Immune cell profiling of the ICAM1 p.K56M heart failure with preserved ejection fraction risk variant.

AIMS: Intercellular adhesion molecule-1 (ICAM-1) facilitates inflammation via leucocyte recruitment and has been implicated in heart failure with preserved ejection fraction (HFpEF). Approximately 35% of African American individuals carry a copy of an ICAM1 missense variant (rs5491; p.K56M), which is associated with an increased risk of HFpEF. The pathways by which rs5491 increases HFpEF risk are not well defined. We evaluated the circulating immune cell profile of rs5491. METHODS: Among African American individuals in the Multi-Ethnic Study of Atherosclerosis, we evaluated the associations of rs5491 with 29 circulating peripheral blood mononuclear cell subsets. The top immune cells were then related to echocardiographic measures of structure and function. RESULTS: Among 502 individuals with immune cell profiling (mean age 63 years, 51% female), 191 individuals (38%) had at least one copy of rs5491. Each additional rs5491 allele was significantly associated with higher proportions of Tc17 CD8+ cytotoxic T cells (ß = 1.34, SE = 0.45, P = 9.5 × 10-5) and Tc2 CD8+ cytotoxic T cells (ß = 1.19, SE = 0.44, P = 0.00012). There were no other associations noted between rs5491 and the remaining immune cells. A higher proportion of Tc17 cells was significantly associated with a higher left ventricular ejection fraction, E/e' average and right ventricular systolic pressure (RVSP), while a higher proportion of Tc2 cells was significantly associated with a higher RVSP. CONCLUSIONS: The ICAM1 p.K56M variant (rs5491) carries a distinct and inflammatory T-cell subset profile. These cytotoxic T cells are in turn associated with alterations in cardiac function and adverse haemodynamics later in life, thus providing insight into pathways by which rs5491 may increase the risk of HFpEF.

Variant level heritability estimates of type 2 diabetes in African Americans.

Type 2 diabetes (T2D) is caused by both genetic and environmental factors and is associated with an increased risk of cardiorenal complications and mortality. Though disproportionately affected by the condition, African Americans (AA) are largely underrepresented in genetic studies of T2D, and few estimates of heritability have been calculated in this race group. Using genome-wide association study (GWAS) data paired with phenotypic data from ~ 19,300 AA participants of the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study, Genetics of Hypertension Associated Treatments (GenHAT) study, and the Electronic Medical Records and Genomics (eMERGE) network, we estimated narrow-sense heritability using two methods: Linkage-Disequilibrium Adjusted Kinships (LDAK) and Genome-Wide Complex Trait Analysis (GCTA). Study-level heritability estimates adjusting for age, sex, and genetic ancestry ranged from 18% to 34% across both methods. Overall, the current study narrows the expected range for T2D heritability in this race group compared to prior estimates, while providing new insight into the genetic basis of T2D in AAs for ongoing genetic discovery efforts.

Pharmacogenomic Characterization of Childbearing-Aged Individuals With Mood Disorders in a Tertiary Care Perinatal Mental Health Clinic.

Objective: The effectiveness of antidepressant treatment for mood disorders is often limited by either a poor response or the emergence of adverse effects. These complications often necessitate multiple drug trials. This clinical challenge intensifies during pregnancy, when medications must be selected to improve the likelihood of response and optimize reproductive outcomes. We determined the distribution of common pharmacogenetic variants, metabolizer phenotypes, past medication responses, and side effects in childbearing-aged individuals seeking treatment in a tertiary care perinatal mental health clinic.Methods: Sixty treatment-seeking women (based on sex at birth) with DSM-5- defined bipolar disorder (n = 28) or major depressive disorder (n = 32) provided DNA samples and completed psychiatric diagnostic and severity assessments between April 2014 and December 2017. Samples were genotyped for single-nucleotide variants in drug metabolizing enzyme genes of commonly prescribed antidepressants (cytochrome P450 [CYP] 1A2, 2B6, 2C9, 2C19, 2D6, 3A4, and 3A5), and the frequency of normative metabolizer status was compared to reference populations data from Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. The Antidepressant Treatment History Form was used to record historic medication trials and side effects.Results: A significantly greater proportion of extensive metabolizers for CYP2B6 was observed in the study population when compared to CPIC population frequency databases in Caucasians (0.64 vs 0.43 [95% CI: 0.49-0.76]; P value = .006) and African Americans (0.71 vs 0.33 [95% CI: 0.29-0.96]; P value = .045). No significant association was found between metabolizer phenotype and the likelihood of a medication side effect.Conclusion: Pharmacogenomic testing may have value for personalized prescribing in individuals capable of or considering pregnancy.

