A polygenic risk score for Alzheimer's disease constructed using APOE-region variants has stronger association than APOE alleles with mild cognitive impairment in Hispanic/Latino adults in the U.S.

INTRODUCTION: Polygenic Risk Scores (PRSs) are summaries of genetic risk alleles for an outcome. METHODS: We used summary statistics from five GWASs of AD to construct PRSs in 4,189 diverse Hispanics/Latinos (mean age 63 years) from the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA). We assessed the PRS associations with MCI in the combined set of people and in diverse subgroups, and when including and excluding the APOE gene region. We also assessed PRS associations with MCI in an independent dataset from the Mass General Brigham Biobank. RESULTS: A simple sum of 5 PRSs ("PRSsum"), each constructed based on a different AD GWAS, was associated with MCI (OR = 1.28, 95% CI [1.14, 1.41]) in a model adjusted for counts of the APOE-[Formula: see text] and APOE-[Formula: see text] alleles. Associations of single-GWAS PRSs were weaker. When removing SNPs from the APOE region from the PRSs, the association of PRSsum with MCI was weaker (OR = 1.17, 95% CI [1.04,1.31] with adjustment for APOE alleles). In all association analyses, APOE-[Formula: see text] and APOE-[Formula: see text] alleles were not associated with MCI. DISCUSSION: A sum of AD PRSs is associated with MCI in Hispanic/Latino older adults. Despite no association of APOE-[Formula: see text] and APOE-[Formula: see text] alleles with MCI, the association of the AD PRS with MCI is stronger when including the APOE region. Thus, APOE variants different than the classic APOE alleles may be important predictors of MCI in Hispanic/Latino adults.

Ancestry-driven metabolite variation provides insights into disease states in admixed populations.

BACKGROUND: Metabolic pathways are related to physiological functions and disease states and are influenced by genetic variation and environmental factors. Hispanics/Latino individuals have ancestry-derived genomic regions (local ancestry) from their recent admixture that have been less characterized for associations with metabolite abundance and disease risk. METHODS: We performed admixture mapping of 640 circulating metabolites in 3887 Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Metabolites were quantified in fasting serum through non-targeted mass spectrometry (MS) analysis using ultra-performance liquid chromatography-MS/MS. Replication was performed in 1856 nonoverlapping HCHS/SOL participants with metabolomic data. RESULTS: By leveraging local ancestry, this study identified significant ancestry-enriched associations for 78 circulating metabolites at 484 independent regions, including 116 novel metabolite-genomic region associations that replicated in an independent sample. Among the main findings, we identified Native American enriched genomic regions at chromosomes 11 and 15, mapping to FADS1/FADS2 and LIPC, respectively, associated with reduced long-chain polyunsaturated fatty acid metabolites implicated in metabolic and inflammatory pathways. An African-derived genomic region at chromosome 2 was associated with N-acetylated amino acid metabolites. This region, mapped to ALMS1, is associated with chronic kidney disease, a disease that disproportionately burdens individuals of African descent. CONCLUSIONS: Our findings provide important insights into differences in metabolite quantities related to ancestry in admixed populations including metabolites related to regulation of lipid polyunsaturated fatty acids and N-acetylated amino acids, which may have implications for common diseases in populations.

Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups.

We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.

Association of Mitochondrial DNA Copy Number With Brain MRI Markers and Cognitive Function: A Meta-analysis of Community-Based Cohorts.

