A Robust Model-free Approach for Rare Variants Association Studies Incorporating Gene-Gene and Gene-Environmental Interactions

Recently more and more evidence suggest that rare variants with much lower minor allele frequencies play significant roles in disease etiology. Advances in next-generation sequencing technologies will lead to many more rare variants association studies. Several statistical methods have been proposed to assess the effect of rare variants by aggregating information from multiple loci across a genetic region and testing the association between the phenotype and aggregated genotype. One limitation of existing methods is that they only look into the marginal effects of rare variants but do not systematically take into account effects due to interactions among rare variants and between rare variants and environmental factors. In this article, we propose the summation of partition approach (SPA), a robust model-free method that is designed specifically for detecting both marginal effects and effects due to gene-gene (G×G) and gene-environmental (G×E) interactions for rare variants association studies. SPA has three advantages. First, it accounts for the interaction information and gains considerable power in the presence of unknown and complicated G×G or G×E interactions. Secondly, it does not sacrifice the marginal detection power; in the situation when rare variants only have marginal effects it is comparable with the most competitive method in current literature. Thirdly, it is easy to extend and can incorporate more complex interactions; other practitioners and scientists can tailor the procedure to fit their own study friendly. Our simulation studies show that SPA is considerably more powerful than many existing methods in the presence of G×G and G×E interactions.     

Meta-analysis of Correlated Traits via Summary Statistics from GWASs with an Application in Hypertension

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple—even distinct—traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10⁻⁸) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10⁻⁷) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes.     

A common variant highly associated with plasma VEGFA levels also contributes to the variation of both LDL-C and HDL-C

Vascular endothelial growth factor A (VEGFA) is among the most-significant stimulators of angiogenesis. Its effect on cardiovascular diseases and on the variation of related risk factors such as lipid parameters is considered important, although as yet unclear. Recently, we identified four common variants (rs6921438, rs4416670, rs6993770, and rs10738760) that explain up to 50% of the heritability of plasma VEGFA levels. In the present study, we aimed at assessing the contribution of these variants to the variation of blood lipid levels (including apoE, triglycerides, total cholesterol, low- and high-density lipoprotein cholesterol levels (LDL-C and HDL-C)] in healthy subjects. The effect of these single-nucleotide polymorphisms (SNPs) on lipid levels was assessed using linear regression in discovery and replication samples (n = 1,006 and n = 1,145; respectively), followed by a meta-analysis. Their gene×gene and gene×environment interactions were also assessed. SNP rs6921438 was associated with HDL-C (β = −0.08 mmol/l, P_overall = 1.2 × 10⁻⁷) and LDL-C (β = 0.13 mmol/l, P_overall = 1.5 × 10⁻⁴). We also identified a significant association between the interaction rs4416670×hypertension and apoE variation (P_overall = 1.7 × 10⁻⁵). Therefore, our present study shows a common genetic regulation between VEGFA and cholesterol homeostasis molecules. The SNP rs6921438 is in linkage disequilibrium with variants located in an enhancer- and promoter-associated histone mark region and could have a regulatory effect in the expression of surrounding genes, including VEGFA.     

Adiposity significantly modifies genetic risk for dyslipidemia

Recent genome-wide association studies have identified multiple loci robustly associated with plasma lipids, which also contribute to extreme lipid phenotypes. However, these common genetic variants explain <12% of variation in lipid traits. Adiposity is also an important determinant of plasma lipoproteins, particularly plasma TGs and HDL cholesterol (HDLc) concentrations. Thus, interactions between genes and clinical phenotypes may contribute to this unexplained heritability. We have applied a weighted genetic risk score (GRS) for both plasma TGs and HDLc in two large cohorts at the extremes of BMI. Both BMI and GRS were strongly associated with these lipid traits. A significant interaction between obese/lean status and GRS was noted for each of TG (P_Interaction = 2.87 × 10⁻⁴) and HDLc (P_Interaction = 1.05 × 10⁻³). These interactions were largely driven by SNPs tagging APOA5, glucokinase receptor (GCKR), and LPL for TG, and cholesteryl ester transfer protein (CETP), GalNAc-transferase (GALNT2), endothelial lipase (LIPG), and phospholipid transfer protein (PLTP) for HDLc. In contrast, the GRS_{LDL cholesterol} × adiposity interaction was not significant. Sexual dimorphism was evident for the GRS_HDL on HDLc in obese (P_Interaction = 0.016) but not lean subjects. SNP by BMI interactions may provide biological insight into specific genetic associations and missing heritability.     

Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models

Twin studies have been adopted for decades to disentangle the relative genetic and environmental contributions for a wide range of traits. However, heritability estimation based on the classical twin models does not take into account dynamic behavior of the variance components over age. Varying variance of the genetic component over age can imply the existence of gene–environment (G × E) interactions that general genome-wide association studies (GWAS) fail to capture, which may lead to the inconsistency of heritability estimates between twin design and GWAS. Existing parametric G × E interaction models for twin studies are limited by assuming a linear or quadratic form of the variance curves with respect to a moderator that can, however, be overly restricted in reality. Here we propose spline-based approaches to explore the variance curves of the genetic and environmental components. We choose the additive genetic, common, and unique environmental variance components (ACE) model as the starting point. We treat the component variances as variance functions with respect to age modeled by B-splines or P-splines. We develop an empirical Bayes method to estimate the variance curves together with their confidence bands and provide an R package for public use. Our simulations demonstrate that the proposed methods accurately capture dynamic behavior of the component variances in terms of mean square errors with a data set of >10,000 twin pairs. Using the proposed methods as an alternative and major extension to the classical twin models, our analyses with a large-scale Finnish twin data set (19,510 MZ twins and 27,312 DZ same-sex twins) discover that the variances of the A, C, and E components for body mass index (BMI) change substantially across life span in different patterns and the heritability of BMI drops to ∼50% after middle age. The results further indicate that the decline of heritability is due to increasing unique environmental variance, which provides more insights into age-specific heritability of BMI and evidence of G × E interactions. These findings highlight the fundamental importance and implication of the proposed models in facilitating twin studies to investigate the heritability specific to age and other modifying factors.     

Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits

The obesity epidemic is responsible for a substantial economic burden in developed countries and is a major risk factor for type 2 diabetes and cardiovascular disease. The disease is the result not only of several environmental risk factors, but also of genetic predisposition. To take advantage of recent advances in gene-mapping technology, we executed a genome-wide association scan to identify genetic variants associated with obesity-related quantitative traits in the genetically isolated population of Sardinia. Initial analysis suggested that several SNPs in the FTO and PFKP genes were associated with increased BMI, hip circumference, and weight. Within the FTO gene, rs9930506 showed the strongest association with BMI (p = 8.6 ×10⁻⁷), hip circumference (p = 3.4 × 10⁻⁸), and weight (p = 9.1 × 10⁻⁷). In Sardinia, homozygotes for the rare “G” allele of this SNP (minor allele frequency = 0.46) were 1.3 BMI units heavier than homozygotes for the common “A” allele. Within the PFKP gene, rs6602024 showed very strong association with BMI (p = 4.9 × 10⁻⁶). Homozygotes for the rare “A” allele of this SNP (minor allele frequency = 0.12) were 1.8 BMI units heavier than homozygotes for the common “G” allele. To replicate our findings, we genotyped these two SNPs in the GenNet study. In European Americans (N = 1,496) and in Hispanic Americans (N = 839), we replicated significant association between rs9930506 in the FTO gene and BMI (p-value for meta-analysis of European American and Hispanic American follow-up samples, p = 0.001), weight (p = 0.001), and hip circumference (p = 0.0005). We did not replicate association between rs6602024 and obesity-related traits in the GenNet sample, although we found that in European Americans, Hispanic Americans, and African Americans, homozygotes for the rare “A” allele were, on average, 1.0–3.0 BMI units heavier than homozygotes for the more common “G” allele. In summary, we have completed a whole genome–association scan for three obesity-related quantitative traits and report that common genetic variants in the FTO gene are associated with substantial changes in BMI, hip circumference, and body weight. These changes could have a significant impact on the risk of obesity-related morbidity in the general population.     