Managing differential performance of polygenic risk scores across groups: Real-world experience of the eMERGE Network.

The differential performance of polygenic risk scores (PRSs) by group is one of the major ethical barriers to their clinical use. It is also one of the main practical challenges for any implementation effort. The social repercussions of how people are grouped in PRS research must be considered in communications with research participants, including return of results. Here, we outline the decisions faced and choices made by a large multi-site clinical implementation study returning PRSs to diverse participants in handling this issue of differential performance. Our approach to managing the complexities associated with the differential performance of PRSs serves as a case study that can help future implementers of PRSs to plot an anticipatory course in response to this issue.

Heart Failure Risk Among African-American Women With an ICAM1 Missense Variant.

BACKGROUND: A common genetic variant of ICAM1 among African-American individuals (rs5491; p.K56M) is associated with heart failure (HF) hospitalization, but whether this risk is specific to heart failure with preserved ejection fraction (HFpEF) remains unclear. Older women are at high risk for HFpEF, and the relationship between rs5491 and HFpEF across the age spectrum is unknown. OBJECTIVES: This study assessed risk of HF and its subtypes conferred by ICAM1 p.K56M (rs5491). METHODS: Associations of rs5491 with risk of HF and its subtypes were estimated among African American individuals in WHI (Women's Health Initiative). The study evaluated whether the association between rs5491 and HF hospitalizations was modified by baseline age. Subsequently, African-American women in WHI and MESA (Multi-Ethnic Study of Atherosclerosis) were pooled and analyses were repeated. RESULTS: Among 8,401 women in WHI, the minor allele frequency of rs5491 was 20.7%, and 731 HF hospitalizations occurred over 19.2 years. The rs5491 variant was not associated with HF or its subtypes across WHI. Interaction analyses suggested that age as a continuous variable modified the association of rs5491 with HFpEF hospitalization (interaction P = 0.04). Upon categorizing women into age decades, rs5491 conferred increased risk of HFpEF among women ≥70 years (HR per additional rs5491 allele: 1.82 [95% CI: 1.25-2.65]; P = 0.002) but was not associated with HFpEF risk among women <70 years. Pooling African-American women in WHI (n = 8,401) and MESA (n = 856) demonstrated that the effect modification by age on the association of rs5491 with HFpEF became more significant (interaction P = 0.009), with consistent HFpEF risk effect estimates among women ≥70 years. CONCLUSIONS: ICAM1 p.K56M (rs5491) is associated with HFpEF among African-American women ≥70 years.

Prospective, multi-site study of healthcare utilization after actionable monogenic findings from clinical sequencing.

As large-scale genomic screening becomes increasingly prevalent, understanding the influence of actionable results on healthcare utilization is key to estimating the potential long-term clinical impact. The eMERGE network sequenced individuals for actionable genes in multiple genetic conditions and returned results to individuals, providers, and the electronic health record. Differences in recommended health services (laboratory, imaging, and procedural testing) delivered within 12 months of return were compared among individuals with pathogenic or likely pathogenic (P/LP) findings to matched individuals with negative findings before and after return of results. Of 16,218 adults, 477 unselected individuals were found to have a monogenic risk for arrhythmia (n = 95), breast cancer (n = 96), cardiomyopathy (n = 95), colorectal cancer (n = 105), or familial hypercholesterolemia (n = 86). Individuals with P/LP results more frequently received services after return (43.8%) compared to before return (25.6%) of results and compared to individuals with negative findings (24.9%; p < 0.0001). The annual cost of qualifying healthcare services increased from an average of $162 before return to $343 after return of results among the P/LP group (p < 0.0001); differences in the negative group were non-significant. The mean difference-in-differences was $149 (p < 0.0001), which describes the increased cost within the P/LP group corrected for cost changes in the negative group. When stratified by individual conditions, significant cost differences were observed for arrhythmia, breast cancer, and cardiomyopathy. In conclusion, less than half of individuals received billed health services after monogenic return, which modestly increased healthcare costs for payors in the year following return.

