospective cohort study of 59,000 US Black women followed by biennial questionnaire since 1995, were used to calculate AUCs and 95% confidence intervals (CIs) for discriminatory accuracy of the BWHS model, the AA-PRS alone, and a new model that combined them. Analyses were based on data from 922 women with invasive breast cancer and 1844 age-matched controls.ResultsAUCs were 0.577 (95% CI 0.556–0.598) for the BWHS model and 0.584 (95% CI 0.563–0.605) for the AA-PRS. For a model that combined estimates from the questionnaire-based BWHS model with the PRS, the AUC increased to 0.623 (95% CI 0.603–0.644).ConclusionsThis combined model represents a step forward for personalized breast cancer preventive care for US Black women, as its performance metrics are similar to those from models in other populations. Use of this new model may mitigate exacerbation of breast cancer disparities if and when it becomes feasible to include a PRS in routine health care decision-making.

Addressing the research gap: access to care hinders genetic discovery in systemic lupus erythematosus patients throughout the African diaspora.

Systemic lupus erythematosus (SLE) is a complex autoimmune condition that disproportionately impacts non-White ethnic and racial groups, particularly individuals in the African diaspora who experience heightened incidence, prevalence, and adverse outcomes. Genetic and epigenetic factors play significant roles in SLE risk, however these factors neither explain the whole of SLE risk nor the stark racial disparities we observe. Moreover, our understanding of genetic risk factors within African ancestry populations is limited due to social and environmental influences on research participation, disease presentation, and healthcare access. Globally, the African diaspora faces barriers in accessing essential SLE diagnostic tools, therapeutics, healthcare practitioners, and high-quality clinical and translational research studies. Here, we provide insights into the current state of genetic studies within African ancestry populations and highlight the unique challenges encountered in SLE care and research across countries of varying income levels. We also identify opportunities to address these disparities and promote scientific equity for individuals affected by SLE within the global African diaspora.

Polygenic Risk Score Reveals Genetic Heterogeneity of Alzheimer's Disease between the Chinese and European Populations.

The polygenic risk score (PRS) aggregates the effects of numerous genetic variants associated with a condition across the human genome and may help to predict late-onset Alzheimer's disease (LOAD). Most of the current PRS studies on Alzheimer's disease (AD) have been conducted in Caucasian ancestry populations, while it is less studied in Chinese. To establish and examine the validity of Chinese PRS, and explore its racial heterogeneity. We constructed a PRS using both discovery (N = 2012) and independent validation samples (N = 1008) from Chinese population. The associations between PRS and age at onset of LOAD or cerebrospinal fluid (CSF) biomarkers were assessed. We also replicated the PRS in an independent replication cohort with CSF data and constructed an alternative PRS using European weights. Multi-center genetics study. A total of 3020 subjects were included in the study. PRS was calculated using genome-wide association studies data and evaluated the performance alone (PRSnoAPOE) and with other predictors (full model: LOAD ~ PRSnoAPOE + APOE+ sex + age) by measuring the area under the receiver operating curve (AUC). PRS of the full model achieved the highest AUC of 84.0% (95% CI = 81.4-86.5) with pT< 0.5, compared with the model containing APOE alone (61.0%). The AUC of PRS with pT<5e-8 was 77.8% in the PRSnoAPOE model, 81.5% in the full model, and only ranged from 67.5% to 75.1% in the PRS with the European weights model. A higher PRS was significantly associated with an earlier age at onset (P <0.001). The PRS also performed well in the replication cohort of the full model (AUC=83.1%, 95% CI = 74.3-92.0). The CSF biomarkers of Aβ42 and the ratio of Aβ42/Aβ40 were significantly inversely associated with the PRS, while p-Tau181 showed a positive association. This finding suggests that PRS reveal genetic heterogeneity and higher prediction accuracy of the PRS for AD can be achieved using a base dataset and validation within the same ethnicity. The effective PRS model has the clinical potential to predict individuals at risk of developing LOAD at a given age and with abnormal levels of CSF biomarkers in the Chinese population.