Inherited genetic variants associated with glucocorticoid sensitivity in leukaemia cells

Identification of genetic variants associated with glucocorticoids (GC) sensitivity of leukaemia cells may provide insight into potential drug targets and tailored therapy. In the present study, within 72 leukaemic cell lines derived from Japanese patients with B‐cell precursor acute lymphoblastic leukaemia (ALL), we conducted genome‐wide genotyping of single nucleotide polymorphisms (SNP) and attempted to identify genetic variants associated with GC sensitivity and NR3C1 (GC receptor) gene expression. IC50 measures for prednisolone (Pred) and dexamethasone (Dex) were available using an alamarBlue cell viability assay. IC50 values of Pred showed the strongest association with rs904419 (P = 4.34 × 10⁻⁸), located between the FRMD4B and MITF genes. The median IC50 values of prednisolone for cell lines with rs904419 AA (n = 13), AG (n = 31) and GG (n = 28) genotypes were 0.089, 0.139 and 297 µmol/L, respectively. For dexamethasone sensitivity, suggestive association was observed for SNP rs2306888 (P = 1.43 × 10⁻⁶), a synonymous SNP of the TGFBR3 gene. For NR3C1 gene expression, suggestive association was observed for SNP rs11982167 (P = 6.44 × 10⁻⁸), located in the PLEKHA8 gene. These genetic variants may affect GC sensitivity of ALL cells and may give rise to opportunities in personalized medicine for effective and safe chemotherapy in ALL patients.     

Identification of Multiple Genetic Susceptibility Loci in Takayasu Arteritis

Takayasu arteritis is a rare inflammatory disease of large arteries. The etiology of Takayasu arteritis remains poorly understood, but genetic contribution to the disease pathogenesis is supported by the genetic association with HLA-B^∗52. We genotyped ∼200,000 genetic variants in two ethnically divergent Takayasu arteritis cohorts from Turkey and North America by using a custom-designed genotyping platform (Immunochip). Additional genetic variants and the classical HLA alleles were imputed and analyzed. We identified and confirmed two independent susceptibility loci within the HLA region (r² < 0.2): HLA-B/MICA (rs12524487, OR = 3.29, p = 5.57 × 10⁻¹⁶) and HLA-DQB1/HLA-DRB1 (rs113452171, OR = 2.34, p = 3.74 × 10⁻⁹; and rs189754752, OR = 2.47, p = 4.22 × 10⁻⁹). In addition, we identified and confirmed a genetic association between Takayasu arteritis and the FCGR2A/FCGR3A locus on chromosome 1 (rs10919543, OR = 1.81, p = 5.89 × 10⁻¹²). The risk allele in this locus results in increased mRNA expression of FCGR2A. We also established the genetic association between IL12B and Takayasu arteritis (rs56167332, OR = 1.54, p = 2.18 × 10⁻⁸).     

Replication of 6 Obesity Genes in a Meta-Analysis of Genome-Wide Association Studies from Diverse Ancestries