Multi-ancestry genome- and phenome-wide association studies of diverticular disease in electronic health records with natural language processing enriched phenotyping algorithm.

OBJECTIVE: Diverticular disease (DD) is one of the most prevalent conditions encountered by gastroenterologists, affecting ~50% of Americans before the age of 60. Our aim was to identify genetic risk variants and clinical phenotypes associated with DD, leveraging multiple electronic health record (EHR) data sources of 91,166 multi-ancestry participants with a Natural Language Processing (NLP) technique. MATERIALS AND METHODS: We developed a NLP-enriched phenotyping algorithm that incorporated colonoscopy or abdominal imaging reports to identify patients with diverticulosis and diverticulitis from multicenter EHRs. We performed genome-wide association studies (GWAS) of DD in European, African and multi-ancestry participants, followed by phenome-wide association studies (PheWAS) of the risk variants to identify their potential comorbid/pleiotropic effects in clinical phenotypes. RESULTS: Our developed algorithm showed a significant improvement in patient classification performance for DD analysis (algorithm PPVs ≥ 0.94), with up to a 3.5 fold increase in terms of the number of identified patients than the traditional method. Ancestry-stratified analyses of diverticulosis and diverticulitis of the identified subjects replicated the well-established associations between ARHGAP15 loci with DD, showing overall intensified GWAS signals in diverticulitis patients compared to diverticulosis patients. Our PheWAS analyses identified significant associations between the DD GWAS variants and circulatory system, genitourinary, and neoplastic EHR phenotypes. DISCUSSION: As the first multi-ancestry GWAS-PheWAS study, we showcased that heterogenous EHR data can be mapped through an integrative analytical pipeline and reveal significant genotype-phenotype associations with clinical interpretation. CONCLUSION: A systematic framework to process unstructured EHR data with NLP could advance a deep and scalable phenotyping for better patient identification and facilitate etiological investigation of a disease with multilayered data.

Missense Genetic Variation of ICAM1 and Incident Heart Failure.

BACKGROUND: Intercellular adhesion molecule-1 (ICAM-1) is a cell surface protein that participates in endothelial activation and is hypothesized to play a central role in heart failure (HF). We evaluated associations of ICAM1 missense genetic variants with circulating ICAM-1 levels and with incident HF. METHODS AND RESULTS: We identified 3 missense variants within ICAM1 (rs5491, rs5498 and rs1799969) and evaluated their associations with ICAM-1 levels in the Coronary Artery Risk Development in Young Adults Study and the Multi-Ethnic Study of Atherosclerosis (MESA). We determined the association among these 3 variants and incident HF in MESA. We separately evaluated significant associations in the Atherosclerosis Risk in Communities (ARIC) study. Of the 3 missense variants, rs5491 was common in Black participants (minor allele frequency [MAF] > 20%) and rare in other race/ethnic groups (MAF < 5%). In Black participants, the presence of rs5491 was associated with higher levels of circulating ICAM-1 at 2 timepoints separated by 8 years. Among Black participants in MESA (n = 1600), the presence of rs5491 was associated with an increased risk of incident HF with preserved ejection fraction (HFpEF; HR = 2.30; [95% CI 1.25-4.21; P = 0.007]). The other ICAM1 missense variants (rs5498 and rs1799969) were associated with ICAM-1 levels, but there were no associations with HF. In ARIC, rs5491 was significantly associated with incident HF (HR = 1.24 [95% CI 1.02 - 1.51]; P = 0.03), with a similar direction of effect for HFpEF that was not statistically significant. CONCLUSIONS: A common ICAM1 missense variant among Black individuals may be associated with increased risk of HF, which may be HFpEF-specific.

Causal effects on complex traits are similar for common variants across segments of different continental ancestries within admixed individuals.