Genomic data reveal strong differentiation and reduced genetic diversity in island golden eagle populations

Abstract Understanding population structure and the extent and distribution of genetic diversity are recognized as central issues in endangered species research, with broad implications for effective conservation management. Advances in whole genome sequencing techniques provide greater resolution of genome-wide genetic diversity and inbreeding. Subspecies of golden eagles (Aquila chrysaetos) in Scotland (A. c. chrysaetos) and Japan (A. c. japonica) are endangered; it is therefore important to understand genetic diversity and inbreeding of these small island populations to increase the chances of conservation success. We investigated this using whole genome sequencing data from golden eagles in Scotland, continental Europe, Japan, and the USA. Following determination of population genetic structure, analysis of heterozygosity and nucleotide diversity revealed reduced levels of genetic diversity together with runs of homozygosity, suggesting evidence of inbreeding attributable to recent shared parental ancestry in the island populations. These results highlight the need to consider genetic reinforcement of small isolated golden eagle populations from neighbouring outbred populations, alongside existing efforts to boost population size through within-island conservation translocations and captive breeding programmes.

Relationship between inflammatory bowel disease and erectile dysfunction: a 2-sample Mendelian randomization study.

Observational studies have indicated a high prevalence of erectile dysfunction (ED) among patients with inflammatory bowel disease (IBD), but a definitive causal relationship remains unestablished. The primary aim of this study was to assess the potential causal relationship between IBD and ED using Mendelian randomization (MR) analysis. We obtained statistical data for 2 subtypes of IBD, ulcerative colitis (UC) and Crohn's disease (CD), as well as for ED, from publicly available genome-wide association studies (GWASs). Subsequently, a 2-sample MR analysis was conducted using these datasets. The primary MR analysis utilized the inverse variance-weighted (IVW) method, complemented by secondary analyses employing MR-Egger and weighted median methods. Furthermore, we assessed heterogeneity using Cochran's Q test and evaluated pleiotropy with the MR-Egger intercept test. To identify potential influential single nucleotide polymorphisms, we employed a leave-one-out analysis. Additionally, outliers were identified using the MR-PRESSO method. The study outcomes encompassed results from 3 MR analyses, namely IVW, MR-Egger, and weighted median, along with sensitivity analyses involving Cochran's Q test, the MR-Egger intercept test, leave-one-out analysis, and the MR-PRESSO method. There was no causal effect of UC and CD on ED in the MR analysis (IVW P > .05). Results of complementary methods were consistent with those of the IVW method. The results of sensitivity analyses supported our conclusion, and no directional pleiotropy was found. Genetically, despite the absence of a causal link between IBD and ED according to MR analysis, we must emphasize the elevated ED prevalence among IBD patients in observational studies, with particular consideration for the influence of negative emotions on erectile function. This study is the inaugural application of a 2-sample MR analysis using extensive GWAS datasets to evaluate the causal relationship between IBD and ED, effectively mitigating biases stemming from confounding factors and reverse causality often present in observational studies. Nevertheless, it is imperative to exercise caution when drawing conclusions due to inherent limitations in GWAS data, encompassing factors like samples overlap, gender categorization, population ancestry, and the persistent ambiguity surrounding the precise functionality of specific single nucleotide polymorphisms. MR analysis did not provide genetic-level evidence supporting a direct causal relationship between IBD (UC and CD) and ED.

Improving dementia phenotype prediction with functional mapping of genetic data in non‐European ancestries

AbstractBackgroundMany common genetic variants have been associated with dementia, but their ability to predict dementia prospectively is unknown, especially in non‐European ancestral populations. We sought to optimize dementia risk prediction models with machine learning in individuals of diverse genetic ancestries.MethodSamples were selected from the University of California Los Angeles Health System with their electronic health records (EHRs) and linked genetic data. Dementia phenotype was defined using diagnosis codes and mapped phecodes. Polygenic risk scores (PRSs) were built using summary statistics of different population‐based genome‐wide association studies (GWASs). Independent significant and functionally mapped single nucleotide polymorphisms (SNPs) were identified using the FUMA tool. Logistic regression models were built with 1) APOE status, 2) a single PRS, or 3) multiple PRSs. The model with age and sex only was built as the baseline model. We trained LASSO models to determine dementia risk SNPs from weighted SNP‐level genetic data. We compared the predictive performance of these models after five‐fold cross‐validation with area under precision‐recall curve (AUPRC) and area under receiver operating characteristic (AUC). Finally, identified risk SNPs were mapped to genes for biological interpretation.ResultThere were 975 individuals included in the final Hispanic Latinx American ancestry sample, of which 9.44% (N = 92) were dementia cases. The model with LASSO‐selected functional mapped SNPs from multiple neurodegenerative diseases GWASs outperformed all other genetic risk score models (AUPRC: 0.39, AUROC: 0.87), resulting in a 19.6% increase in AUPRC from the best PRS model, and a 26.9% increase from the baseline model. The best‐performing LASSO model included nine SNPs, mostly located in the 19q13, 4p15, and 17q21 regions. Results of mapped genes not only revealed well‐known risk genes of dementia but identified risk genes from other neurodegenerative diseases.ConclusionWe demonstrated that building genetic risk scores with trans‐ancestry GWAS and selecting potential causal SNPs can be beneficial for dementia prediction in non‐European ancestry populations. Further training using machine learning methods with functionally mapped SNP‐level genetic data showed significant improvement in predictive power compared to PRS models. Genetic risks of multiple neurodegenerative diseases may contribute to the predisposition to dementia.