Obesity is a major public health problem with a significant genetic component. Multiple DNA polymorphisms/genes have been shown to be strongly associated with obesity, typically in populations of European descent. The aim of this study was to verify the extent to which 6 confirmed obesity genes (FTO, CTNNBL1, ADRB2, LEPR, PPARG and UCP2 genes) could be replicated in 8 different samples (n = 11,161) and to explore whether the same genes contribute to obesity-susceptibility in populations of different ancestries (five Caucasian, one Chinese, one African-American and one Hispanic population). GWAS-based data sets with 1000 G imputed variants were tested for association with obesity phenotypes individually in each population, and subsequently combined in a meta-analysis. Multiple variants at the FTO locus showed significant associations with BMI, fat mass (FM) and percentage of body fat (PBF) in meta-analysis. The strongest association was detected at rs7185735 (P-value = 1.01×10⁻⁷ for BMI, 1.80×10⁻⁶ for FM, and 5.29×10⁻⁴ for PBF). Variants at the CTNNBL1, LEPR and PPARG loci demonstrated nominal association with obesity phenotypes (meta-analysis P-values ranging from 1.15×10⁻³ to 4.94×10⁻²). There was no evidence of association with variants at ADRB2 and UCP2 genes. When stratified by sex and ethnicity, FTO variants showed sex-specific and ethnic-specific effects on obesity traits. Thus, it is likely that FTO has an important role in the sex- and ethnic-specific risk of obesity. Our data confirmed the role of FTO, CTNNBL1, LEPR and PPARG in obesity predisposition. These findings enhanced our knowledge of genetic associations between these genes and obesity-related phenotypes, and provided further justification for pursuing functional studies of these genes in the pathophysiology of obesity. Sex and ethnic differences in genetic susceptibility across populations of diverse ancestries may contribute to a more targeted prevention and customized treatment of obesity.     

Genetic Variation in the 3'-Untranslated Region of NBN Gene Is Associated with Gastric Cancer Risk in a Chinese Population

NBN plays a crucial role in carcinogenesis as a core component for both homologous recombination (HR) and non-homologous end-joining (NHEJ) DNA double-strand breaks (DSBs) repair pathways. Genetic variants in the NBN gene have been associated with multiple cancers risk, suggesting pleiotropic effect on cancer. We hypothesized that genetic variants in the NBN gene may modify the risk of gastric cancer. To test this hypothesis, we evaluated the association between four potentially functional single nucleotide polymorphisms in NBN and gastric cancer risk in a case–control study of 1,140 gastric cancer cases and 1,547 controls in a Chinese population. We found that the A allele of rs10464867 (G>A) was significantly associated with a decreased risk of gastric cancer (odds ratio [OR] = 0.81, 95% confidence interval [95% CI] = 0.71–0.94; P = 4.71×10⁻³). Furthermore, the association between A allele of rs10464867 and decreased risk of gastric cancer was more significantly in elder individuals (per-allele OR = 0.72[0.59–0.88], P = 1.07×10⁻³), and male individuals (per-allele OR = 0.73[0.62–0.87], P = 3.68×10⁻⁴). We further conducted a haplotype analysis and identified that the NBN A_rs10464867G_rs14448G_rs1063053 haplotype conferred stronger protective effect on gastric cancer (OR = 0.76[0.65–0.89], P = 6.39×10⁻⁴). In summary, these findings indicate that genetic variants at NBN gene may contribute to gastric cancer susceptibility and may further advance our understanding of NBN gene in cancer development.     

Imputation of Exome Sequence Variants into Population- Based Samples and Blood-Cell-Trait-Associated Loci in African Americans: NHLBI GO Exome Sequencing Project

Researchers have successfully applied exome sequencing to discover causal variants in selected individuals with familial, highly penetrant disorders. We demonstrate the utility of exome sequencing followed by imputation for discovering low-frequency variants associated with complex quantitative traits. We performed exome sequencing in a reference panel of 761 African Americans and then imputed newly discovered variants into a larger sample of more than 13,000 African Americans for association testing with the blood cell traits hemoglobin, hematocrit, white blood count, and platelet count. First, we illustrate the feasibility of our approach by demonstrating genome-wide-significant associations for variants that are not covered by conventional genotyping arrays; for example, one such association is that between higher platelet count and an MPL c.117G>T (p.Lys39Asn) variant encoding a p.Lys39Asn amino acid substitution of the thrombpoietin receptor gene (p = 1.5 × 10⁻¹¹). Second, we identified an association between missense variants of LCT and higher white blood count (p = 4 × 10⁻¹³). Third, we identified low-frequency coding variants that might account for allelic heterogeneity at several known blood cell-associated loci: MPL c.754T>C (p.Tyr252His) was associated with higher platelet count; CD36 c.975T>G (p.Tyr325^∗) was associated with lower platelet count; and several missense variants at the α-globin gene locus were associated with lower hemoglobin. By identifying low-frequency missense variants associated with blood cell traits not previously reported by genome-wide association studies, we establish that exome sequencing followed by imputation is a powerful approach to dissecting complex, genetically heterogeneous traits in large population-based studies.     

