Effect of genotype × alcoholism interaction on linkage analysis of an alcoholism-related quantitative phenotype

Studies have shown that genetic and environmental factors and their interactions affect several alcoholism phenotypes. Genotype × alcoholism (G×A) interaction refers to the environmental (alcoholic and non-alcoholic) influences on the autosomal genes contributing to variation in an alcoholism-related quantitative phenotype. The purpose of this study was to examine the effects of G×A interaction on the detection of linkage for alcoholism-related phenotypes. We used phenotypic and genotypic data from the Collaborative Study on the Genetics of Alcoholism relating to 1,388 subjects as part of Genetic Analysis Workshop 14 problem 1. We analyzed the MXDRNK phenotype to detect G×A interaction using SOLAR. Upon detecting significant interaction, we conducted variance-component linkage analyses using microsatellite marker data. For maximum number of drinks per a 24 hour period, the highest LODs were observed on chromosomes 1, 4, and 13 without G×A interaction. Interaction analysis yielded four regions on chromosomes 1, 4, 13, and 15. On chromosome 4, a maximum LOD of 1.5 at the same location as the initial analysis was obtained after incorporating G×A interaction effects. However, after correcting for extra parameters, the LOD score was reduced to a corrected LOD of 1.1, which is similar to the LOD observed in the non-interaction analysis. Thus, we see little differences in LOD scores, while some linkage regions showed large differences in the magnitudes of estimated quantitative trait loci heritabilities between the alcoholic and non-alcoholic groups. These potential hints of differences in genetic effect may influence future analyses of variants under these linkage peaks

Genetic Variation in the Population of Ibiza (Spain): Genetic Structure, Geography, and Language

This is the published version, also available here: http://www.jstor.org/stable/41465529

Heritability of anthropometric phenotypes in caste populations of Visakhapatnam, India

This is the publisher's version, also available electronically from http://digitalcommons.wayne.edu/humbiol/vol74/iss3/1/.In this study, we used anthropometric data from six Andhra caste populations to examine heritability patterns of 23 anthropometric phenotypes (linear, craniofacial, and soft tissue measures) with special reference to caste differences. We obtained anthropometric data from 342 nuclear families from Brahmin, Reddy, Telaga, Nagara, Ag. Kshatriya, and Mala castes of Visakhapatnam, India. These caste groups represent the existing hierarchical stratification of Indian populations. We used a variance components approach to determine the heritability (h2) of these 23 anthropometric phenotypes (height, weight, BMI, etc.). The sample consisted of 1918 individuals ranging in age from 6 to 72 years (mean = 21.5, S.D. = 13.8). The heritabilities (h2 ± S.E.) for all anthropometric traits for the entire sample were significant (p < 0.0001) and varied from 0.25 ± 0.05 (BMI) to 0.61 ± 0.05 (bizygomatic breadth) after accounting for sex, age, and caste effects. Since data on socioeconomic and nutritional covariates were available for a subset of families, we repeated the genetic analyses using this subset, which has yielded higher heritabilities ranging from 0.21 ± 0.16 (head breadth) to 0.72 ± 0.18 (nasal breadth). In general, craniofacial measurements exhibited higher h2 compared to linear measures. Breadth measurements and circumferences yielded more or less similar heritabilities. Age and sex effects were significant (p < 0.0001) for most of the traits, while the effects of caste, socioeconomic status, and nutritional status were inconsistent across the traits. In conclusion, anthropometric phenotypes examined in this study are under appreciable additive genetic influences

Burden of Type 2 Diabetes and Associated Cardiometabolic Traits and Their Heritability Estimates in Endogamous Ethnic Groups of India: Findings From the INDIGENIUS Consortium

To assess the burden of type 2 diabetes (T2D) and its genetic profile in endogamous populations of India given the paucity of data, we aimed to determine the prevalence of T2D and estimate its heritability using family-based cohorts from three distinct Endogamous Ethnic Groups (EEGs) representing Northern (Rajasthan [Agarwals: AG]) and Southern (Tamil Nadu [Chettiars: CH] and Andhra Pradesh [Reddys: RE]) states of India. For comparison, family-based data collected previously from another North Indian Punjabi Sikh (SI) EEG was used. In addition, we examined various T2D-related cardiometabolic traits and determined their heritabilities. These studies were conducted as part of the Indian Diabetes Genetic Studies in collaboration with US (INDIGENIUS) Consortium. The pedigree, demographic, phenotypic, covariate data and samples were collected from the CH, AG, and RE EEGs. The status of T2D was defined by ADA guidelines (fasting glucose ≥ 126 mg/dl or HbA1c ≥ 6.5% and/or use of diabetes medication/history). The prevalence of T2D in CH (N = 517, families = 21, mean age = 47y, mean BMI = 27), AG (N = 530, Families = 25, mean age = 43y, mean BMI = 27), and RE (N = 500, Families = 22, mean age = 46y, mean BMI = 27) was found to be 33%, 37%, and 36%, respectively, Also, the study participants from these EEGs were found to be at increased cardiometabolic risk (e.g., obesity and prediabetes). Similar characteristics for the SI EEG (N = 1,260, Families = 324, Age = 51y, BMI = 27, T2D = 75%) were obtained previously. We used the variance components approach to carry out genetic analyses after adjusting for covariate effects. The heritability (h2) estimates of T2D in the CH, RE, SI, and AG were found to be 30%, 46%, 54%, and 82% respectively, and statistically significant (P ≤ 0.05). Other T2D related traits (e.g., BMI, lipids, blood pressure) in AG, CH, and RE EEGs exhibited strong additive genetic influences (h2 range: 17% [triglycerides/AG and hs-CRP/RE] - 86% [glucose/non-T2D/AG]). Our findings highlight the high burden of T2D in Indian EEGs with significant and differential additive genetic influences on T2D and related traits

Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1–5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (\u3e80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D

Association of HIV-1 Infection and Antiretroviral Therapy With Type 2 Diabetes in the Hispanic Population of the Rio Grande Valley, Texas, USA

The Rio Grande Valley (RGV) in South Texas has one of the highest prevalence of obesity and type 2 diabetes (T2D) in the United States (US). We report for the first time the T2D prevalence in persons with HIV (PWH) in the RGV and the interrelationship between T2D, cardiometabolic risk factors, HIV-related indices, and antiretroviral therapies (ART). The PWH in this study received medical care at Valley AIDS Council (VAC) clinic sites located in Harlingen and McAllen, Texas. Henceforth, this cohort will be referred to as Valley AIDS Council Cohort (VACC). Cross-sectional analyses were conducted using retrospective data obtained from 1,827 registries. It included demographic and anthropometric variables, cardiometabolic traits, and HIV-related virological and immunological indices. For descriptive statistics, we used mean values of the quantitative variables from unbalanced visits across 20 months. Robust regression methods were used to determine the associations. For comparisons, we used cardiometabolic trait data obtained from HIV-uninfected San Antonio Mexican American Family Studies (SAMAFS; N = 2,498), and the Mexican American population in the National Health and Nutrition Examination Survey (HHANES; N = 5,989). The prevalence of T2D in VACC was 51% compared to 27% in SAMAFS and 19% in HHANES, respectively. The PWH with T2D in VACC were younger (4.7 years) and had lower BMI (BMI 2.43 units less) when compared to SAMAFS individuals. In contrast, VACC individuals had increased blood pressure and dyslipidemia. The increased T2D prevalence in VACC was independent of BMI. Within the VACC, ART was associated with viral load and CD4+ T cell counts but not with metabolic dysfunction. Notably, we found that individuals with any INSTI combination had higher T2D risk: OR 2.08 (95%CI 1.67, 2.6; p \u3c 0.001). In summary, our results suggest that VACC individuals may develop T2D at younger ages independent of obesity. The high burden of T2D in these individuals necessitates rigorously designed longitudinal studies to draw potential causal inferences and develop better treatment regimens

Data on genetic associations of carotid atherosclerosis markers in Mexican American and European American rheumatoid arthritis subjects

Carotid Intima-media thickness (CIMT) and plaque are well established markers of subclinical atherosclerosis and are widely used for identifying subclinical atherosclerotic disease. We performed association analyses using Metabochip array to identify genetic variants that influence variation in CIMT and plaque, measured using B-mode ultrasonography, in rheumatoid arthritis (RA) patients. Data on genetic associations of common variants associated with both CIMT and plaque in RA subjects involving Mexican Americans (MA) and European Americans (EA) populations are presented in this article. Strong associations were observed after adjusting for covariate effects including baseline clinical characteristics and statin use. Susceptibility loci and genes and/or nearest genes associated with CIMT in MAs and EAs with RA are presented. In addition, common susceptibility loci influencing CIMT and plaque in both MAs and EAs have been presented. Polygenic Risk Score (PRS) plots showing complementary evidence for the observed CIMT and plaque association signals are also shown in this article. For further interpretation and details, please see the research article titled A Genetic Association Study of Carotid Intima-Media Thickness (CIMT) and Plaque in Mexican Americans and European Americans with Rheumatoid Arthritis which is being published in Atherosclerosis (Arya et al., 2018) [1].(Arya et al., in press) Thus, common variants in several genes exhibited significant associations with CIMT and plaque in both MAs and EAs as presented in this article. These findings may help understand the genetic architecture of subclinical atherosclerosis in RA populations

A genetic association study of carotid intima-media thickness (CIMT) and plaque in Mexican Americans and European Americans with rheumatoid arthritis

Background and aims: Little is known about specific genetic determinants of carotid-intima-media thickness (CIMT) and carotid plaque in subjects with rheumatoid arthritis (RA). We have used the Metabochip array to fine map and replicate loci that influence variation in these phenotypes in Mexican Americans (MAs) and European Americans (EAs). Methods: CIMT and plaque were measured using ultrasound from 700 MA and 415 EA patients with RA and we conducted association analyses with the Metabochip single nucleotide polymorphism (SNP) data using PLINK. Results: In MAs, 12 SNPs from 11 chromosomes and 6 SNPs from 6 chromosomes showed suggestive associations (p \u3c 1 × 10-4) with CIMT and plaque, respectively. The strongest association was observed between CIMT and rs17526722 (SLC17A2 gene) (β ± SE = -0.84 ± 0.18, p = 3.80 × 10-6). In EAs, 9 SNPs from 7 chromosomes and 7 SNPs from 7 chromosomes showed suggestive associations with CIMT and plaque, respectively. The top association for CIMT was observed with rs1867148 (PPCDC gene, β ± SE = -0.28 ± 0.06, p = 5.11 × 10-6). We also observed strong association between plaque and two novel loci: rs496916 from COL4A1 gene (OR = 0.51, p = 3.15 × 10-6) in MAs and rs515291 from SLCA13 gene (OR = 0.50, p = 3.09 × 10-5) in EAs. Conclusions: We identified novel associations between CIMT and variants in SLC17A2 and PPCDC genes, and between plaque and variants from COL4A1 and SLCA13 that may pinpoint new candidate risk loci for subclinical atherosclerosis associated with RA