Multimorbidity in African ancestry populations: a scoping review

ObjectivesMultimorbidity (MM) is a growing concern linked to poor outcomes and higher healthcare costs. While most MM research targets European ancestry populations, the prevalence and patterns in African ancestry groups...

Association Between HSV‐1 and Risk of Alzheimer’s Disease Detected by a Propensity‐Score Matched Case Design

AbstractBackgroundHerpes simplex virus 1 (HSV‐1) is a neurotropic and neuroinvasive species that can enter the brain triggering inflammation and an immune response, increasing the risk of Alzheimer disease (AD). Previously, we found a significant association between HSV‐1 and AD in whole‐exome sequencing (WES) data (OR = 3.69, P = 6.71×10−4) but not whole‐genome sequenced (WGS) data (OR = 0.92, P = 0.27) from the AD Sequencing Project (ADSP).MethodTo understand this discrepancy, and to better control for the numerous covariates and technical differences that influenced viral quantity, we created a novel algorithm using propensity score analysis (PSA) which permits analysis of observational study data comparable to a randomized controlled trial. WGS reads from 6,541 AD cases and 6,855 controls from the ADSP (including 7,395 non‐Hispanic Whites, 2,961 African Americans, and 3,040 Caribbean Hispanics) that did not align to the human genome were mapped to viral reference sequences and quantified. Propensity scores were derived for 7,619 individuals with at least one HSV‐1 read and 5,777 individuals lacking any HSV‐1 reads using a binary treatment indicator for HSV‐1 status. We applied forward stepwise regression including known confounders (APOE ε4 status, sex, age, tissue source (blood or brain), population ancestry, sequencing center, and PCR amplification) to identify other potential confounders and/or interactions and quadratic terms for creating propensity scores. We tried several matching algorithms to generate matched sets of individuals with and without HSV‐1. Utilizing the best quality matched set, we evaluated the association of AD with HSV‐1 status using a weighted generalized linear model.ResultThe final regression model included terms for the covariates mentioned above that were available for most of the original sample (5828 AD cases and 6487 controls). We found a significant association between HSV‐1 and AD (OR = 1.10, P = 0.02).ConclusionResults from WGS data confirm our previous findings obtained from WES data and support the hypothesis that HSV‐1 is associated with an increased AD risk, highlighting the utility of PSA for analyzing association of risk factors with complex disorders like AD. Further studies are needed to replicate this finding in other ancestral populations and explain the lack of association in WGS data.

The Alzheimer’s Disease Sequencing Project – Follow Up Study (ADSP‐FUS): APOE genotype status and demographic characteristics across datasets

