Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

A nonsense loss-of-function mutation in PCSK1 contributes to dominantly inherited human obesity

BACKGROUND

A significant proportion of severe familial forms of obesity remain genetically elusive. Taking advantage of our unique cohort of multigenerational obese families, we aimed to assess the contribution of rare mutations in 29 common obesity-associated genes to familial obesity, and to evaluate in these families the putative presence of nine known monogenic forms of obesity.

METHODS

Through next-generation sequencing, we sequenced the coding regions of 34 genes involved in polygenic and/or monogenic forms of obesity in 201 participants (75 normal weight individuals, 54 overweight individuals and 72 individuals with obesity class I, II or III) from 13 French families. In vitro functional analyses were performed to investigate the mutation PCSK1-p.Arg80* which was identified in a family.

RESULTS

A novel heterozygous nonsense variant in PCSK1 (p.Arg80*), encoding a propeptide truncated to less than two exons (out of 14), was found to co-segregate with obesity in a three-generation family. We demonstrated that this mutation inhibits PCSK1 enzyme activity and that this inhibition most likely does not involve a strong physical interaction. Furthermore, both mutations PCSK1-p.Asn180Ser and POMC-p.Phe144Leu, which had previously been reported to be associated with severe obesity, were also identified in this study, but did not co-segregate with obesity. Finally, we did not identify any rare mutations co-segregating with obesity in common obesity susceptibility genes, except for CADM2 and QPCTL, where we found two novel variants (p.Arg81His and p.Leu98Pro, respectively) in three obese individuals.

CONCLUSIONS

We showed for the first time that a nonsense mutation in PCSK1 was likely to cause dominantly inherited human obesity, due to the inhibiting properties of the propeptide fragment encoded by the null allele. Furthermore, the present family sequencing design challenged the contribution of previously reported mutations to monogenic or at least severe obesity.

On the association of common and rare genetic variation influencing body mass index: a combined SNP and CNV analysis

Background

As the architecture of complex traits incorporates a widening spectrum of genetic variation, analyses integrating common and rare variation are needed. Body mass index (BMI) represents a model trait, since common variation shows robust association but accounts for a fraction of the heritability. A combined analysis of single nucleotide polymorphisms (SNP) and copy number variation (CNV) was performed using 1850 European and 498 African-Americans from the Study of Addiction: Genetics and Environment. Genetic risk sum scores (GRSS) were constructed using 32 BMI-validated SNPs and aggregate-risk methods were compared: count versus weighted and proxy versus imputation.

Results

The weighted SNP-GRSS constructed from imputed probabilities of risk alleles performed best and was highly associated with BMI (p = 4.3×10⁻¹⁶) accounting for 3% of the phenotypic variance. In addition to BMI-validated SNPs, common and rare BMI/obesity-associated CNVs were identified from the literature. Of the 84 CNVs previously reported, only 21-kilobase deletions on 16p12.3 showed evidence for association with BMI (p = 0.003, frequency = 16.9%), with two CNVs nominally associated with class II obesity, 1p36.1 duplications (OR = 3.1, p = 0.009, frequency 1.2%) and 5q13.2 deletions (OR = 1.5, p = 0.048, frequency 7.7%). All other CNVs, individually and in aggregate, were not associated with BMI or obesity. The combined model, including covariates, SNP-GRSS, and 16p12.3 deletion accounted for 11.5% of phenotypic variance in BMI (3.2% from genetic effects). Models significantly predicted obesity classification with maximum discriminative ability for morbid-obesity (p = 3.15×10⁻¹⁸).

Conclusion

Results show that incorporating validated effect sizes and allelic probabilities improve prediction algorithms. Although rare-CNVs did not account for significant phenotypic variation, results provide a framework for integrated analyses.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-368) contains supplementary material, which is available to authorized users.