Individuals of admixed ancestries (for example, African Americans) inherit a mosaic of ancestry segments (local ancestry) originating from multiple continental ancestral populations. This offers the unique opportunity of investigating the similarity of genetic effects on traits across ancestries within the same population. Here we introduce an approach to estimate correlation of causal genetic effects (radmix) across local ancestries and analyze 38 complex traits in African-European admixed individuals (N = 53,001) to observe very high correlations (meta-analysis radmix = 0.95, 95% credible interval 0.93-0.97), much higher than correlation of causal effects across continental ancestries. We replicate our results using regression-based methods from marginal genome-wide association study summary statistics. We also report realistic scenarios where regression-based methods yield inflated heterogeneity-by-ancestry due to ancestry-specific tagging of causal effects, and/or polygenicity. Our results motivate genetic analyses that assume minimal heterogeneity in causal effects by ancestry, with implications for the inclusion of ancestry-diverse individuals in studies.

Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.

Few studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry. ARTICLE HIGHLIGHTS: We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Secretory leukocyte protease inhibitor and risk of heart failure in the Multi-Ethnic Study of Atherosclerosis.

Circulating protease inhibitors are important regulators of inflammation that are implicated in the pathophysiology of heart failure (HF). Secretory leukocyte protease inhibitor (SLPI) is a serine protease inhibitor which protects pulmonary tissues against inflammatory damage; however, its role in HF is not well understood. We sought to evaluate associations of circulating SLPI and genetically-mediated serum SLPI with incident HF and its subtypes in a multi-ethnic cohort of adults using clinical and genetic epidemiological approaches. Among 2,297 participants in the Multi-Ethnic Study of Atherosclerosis (MESA), each doubling of serum SLPI was independently associated with incident HF (HR 1.77; 95% CI 1.02-3.02; P = 0.04), particularly incident HF with preserved ejection fraction (HFpEF; HR 2.44; 95% CI 1.23-4.84; P = 0.01) but not HF with reduced ejection fraction (HFrEF; HR 0.95; 95% CI 0.36-2.46; P = 0.91). Previously reported circulating SLPI protein quantitative trait loci (pQTLs) were not associated with serum SLPI levels or incident HF among MESA participants. In conclusion, baseline serum SLPI levels, but not genetically-determined serum SLPI, were significantly associated with incident HF and HFpEF over long-term follow-up in a multi-ethnic cohort. Serum circulating SLPI may be a correlate of inflammation that sheds insight on the pathobiology of HFpEF.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

Genome-wide association and multi-trait analyses characterize the common genetic architecture of heart failure.

Heart failure is a leading cause of cardiovascular morbidity and mortality. However, the contribution of common genetic variation to heart failure risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We report a multi-ancestry genome-wide association study meta-analysis of all-cause heart failure including up to 115,150 cases and 1,550,331 controls of diverse genetic ancestry, identifying 47 risk loci. We also perform multivariate genome-wide association studies that integrate heart failure with related cardiac magnetic resonance imaging endophenotypes, identifying 61 risk loci. Gene-prioritization analyses including colocalization and transcriptome-wide association studies identify known and previously unreported candidate cardiomyopathy genes and cellular processes, which we validate in gene-expression profiling of failing and healthy human hearts. Colocalization, gene expression profiling, and Mendelian randomization provide convergent evidence for the roles of BCKDHA and circulating branch-chain amino acids in heart failure and cardiac structure. Finally, proteome-wide Mendelian randomization identifies 9 circulating proteins associated with heart failure or quantitative imaging traits. These analyses highlight similarities and differences among heart failure and associated cardiovascular imaging endophenotypes, implicate common genetic variation in the pathogenesis of heart failure, and identify circulating proteins that may represent cardiomyopathy treatment targets.

Trajectories of Depressive and Anxiety Symptoms Across Pregnancy and Postpartum in Selective Serotonin Reuptake Inhibitor-Treated Women.

