BACKGROUND: Apolipoprotein E (APOE) alleles are well-established genetic risk factors for Alzheimer's disease (AD), but their effects on AD biomarkers (amyloid beta [Aβ]42/40, phosphorylated tau [p-tau]181, neurofilament light chain [NfL], and glial fibrillary acidic protein [GFAP]) may vary across populations due to ancestry-, age-, and sex-related differences. We hypothesized that these effects vary across Hispanic/Latino background groups with distinct ancestral admixture.

METHODS: We analyzed ε2 and ε4 allele associations with AD biomarkers using survey-weighted linear regression models, adjusting for demographic covariates. Secondary analyses examined genetic analysis group- and ancestry-specific effects.

RESULTS: ε4 was associated with lower Aβ42/40 and higher p-tau181and GFAP levels, but not with NfL, suggesting its role in Aβ and tau deposition and neuroinflammation. ε4 associations were stronger in those with higher European and lower African ancestry.

DISCUSSION: These findings expand on prior studies suggesting that genetic ancestry modifies APOE-associated AD risk in Hispanic/Latino populations and highlight the importance of capturing ancestry-based heterogeneity in AD biomarker research.

Prediction models for cognitive aging measures have largely evaluated demographic variables and APOE carrier status in populations of European ancestry. To comprehensively assess prediction models among Hispanic/Latinos, we considered 12 models (6 predictor sets and 2 methods) for global cognitive score change (GCSC) and mild cognitive impairment (MCI) in the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) (N = 5856). Based on the average mean squared error (MSE) for GCSC or average area under the curve (AUC) for MCI across 100 randomly split testing and training sets, performance was similar across models, but slightly better for the following models: the chronic conditions model and genetic model (mean MSEs = 0.2464) using gradient-boosted trees for GCSC prediction and the chronic conditions model (mean AUC = 62%) and metabolite model (mean AUC = 60%) using logistic regression for MCI prediction. Using the Shapley Additive Explanations (SHAP) method, age at baseline, time between exams, and sex were the most important predictors for GCSC, followed by diabetes and global ancestral proportions. Diabetes and the metabolite ribitol had the highest influence on prediction of MCI. Although prediction performance was not especially high and did not vary greatly across models, incorporating information on diabetes, ancestry and metabolites may help improve prediction of GCSC and MCI.

In admixed populations, formed by a mixing of two or more previously isolated populations, genomic segments can be traced to their ancestral populations ('ancestries'). Admixture mapping (AM) associates local ancestry with outcomes in admixed populations, detecting signals when causal variants differ in frequency or effect across ancestral populations. Prior work showed that adjusting for nearby GWAS-identified common variants does not fully explain some AM signals. Here, we assessed two approaches to explain the previously unexplained AM signal: (1) including sets of rare variants; (2) increasing the genomic region considered when searching for common variants. We studied these hypotheses comprehensively using a whole-genome sequencing dataset coupled with metabolomics from the Hispanic Community Health Study/Study of Latinos. From 16 genomic regions of interest, we identified 35 rare-variant sets associated with metabolite levels, of which 4 associations replicated. The locations of identified rare variant sets are either within the same gene or in proximity to adjusted common variants. Overall, our study provides new insight into the genetic architecture underlying AM signals via evaluating the contributions of common and rare variant sets. By integrating rare-variant analysis within the AM framework, our work highlights the potential interplay between variant types and establishes a novel strategy to guide future fine-mapping and causal variant identification in admixed populations. Yet the detected rare variants appear to explain only a small fraction of the AM signal, while inclusion of common variants from a larger genomic region appears to explain most of the AM signals.

BACKGROUND: Whole genome sequence (WGS) data in multi-ancestry samples supports discovery of low-frequency or population-specific genetic variants associated with chronic obstructive pulmonary disease (COPD) and lung function.