AbstractBackgroundThe ADSP‐FUS is a National Institute on Aging (NIA) initiative focused on identifying genetic risk and protective variants for Alzheimer Disease (AD) by expanding the ADSP beyond non‐Hispanic Whites of European Ancestry (NHW‐EA) populations. Given the lack of diversity in the ADSP, the ADSP‐FUS was designed to whole genome sequence (WGS) existing ethnically diverse and unique cohorts. The upcoming phase ADSP‐ FUS 2.0: The Diverse Population Initiative, focuses on inclusion of Hispanic/Latino (HL), non‐Hispanic Black with African Ancestry (NHB‐AA), and Asian populations.MethodsADSP‐FUS cohorts consist of studies of AD, dementia, and age‐related conditions. Clinical classifications are assigned based on standard criteria from clinical measures and history, as well as additional neuropathologic data. In addition to production of WGS, genome‐wide array and APOE genotyping is acquired or performed for all ADSP‐FUS samples.ResultsThe ADSP‐FUS currently consists of 38 cohorts comprised of ∼40,000 individuals, with plan to sequence &gt;100,000 individuals from diverse ancestries. Genotyping, sequencing, and clinical adjudication has been performed on 23,428 participants (cases N = 6,961, median age = 73; controls N = 13,007, median age = 72; ADRD N = 3,460, median age = 77. More participants are female (62.3%) than male and are evenly distributed across cases (61.0%), controls (63.1%), and ADRD (61.8%). As expected, the most prevalent APOE genotype is APOE 3/3 (% by cases/controls for 2/2 = 0.2,0.4; 2/3 = 4.3, 8.2; 2/4 = 2.2, 1.8; 3/3 = 43.8, 64.4; 3/4 = 39.5, 23.0; 4/4 = 10.1, 2.2). These proportions vary greatly between ethnicities, with the highest for APOE 4/4 observed in Asian participants (8.8%) and the lowest in Hispanic participants (2.5%), for example. Mean Braak stage for AD cases is higher (5.1+1.2) than controls (2.6+1.3) and ADRD participants (3.5+1.6).ConclusionThe results provide an overview of features of ADSP‐FUS cohorts. As the ADSP‐FUS expands in size and diversity, this genomic resource, available via NIAGADS, will be integrated with ADSP programs focused on phenotype harmonization, association analyses, functional genomics, and machine learning. In concert with these programs, the ADSP‐FUS will accelerate the identification and understanding of potential genetic risk and protective variants for AD across all populations with the target of developing new treatments that are globally effective.

Identifying Rare Genetic Determinants for Improved Polygenic Risk Prediction of Bone Mineral Density and Fracture Risk.

Osteoporosis and fractures severely impact the elderly population. Polygenic risk scores for bone mineral density have demonstrated potential clinical utility. However, the value of rare genetic determinants in risk prediction has not been assessed. With whole-exome sequencing data from 436,824 UK Biobank participants, we assigned White British ancestry individuals into a training data set (n = 317,434) and a test data set (n = 74,825). In the training data set, we developed a common variant-based polygenic risk score for heel ultrasound speed of sound (SOS). Next, we performed burden testing to identify genes harboring rare determinants of bone mineral density, targeting influential rare variants with predicted high deleteriousness. We constructed a genetic risk score, called ggSOS, to incorporate influential rare variants in significant gene burden masks into the common variant-based polygenic risk score. We assessed the predictive performance of ggSOS in the White British test data set, as well as in populations of non-White British European (n = 18,885), African (n = 7165), East Asian (n = 2236), South Asian (n = 9829), and other admixed (n = 1481) ancestries. Twelve genes in pivotal regulatory pathways of bone homeostasis harbored influential rare variants associated with SOS (p < 5.5 × 10-7 ), including AHNAK, BMP5, CYP19A1, FAM20A, FBXW5, KDM5B, KREMEN1, LGR4, LRP5, SMAD6, SOST, and WNT1. Among 4013 (5.4%) individuals in the test data set carrying these variants, a one standard deviation decrease in ggSOS was associated with 1.35-fold (95% confidence interval [CI] 1.16-1.57) increased hazard of major osteoporotic fracture. However, compared with a common variant-based polygenic risk score (C-index = 0.641), ggSOS had only marginally improved prediction accuracy in identifying at-risk individuals (C-index = 0.644), with overlapping confidence intervals. Similarly, ggSOS did not demonstrate substantially improved predictive performance in non-European ancestry populations. In summary, modeling the effects of rare genetic determinants may assist polygenic prediction of fracture risk among carriers of influential rare variants. Nonetheless, improved clinical utility is not guaranteed for population-level risk screening. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Abstract B061: Nonalcoholic fatty liver disease (NAFLD) polygenic risk score and risk of hepatocellular carcinoma in a multiethnic population