BACKGROUND AND OBJECTIVES: Previous studies suggest that lower mitochondrial DNA (mtDNA) copy number (CN) is associated with neurodegenerative diseases. However, whether mtDNA CN in whole blood is related to endophenotypes of Alzheimer disease (AD) and AD-related dementia (AD/ADRD) needs further investigation. We assessed the association of mtDNA CN with cognitive function and MRI measures in community-based samples of middle-aged to older adults. METHODS: We included dementia-free participants from 9 diverse community-based cohorts with whole-genome sequencing in the Trans-Omics for Precision Medicine (TOPMed) program. Circulating mtDNA CN was estimated as twice the ratio of the average coverage of mtDNA to nuclear DNA. Brain MRI markers included total brain, hippocampal, and white matter hyperintensity volumes. General cognitive function was derived from distinct cognitive domains. We performed cohort-specific association analyses of mtDNA CN with AD/ADRD endophenotypes assessed within ±5 years (i.e., cross-sectional analyses) or 5-20 years after blood draw (i.e., prospective analyses) adjusting for potential confounders. We further explored associations stratified by sex and age (<60 vs ≥60 years). Fixed-effects or sample size-weighted meta-analyses were performed to combine results. Finally, we performed mendelian randomization (MR) analyses to assess causality. RESULTS: We included up to 19,152 participants (mean age 59 years, 57% women). Higher mtDNA CN was cross-sectionally associated with better general cognitive function (ß = 0.04; 95% CI 0.02-0.06) independent of age, sex, batch effects, race/ethnicity, time between blood draw and cognitive evaluation, cohort-specific variables, and education. Additional adjustment for blood cell counts or cardiometabolic traits led to slightly attenuated results. We observed similar significant associations with cognition in prospective analyses, although of reduced magnitude. We found no significant associations between mtDNA CN and brain MRI measures in meta-analyses. MR analyses did not reveal a causal relation between mtDNA CN in blood and cognition. DISCUSSION: Higher mtDNA CN in blood is associated with better current and future general cognitive function in large and diverse communities across the United States. Although MR analyses did not support a causal role, additional research is needed to assess causality. Circulating mtDNA CN could serve nevertheless as a biomarker of current and future cognitive function in the community.

Genome-wide association study of obstructive sleep apnoea in the Million Veteran Program uncovers genetic heterogeneity by sex.

BACKGROUND: Genome-wide association studies (GWAS) for obstructive sleep apnoea (OSA) are limited due to the underdiagnosis of OSA, leading to misclassification of OSA, which consequently reduces statistical power. We performed a GWAS of OSA in the Million Veteran Program (MVP) of the U.S. Department of Veterans Affairs (VA) healthcare system, where OSA prevalence is close to its true population prevalence. METHODS: We performed GWAS of 568,576 MVP participants, stratified by biological sex and by harmonized race/ethnicity and genetic ancestry (HARE) groups of White, Black, Hispanic, and Asian individuals. We considered both BMI adjusted (BMI-adj) and unadjusted (BMI-unadj) models. We replicated associations in independent datasets, and analysed the heterogeneity of OSA genetic associations across HARE and sex groups. We finally performed a larger meta-analysis GWAS of MVP, FinnGen, and the MGB Biobank, totalling 916,696 individuals. FINDINGS: MVP participants are 91% male. OSA prevalence is 21%. In MVP there were 18 and 6 genome-wide significant loci in BMI-unadj and BMI-adj analyses, respectively, corresponding to 21 association regions. Of these, 17 were not previously reported in association with OSA, and 13 replicated in FinnGen (False Discovery Rate p-value < 0.05). There were widespread significant differences in genetic effects between men and women, but less so across HARE groups. Meta-analysis of MVP, FinnGen, and MGB biobank revealed 17 additional, previously unreported, genome-wide significant regions. INTERPRETATION: Sex differences in genetic associations with OSA are widespread, likely associated with multiple OSA risk factors. OSA shares genetic underpinnings with several sleep phenotypes, suggesting shared aetiology and causal pathways. FUNDING: Described in acknowledgements.

An integrated multi-omics analysis of sleep-disordered breathing traits implicates P2XR4 purinergic signaling.

Sleep Disordered Breathing (SDB) is a common disease associated with increased risk for cardiometabolic, cardiovascular, and cognitive diseases. How SDB affects the molecular environment is still poorly understood. We study the association of three SDB measures with gene expression measured using RNA-seq in multiple blood tissues from the Multi-Ethnic Study of Atherosclerosis. We develop genetic instrumental variables for the associated transcripts as polygenic risk scores (tPRS), then generalize and validate the tPRS in the Women's Health Initiative. We measure the associations of the validated tPRS with SDB and serum metabolites in Hispanic Community Health Study/Study of Latinos. Here we find differential gene expression by blood cell type in relation to SDB traits and link P2XR4 expression to average oxyhemoglobin saturation during sleep and butyrylcarnitine (C4) levels. These findings can be used to develop interventions to alleviate the effect of SDB on the human molecular environment.

Machine learning models for blood pressure phenotypes combining multiple polygenic risk scores.