Distribution and Medical Impact of Loss-of-Function Variants in the Finnish Founder Population

Exome sequencing studies in complex diseases are challenged by the allelic heterogeneity, large number and modest effect sizes of associated variants on disease risk and the presence of large numbers of neutral variants, even in phenotypically relevant genes. Isolated populations with recent bottlenecks offer advantages for studying rare variants in complex diseases as they have deleterious variants that are present at higher frequencies as well as a substantial reduction in rare neutral variation. To explore the potential of the Finnish founder population for studying low-frequency (0.5–5%) variants in complex diseases, we compared exome sequence data on 3,000 Finns to the same number of non-Finnish Europeans and discovered that, despite having fewer variable sites overall, the average Finn has more low-frequency loss-of-function variants and complete gene knockouts. We then used several well-characterized Finnish population cohorts to study the phenotypic effects of 83 enriched loss-of-function variants across 60 phenotypes in 36,262 Finns. Using a deep set of quantitative traits collected on these cohorts, we show 5 associations (p<5×10⁻⁸) including splice variants in LPA that lowered plasma lipoprotein(a) levels (P = 1.5×10⁻¹¹⁷). Through accessing the national medical records of these participants, we evaluate the LPA finding via Mendelian randomization and confirm that these splice variants confer protection from cardiovascular disease (OR = 0.84, P = 3×10⁻⁴), demonstrating for the first time the correlation between very low levels of LPA in humans with potential therapeutic implications for cardiovascular diseases. More generally, this study articulates substantial advantages for studying the role of rare variation in complex phenotypes in founder populations like the Finns and by combining a unique population genetic history with data from large population cohorts and centralized research access to National Health Registers.     

Rare coding variation in paraoxonase-1 is associated with ischemic stroke in the NHLBI Exome Sequencing Project

HDL-associated paraoxonase-1 (PON1) is an enzyme whose activity is associated with cerebrovascular disease. Common PON1 genetic variants have not been consistently associated with cerebrovascular disease. Rare coding variation that likely alters PON1 enzyme function may be more strongly associated with stroke. The National Heart, Lung, and Blood Institute Exome Sequencing Project sequenced the coding regions (exomes) of the genome for heart, lung, and blood-related phenotypes (including ischemic stroke). In this sample of 4,204 unrelated participants, 496 had verified, noncardioembolic ischemic stroke. After filtering, 28 nonsynonymous PON1 variants were identified. Analysis with the sequence kernel association test, adjusted for covariates, identified significant associations between PON1 variants and ischemic stroke (P = 3.01 × 10⁻³). Stratified analyses demonstrated a stronger association of PON1 variants with ischemic stroke in African ancestry (AA) participants (P = 5.03 × 10⁻³). Ethnic differences in the association between PON1 variants with stroke could be due to the effects of PON1_Val109Ile (overall P = 7.88 × 10⁻³; AA P = 6.52 × 10⁻⁴), found at higher frequency in AA participants (1.16% vs. 0.02%) and whose protein is less stable than the common allele. In summary, rare genetic variation in PON1 was associated with ischemic stroke, with stronger associations identified in those of AA. Increased focus on PON1 enzyme function and its role in cerebrovascular disease is warranted.     

