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Secretory IgA (SIgA) is released into mucosal surfaces where its function extends beyond that of host defense to include the shaping of resident microbial communities by mediating exclusion/inclusion of respective microbes and regulating bacterial gene expression. In this capacity, SIgA acts as the fulcrum on which host immunity and the health of the microbiota are balanced. We recently completed an analysis of the gut and salivary IgA-Biomes (16S rDNA sequencing of SIgA-coated/uncoated bacteria) in Mexican-American adults that identified IgA-Biome differences across the glycemic spectrum. As Th17:Treg ratio imbalances are associated with gut microbiome dysbiosis and chronic inflammatory conditions such as type 2 diabetes, the present study extends our prior work by examining the impact of Th17:Treg ratios (pro-inflammatory:anti-inflammatory T-cell ratios) and the SIgA response (Th17:Treg-SIgA axis) in shaping microbial communities. Examining the impact of Th17:Treg ratios (determined by epigenetic qPCR lymphocyte subset quantification) on the IgA-Biome across diabetes phenotypes identified a proportional relationship between Th17:Treg ratios and alpha diversity in the stool IgA-Biome of those with dysglycemia, significant changes in community composition of the stool and salivary microbiomes across glycemic profiles, and genera preferentially abundant by T-cell inflammatory phenotype. This is the first study to associate epigenetically quantified Th17:Treg ratios with both the larger and SIgA-fractionated microbiome, assess these associations in the context of a chronic inflammatory disease, and offers a novel frame through which to evaluate mucosal microbiomes in the context of host responses and inflammation.

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 ( PRIM1 ) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV 1 /FVC), and an eQTL of matrix metallopeptidase 15 ( MMP15 ) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 ( HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.

Prediabetes is one of the main health concerns in public health, and various etiological factors contribute to its onset. This study aimed to evaluate genetic associations and gene‐macronutrient interaction with prediabetes‐related metabolites to understand how genetic variation and dietary intake contribute to dysglycemia. We analyzed a total of 482 self‐identified Mexican American participants recruited from Starr County, Texas in 2018‐2019. Untargeted metabolomic profiling was performed using LC‐MS. Nutrient densities of six macronutrients were derived from a 106‐item food frequency questionnaire. Genetic associations for each metabolite were tested using Generalized linear Mixed Model Association Tests (GMMAT). Gene‐macronutrient interactions on prediabetes‐associated metabolites were assessed with the Mixed Model Association Test for GEne‐Environment Interaction (MAGEE). Age, gender, and BMI were included as covariates in all association tests. Among 308 named and 2,471 unnamed metabolites, 17 novel variant‐metabolite pairs were discovered, including rs10947898 in LRFN2 associated with diacylglycerol DG32:1(p‐value: 8.95E‐09). Among 145 named and 687 unnamed metabolites after filtering, gene‐macronutrient interaction analyses identified seven named metabolites, including a variant(rs111251222) in MXD3 that interacted with monounsaturated fat to influence eicosadienoic acid levels (Interaction p‐value: 9.88E‐09). Prediabetes and nutrient‐related metabolites in Mexican Americans showed significant genetic associations and gene‐nutrient interactions. We studied how genes and diet influence metabolites in Mexican Americans. We found new genetic links to 17 blood metabolites and discovered 7 interactions between genetic variants and macronutrients like protein and various types of fat. These findings could help personalize strategies for preventing diabetes based on genetic and dietary factors in Mexican Americans.

We performed genome-wide meta-analysis of lipid traits on three samples of Mexican and Mexican American ancestry comprising 4,383 individuals and followed up significant and highly suggestive associations in three additional Hispanic samples comprising 7,876 individuals. Genome-wide significant signals were observed in or near CELSR2 , ZNF259/APOA5 , KANK2/DOCK6 and NCAN/MAU2 for total cholesterol, LPL, ABCA1, ZNF259/APOA5 , LIPC and CETP for HDL cholesterol, CELSR2, APOB and NCAN/MAU2 for LDL cholesterol and GCKR , TRIB1 , ZNF259/APOA5 and NCAN/ MAU2 for triglycerides. Linkage disequilibrium and conditional analyses indicate that signals observed at ABCA1 and LIPC for HDL cholesterol and NCAN/MAU2 for triglycerides are independent of previously reported lead SNP associations. Analyses of lead SNPs from the European Global Lipids Genetics Consortium (GLGC) dataset in our Hispanic samples show remarkable concordance of direction of effects as well as strong correlation in effect sizes. A meta-analysis of the European GLGC and our Hispanic datasets identified five novel regions reaching genome-wide significance: two for total cholesterol ( FN1 and SAMM50 ), two for HDL cholesterol ( LOC100996634 and COPB1 ) and one for LDL cholesterol ( LINC00324/CTC1/PFAS ). The top meta-analysis signals were found to be enriched for SNPs associated with gene expression in a tissue-specific fashion, suggesting an enrichment of tissue-specific function in lipid-associated loci.

We carried out an admixture mapping study of lipid traits in two samples from Mexico City. Native American locus ancestry was significantly associated with triglyceride levels in a broad region of chromosome 11 overlapping the BUD13, ZNF259 and APOA5 genes. In our fine-mapping analysis of this region using dense genome-wide data, rs964184 is the only marker included in the 99% credible set of SNPs, providing strong support for rs964184 as the causal variant within this region. The frequency of the allele associated with increased triglyceride concentrations (rs964184-G) is between 30-40% higher in Native American populations from Mexico than in European populations. The evidence currently available for this variant indicates that it may be exerting its effect through three potential mechanisms: 1) modification of enhancer activity, 2) regulation of the expression of several genes in cis and/or trans, or 3) modification of the methylation patterns of the promoter of the APOA5 gene.