We construct non-linear machine learning (ML) prediction models for systolic and diastolic blood pressure (SBP, DBP) using demographic and clinical variables and polygenic risk scores (PRSs). We developed a two-model ensemble, consisting of a baseline model, where prediction is based on demographic and clinical variables only, and a genetic model, where we also include PRSs. We evaluate the use of a linear versus a non-linear model at both the baseline and the genetic model levels and assess the improvement in performance when incorporating multiple PRSs. We report the ensemble model's performance as percentage variance explained (PVE) on a held-out test dataset. A non-linear baseline model improved the PVEs from 28.1% to 30.1% (SBP) and 14.3% to 17.4% (DBP) compared with a linear baseline model. Including seven PRSs in the genetic model computed based on the largest available GWAS of SBP/DBP improved the genetic model PVE from 4.8% to 5.1% (SBP) and 4.7% to 5% (DBP) compared to using a single PRS. Adding additional 14 PRSs computed based on two independent GWASs further increased the genetic model PVE to 6.3% (SBP) and 5.7% (DBP). PVE differed across self-reported race/ethnicity groups, with primarily all non-White groups benefitting from the inclusion of additional PRSs.

Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOL.

BACKGROUND: Obstructive Sleep Apnoea (OSA) often co-occurs with cardiometabolic and pulmonary diseases. This study is to apply genetic analysis methods to explain the associations between OSA and related phenotypes. METHODS: In the Hispanic Community Healthy Study/Study of Latinos, we estimated genetic correlations ρg between the respiratory event index (REI) and 54 anthropometric, glycemic, cardiometabolic, and pulmonary phenotypes. We used summary statistics from published genome-wide association studies to construct Polygenic Risk Scores (PRSs) representing the genetic basis of each correlated phenotype (ρg>0.2 and p-value<0.05), and of OSA. We studied the association of the PRSs of the correlated phenotypes with both REI and OSA (REI≥5), and the association of OSA PRS with the correlated phenotypes. Causal relationships were tested using Mendelian Randomization (MR) analysis. FINDINGS: The dataset included 11,155 participants, 31.03% with OSA. 22 phenotypes were genetically correlated with REI. 10 PRSs covering obesity and fat distribution (BMI, WHR, WHRadjBMI), blood pressure (DBP, PP, MAP), glycaemic control (fasting insulin, HbA1c, HOMA-B) and insomnia were associated with REI and/or OSA. OSA PRS was associated with BMI, WHR, DBP and glycaemic traits (fasting insulin, HbA1c, HOMA-B and HOMA-IR). MR analysis identified robust causal effects of BMI and WHR on OSA, and probable causal effects of DBP, PP, and HbA1c on OSA/REI. INTERPRETATION: There are shared genetic underpinnings of anthropometric, blood pressure, and glycaemic phenotypes with OSA, with evidence for causal relationships between some phenotypes. FUNDING: Described in Acknowledgments.

Non-linear machine learning models incorporating SNPs and PRS improve polygenic prediction in diverse human populations.

Polygenic risk scores (PRS) are commonly used to quantify the inherited susceptibility for a trait, yet they fail to account for non-linear and interaction effects between single nucleotide polymorphisms (SNPs). We address this via a machine learning approach, validated in nine complex phenotypes in a multi-ancestry population. We use an ensemble method of SNP selection followed by gradient boosted trees (XGBoost) to allow for non-linearities and interaction effects. We compare our results to the standard, linear PRS model developed using PRSice, LDpred2, and lassosum2. Combining a PRS as a feature in an XGBoost model results in a relative increase in the percentage variance explained compared to the standard linear PRS model by 22% for height, 27% for HDL cholesterol, 43% for body mass index, 50% for sleep duration, 58% for systolic blood pressure, 64% for total cholesterol, 66% for triglycerides, 77% for LDL cholesterol, and 100% for diastolic blood pressure. Multi-ancestry trained models perform similarly to specific racial/ethnic group trained models and are consistently superior to the standard linear PRS models. This work demonstrates an effective method to account for non-linearities and interaction effects in genetics-based prediction models.

Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea.

Rationale: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epidemiologic evidence supporting the importance of genetic factors influencing OSA but limited data implicating specific genes. Objectives: To search for rare variants contributing to OSA severity. Methods: Leveraging high-depth genomic sequencing data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the CFS (Cleveland Family Study), followed by multistage gene-based association analyses in independent cohorts for apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry. Measurements and Main Results: Linkage analysis in the CFS identified a suggestive linkage peak on chromosome 7q31 (LOD = 2.31). Gene-based analysis identified 21 noncoding rare variants in CAV1 (Caveolin-1) associated with lower AHI after accounting for multiple comparisons (P = 7.4 × 10-8). These noncoding variants together significantly contributed to the linkage evidence (P < 10-3). Follow-up analysis revealed significant associations between these variants and increased CAV1 expression, and increased CAV1 expression in peripheral monocytes was associated with lower AHI (P = 0.024) and higher minimum overnight oxygen saturation (P = 0.007). Conclusions: Rare variants in CAV1, a membrane-scaffolding protein essential in multiple cellular and metabolic functions, are associated with higher CAV1 gene expression and lower OSA severity, suggesting a novel target for modulating OSA severity.

