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Genetic factors related to pregnancy-related traits are understudied, especially in ancestrally diverse cohorts. To assess maternal contributions to hypertensive disorders of pregnancy (HDP), we performed a multi-ancestry genome-wide association study (GWAS) of HDP in data from the North Carolina-based Personalized Environment and Genes Study (PEGS) cohort with validation in the UK Biobank (UKBB). The GWAS revealed two maternal loci associated with HDP at the genome-wide significance level. The lead independent variants were rs114954125 on chromosome 2 (near LRP1B; odds ratio [OR] [95% confidence interval {CI}]): 2.96 [2.02-4.34]; p = 2.82 × 10 -8 ) and rs61176331 on chromosome 3 (on RARB; OR (95% CI): 3.08 (2.12-4.48); p = 3.52 × 10 -9 ). We validated the associations near RARB with a meta-analysis of PEGS and the UKBB. We also identified cis-expression quantitative trait loci in the candidate region associated with decreased RARB expression in macrophage cells exposed to Salmonella. Chromatin mapping in FUMA identified a significant interaction within chromosome 3's enhancer and open chromatin regions, with strong effects observed for RARB and H3P10 gene regulation in mesendoderm cells, mesenchymal stem cells, and trophoblast-like stem cells. We applied existing polygenic scores (PGS) for preeclampsia and gestational hypertension and found that the scores were significantly associated with HDP in PEGS. The findings demonstrate the power of multi-ancestry studies for genetic discovery and highlight the relationship between immune response, regulation, and HDP and the utility of PGS for risk prediction. (PEGS is registered at ClinicalTrials.gov: NCT00341237.)., Competing Interests: Declaration of interests The authors declare no competing interests., (Published by Elsevier Inc.)

Introduction: We investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications., Methods: We conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial ( N = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis. We followed up with stratified GWAS analyses by sex and self-reported race., Results: In ACCORD, we identified single nucleotide polymorphisms (SNPs) associated with HGI, including a peak with the strongest association at the intergenic SNP rs73407935 (7q11.22) ( P = 5.8e-10) with a local replication in ARIC. In black individuals, the variant rs10739419 on chromosome 9 in the Whirlin ( WHRN ) gene formally replicated (meta- P = 2.2e-9). The SNP-based heritability of HGI was 0.39 ( P < 1e-10). HGI had significant sex-specific associations with SNPs in or near GALNT11 in women and HECW2 in men. Finally, in Hispanic participants, we observed genome-wide significant associations with variants near USF1 and NXNL2/SPIN1 ., Discussion: Many HGI-associated SNPs were distinct from those associated with fasting plasma glucose or HbA1c, lending further support for HGI as a distinct biomarker of diabetes complications. The results of this first evaluation of the genetic etiology of HGI indicate that it is highly heritable and point to heterogeneity by sex and race., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 House, Breeyear, Akhtari, Evans, Buse, Hempe, Doria, Mychaleckyi, Fonseca, Shi, Li, Liu, Kelly, Rotroff and Motsinger-Reif.)

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., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Understanding of human variation in toxicity to environmental chemicals remains limited, so human health risk assessments still largely rely on a generic 10-fold factor (10½ each for toxicokinetics and toxicodynamics) to account for sensitive individuals or subpopulations., Objectives: We tested a hypothesis that population-wide in vitro cytotoxicity screening can rapidly inform both the magnitude of and molecular causes for interindividual toxicodynamic variability., Methods: We used 1,086 lymphoblastoid cell lines from the 1000 Genomes Project, representing nine populations from five continents, to assess variation in cytotoxic response to 179 chemicals. Analysis included assessments of population variation and heritability, and genome-wide association mapping, with attention to phenotypic relevance to human exposures., Results: For about half the tested compounds, cytotoxic response in the 1% most "sensitive" individual occurred at concentrations within a factor of 10½ (i.e., approximately 3) of that in the median individual; however, for some compounds, this factor was > 10. Genetic mapping suggested important roles for variation in membrane and transmembrane genes, with a number of chemicals showing association with SNP rs13120371 in the solute carrier SLC7A11, previously implicated in chemoresistance., Conclusions: This experimental approach fills critical gaps unaddressed by recent large-scale toxicity testing programs, providing quantitative, experimentally based estimates of human toxicodynamic variability, and also testable hypotheses about mechanisms contributing to interindividual variation.

