Methylation of SOCS3 is inversely associated with metabolic syndrome in an epigenome-wide association study of obesity

Epigenetic mechanisms, including DNA methylation, mediate the interaction between gene and environment and may play an important role in the obesity epidemic. We assessed the relationship between DNA methylation and obesity in peripheral blood mononuclear cells (PBMCs) at 485,000 CpG sites across the genome in family members (8-90 y of age) using a discovery cohort (192 individuals) and a validation cohort (1,052 individuals) of Northern European ancestry. After Bonferroni-correction (Pα=0.05 = 1.31 × 10-7) for genome-wide significance, we identified 3 loci, cg18181703 (SOCS3), cg04502490 (ZNF771), and cg02988947 (LIMD2), where methylation status was associated with body mass index percentile (BMI%), a clinical index for obesity in children, adolescents, and adults. These sites were also associated with multiple metabolic syndrome (MetS) traits, including central obesity, fat depots, insulin responsiveness, and plasma lipids. The SOCS3 methylation locus was also associated with the clinical definition of MetS. In the validation cohort, SOCS3 methylation status was found to be inversely associated with BMI% (P = 1.75 × 10-6), waist to height ratio (P = 4.18 × 10-7), triglycerides (P = 4.01 × 10-4), and MetS (P = 4.01 × 10-7), and positively correlated with HDL-c (P = 4.57 × 10-8). Functional analysis in a sub cohort (333 individuals) demonstrated SOCS3 methylation and gene expression in PBMCs were inversely correlated (P = 2.93 × 10-4) and expression of SOCS3 was positively correlated with status of MetS (P = 0.012). We conclude that epigenetic modulation of SOCS3, a gene involved in leptin and insulin signaling, may play an important role in obesity and MetS

Genetic Variants Related to Cardiometabolic Traits Are Associated to B Cell Function, Insulin Resistance, and Diabetes Among AmeriCan Indians: The Strong Heart Family Study

Background: Genetic research may inform underlying mechanisms for disparities in the burden of type 2 diabetes mellitus among American Indians. Our objective was to assess the association of genetic variants in cardiometabolic candidate genes with B cell dysfunction via HOMA-B, insulin resistance via HOMA-IR, and type 2 diabetes mellitus in the Strong Heart Family Study (SHFS). Methods and Results: We examined the association of variants, previously associated with cardiometabolic traits (∼200,000 from Illumina Cardio MetaboChip), using mixed models of HOMA-B residuals corrected for HOMA-IR (cHOMA-B), log transformed HOMA-IR, and incident diabetes, adjusted for age, sex, population stratification, and familial relatedness. Center-specific estimates were combined using fixed effect meta-analyses. We used Bonferroni correction to account for multiple testing (P \u3c 4.13 × 10−7). We also assessed the association between variants in candidate diabetes genes with these metabolic traits. We explored the top SNPs in an independent, replication sample from Southwestern Arizona. We identified significant associations with cHOMA-B for common variants at 26 loci of which 8 were novel (PRSS7, FCRL5, PEL1, LRP12, IGLL1, ARHGEF10, PARVA, FLJ16686). The most significant variant association with cHOMA-B was observed on chromosome 5 for an intergenic variant near PARP8 (rs2961831, P = 6.39 × 10−9). In the replication study, we found a signal at rs4607517 near GCK/YKT6 (P = 0.01). Variants near candidate diabetes genes (especially GCK and KCNQ1) were also nominally associated with HOMA-IR and cHOMA-B. Conclusion: We identified variants at novel loci and confirmed those at known candidate diabetes loci associations for cHOMA-B. This study also provided evidence for association of variants at KCNQ2, CTNAA2, and KCNQ1with cHOMA-B among American Indians. Further studies are needed to account for the high heritability of diabetes among the American Indian participants of the SHFS cohort

Independent test assessment using the extreme value distribution theory

The new generation of whole genome sequencing platforms offers great possibilities and challenges for dissecting the genetic basis of complex traits. With a very high number of sequence variants, a naïve multiple hypothesis threshold correction hinders the identification of reliable associations by the overreduction of statistical power. In this report, we examine 2 alternative approaches to improve the statistical power of a whole genome association study to detect reliable genetic associations. The approaches were tested using the Genetic Analysis Workshop 19 (GAW19) whole genome sequencing data. The first tested method estimates the real number of effective independent tests actually being performed in whole genome association project by the use of an extreme value distribution and a set of phenotype simulations. Given the familiar nature of the GAW19 data and the finite number of pedigree founders in the sample, the number of correlations between genotypes is greater than in a set of unrelated samples. Using our procedure, we estimate that the effective number represents only 15 % of the total number of independent tests performed. However, even using this corrected significance threshold, no genome-wide significant association could be detected for systolic and diastolic blood pressure traits. The second approach implements a biological relevance-driven hypothesis tested by exploiting prior computational predictions on the effect of nonsynonymous genetic variants detected in a whole genome sequencing association study. This guided testing approach was able to identify 2 promising single-nucleotide polymorphisms (SNPs), 1 for each trait, targeting biologically relevant genes that could help shed light on the genesis of the human hypertension. The first gene, PFH14, associated with systolic blood pressure, interacts directly with genes involved in calcium-channel formation and the second gene, MAP4, encodes a microtubule-associated protein and had already been detected by previous genome-wide association study experiments conducted in an Asian population. Our results highlight the necessity of the development of alternative approached to improve the efficiency on the detection of reasonable candidate associations in whole genome sequencing studies