Objective: Tracking perinatal mood and anxiety disorders is championed by the American Psychiatric Association and the International Marcé Society for Perinatal Mental Health. We conducted this study to examine trajectories of monthly depressive and anxiety symptoms through pregnancy and postpartum. Methods: This is a prospective longitudinal observational cohort study of pregnant women interviewed at baseline (≤18th gestational week), every four weeks through delivery and at 6 and 14 weeks postpartum at three urban academic medical centers (N = 85) and a single rural health center (N = 3) from 2016 to 2020. Pregnant women had at least one prior episode of major depressive disorder, were not in a current episode, and were treated with sertraline, fluoxetine, citalopram, or escitalopram. Of 192 women screened, 88 (46%) women enrolled, and 77 (88%) women completed the postpartum follow-up. Symptom trajectories were generated with scores from the Edinburgh Postnatal Depression Scale, the Quick Inventory of Depressive Symptoms, the Generalized Anxiety Disorder Scale, 7-item, and the Patient-Reported Outcomes Measurement Information System Global Health measure. A semi-parametric, group-based mixture model (trajectory analysis) was applied. Results: Three relatively stable depression trajectories emerged, described as Minimal, Mild, and Subthreshold, in each group across pregnancy. Two of the four anxiety trajectories were stable, including Asymptomatic and Minimal, while the third, termed Breakthrough, was ascending with increasing symptoms and the fourth trajectory, described as Mild, had descending symptoms. Conclusions: Screening for anxiety with depression for pregnant women will yield a comprehensive view of psychiatric symptoms and treatment targets in perinatal women.

Changes in Sertraline Plasma Concentrations Across Pregnancy and Postpartum.

Major depressive disorder (MDD) is a common disorder in pregnancy. Although sertraline is the most frequently prescribed antidepressant for pregnant people in the United States, limited information about its pharmacokinetics in pregnancy is available. Our objectives were to characterize plasma sertraline concentration to dose (C/D) ratios across pregnancy and postpartum and investigate the effect of pharmacogenetic variability on sertraline elimination. We performed a prospective observational cohort study in people with a singleton pregnancy ≤ 18 weeks gestation and a lifetime diagnosis of MDD at the 3 Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD)-funded Obstetrical-Fetal Pharmacology Research Center sites. Subjects (N = 47) were receiving maintenance sertraline therapy and chose to continue it during pregnancy. Blood samples were obtained 24-hours postdose every 4 weeks across pregnancy and twice postpartum for measurement of plasma concentrations of sertraline and desmethylsertraline. Overall mean sertraline C/D ratios were decreased at study onset and remained consistently low until after delivery. During the last 4 weeks of pregnancy the mean sertraline C/D ratio (95% confidence interval (CI)), 0.25 (95% CI, 0.19, 0.3) ng/mL/dose (mg/day), was smaller than the mean ratio at ≥ 8 weeks after delivery, 0.32 (95% CI, 0.27, 0.37) ng/mL/dose (mg/day), a 22% difference. Mean sertraline/desmethylsertraline ratios were highest after birth, which confirmed increased sertraline elimination during pregnancy. Sertraline C/D ratios in participants with functional CYP2C19 activity did not change significantly during pregnancy, whereas ratios in participants with poor or intermediate CYP2C19 activity decreased by 51%. Exploratory pharmacogenomic analysis indicated that pregnant people with poor or intermediate CYP2C19 activity are at risk for subtherapeutic sertraline concentrations during pregnancy.

Whole genome sequence association analysis of fasting glucose and fasting insulin levels in diverse cohorts from the NHLBI TOPMed program.

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.

Large-scale genomic analyses reveal insights into pleiotropy across circulatory system diseases and nervous system disorders.

Clinical and epidemiological studies have shown that circulatory system diseases and nervous system disorders often co-occur in patients. However, genetic susceptibility factors shared between these disease categories remain largely unknown. Here, we characterized pleiotropy across 107 circulatory system and 40 nervous system traits using an ensemble of methods in the eMERGE Network and UK Biobank. Using a formal test of pleiotropy, five genomic loci demonstrated statistically significant evidence of pleiotropy. We observed region-specific patterns of direction of genetic effects for the two disease categories, suggesting potential antagonistic and synergistic pleiotropy. Our findings provide insights into the relationship between circulatory system diseases and nervous system disorders which can provide context for future prevention and treatment strategies.

Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations.

BACKGROUND: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations. METHODS: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts. RESULTS: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance. CONCLUSIONS: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.