Aim: We investigate the role of ethnicity and admixture in drug response across a broad group of chemotherapeutic drugs. Also, we generate hypotheses on the genetic variants driving differential drug response through multivariate genome-wide association studies., Methods: Immortalized lymphoblastoid cell lines from 589 individuals (Hispanic or non-Hispanic/Caucasian) were used to investigate dose-response for 28 chemotherapeutic compounds. Univariate and multivariate statistical models were used to elucidate associations between genetic variants and differential drug response as well as the role of ethnicity in drug potency and efficacy., Results & Conclusion: For many drugs, the variability in drug response appears to correlate with self-reported race and estimates of genetic ancestry. Additionally, multivariate genome-wide association analyses offered interesting hypotheses governing these differential responses.

Aim: Association mapping with lymphoblastoid cell lines (LCLs) is a promising approach in pharmacogenomics research, and in the current study we utilized LCLs to perform association mapping for 29 chemotherapy drugs., Materials & Methods: Currently, we use LCLs to perform genome-wide association mapping of the cytotoxic response of 520 European-Americans to 29 different anticancer drugs; the largest LCL study to date. A novel association approach using a multivariate analysis of covariance design was employed with the software program MAGWAS, testing for differences in the dose-response profiles between genotypes without making assumptions about the response curve or the biologic mode of association. Additionally, by classifying 25 of the 29 drugs into eight families according to structural and mechanistic relationships, MAGWAS was used to test for associations that were shared across each drug family. Finally, a unique algorithm using multivariate responses and multiple linear regressions across pairs of response curves was used for unsupervised clustering of drugs., Results: Among the single-drug studies, suggestive associations were obtained for 18 loci, 12 within/near genes. Three of these, MED12L, CHN2 and MGMT, have been previously implicated in cancer pharmacogenomics. The drug family associations resulted in four additional suggestive loci (three contained within/near genes). One of these genes, HDAC4, associated with the DNA alkylating agents, shows possible clinical interactions with temozolomide. For the drug clustering analysis, 18 of 25 drugs clustered into the appropriate family., Conclusion: This study demonstrates the utility of LCLs in identifying genes that have clinical importance in drug response and for assigning unclassified agents to specific drug families, and proposes new candidate genes for follow-up in a large number of chemotherapy drugs.

Objective: As genotyping technology has progressed, genome-wide association studies (GWAS) have matured into efficient and effective tools for mapping genes underlying human phenotypes., Methods: Recent studies have shown the utility of the GWAS approach for examining pharmacogenomic traits, including drug metabolism, efficacy, and toxicity., Results: Application of GWAS to pharmacogenomic outcomes presents unique challenges and opportunities., Conclusion: In the current review, we discuss the potential promises and potential caveats of this approach specifically as it relates to pharmacogenomic studies. Concerns with study design, power and sample size, and analysis are reviewed. We further examine the features of successful pharmacogenomic GWAS, and describe consortia efforts that are likely to expand the reach of pharmacogenomic GWAS in the future.