Abstract Purpose: Hepatocellular carcinoma (HCC) is the third cause of cancer mortality globally, with 10%-12% of cases attributable to nonalcoholic fatty liver disease (NAFLD). Genetic variants included in NAFLD polygenic risk scores (PRS) have been associated with HCC risk. Since these associations have been studied primarily among European ancestry populations, in the current study we assessed the transportability of a NAFLD PRS associated with HCC risk in a racially/ethnically diverse population. Methods: We conducted a nested case-control study including 275 incident HCC cases and 73,045 controls from the Multiethnic Cohort Study, using a 21-variant PRS for NAFLD created based on prior GWAS and replication studies on MEC participants and other populations. Associations between PRS (per standard deviation) and HCC were estimated using logistic regression adjusting for age, sex, and global ancestry. A stratified analysis was conducted by body mass index (BMI) due to the direct relationship of obesity with NAFLD and HCC. Results: The PRS was associated with HCC risk in the combined sample (ORper SD= 1.84, 95% CI: 1.64-2.06). Signifcant associations were observed in Japanese Americans [ORper SD=2.26 (1.87-2.72)], Latinos [ORper SD=1.89 (1.52-2.35)], Native Hawaiians [ORper SD=1.84 (1.26-2.69)], and with the associations being weaker and non-significant in whites [ORper SD=1.33 (0.92-1.93)] and African Americans [ORper SD=1.25 (0.90-1.75)]. The PRS association was stronger among those with BMI &amp;gt;= 25 kg/m2 for the combined sample (ORper SD :2.46, 95% CI:1.92-3.14), (P heterogeneity &amp;lt;0.0001); and all racial/ethnic groups [Latino: 3.01(1.88-4.81), African American: 2.72 (95% CI: 1.18-6.27), Hawaiian: 2.25 (1.17-4.32), Japanese: 2.13 (1.36-3.36), and White:2.11(1.10-4.04)]. Conclusion: A NAFLD PRS is applicable for HCC risk prediction across racial/ethnic populations. BMI may modifiy this PRS-HCC risk association. Citation Format: Homa Sadeghi, David Bogumil, David V. Conti, Christopher Haiman, Loïc Le Marchand, Veronica Wendy Setiawan. Nonalcoholic fatty liver disease (NAFLD) polygenic risk score and risk of hepatocellular carcinoma in a multiethnic population [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr B061.

SNP heterozygosity, relatedness and inbreeding of whole genomes from the isolated population of the Faroe Islands

BackgroundThe population of the Faroe Islands is an isolated population but very little is known about it from whole genome sequencing. The population of about 50000 people has a high incidence of rare diseases e.g., 1:300 for Primary Carnitine Deficiency. A screening programme was implemented, and eleven persons were also whole genome sequenced at x37 coverage for diagnostic purposes of those cases that were not affected by the known mutations. The purpose of our study is to utilize the high coverage data to explore the genomic variation and the ancestral history of the population. We study the SNP heterozygosity, the pairwise relatedness from kinship, the inbreeding from runs of homozygosity ROH, and we find the minor allele frequency distribution. We estimate the population ancestry and the timing of the founding event by using the whole genomes from eight consenting individuals.ResultsWe find the number of SNPs and the heterozygosity for the eight individual samples, and for merged samples, for which we also study the relatedness. We find close relatedness between the supposedly unrelated individuals. From ROH, we interpret the high relatedness as an ancient property of the isolated population. A bottleneck event is estimated starting between years sim 50-300 with a maximum consanguineous population in year sim 600 and similarly consanguineous between years 500-700. The ancestry analysis shows the population descends from founders of >99% European and <1% Admixed American ancestry. A distinct clustering near the central European and British populations of the 1000 Genome Project is likely the result of the population isolation and genetic drift. The minor allele frequency distribution suggests many rare variants.ConclusionsThe ancestry is mainly European while the inbreeding is higher compared to European populations and population isolates. The Faroese population has inbreeding more like ancient Europeans. We discovered a bottlenecked and consanguineous population event and estimated it starting in the 1st-4th century as compared to the oldest archaeological findings from the 4th-6th century.

Does gestational diabetes mellitus increase the risk of cardiovascular disease? A Mendelian randomization study.

In recent years, epidemiological studies have revealed the relationship between gestational diabetes mellitus (GDM) and cardiovascular disease (CVD). In this study, we utilized Mendelian randomization (MR) to investigate the potential causal impact of GDM on cardiovascular disease for the first time. We retrieved summary statistics from published genome-wide association studies. MR was first performed using significant SNPs extracted from the eighth data release of the FinnGen study. Next, a replication analysis for coronary artery disease (CAD) was conducted in another European ancestry population to validate our findings. Finally, mediation analysis was carried out to assess potential mediation effects. Our data analysis revealed that genetically predicted GDM was significantly associated with increased CAD risk (OR 1.10, 95% CI 1.02-1.18, p 0.006). Replication analysis confirmed a significant genetic association between GDM and CAD (OR 1.07, 95% CI 1.02-1.12, p 0.003) in another European ancestry population. Mediation analysis indicated no significant mediation effect by type 2 diabetes mellitus (T2DM)on the GDM-CAD relationship (mediation effect β [95% CI]: 0.005 [-0.003, -0.017]). Women with a prior history of GDM face an elevated risk of future CAD. This increased risk of CAD cannot be solely attributed to the subsequent onset of diabetes. Regular CAD risk assessment and primary prevention strategies are of paramount importance for women with a history of GDM.