RESULTS: We performed single variant, structural variant, and gene-based analysis of pulmonary function (FEV1, FVC and FEV1/FVC) and COPD case-control status in 44,287 multi-ancestry participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We validated findings using the UK Biobank and assessed implicated genes using lung single-cell RNA-seq (scRNA-seq) data sets. Applying a genome-wide significance threshold (P < 5 × 10-9), we replicated known loci and identified novel associations near LY86, MAGI1, GRK7, and LINC02668. Colocalization with gene expression quantitative trait loci (eQTL) from the Lung Tissue Research Consortium highlighted known candidate genes including ADAM19, THSD4, C4B, and PSMA4, which were not identified through other eQTL sources. Multi-ancestry analysis improved fine-mapping resolution (e.g., HTR4 and RIN3). Gene-based analysis identified and replicated HMCN1. In human lung scRNA-seq data sets, lung epithelial cells and immune cell types showed enriched expression, while fibroblasts showed higher expression for HMCN1. CRISPR targeting HMCN1 in IMR90 demonstrated reduced expression of collagen genes.

CONCLUSIONS: Large-scale multi-ancestry WGS analysis improves variant discovery and fine-mapping resolution for lung function and COPD and highlights biologically relevant genes and pathways.

STUDY OBJECTIVES: Since genome-wide association studies (GWAS) of sleep phenotypes have been conducted in differing populations and definitions of sleep phenotypes vary across studies, we investigated associations between several polygenic risk scores (PRSs) and potential sleep definitions among multiethnic cohorts.

METHODS: Using data from four cohorts (HCHS/SOL, ARIC, MESA, BHS, N = 16 895), we considered multiple definitions of short and long sleep, insomnia, and excessive daytime sleepiness (EDS). PRSs were developed based on summary statistics from GWAS in European ancestry individuals from the UK Biobank (UKB) and from GWAS conducted in a multiethnic population from the Million Veteran Program (MVP). Study-specific analyses estimated associations between sleep PRSs and corresponding sleep measures per 1 standard deviation increase in the PRS. Models were adjusted for age, sex, ancestral principal components, and center and race as appropriate. Results were meta-analyzed across studies.

RESULTS: PRSs based on European ancestry UKB GWAS had statistically significant associations with multiple definitions of the corresponding sleep phenotypes. Associations that were most consistent across studies included: short sleep PRS with ≤6 hours (OR = 1.23,p = 1.80x10-7,phet = 0.97); long sleep PRS with ≥9 hours (OR = 1.09,p = 6.76x10-4,phet = 0.77); insomnia PRS with the Women's Health Initiative Insomnia Rating Scale (WHIIRS) ≥10 or a subset of three questions ≥6 in ARIC (OR = 1.17,p = 5.51x10-10,phet = 0.69); and EDS PRS with Epworth Sleepiness Scale (ESS) ≥11 (OR = 1.23,p = 1.83x10-13,phet = 0.83). PRSs based on multi-ancestry MVP GWAS had weaker associations compared to those based on European ancestry only.

CONCLUSIONS: By evaluating several types of sleep PRSs and sleep phenotypes, we were able to highlight which sleep PRS performed well across diverse populations and which sleep definitions better captured genetic underpinnings.

BACKGROUND: The APOE ε4 allele has weaker association with ADRD outcomes in Hispanic/Latino populations compared to non-Hispanic White and East Asian populations.

METHODS: We used whole-genome sequencing data from 13,025 Hispanic/Latino adults to infer population groups (clusters) from short DNA sequences at the APOE gene region. We estimated the associations between these clusters and mild cognitive impairment (MCI) and age-adjusted significant cognitive decline assessed via the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA) study (n = 5334). We compared these associations to those of the conventional APOE alleles.

RESULTS: We identified three clusters of individuals. Relative to the largest Cluster 1, being in Cluster 3 had higher likelihood of having significant cognitive decline, with odds ratio (OR) = 1.47, 95% confidence interval (CI) [1.18, 1.84], p < 0.001. The association with having prevalent MCI at the SOL-INCA exam was not statistically significant, with OR = 1.33, 95% CI [0.97, 1.83], p = 0.08. Associations of the ε4 allele with these traits were not statistically significant.

DISCUSSION: The new APOE profile has stronger risk association with age-adjusted significant cognitive decline in SOL-INCA Hispanics/Latinos compared to the ε4 allele.