Integration of New Genes into Cellular Networks,and Their Structural Maturation

It has been recently discovered that new genes can originate de novo from noncoding DNA, and several biological traits including expression or sequence composition form a continuum from noncoding sequences to conserved genes. In this article, using yeast genes I test whether the integration of new genes into cellular networks and their structural maturation shows such a continuum by analyzing their changes with gene age. I show that 1) The number of regulatory, protein–protein, and genetic interactions increases continuously with gene age, although with very different rates. New regulatory interactions emerge rapidly within a few million years, while the number of protein–protein and genetic interactions increases slowly, with a rate of 2–2.25 × 10⁻⁸/year and 4.8 × 10⁻⁸/year, respectively. 2) Gene essentiality evolves relatively quickly: the youngest essential genes appear in proto-genes ∼14 MY old. 3) In contrast to interactions, the secondary structure of proteins and their robustness to mutations indicate that new genes face a bottleneck in their evolution: proto-genes are characterized by high β-strand content, high aggregation propensity, and low robustness against mutations, while conserved genes are characterized by lower strand content and higher stability, most likely due to the higher probability of gene loss among young genes and accumulation of neutral mutations.     

A Genetic Variant in 12q13, a Possible Risk Factor for Bipolar Disorder,Is Associated with Depressive State,Accounting for Stressful Life Events

Genome-wide association studies (GWASs) have identified a number of susceptibility genes for schizophrenia (SCZ) and bipolar disorder (BD). However, the identification of risk genes for major depressive disorder (MDD) has been unsuccessful because the etiology of MDD is more influenced by environmental factors; thus, gene–environment (G×E) interactions are important, such as interplay with stressful life events (SLEs). We assessed the G×E interactions and main effects of genes targeting depressive symptoms. Using a case–control design, 922 hospital staff members were evaluated for depressive symptoms according to Beck Depressive Inventory (BDI; “depression” and “control” groups were classified by scores of 10 in the BDI test), SLEs, and personality. A total of sixty-three genetic variants were selected on the basis of previous GWASs of MDD, SCZ, and BD as well as candidate-gene (SLC6A4, BDNF, DBH, and FKBP5) studies. Logistic regression analysis revealed a marginally significant interaction (genetic variant × SLE) at rs4523957 (P_uncorrected = 0.0034) with depression and a significant association of single nucleotide polymorphism identified from evidence of BD GWAS (rs7296288, downstream of DHH at 12q13.1) with depression as the main effect (P_uncorrected = 9.4×10⁻⁴, P_corrected = 0.0424). We also found that SLEs had a larger impact on depression (odds ratio∼3), as reported previously. These results suggest that DHH plays a possible role in depression etiology; however, variants from MDD or SCZ GWAS evidence or candidate genes showed no significant associations or minimal effects of interactions with SLEs on depression.     

Genotype by environment interactions in relation to growth traits in slow growing chickens

Since feed conversion ratio (FCR) is higher in slow-growing "Label Rouge" chickens than in broiler chickens, it is important to work on its improvement in this breed. However, this involves rearing animals in cages (C), an environment very different from that used for selection (in floor pens, S) and production (outdoor, E). The aim of this study was to evaluate the importance of genotype by environment (G × E) interactions between S, C, and E environments, to find the best way to select for FCR, using 2002 related animals. Growth curve parameters were estimated and body composition measured. Individual feed conversion ratios (FCR) were recorded between 8 and 10 weeks in C. The presence of G × E interactions was assessed by the genetic correlations between the same trait recorded in different environments. Moderate but significant G × E interactions were detected for carcass traits, a significant one was observed between E and S or C for growth curve parameters but none between C and S. If G × E interactions are set aside, i.e. selecting on traits recorded in C, abdominal fatness is the best indirect selection criterion for FCR but if they are taken in account then leg yield or growth curve parameters in S and growth curve parameters in E are better.     

Rare Genomic Structural Variants in Complex Disease: Lessons from the Replication of Associations with Obesity

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the ‘missing heritability’. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10⁻⁴ (95% confidence interval [9.6×10⁻⁵–3.1×10⁻⁴]); accounts overall for 0.5% [0.19%–0.82%] of severe childhood obesity cases (P = 3.8×10⁻¹⁰; odds ratio = 25.0 [9.9–60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m⁻² [1.8–10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.     