CYP2C19 genotype prevalence and association with recurrent myocardial infarction in British-South Asians treated with clopidogrel

Abstract Background Pharmacogenomics examines how genes and drugs interact to explain some of the inter-individual variability in response to medications. CYP2C19 is a hepatic enzyme involved in the metabolism of clopidogrel from a prodrug to its active metabolite. Although the European Society of Cardiology and National Institute for Care Excellence recommend ticagrelor (a non CYP2C19 dependent P2Y12 antagonist) as the antiplatelet agent of choice, clopidogrel remains widely prescribed for acute coronary syndrome and myocardial infarction. CYP2C19 poor metabolizers are known to be more common in Asian ancestry but very few studies have looked specifically at South Asian populations or linked metabolizer diplotypes with clinical efficacy data in this population. The outcome studies on which clopidogrel was licensed for efficacy and safety did not include significant South Asian representation. Furthermore, South Asians are known to have a higher prevalence of cardio-metabolic disease compared with European ancestry populations. Methods We studied the Genes &amp; Health cohort of British Bangladeshi and Pakistani ancestry participants to look at prevalence of CYP2C19 metabolizer genotypes and correlate these with recurrent myocardial infarction risk for those who had been prescribed clopidogrel in primary care. Multivariable regression was used to test for association between known CYP2C19 diptotypes and recurrent myocardial infarction in those prescribed clopidogrel, controlling for known CVD risk factors, percutaneous coronary intervention, age, and gender. Results Genes &amp; Health cohort participants (N = 44,396) have a high prevalence (57%) of intermediate or poor CYP2C19 metabolizers, with at least 1 loss of function allele. The prevalence of poor metabolizers carrying 2 CYP2C19 loss of function alleles is 13%, which is higher than in previously studied European (2.4%) and Central/South Asian populations (8.2%). This is primarily due to the *2 LOF allele present in 56% of the population. 69% of the cohort who were diagnosed with an acute MI were prescribed clopidogrel. The presence of the poor metabolizer diplotype is significantly associated with higher risk of recurrent MI, or failed secondary prevention on clopidogrel in this population, OR 3.1 (p = 0.02), with some subsequent ischemic events already described in this young cohort (Acute MI prescribed clopidogrel N = 697, Recurrent MI in this group N=39). Conclusions A pharmacogenomic-driven approach to clopidogrel prescribing has the potential to impact significantly on clinical management and outcomes in individuals of Bangladeshi and Pakistani ancestry. In absence of genotype guided prescribing, maximal adherence to guidelines recommending non CYP2C19 dependent P2Y12 anti-platelet therapy is likely to be disproportionately beneficial in this ethnic cohort.Risk of recurrent MICentral illustration

Abstract 18928: Phenotypic Manifestations of Polygenic Risk for Ischemic Stroke in Adults Free From Disease

Introduction: Ischemic stroke is a complex heritable disease with a substantial proportion of risk attributable to polygenic factors. Little is known about how polygenic risk for stroke may manifest as intermediate phenotypes. Hypothesis: Polygenic liability for ischemic stroke will be associated with cardiometabolic phenotypes even in young adults free from disease. Methods: Polygenic risk derived from a multi ancestry population (GIGASTROKE ~1.2 million SNPs) was applied to 454 White adults from the HERITAGE Family Study with imputed whole genome data available. Participants (mean age = 31.5 ±14.5 years, 51% female) underwent robust cardiometabolic profiling including deeply phenotyped cardiopulmonary exercise tests, body composition, lipid panels, inflammatory markers, and measures of glucose homeostasis. General linear models adjusted for age and sex were used to test the association between z-scored polygenic risk of stroke (SPRS) and 130 phenotypes. A false discovery rate of &lt;5% was used to determine significance. Results: SPRS did not associate with demographic traits or measures of body composition. SPRS was positively associated with several blood pressure related phenotypes with the strongest association between SPRS and systolic blood pressure response to acute exercise (β=0.01, p=2.86e-05), which persisted after adjustment for resting systolic blood pressure. Additionally, 19 total phenotypes were nominally associated (p&lt;0.05) with SPRS including multiple apoB related plasma lipid traits ( Table 1 ). Interestingly, SPRS was also inversely associated with hematocrit (β= -0.06, FDR=0.004). Conclusions: Genetic risk of ischemic stroke is associated with hemodynamic traits even in a cohort of relatively young adults free from overt cardiometabolic disease. Additionally, blood pressure response to acute exercise may represent an early manifestation of genetic liability to stroke.