A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood.

In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.

Upregulated heme biosynthesis increases obstructive sleep apnea severity: a pathway-based Mendelian randomization study.

Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Iron and heme metabolism, implicated in ventilatory control and OSA comorbidities, was associated with OSA phenotypes in recent admixture mapping and gene enrichment analyses. However, its causal contribution was unclear. In this study, we performed pathway-level transcriptional Mendelian randomization (MR) analysis to investigate the causal relationships between iron and heme related pathways and OSA. In primary analysis, we examined the expression level of four iron/heme Reactome pathways as exposures and four OSA traits as outcomes using cross-tissue cis-eQTLs from the Genotype-Tissue Expression portal and published genome-wide summary statistics of OSA. We identify a significant putative causal association between up-regulated heme biosynthesis pathway with higher sleep time percentage of hypoxemia (p = 6.14 × 10-3). This association is supported by consistency of point estimates in one-sample MR in the Multi-Ethnic Study of Atherosclerosis using high coverage DNA and RNA sequencing data generated by the Trans-Omics for Precision Medicine project. Secondary analysis for 37 additional iron/heme Gene Ontology pathways did not reveal any significant causal associations. This study suggests a causal association between increased heme biosynthesis and OSA severity.

BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion.

Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.

Benchmarking association analyses of continuous exposures with RNA-seq in observational studies.

Large datasets of hundreds to thousands of individuals measuring RNA-seq in observational studies are becoming available. Many popular software packages for analysis of RNA-seq data were constructed to study differences in expression signatures in an experimental design with well-defined conditions (exposures). In contrast, observational studies may have varying levels of confounding transcript-exposure associations; further, exposure measures may vary from discrete (exposed, yes/no) to continuous (levels of exposure), with non-normal distributions of exposure. We compare popular software for gene expression-DESeq2, edgeR and limma-as well as linear regression-based analyses for studying the association of continuous exposures with RNA-seq. We developed a computation pipeline that includes transformation, filtering and generation of empirical null distribution of association P-values, and we apply the pipeline to compute empirical P-values with multiple testing correction. We employ a resampling approach that allows for assessment of false positive detection across methods, power comparison and the computation of quantile empirical P-values. The results suggest that linear regression methods are substantially faster with better control of false detections than other methods, even with the resampling method to compute empirical P-values. We provide the proposed pipeline with fast algorithms in an R package Olivia, and implemented it to study the associations of measures of sleep disordered breathing with RNA-seq in peripheral blood mononuclear cells in participants from the Multi-Ethnic Study of Atherosclerosis.

APOE alleles' association with cognitive function differs across Hispanic/Latino groups and genetic ancestry in the study of Latinos-investigation of neurocognitive aging (HCHS/SOL).

INTRODUCTION: Apolipoprotein E (APOE) alleles are associated with cognitive decline, mild cognitive impairment (MCI), and Alzheimer's disease in Whites, but have weaker and inconsistent effects reported in Latinos. We hypothesized that this heterogeneity is due to ancestry-specific genetic effects. METHODS: We investigated the associations of the APOE alleles with significant cognitive decline and MCI in 4183 Latinos, stratified by six Latino backgrounds, and explored whether the proportion of continental genetic ancestry (European, African, and Amerindian) modifies these associations. RESULTS: APOE ε4 was associated with an increased risk of significant cognitive decline (odds ratio [OR] = 1.15, P-value = 0.03), with the strongest association in Cubans (OR = 1.46, P-value = 0.007). APOE-ε2 was associated with decreased risk of MCI (OR = 0.37, P-value = 0.04) in Puerto Ricans. Amerindian genetic ancestry was found to protect from the risk conferred by APOE ε4 on significant cognitive decline. DISCUSSION: Results suggest that APOE alleles' effects on cognitive outcomes differ across six Latino backgrounds and are modified by continental genetic ancestry.

Association of mitochondrial DNA copy number with cardiometabolic diseases.