Insight in Genome-Wide Association of Metabolite Quantitative Traits by Exome Sequence Analyses

Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. ¹H Nuclear Magnetic Resonance (¹H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10⁻³²), PRODH with proline (P-value  = 1.11×10⁻¹⁹), SLC16A9 with carnitine level (P-value  = 4.81×10⁻¹⁴) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10⁻¹⁹) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10⁻⁸), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10⁻⁸) and 2p12 locus with valine (P-value  = 3.49×10⁻⁸). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution ¹H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.     

Common Variants of FTO Are Associated with Childhood Obesity in a Cross-Sectional Study of 3,126 Urban Indian Children

Background

FTO variants are robustly associated with obesity and related traits in many population and shown to have variable impact during life course. Although studies have shown association of FTO variants with adiposity in adult Indian, its association in Indian children is yet to be confirmed.

Methods

Here we examined association of FTO variants (rs9939609 and rs8050136) with obesity and related anthropometric and biochemical traits in 3,126 Indian children (aged 11–17 years) including 2,230 normal-weight and 896 over-weight/obese children. We also compared effects observed in the present study with that observed in previous studies on South Asian adults and children of other ethnic groups.

Results

The variant rs9939609 showed significant association with risk of obesity [OR = 1.21, P = 2.5×10⁻³] and its measures BMI, weight, waist circumference and hip circumference [β range = 0.11 to 0.14 Z-score units; P range = 1.3×10⁻⁴ to 1.6×10⁻⁷] in children. The observed effect sizes in Indian children were similar to those reported for European children. Variant rs9939609 explained 0.88% of BMI variance in Indian children. The effect sizes of rs9939609 on BMI and WC were ∼2 fold higher in children than adults. Interestingly rs9939609 was also associated with serum levels of thyroid stimulating hormone (TSH) [β = 0.10 Z-score, P = 5.8×10⁻³]. The other variant rs8050136 was in strong linkage disequilibrium with rs9939609 (r² = 0.97) and provided similar association results.

Conclusion

The study provides first report of association of FTO variants with obesity and related anthropometric traits in Indian children with higher impact in children compared to adults. We also demonstrated association of FTO variant with serum levels of TSH, indicating putative influence of FTO in hypothalamic-pituitary-thyroid axis.     

Obesity polymorphisms identified in genome-wide association studies interact with n-3 polyunsaturated fatty acid intake and modify the genetic association with adiposity phenotypes in Yup’ik people

n-3 Polyunsaturated fatty acids (n-3 PUFAs) have anti-obesity effects that may modulate risk of obesity, in part, through interactions with genetic factors. Genome-wide association studies (GWAS) have identified genetic variants associated with body mass index (BMI); however, the extent to which these variants influence adiposity through interactions with n-3 PUFAs remains unknown. We evaluated 10 highly replicated obesity GWAS single nucleotide polymorphisms (SNPs) for individual and cumulative associations with adiposity phenotypes in a cross-sectional sample of Yup’ik people (n = 1,073) and evaluated whether genetic associations with obesity were modulated by n-3 PUFA intake. A genetic risk score (GRS) was calculated by adding the BMI-increasing alleles across all 10 SNPs. Dietary intake of n-3 PUFAs was estimated using nitrogen stable isotope ratio (δ¹⁵N) of red blood cells, and genotype–phenotype analyses were tested in linear models accounting for familial correlations. GRS was positively associated with BMI (p = 0.012), PBF (p = 0.022), ThC (p = 0.025), and waist circumference (p = 0.038). The variance in adiposity phenotypes explained by the GRS included BMI (0.7 %), PBF (0.3 %), ThC (0.7 %), and WC (0.5 %). GRS interactions with n-3 PUFAs modified the association with adiposity and accounted for more than twice the phenotypic variation (~1–2 %), relative to GRS associations alone. Obesity GWAS SNPs contribute to adiposity in this study population of Yup’ik people and interactions with n-3 PUFA intake potentiated the risk of fat accumulation among individuals with high obesity GRS. These data suggest the anti-obesity effects of n-3 PUFAs among Yup’ik people may, in part, be dependent upon an individual’s genetic predisposition to obesity.

Electronic supplementary material

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