Abstract 13352: The Impact of Machine Learning Models in Reducing Variants of Uncertain Significance in Individuals From Underrepresented Populations Who Are Undergoing Genetic Testing for Heritable Heart Conditions

Introduction: Many missense variants remain categorized as variants of uncertain significance (VUS) due to limited evidence. VUS are at the core of disparities, as underrepresented individuals tend to receive more VUS. To improve variant classification (VC) across race, ethnicity and ancestry (REA) groups, we developed machine learning (ML) models by leveraging genomic datasets. For this study, we evaluated the impact of ML-informed VC for cardiomyopathy, arrhythmia, lipidemia, aortopathy, hereditary hemorrhagic telangiectasia, and pulmonary hypertension genes. Research Question: What is the utility of ML models for cardiovascular disease panel testing VC across REA groups? Methods: From 1/1/2022 to 5/22/2023, ML algorithms that leveraged SpliceAI, gnomAD, AlphaFold and others were validated. ML evidence that met a negative or positive predictive value &gt;80% was incorporated into Sherloc, an ACMG/AMP-based VC framework. At least 1 validated model was available for 225 genes. Analyses of &gt;20,000 patients were performed from random sampling of 20,000 patients with extrapolation. Measurement error was less than 2% variation by bootstrapping. VCs impacted by ML were evaluated, stratified by REA. Results: Out of 113,206 (32% were from an underrepresent group) US-based individuals that underwent panel genetic testing, ~65,900 (58%) had ML evidence applied to at least 1 variant. ML contributed to classifying at least 1 benign/likely benign (B/LB) variant in ~33,200 (29%) and at least 1 pathogenic/likely pathogenic (P/LP) variant in ~2,700 (2.4%) individuals. A higher percentage of Asian (43%), Black (42%), and Hispanic (37%) individuals had an ML-dependent definitive VC (P/LP or B/LB) relative to White (28%) individuals by a one-tailed, two-sample proportion test (p&lt;2.0x10 -58 ). Conclusions: ML modeling demonstrated utility in cardiology diagnostic gene panel testing. Among individuals who had at least 1 variant with ML evidence applied, 54% resulted in definitive classifications. Additionally, ML appears to provide more definitive VCs for underrepresented individuals. ML can assess factors in ways that are agnostic to population ancestry and, when appropriately incorporated into VC, can narrow the VUS gap rates across REA groups.

APOE Genotype and Alzheimer Disease Risk Across Age, Sex, and Population Ancestry

Apolipoprotein E (APOE)*2 and APOE*4 are, respectively, the strongest protective and risk-increasing, common genetic variants for late-onset Alzheimer disease (AD), making APOE status highly relevant toward clinical trial design and AD research broadly. The associations of APOE genotypes with AD are modulated by age, sex, race and ethnicity, and ancestry, but these associations remain unclear, particularly among racial and ethnic groups understudied in the AD and genetics research fields. To assess the stratified associations of APOE genotypes with AD risk across sex, age, race and ethnicity, and global population ancestry. This genetic association study included case-control, family-based, population-based, and longitudinal AD-related cohorts that recruited referred and volunteer participants. Data were analyzed between March 2022 and April 2023. Genetic data were available from high-density, single-nucleotide variant microarrays, exome microarrays, and whole-exome and whole-genome sequencing. Summary statistics were ascertained from published AD genetic studies. The main outcomes were risk for AD (odds ratios [ORs]) and risk of conversion to AD (hazard ratios [HRs]), with 95% CIs. Risk for AD was evaluated through case-control logistic regression analyses. Risk of conversion to AD was evaluated through Cox proportional hazards regression survival analyses. Among 68 756 unique individuals, analyses included 21 852 East Asian (demographic data not available), 5738 Hispanic (68.2% female; mean [SD] age, 75.4 [8.8] years), 7145 non-Hispanic Black (hereafter referred to as Black) (70.8% female; mean [SD] age, 78.4 [8.2] years), and 34 021 non-Hispanic White (hereafter referred to as White) (59.3% female; mean [SD] age, 77.0 [9.1] years) individuals. There was a general, stepwise pattern of ORs for APOE*4 genotypes and AD risk across race and ethnicity groups. Odds ratios for APOE*34 and AD risk attenuated following East Asian (OR, 4.54; 95% CI, 3.99-5.17),White (OR, 3.46; 95% CI, 3.27-3.65), Black (OR, 2.18; 95% CI, 1.90-2.49) and Hispanic (OR, 1.90; 95% CI, 1.65-2.18) individuals. Similarly, ORs for APOE*22+23 and AD risk attenuated following White (OR, 0.53, 95% CI, 0.48-0.58), Black (OR, 0.69, 95% CI, 0.57-0.84), and Hispanic (OR, 0.89; 95% CI, 0.72-1.10) individuals, with no association for Hispanic individuals. Deviating from the global pattern of ORs, APOE*22+23 was not associated with AD risk in East Asian individuals (OR, 0.97; 95% CI, 0.77-1.23). Global population ancestry could not explain why Hispanic individuals showed APOE associations with less pronounced AD risk compared with Black and White individuals. Within Black individuals, decreased global African ancestry or increased global European ancestry showed a pattern of APOE*4 dosage associated with increasing AD risk, but no such pattern was apparent for APOE*2 dosage with AD risk. The sex-by-age-specific interaction effect of APOE*34 among White individuals (higher risk in women) was reproduced but shifted to ages 60 to 70 years (OR, 1.48; 95% CI, 1.10-2.01) and was additionally replicated in a meta-analysis of Black individuals and Hispanic individuals (OR, 1.72; 95% CI, 1.01-2.94). Through recent advances in AD-related genetic cohorts, this study provided the largest-to-date overview of the association of APOE with AD risk across age, sex, race and ethnicity, and population ancestry. These novel insights are critical to guide AD clinical trial design and research.