IMPORTANCE: Apolipoprotein B (apoB) distribution and its implications as an atherosclerotic cardiovascular disease (ASCVD) risk-enhancing factor among individuals of diverse Hispanic or Latino backgrounds have not been described.

OBJECTIVE: To describe the distribution of apoB in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) cohort and to characterize associations of baseline sociodemographic and clinical variables with apoB and self-identified Hispanic or Latino background.

DESIGN, SETTING, AND PARTICIPANTS: The HCHS/SOL was a prospective, population-based cohort study of diverse Hispanic or Latino adults living in the US who were recruited and screened between March 2008 and June 2011. Sampling weights were used to generate a population-based sample of Hispanic or Latino participants aged 18 to 74 years who resided in 4 US metropolitan areas (Bronx, New York; Chicago, Illinois; Miami, Florida; and San Diego, California). ApoB concentration was measured in participants from the HCHS/SOL, and apoB tertiles were compared across demographic groups, including self-identified Hispanic or Latino background. Median percentage continental genetic ancestry (West African, Amerindian, and European) was compared across apoB tertiles.

EXPOSURE: ApoB measured in mg/dL from serum or plasma using an immunoturbidimetric assay.

MAIN OUTCOMES AND MEASURES: ApoB tertiles were determined, and traditional lipids were evaluated across apoB tertiles. ApoB and traditional lipid measurements were assessed across ASCVD risk categories. Additionally, scatterplots were created to observe correlations between apoB and low-density lipoprotein cholesterol or non-high-density lipoprotein cholesterol.

RESULTS: Overall mean (SD) apoB concentration was 99.8 (0.4) mg/dL, with male participants displaying significantly higher mean levels than female participants (102.4 vs 97.4 mg/dL, respectively). Mean (SD) participant age was 41.1 (0.8) years, and 8376 participants (51.9%) were female. ApoB levels were higher among older age groups. There was significant heterogeneity in mean apoB concentrations across self-identified Hispanic or Latino background groups, ranging from 95.1 mg/dL in Dominican individuals to 104.8 mg/dL in Cuban individuals. The prevalence of elevated apoB (≥130 mg/dL) was greater across higher predicted ASCVD risk categories. Among participants with a 10-year predicted ASCVD risk of 7.5% or higher, 26.5% had an elevated apoB. Median West African ancestry was lower across higher tertiles of apoB.

CONCLUSIONS AND RELEVANCE: In this cohort study among participants from the HCHS/SOL, elevated apoB was present in one-quarter of a diverse cohort study of Hispanic or Latino individuals who were at intermediate or high predicted ASCVD risk. Differences in apoB distribution among Hispanic or Latino individuals may have important implications for apoB's use in ASCVD risk assessment.

IMPORTANCE: Apolipoprotein B (apoB) distribution and its implications as an atherosclerotic cardiovascular disease (ASCVD) risk-enhancing factor among individuals of diverse Hispanic or Latino backgrounds have not been described.

OBJECTIVE: To describe the distribution of apoB in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) cohort and to characterize associations of baseline sociodemographic and clinical variables with apoB and self-identified Hispanic or Latino background.

DESIGN, SETTING, AND PARTICIPANTS: The HCHS/SOL was a prospective, population-based cohort study of diverse Hispanic or Latino adults living in the US who were recruited and screened between March 2008 and June 2011. Sampling weights were used to generate a population-based sample of Hispanic or Latino participants aged 18 to 74 years who resided in 4 US metropolitan areas (Bronx, New York; Chicago, Illinois; Miami, Florida; and San Diego, California). ApoB concentration was measured in participants from the HCHS/SOL, and apoB tertiles were compared across demographic groups, including self-identified Hispanic or Latino background. Median percentage continental genetic ancestry (West African, Amerindian, and European) was compared across apoB tertiles.

EXPOSURE: ApoB measured in mg/dL from serum or plasma using an immunoturbidimetric assay.

