Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.
Data availabilitySummary statistics generated by COVID-19 Host Genetics Initiative are available online (https://www.covid19hg.org/results/r6/). The analyses described here use the freeze 6 data. The COVID-19 Host Genetics Initiative continues to regularly release new data freezes. Summary statistics for samples from individuals of non-European ancestry are not currently available owing to the small individual sample sizes of these groups, but the results for 23 loci lead variants are reported in Supplementary Table 3. Individual-level data can be requested directly from the authors of the contributing studies, listed in Supplementary Table 1.
Pediatric metabolic syndrome (MS) and its cardiometabolic components (MSCs) have become increasingly prevalent, yet little is known about the genetics underlying MS risk in children. We examined the prevalence and genetics of MS-related traits among 670 non-diabetic Mexican American (MA) children and adolescents, aged 6–17 years (49 % female), who were participants in the San Antonio Family Assessment of Metabolic Risk Indicators in Youth (SAFARI) study. These children are offspring or biological relatives of adult participants from three well-established Mexican American family studies in San Antonio, Texas, at increased risk of type 2 diabetes. MS was defined as ≥ 3 abnormalities among 6 MSC measures: waist circumference, systolic and/or diastolic blood pressure, fasting insulin, triglycerides, HDL-cholesterol, and fasting and/or 2-h OGTT glucose. Genetic analyses of MS, number of MSCs (MSC-N), MS factors, and bivariate MS traits were performed. Overweight/obesity (53 %), pre-diabetes (13 %), acanthosis nigricans (33 %), and MS (19 %) were strikingly prevalent, as were MS components, including abdominal adiposity (32 %) and low HDL-cholesterol (32 %). Factor analysis of MS traits yielded three constructs: adipo-insulin-lipid, blood pressure, and glucose factors, and their factor scores were highly heritable. MS itself exhibited 68 % heritability. MSC-N showed strong positive genetic correlations with obesity, insulin resistance, inflammation, and acanthosis nigricans, and negative genetic correlation with physical fitness. MS trait pairs exhibited strong genetic and/or environmental correlations. These findings highlight the complex genetic architecture of MS/MSCs in MA children, and underscore the need for early screening and intervention to prevent chronic sequelae in this vulnerable pediatric population.
Type 2 diabetes (T2D) is a complex metabolic disease that is more prevalent in ethnic groups such as Mexican Americans, and is strongly associated with the risk factors obesity and insulin resistance. The goal of this study was to perform whole genome gene expression profiling in adipose tissue to detect common patterns of gene regulation associated with obesity and insulin resistance. We used phenotypic and genotypic data from 308 Mexican American participants from the Veterans Administration Genetic Epidemiology Study (VAGES). Basal fasting RNA was extracted from adipose tissue biopsies from a subset of 75 unrelated individuals, and gene expression data generated on the Illumina BeadArray platform. The number of gene probes with significant expression above baseline was approximately 31,000. We performed multiple regression analysis of all probes with 15 metabolic traits. Adipose tissue had 3,012 genes significantly associated with the traits of interest (false discovery rate, FDR ≤ 0.05). The significance of gene expression changes was used to select 52 genes with significant (FDR ≤ 10-4) gene expression changes across multiple traits. Gene sets/Pathways analysis identified one gene, alcohol dehydrogenase 1B (ADH1B) that was significantly enriched (P < 10-60) as a prime candidate for involvement in multiple relevant metabolic pathways. Illumina BeadChip derived ADH1B expression data was consistent with quantitative real time PCR data. We observed significant inverse correlations with waist circumference (2.8 x 10-9), BMI (5.4 x 10-6), and fasting plasma insulin (P < 0.001). These findings are consistent with a central role for ADH1B in obesity and insulin resistance and provide evidence for a novel genetic regulatory mechanism for human metabolic diseases related to these traits.
Aims Although newer approaches have identified several metabolites associated with obesity, there is paucity of such information in pediatric populations, especially among Mexican Americans (MAs) who are at high risk of obesity. Therefore, we performed a global serum metabolite screening in MA children to identify biomarkers of childhood obesity. Materials and methods We selected 15 normal-weight, 13 overweight and 14 obese MA children (6–17 years), and performed global serum metabolite screening using UPLC system with Q-Tof-Micromass-spectrometer. Metabolite values were analyzed to assess mean differences among groups using one-way ANOVA, test for linear trend across groups, and examine Pearson’s correlations between them and seven cardiometabolic traits (CMTs): body mass index (BMI), waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), insulin resistance (HOMA-IR), triglycerides (TG), and HDL-cholesterol (HDL-C). Results We identified 14 metabolites exhibiting differences between groups as well as linear trend across groups with nominal statistical significance. After adjustment for multiple testing mean differences and linear trends across groups remained significant (P < 5.9 × 10−5) for L-thyronine, bradykinin, and naringenin. Of the examined metabolite-CMT trait pairs, all metabolites except for 2-methylbutyroylcarnitine were nominally associated with two or more CMTs, some exhibiting significance even after accounting for multiple testing(P < 3.6 × 10−3). Conclusions To our knowledge, this study - albeit pilot in nature - is the first study to identify these metabolites as novel biomarkers of childhood obesity and its correlates. These findings signify the need for future systematic investigations of metabolic pathways underlying childhood obesity.