The genetic basis of the comorbidity between cannabis use and major depression

Background and aims—While the prevalence of major depression is elevated amongst cannabis users, the role of genetics in this pattern of comorbidity is not clear. This study aimed to estimate the heritability of cannabis use and major depression, quantify the genetic overlap between these two traits, and localize regions of the genome that segregate in families with cannabis use and major depression. Design—Family-based univariate and bivariate genetic analysis. Setting—San Antonio, Texas, USA Participants—Genetics of Brain Structure and Function study (GOBS) participants: 1,284 Mexican-Americans from 75 large multi-generation families and an additional 57 genetically unrelated spouses. Measurements—Phenotypes of lifetime history of cannabis use and major depression, measured using the semi-structured MINI-Plus interview. Genotypes measured using ~1M single nucleotide polymorphisms (SNPs) on Illumina BeadChips. A sub-selection of these SNPs were used to build multipoint identity-by-descent matrices for linkage analysis. Findings—Both cannabis use (h2=0.614, p=1.00×10−6, SE=0.151) and major depression (h2=0.349, p=1.06×10−5, SE=0.100) are heritable traits, and there is significant genetic correlation between the two (ρg=0.424, p=0.0364, SE=0.195). Genome-wide linkage scans identify a significant univariate linkage peak for major depression on chromosome 22 (LOD=3.144 at 2cM), with a suggestive peak for cannabis use on chromosome 21 (LOD=2.123 at 37cM). A significant pleiotropic linkage peak influencing both cannabis use and major depression was identified on chromosome 11, using a bivariate model (LOD=3.229 at 112cM). Follow-up of this pleiotropic signal identified a SNP 20kb upstream of NCAM1 (rs7932341) that shows significant bivariate association (p=3.10×10−5). However this SNP is rare (7 minor allele carriers) and does not drive the linkage signal observed. Conclusions—There appears to be significant genetic overlap between cannabis use and major depression among Mexican-Americans, a pleiotropy that appears to be localized to a region on chromosome 11q23 that has been previously linked to these phenotypes

Genome-wide significant loci for addiction and anxiety

Background Psychiatric comorbidity is common among individuals with addictive disorders, with patients frequently suffering from anxiety disorders. While the genetic architecture of comorbid addictive and anxiety disorders remains unclear, elucidating the genes involved could provide important insights into the underlying etiology. Methods Here we examine a sample of 1284 Mexican-Americans from randomly selected extended pedigrees. Variance decomposition methods were used to examine the role of genetics in addiction phenotypes (lifetime history of alcohol dependence, drug dependence or chronic smoking) and various forms of clinically relevant anxiety. Genome-wide univariate and bivariate linkage scans were conducted to localize the chromosomal regions influencing these traits. Results Addiction phenotypes and anxiety were shown to be heritable and univariate genome-wide linkage scans revealed significant quantitative trait loci for drug dependence (14q13.2-q21.2, LOD = 3.322) and a broad anxiety phenotype (12q24.32-q24.33, LOD = 2.918). Significant positive genetic correlations were observed between anxiety and each of the addiction subtypes (ρg = 0.550–0.655) and further investigation with bivariate linkage analyses identified significant pleiotropic signals for alcohol dependence-anxiety (9q33.1-q33.2, LOD = 3.054) and drug dependence-anxiety (18p11.23-p11.22, LOD = 3.425). Conclusions This study confirms the shared genetic underpinnings of addiction and anxiety and identifies genomic loci involved in the etiology of these comorbid disorders. The linkage signal for anxiety on 12q24 spans the location of TMEM132D, an emerging gene of interest from previous GWAS of anxiety traits, whilst the bivariate linkage signal identified for anxiety-alcohol on 9q33 peak coincides with a region where rare CNVs have been associated with psychiatric disorders. Other signals identified implicate novel regions of the genome in addiction genetics

High dimensional endophenotype ranking in the search for major depression risk genes.