ObjectiveSulfonylureas, the first available drugs for the management of type 2 diabetes, remain widely prescribed today. However, there exists significant variability in glycemic response to treatment. We aimed to establish heritability of sulfonylurea response and identify genetic variants and interacting treatments associated with HbA1c reduction.Research design and methodsAs an initiative of the Metformin Genetics Plus Consortium (MetGen Plus) and the DIabetes REsearCh on patient straTification (DIRECT) consortium, 5,485 White Europeans with type 2 diabetes treated with sulfonylureas were recruited from six referral centers in Europe and North America. We first estimated heritability using the generalized restricted maximum likelihood approach and then undertook genome-wide association studies of glycemic response to sulfonylureas measured as HbA1c reduction after 12 months of therapy followed by meta-analysis. These results were supported by acute glipizide challenge in humans who were naïve to type 2 diabetes medications, cis expression quantitative trait loci (eQTL), and functional validation in cellular models. Finally, we examined for possible drug-drug-gene interactions.ResultsAfter establishing that sulfonylurea response is heritable (mean ± SEM 37 ± 11%), we identified two independent loci near the GXYLT1 and SLCO1B1 genes associated with HbA1c reduction at a genome-wide scale (P < 5 × 10-8). The C allele at rs1234032, near GXYLT1, was associated with 0.14% (1.5 mmol/mol), P = 2.39 × 10-8), lower reduction in HbA1c. Similarly, the C allele was associated with higher glucose trough levels (β = 1.61, P = 0.005) in healthy volunteers in the SUGAR-MGH given glipizide (N = 857). In 3,029 human whole blood samples, the C allele is a cis eQTL for increased expression of GXYLT1 (β = 0.21, P = 2.04 × 10-58). The C allele of rs10770791, in an intronic region of SLCO1B1, was associated with 0.11% (1.2 mmol/mol) greater reduction in HbA1c (P = 4.80 × 10-8). In 1,183 human liver samples, the C allele at rs10770791 is a cis eQTL for reduced SLCO1B1 expression (P = 1.61 × 10-7), which, together with functional studies in cells expressing SLCO1B1, supports a key role for hepatic SLCO1B1 (encoding OATP1B1) in regulation of sulfonylurea transport. Further, a significant interaction between statin use and SLCO1B1 genotype was observed (P = 0.001). In statin nonusers, C allele homozygotes at rs10770791 had a large absolute reduction in HbA1c (0.48 ± 0.12% [5.2 ± 1.26 mmol/mol]), equivalent to that associated with initiation of a dipeptidyl peptidase 4 inhibitor.ConclusionsWe have identified clinically important genetic effects at genome-wide levels of significance, and important drug-drug-gene interactions, which include commonly prescribed statins. With increasing availability of genetic data embedded in clinical records these findings will be important in prescribing glucose-lowering drugs.

Metformin is the first-line treatment for type 2 diabetes (T2D). Although widely prescribed, the glucose-lowering mechanism for metformin is incompletely understood. Here, we used a genome-wide association approach in a diverse group of individuals with T2D from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial to identify common and rare variants associated with HbA1c response to metformin treatment and followed up these findings in four replication cohorts. Common variants in PRPF31 and CPA6 were associated with worse and better metformin response, respectively (P < 5 × 10-6), and meta-analysis in independent cohorts displayed similar associations with metformin response (P = 1.2 × 10-8 and P = 0.005, respectively). Previous studies have shown that PRPF31(+/-) knockout mice have increased total body fat (P = 1.78 × 10-6) and increased fasted circulating glucose (P = 5.73 × 10-6). Furthermore, rare variants in STAT3 associated with worse metformin response (q

Hydrochlorothiazide is among the most commonly prescribed antihypertensives; yet,

BackgroundFibrates are commonly prescribed for hypertriglyceridemia, but they also lower LDL cholesterol and increase HDL cholesterol. Large interindividual variations in lipid response suggest that some patients may benefit more than others and genetic studies could help identify such patients.MethodsWe carried out the first genome-wide association study of lipid response to fenofibrate using data from two well-characterized clinical trials: the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study and the Action to Control Cardiovascular Risk in Diabetes (ACCORD) Study. Genome-wide association study data from both studies were imputed to the 1000 Genomes CEU reference panel (phase 1). Lipid response was modeled as the log ratio of the post-treatment lipid level to the pretreatment level. Linear mixed models (GOLDN, N=813 from 173 families) and linear regression models (ACCORD, N=781) adjusted for pretreatment lipid level, demographic variables, clinical covariates, and ancestry were used to evaluate the association of genetic markers with lipid response. Among Caucasians, the results were combined using inverse-variance weighted fixed-effects meta-analyses. The main findings from the meta-analyses were examined in other ethnic groups from the HyperTG study (N=267 Hispanics) and ACCORD (N=83 Hispanics, 138 African Americans).ResultsA known lipid locus harboring the pre-B-cell leukemia homeobox 4 (PBX4) gene on chromosome 19 is important for LDL cholesterol response to fenofibrate (smallest P=1.5×10). The main results replicated with nominal statistical significance in Hispanics from ACCORD (P

ObjectiveRecently, lymphoblastoid cell lines (LCLs) have emerged as an innovative model system for mapping gene variants that predict the dose response to chemotherapy drugs.MethodsIn the current study, this strategy was expanded to the in-vitro genome-wide association approach, using 516 LCLs derived from a White cohort to assess the cytotoxic response to temozolomide.ResultsGenome-wide association analysis using ∼2.1 million quality-controlled single-nucleotide polymorphisms (SNPs) identified a statistically significant association (P