Mitochondrial DNA variants in obesity

Heritability estimates for body mass index (BMI) variation are high. For mothers and their offspring higher BMI correlations have been described than for fathers. Variation(s) in the exclusively maternally inherited mitochondrial DNA (mtDNA) might contribute to this parental effect. Thirty-two to 40 mtDNA single nucleotide polymorphisms (SNPs) were available from genome-wide association study SNP arrays (Affymetrix 6.0). For discovery, we analyzed association in a case-control (CC) sample of 1,158 extremely obese children and adolescents and 435 lean adult controls. For independent confirmation, 7,014 population-based adults were analyzed as CC sample of n = 1,697 obese cases (BMI ≥ 30 kg/m2) and n = 2,373 normal weight and lean controls (BMI<25 kg/m2). SNPs were analyzed as single SNPs and haplogroups determined by HaploGrep. Fisher's two-sided exact test was used for association testing. Moreover, the D-loop was re-sequenced (Sanger) in 192 extremely obese children and adolescents and 192 lean adult controls. Association testing of detected variants was performed using Fisher's two-sided exact test. For discovery, nominal association with obesity was found for the frequent allele G of m.8994G/A (rs28358887, p = 0.002) located in ATP6. Haplogroup W was nominally overrepresented in the controls (p = 0.039). These findings could not be confirmed independently. For two of the 252 identified D-loop variants nominal association was detected (m.16292C/T, p = 0.007, m.16189T/C, p = 0.048). Only eight controls carried the m.16292T allele, five of whom belonged to haplogroup W that was initially enriched among these controls. m.16189T/C might create an uninterrupted poly-C tract located near a regulatory element involved in replication of mtDNA. Though follow-up of some D-loop variants still is conceivable, our hypothesis of a contribution of variation in the exclusively maternally inherited mtDNA to the observed larger correlations for BMI between mothers and their offspring could not be substantiated by the findings of the present study.

A marker-derived gene network reveals the regulatory role of PPARGC1A, HNF4G, and FOXP3 in intramuscular fat deposition of beef cattle

High intramuscular fat (IMF) awards price premiums to beef producers and is associated with meat quality and flavor. Studying gene interactions and pathways that affect IMF might unveil causative physiological mechanisms and inform genomic selection, leading to increased accuracy of predictions of breeding value. To study gene interactions and pathways, a gene network was derived from genetic markers associated with direct measures of IMF, other fat phenotypes, feedlot performance, and a number of meat quality traits relating to body conformation, development, and metabolism that might be plausibly expected to interact with IMF biology. Marker associations were inferred from genomewide association studies (GWAS) based on high density genotypes and 29 traits measured on 10,181 beef cattle animals from 3 breed types. For the network inference, SNP pairs were assessed according to the strength of the correlation between their additive association effects across the 29 traits. The co-association inferred network was formed by 2,434 genes connected by 28,283 edges. Topological network parameters suggested a highly cohesive network, in which the genes are strongly functionally interconnected. Pathway and network analyses pointed towards a trio of transcription factors (TF) as key regulators of carcass IMF: PPARGC1A, HNF4G, and FOXP3. Importantly, none of these genes would have been deemed as significantly associated with IMF from the GWAS. Instead, a total of 313 network genes show significant co-association with the 3 TF. These genes belong to a wide variety of biological functions, canonical pathways, and genetic networks linked to IMF-related phenotypes. In summary, our GWAS and network predictions are supported by the current literature and suggest a cooperative role for the 3 TF and other interacting genes including CAPN6, STC2, MAP2K4, EYA1, COPS5, XKR4, NR2E1, TOX, ATF1, ASPH, TGS1, and TTPA as modulators of carcass and meat quality traits in beef cattle.

Quality control and conduct of genome-wide association meta-analyses

Rigorous organization and quality control (QC) are necessary to facilitate successful genome-wide association meta-analyses (GWAMAs) of statistics aggregated across multiple genome-wide association studies. This protocol provides guidelines for (i) organizational aspects of GWAMAs, and for (ii) QC at the study file level, the meta-level across studies and the meta-analysis output level. Real-world examples highlight issues experienced and solutions developed by the GIANT Consortium that has conducted meta-analyses including data from 125 studies comprising more than 330,000 individuals. We provide a general protocol for conducting GWAMAs and carrying out QC to minimize errors and to guarantee maximum use of the data. We also include details for the use of a powerful and flexible software package called EasyQC. Precise timings will be greatly influenced by consortium size. For consortia of comparable size to the GIANT Consortium, this protocol takes a minimum of about 10 months to complete.

Reading and language disorders: the importance of both quantity and quality

Reading and language disorders are common childhood conditions that often co-occur with each other and with other neurodevelopmental impairments. There is strong evidence that disorders, such as dyslexia and Specific Language Impairment (SLI), have a genetic basis, but we expect the contributing genetic factors to be complex in nature. To date, only a few genes have been implicated in these traits. Their functional characterization has provided novel insight into the biology of neurodevelopmental disorders. However, the lack of biological markers and clear diagnostic criteria have prevented the collection of the large sample sizes required for well-powered genome-wide screens. One of the main challenges of the field will be to combine careful clinical assessment with high throughput genetic technologies within multidisciplinary collaborations.