MAIN OUTCOMES AND MEASURES: ApoB tertiles were determined, and traditional lipids were evaluated across apoB tertiles. ApoB and traditional lipid measurements were assessed across ASCVD risk categories. Additionally, scatterplots were created to observe correlations between apoB and low-density lipoprotein cholesterol or non-high-density lipoprotein cholesterol.

RESULTS: Overall mean (SD) apoB concentration was 99.8 (0.4) mg/dL, with male participants displaying significantly higher mean levels than female participants (102.4 vs 97.4 mg/dL, respectively). Mean (SD) participant age was 41.1 (0.8) years, and 8376 participants (51.9%) were female. ApoB levels were higher among older age groups. There was significant heterogeneity in mean apoB concentrations across self-identified Hispanic or Latino background groups, ranging from 95.1 mg/dL in Dominican individuals to 104.8 mg/dL in Cuban individuals. The prevalence of elevated apoB (≥130 mg/dL) was greater across higher predicted ASCVD risk categories. Among participants with a 10-year predicted ASCVD risk of 7.5% or higher, 26.5% had an elevated apoB. Median West African ancestry was lower across higher tertiles of apoB.

CONCLUSIONS AND RELEVANCE: In this cohort study among participants from the HCHS/SOL, elevated apoB was present in one-quarter of a diverse cohort study of Hispanic or Latino individuals who were at intermediate or high predicted ASCVD risk. Differences in apoB distribution among Hispanic or Latino individuals may have important implications for apoB's use in ASCVD risk assessment.

INTRODUCTION: We studied the replication and generalization of previously identified metabolites potentially associated with global cognitive function in multiple race/ethnicities and assessed the contribution of diet to these associations.

METHODS: We tested metabolite-cognitive function associations in U.S.A. Hispanic/Latino adults (n = 2222) from the Community Health Study/ Study of Latinos (HCHS/SOL) and in European (n = 1365) and African (n = 478) Americans from the Atherosclerosis Risk In Communities (ARIC) Study. We applied Mendelian Randomization (MR) analyses to assess causal associations between the metabolites and cognitive function and between Mediterranean diet and cognitive function.

RESULTS: Six metabolites were consistently associated with lower global cognitive function across all studies. Of these, four were sugar-related (e.g., ribitol). MR analyses provided weak evidence for a potential causal effect of ribitol on cognitive function and bi-directional effects of cognitive performance on diet.

DISCUSSION: Several diet-related metabolites were associated with global cognitive function across studies with different race/ethnicities.

HIGHLIGHTS: Metabolites associated with cognitive function in Puerto Rican adults were recently identified. We demonstrate the generalizability of these associations across diverse race/ethnicities. Most identified metabolites are related to sugars. Mendelian Randomization (MR) provides weak evidence for a causal effect of ribitol on cognitive function. Beta-cryptoxanthin and other metabolites highlight the importance of a healthy diet.

Estimated glomerular filtration rate (eGFR) is used to evaluate kidney function and determine the presence of chronic kidney disease (CKD), a highly prevalent disease in the US1 , 2 , 3 that varies among subgroups of Hispanic/Latino individuals.4 , 5 The polygenic risk score (PRS) is a popular method that uses large genome-wide association studies (GWASs) to provide a strong estimate of disease risk.7 However, due to the limited availability of summary statistics from GWAS meta-analyses based on Hispanic/Latino populations, PRSs can only be computed using different ancestry GWASs. The performance of eGFR PRSs derived from other GWAS reference populations for Hispanic/Latino population has not been examined. We compared PRS constructions for eGFR prediction in Hispanic/Latino individuals using GWAS-significant variants, clumping and thresholding (C&T),8 and PRS-CS,22 as well as a combination of PRSs calculated with different reference GWAS meta-analyses from European and multi-ethnic studies in Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). All eGFR PRSs were highly associated with eGFR (p < 1E-20). Additionally, eGFR PRSs were significantly associated with lower risk of prevalent CKD at visit 1 or 2 and incident CKD at visit 2, with the combined PRSs having the best performance. These PRS findings were replicated in an additional dataset of Hispanic/Latino individuals using data from the Women's Health Initiative SNP Health Association Resource (WHI-SHARe).17.