The electrocardiographically quantified QRS duration measures ventricular depolarization and conduction. QRS prolongation has been associated with poor heart failure prognosis and cardiovascular mortality, including sudden death. While previous genome-wide association studies (GWAS) have identified 32 QRS SNPs across 26 loci among European, African, and Asian-descent populations, the genetics of QRS among Hispanics/Latinos has not been previously explored. We performed a GWAS of QRS duration among Hispanic/Latino ancestry populations (n = 15,124) from four studies using 1000 Genomes imputed genotype data (adjusted for age, sex, global ancestry, clinical and study-specific covariates). Study-specific results were combined using fixed-effects, inverse variance-weighted meta-analysis. We identified six loci associated with QRS (P<5x10-8), including two novel loci: MYOCD, a nuclear protein expressed in the heart, and SYT1, an integral membrane protein. The top SNP in the MYOCD locus, intronic SNP rs16946539, was found in Hispanics/Latinos with a minor allele frequency (MAF) of 0.04, but is monomorphic in European and African descent populations. The most significant QRS duration association was with intronic SNP rs3922344 (P = 1.19x10-24) in SCN5A/SCN10A. Three other previously identified loci, CDKN1A, VTI1A, and HAND1, also exceeded the GWAS significance threshold among Hispanics/Latinos. A total of 27 of 32 previously identified QRS duration SNPs were shown to generalize in Hispanics/Latinos. Our QRS duration GWAS, the first in Hispanic/Latino populations, identified two new loci, underscoring the utility of extending large scale genomic studies to currently under-examined populations.

Chagas disease is a chronic parasitic infection that progresses to dilated cardiomyopathy in 30% of human cases. Public health efforts target diagnosing asymptomatic cases, as therapeutic efficacy diminishes as irreversible tissue damage progresses. Physician diagnosis of Chagas disease cases in the United States is low, partially due to lack of awareness of the potential burden in the United States. The current study tested a patient cohort of 1,196 Starr County, Texas residents using the Hemagen Chagas ELISA Kit as a preliminary screening assay. Samples testing positive using the Hemagen test were subjected to additional confirmatory tests. Two patients (0.17%) without previous Chagas disease diagnosis were identified; both had evidence of acquiring disease in the United States or along the Texas-Mexico border. The Texas-Mexico border is a foci of Chagas disease human cases, with a local disease burden potentially twice the national estimate of Hispanic populations. It is imperative that physicians consider persons with residential histories along the Texas-Mexico border for Chagas disease testing.

Staphylococcus aureus is the number one cause of hospital-acquired infections. Understanding host pathogen interactions is paramount to the development of more effective treatment and prevention strategies. Therefore, whole exome sequence and chip-based genotype data were used to conduct rare variant and genome-wide association analyses in a Mexican-American cohort from Starr County, Texas to identify genes and variants associated with S. aureus nasal carriage. Unlike most studies of S. aureus that are based on hospitalized populations, this study used a representative community sample. Two nasal swabs were collected from participants (n = 858) 11-17 days apart between October 2009 and December 2013, screened for the presence of S. aureus, and then classified as either persistent, intermittent, or non-carriers. The chip-based and exome sequence-based single variant association analyses identified 1 genome-wide significant region (KAT2B) for intermittent and 11 regions suggestively associated with persistent or intermittent S. aureus carriage. We also report top findings from gene-based burden analyses of rare functional variation. Notably, we observed marked differences between signals associated with persistent and intermittent carriage. In single variant analyses of persistent carriage, 7 of 9 genes in suggestively associated regions and all 5 top gene-based findings are associated with cell growth or tight junction integrity or are structural constituents of the cytoskeleton, suggesting that variation in genes associated with persistent carriage impact cellular integrity and morphology.

Background To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups. Methods Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina’s Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American group, where we used additive genetic models with gene-dropping. Results Findings included ethnic-specific genetic associations and heterogeneity across ethnicities. Most significant associations were outside our candidate linkage regions and were coincident within a gene or intergenic region, with two exceptions in European-American families: (a) within previously identified linkage region on chromosome 2, two significant GLI2-TFCP2L1 associations with weight, and (b) one chromosome 11 variant near CADM1-LINC00900 with pleiotropic blood pressure effects. Conclusions This multiethnic family study found genetic heterogeneity and coincident associations (with one case of pleiotropy), highlighting the importance of including diverse populations in genetic research and illustrating the complex genetic architecture underlying MetS.

Cysticercosis is a parasitic infection and neglected tropical disease caused by Taenia solium, or the pork tapeworm. Cysticercosis with central nervous system involvement, or neurocysticercosis, is a leading cause of chronic headaches and epilepsy in endemic regions, including Latin America and Asia. In the United States, the epidemiology of cysticercosis has not been well described. We conducted a cross-section serosurvey of Mexican-American adults residing along the Texas–Mexico border (Starr County, Texas) and identified an overall seroprevalence of 7.4% (45/605) for cysticercosis. Brain imaging studies conducted on seropositive study participants identified lesions consistent with calcified neurocysticercosis in 2 of the 45 seropositive individuals. Female sex (p = 0.021), employment in healthcare, caregiving, or social service (p = 0.002), and indoor occupation (p < 0.001) were found to be significantly associated with seropositivity. Further study is needed to evaluate the burden of neurocysticercosis and local transmission risk in this community.