Background: Dietary intake of phytonutrients present in fruits and vegetables, such as carotenoids, is associated with a lower risk of obesity and related traits, but the impact of genetic variation on these associations is poorly understood, especially in children. Objective: We estimated common genetic influences on serum carotenoid concentrations and obesity-related traits in Mexican American (MA) children. Design: Obesity-related data were obtained from 670 nondiabetic MA children, aged 6-17 y. Serum a-and b-carotenoid concentrations were measured in w570 (a-carotene in 565 and b-carotene in 572) of these children with the use of an ultraperformance liquid chromatography-photodiode array. We determined heritabilities for both carotenoids and examined their genetic relation with 10 obesity-related traits [body mass index (BMI), waist circumference (WC), high-density lipoprotein (HDL) cholesterol, triglycerides, fat mass (FM), systolic and diastolic blood pressure, fasting insulin and glucose, and homeostasis model assessment of insulin resistance] by using family data and a variance components approach. For these analyses, carotenoid values were inverse normalized, and all traits were adjusted for significant covariate effects of age and sex. Results: Carotenoid concentrations were highly heritable and significant [a-carotene: heritability (h 2 ) = 0.81, P = 6.7 3 10 211 ; b-carotene: h 2 = 0.90, P = 3.5 3 10 215 ]. After adjusting for multiple comparisons, we found significant (P # 0.05) negative phenotypic correlations between carotenoid concentrations and the following traits: BMI, WC, FM, and triglycerides (range: a-carotene = 20.19 to 20.12; b-carotene = 20.24 to 20.13) and positive correlations with HDL cholesterol (a-carotene = 0.17; b-carotene = 0.24). However, when the phenotypic correlations were partitioned into genetic and environmental correlations, we found marginally significant (P = 0.051) genetic correlations only between b-carotene and BMI (20.27), WC (20.30), and HDL cholesterol (0.31) after accounting for multiple comparisons. None of the environmental correlations were significant. Conclusions: The findings from this study suggest that the serum carotenoid concentrations were under strong additive genetic influences based on variance components analyses, and that the common genetic factors may influence b-carotene and obesity and lipid traits in MA children. Am J Clin Nutr 2017;106:52-8.
Background/Aims: The increased occurrence of type 2 diabetes and its clinical correlates is a global public health issue, and there are continued efforts to find its genetic determinant across ethnically diverse populations. The aims of this study were to determine the heritability of diabetes and metabolic syndrome phenotypes in the Arizona Insulin Resistance (AIR) registry and to perform an association analysis of common single nucleotide polymorphisms (SNPs) identified by GWAS with these traits. All study participants were Mexican Americans from the AIR registry. Methods: Metabolic, anthropometric, demographic and medical history information was obtained on the 667 individuals enrolled in the registry. Results: The heritability estimates were moderate to high in magnitude and significant, indicating that the AIR registry is well suited for the identification of genetic factors contributing to diabetes and the metabolic syndrome. From the 30 GWAS genes selected (some genes were represented by multiple SNPs), 20 SNPs exhibited associations with one or more of the diabetes related traits with nominal significance (p ≤ 0.05). In addition, 25 SNPs were nominally significantly associated with one or more of the metabolic phenotypes tested (p ≤ 0.05). Most notably, 5 SNPs from 5 genes [body mass index (BMI), hip circumference: rs3751812/FTO; fasting plasma glucose, hemoglobin A1c: rs4607517/GCK; very-low-density lipoprotein: rs10830963/MTNR1B; BMI: rs13266634/SLC30A8, and total cholesterol, low-density lipoprotein: rs7578597/THADA] were significantly associated with obesity, glycemic, and lipid phenotypes when using the multiple testing significance threshold of 0.0015. Conclusion: These findings extend previous work on Mexican Americans to suggest that metabolic disease is strongly influenced by genetic background in this high-risk population.
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