BACKGROUND: Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here, we describe the endophenotype ranking value, a new objective index of the genetic utility of endophenotypes for any heritable illness. METHODS: Applying endophenotype ranking value analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individuals (n = 1122) from large randomly selected extended pedigrees. RESULTS: Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume, and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (logarithm of odds = 3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk. CONCLUSIONS: The wider use of quantitative endophenotypes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression

GWAS and transcriptional analysis prioritize ITPR1 and CNTN4 for a serum uric acid 3p26 QTL in Mexican Americans

Background: The variation in serum uric acid concentrations is under significant genetic influence. Elevated SUA concentrations have been linked to increased risk for gout, kidney stones, chronic kidney disease, and cardiovascular disease whereas reduced serum uric acid concentrations have been linked to multiple sclerosis, Parkinson’s disease and Alzheimer’s disease. Previously, we identified a novel locus on chromosome 3p26 affecting serum uric acid concentrations in Mexican Americans from San Antonio Family Heart Study. As a follow up, we examined genome-wide single nucleotide polymorphism data in an extended cohort of 1281 Mexican Americans from multigenerational families of the San Antonio Family Heart Study and the San Antonio Family Diabetes/ Gallbladder Study. We used a linear regression-based joint linkage/association test under an additive model of allelic effect, while accounting for non-independence among family members via a kinship variance component. Results:Univariate genetic analysis indicated serum uric acid concentrations to be significant heritable (h2 = 0.50 ± 0.05, p Conclusion: Our results confirm the importance of the chromosome 3p26 locus and genetic variants in this region in the regulation of serum uric acid concentrations

Genome-wide Linkage on Chromosome 10q26 for a Dimensional Scale of Major Depression

Major depressive disorder (MDD) is a common and potentially life-threatening mood disorder. Identifying genetic markers for depression might provide reliable indicators of depression risk, which would, in turn, substantially improve detection, enabling earlier and more effective treatment. The aim of this study was to identify rare variants for depression, modeled as a continuous trait, using linkage and post-hoc association analysis. The sample comprised 1221 Mexican–American individuals from extended pedigrees. A single dimensional scale of MDD was derived using confirmatory factor analysis applied to all items from the Past Major Depressive Episode section of the Mini-International Neuropsychiatric Interview. Scores on this scale of depression were subjected to linkage analysis followed by QTL region-specific association analysis. Linkage analysis revealed a single genome-wide significant QTL (LOD=3.43) on 10q26.13, QTL-specific association analysis conducted in the entire sample revealed a suggestive variant within an intron of the gene LHPP (rs11245316, p=7.8×10−04; LD-adjusted Bonferroni-corrected p=8.6×10−05). This region of the genome has previously been implicated in the etiology of MDD; the present study extends our understanding of the involvement of this region by highlighting a putative gene of interest (LHPP)

Genetic variant rs1205 is associated with COVID-19 outcomes: The Strong Heart Study and Strong Heart Family Study

Background Although COVID-19 infection has been associated with a number of clinical and environmental risk factors, host genetic variation has also been associated with the incidence and morbidity of infection. The CRP gene codes for a critical component of the innate immune system and CRP variants have been reported associated with infectious disease and vaccination outcomes. We investigated possible associations between COVID-19 outcome and a limited number of candidate gene variants including rs1205. Methodology/Principal findings The Strong Heart and Strong Heart Family studies have accumulated detailed genetic, cardiovascular risk and event data in geographically dispersed American Indian communities since 1988. Genotypic data and 91 COVID-19 adjudicated deaths or hospitalizations from 2/1/20 through 3/1/23 were identified among 3,780 participants in two subsets. Among 21 candidate variants including genes in the interferon response pathway, APOE, TMPRSS2, TLR3, the HLA complex and the ABO blood group, only rs1205, a 3’ untranslated region variant in the CRP gene, showed nominally significant association in T-dominant model analyses (odds ratio 1.859, 95%CI 1.001–3.453, p = 0.049) after adjustment for age, sex, center, body mass index, and a history of cardiovascular disease. Within the younger subset, association with the rs1205 T-Dom genotype was stronger, both in the same adjusted logistic model and in the SOLAR analysis also adjusting for other genetic relatedness. Conclusion A T-dominant genotype of rs1205 in the CRP gene is associated with COVID-19 death or hospitalization, even after adjustment for relevant clinical factors and potential participant relatedness. Additional study of other populations and genetic variants of this gene are warranted

Transcriptoma en mexicanos: metodología para analizar el perfil de expresión genética de gran escala en muestras simultáneas de tejido muscular, adiposo y linfocitos obtenidas en un mismo individuo

Describir la metodología de análisis de múltiples trasncritos con técnicas de microarreglo en biopsisas simultáneas de tejido muscular, adiposo y sangre en un mismo individuo, como parte de la estandarización del estudio GEMM (Genética de las enfermedades Metabólicas en México