Deconstructing the genetic architecture of treatment-resistant schizophrenia in East Asian ancestry

BackgroundTreatment-resistant schizophrenia (TRS) affects a substantial proportion of patients who do not respond adequately to antipsychotic medications, yet the underlying biological mechanism remains poorly understood. This study investigates the link between the genetic predisposition to schizophrenia and TRS. Methods857 individuals diagnosed with schizophrenia were divided into TRS (n = 142) and non-TRS (n = 715) based on well-defined TRS criteria. Polygenic risk scores (PRS) were calculated using schizophrenia genome-wide association summary statistics from East-Asian and European ancestry populations. PRS was estimated using both P-value thresholding and Bayesian framework methods. Logistic regression analyses were performed to differentiate between TRS and non-TRS individuals. ResultsThe schizophrenia PRS derived from the East-Asian training dataset effectively distinguished between TRS and non-TRS individuals (R2 = 0.029, p = 4.86 ×10-5, pT = 0.1, OR = 1.52, 95% CI = 1.242–1.861), with higher PRS values observed in the TRS group. Similar PRS analysis was conducted based on the European ancestry GWAS summary statistics, but we found superior prediction based on the East-Asian ancestry discovery data. ConclusionThis study reveals an association between common risk variants for schizophrenia and TRS status, suggesting that the genetic burden of schizophrenia may partly contribute to treatment resistance in individuals with schizophrenia. These findings propose the potential use of genetic risk factors for early TRS identification and timely access to clozapine. However, the ancestral background of the discovery sample is crucial for successfully implementing PRS in clinical settings.

Does the definition of a novel environment affect the ability to detect cryptic genetic variation?

Anthropogenic change exposes populations to environments that have been rare or entirely absent from their evolutionary past. Such novel environments are hypothesized to release cryptic genetic variation, a hidden store of variance that can fuel evolution. However, support for this hypothesis is mixed. One possible reason is a lack of clarity in what is meant by 'novel environment', an umbrella term encompassing conditions with potentially contrasting effects on the exposure or concealment of cryptic variation. Here, we use a meta-analysis approach to investigate changes in the total genetic variance of multivariate traits in ancestral versus novel environments. To determine whether the definition of a novel environment could explain the mixed support for a release of cryptic genetic variation, we compared absolute novel environments, those not represented in a population's evolutionary past, to extreme novel environments, those involving frequency or magnitude changes to environments present in a population's ancestry. Despite sufficient statistical power, we detected no broad-scale pattern of increased genetic variance in novel environments, and finding the type of novel environment did not explain any significant variation in effect sizes. When effect sizes were partitioned by experimental design, we found increased genetic variation in studies based on broad-sense measures of variance, and decreased variation in narrow-sense studies, in support of previous research. Therefore, the source of genetic variance, not the definition of a novel environment, was key to understanding environment-dependant genetic variation, highlighting non-additive genetic variance as an important component of cryptic genetic variation and avenue for future research.