Mitochondrial DNA (mtDNA) is present in multiple copies in human cells. We evaluated cross-sectional associations of whole blood mtDNA copy number (CN) with several cardiometabolic disease traits in 408,361 participants of multiple ancestries in TOPMed and UK Biobank. Age showed a threshold association with mtDNA CN: among younger participants (<65 years of age), each additional 10 years of age was associated with 0.03 standard deviation (s.d.) higher level of mtDNA CN (P = 0.0014) versus a 0.14 s.d. lower level of mtDNA CN (P = 1.82 × 10-13) among older participants (≥65 years). At lower mtDNA CN levels, we found age-independent associations with increased odds of obesity (P = 5.6 × 10-238), hypertension (P = 2.8 × 10-50), diabetes (P = 3.6 × 10-7), and hyperlipidemia (P = 6.3 × 10-5). The observed decline in mtDNA CN after 65 years of age may be a key to understanding age-related diseases.

Low oxygen saturation during sleep reduces CD1D and RAB20 expressions that are reversed by CPAP therapy.

BACKGROUND: Sleep Disordered Breathing (SDB) is associated with a wide range of pathophysiological changes due, in part, to hypoxemia during sleep. We sought to identify gene transcription associations with measures of SDB and hypoxemia during sleep, and study their response to treatment. METHODS: In two discovery cohorts, Framingham Offspring Study (FOS; N = 571) and the Multi-Ethnic Study of Atherosclerosis (MESA; N = 580), we studied gene expression in peripheral blood mononuclear cells in association with three measures of SDB: Apnea Hypopnea Index (AHI); average oxyhemoglobin saturation (avgO2) during sleep; and minimum oxyhemoglobin saturation (minO2) during sleep. Associated genes were used for analysis of gene expression in the blood of 15 participants with moderate or severe obstructive sleep apnea (OSA) from the Heart Biomarkers In Apnea Treatment (HeartBEAT) trial. These genes were studied pre- and post-treatment (three months) with continuous positive airway pressure (CPAP). We also performed Gene Set Enrichment Analysis (GSEA) on all traits and cohort analyses. FINDINGS: Twenty-two genes were associated with SDB traits in both MESA and FOS. Of these, lower expression of CD1D and RAB20 was associated with lower avgO2 in MESA and FOS. CPAP treatment increased the expression of these genes in HeartBEAT participants. Immunity and inflammation pathways were up-regulated in subjects with lower avgO2; i.e., in those with a more severe SDB phenotype (MESA), whereas immuno-inflammatory processes were down-regulated following CPAP treatment (HeartBEAT). INTERPRETATION: Low oxygen saturation during sleep is associated with alterations in gene expression and transcriptional programs that are partially reversed by CPAP treatment.

Variants Associated with the Ankle Brachial Index Differ by Hispanic/Latino Ethnic Group: a genome-wide association study in the Hispanic Community Health Study/Study of Latinos.

Lower extremity peripheral artery disease (PAD) burden differs by race/ethnicity. Although familial aggregation and heritability studies suggest a genetic basis, little is known about the genetic susceptibility to PAD, especially in non-European descent populations. Genome-wide association studies (GWAS) of the ankle brachial index (ABI) and PAD (defined as an ABI < 0.90) have not been conducted in Hispanics/Latinos. We performed a GWAS of PAD and the ABI in 7,589 participants aged >45 years from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We also performed GWAS for ABI stratified by Hispanic/Latino ethnic subgroups: Central American, Mexican, and South American (Mainland group), and Cuban, Dominican, and Puerto Rican (Caribbean group). We detected two genome-wide significant associations for the ABI in COMMD10 in Puerto Ricans, and at SYBU in the Caribbean group. The lead SNP rs4466200 in the COMMD10 gene had a replication p = 0.02 for the ABI in Multi-Ethnic Study of Atherosclerosis (MESA) African Americans, but it did not replicate in African Americans from the Cardiovascular Health Study (CHS). In a regional look-up, a nearby SNP rs12520838 had Bonferroni adjusted p = 0.05 (unadjusted p = 7.5 × 10-5) for PAD in MESA Hispanics. Among three suggestive associations (p < 10-7) in subgroup-specific analyses, DMD on chromosome X, identified in Central Americans, replicated in MESA Hispanics (p = 2.2 × 10-4). None of the previously reported ABI and PAD associations in whites generalized to Hispanics/Latinos.