The genetics of major depression

Major depression is the commonest psychiatric disorder and in the U.S. has the greatest impact of all biomedical diseases on disability. Here we review evidence of the genetic contribution to disease susceptibility and the current state of molecular approaches. Genome-wide association and linkage results provide constraints on the allele frequencies and effect sizes of susceptibility loci, which we use to interpret the voluminous candidate gene literature. We consider evidence for the genetic heterogeneity of the disorder and the likelihood that subtypes exist that represent more genetically homogenous conditions than have hitherto been analyzed.

The stunting syndrome in developing countries

Linear growth failure is the most common form of undernutrition globally. With an estimated 165 million children below 5 years of age affected, stunting has been identified as a major public health priority, and there are ambitious targets to reduce the prevalence of stunting by 40% between 2010 and 2025. We view this condition as a 'stunting syndrome' in which multiple pathological changes marked by linear growth retardation in early life are associated with increased morbidity and mortality, reduced physical, neurodevelopmental and economic capacity and an elevated risk of metabolic disease into adulthood. Stunting is a cyclical process because women who were themselves stunted in childhood tend to have stunted offspring, creating an intergenerational cycle of poverty and reduced human capital that is difficult to break. In this review, the mechanisms underlying linear growth failure at different ages are described, the short-, medium- and long-term consequences of stunting are discussed, and the evidence for windows of opportunity during the life cycle to target interventions at the stunting syndrome are evaluated.

Imputation without doing imputation: a new method for the detection of non-genotyped causal variants

Genome-wide association studies allow detection of non-genotyped disease-causing variants through testing of nearby genotyped SNPs. This approach may fail when there are no genotyped SNPs in strong LD with the causal variant. Several genotyped SNPs in weak LD with the causal variant may, however, considered together, provide equivalent information. This observation motivates popular but computationally intensive approaches based on imputation or haplotyping. Here we present a new method and accompanying software designed for this scenario. Our approach proceeds by selecting, for each genotyped "anchor" SNP, a nearby genotyped "partner" SNP, chosen via a specific algorithm we have developed. These two SNPs are used as predictors in linear or logistic regression analysis to generate a final significance test. In simulations, our method captures much of the signal captured by imputation, while taking a fraction of the time and disc space, and generating a smaller number of false-positives. We apply our method to a case/control study of severe malaria genotyped using the Affymetrix 500K array. Previous analysis showed that fine-scale sequencing of a Gambian reference panel in the region of the known causal locus, followed by imputation, increased the signal of association to genome-wide significance levels. Our method also increases the signal of association from P ≈ 2 × 10⁻⁶ to P ≈ 6 × 10⁻¹¹. Our method thus, in some cases, eliminates the need for more complex methods such as sequencing and imputation, and provides a useful additional test that may be used to identify genetic regions of interest.

High frequency of rare variants with a moderate-to-high predicted biological effect in protocadherin genes of extremely obese

Relatively rare variants with a moderate-to-high biological effect may contribute to the genetic predisposition of common disorders. To investigate this for obesity, we performed exome sequencing for 30 young (mean age: 29.7 years) extremely obese Caucasian subjects (mean body mass index: 51.1 kg/m(2); m/f = 11/29). Rare variants with a moderate-to-high predicted biological effect were assembled and subjected to functional clustering analysis. It showed that the 55 clustered protocadherin genes on chromosome 5q31 have a significantly (P = 0.002) higher frequency of rare variants than a set of 325 reference genes. Since the protocadherin genes are expressed in the hypothalamus, we tested another 167 genes related to the function of the hypothalamus, but in those genes, the frequency of rare variants was not different from that of the reference genes. To verify the relation of variation in the protocadherin genes with extreme obesity, we analyzed data from more than 4,000 European Americans present on the Exome Variant Server, representing a sample of the general population. The significant enrichment of rare variants in the protocadherin genes was only observed with the group of extremely obese individuals but not in the "general population", indicating an association between rare variants in the protocadherin cluster genes and extreme obesity.

IgA measurements in over 12 000 Swedish twins reveal sex differential heritability and regulatory locus near CD30L

In a broad attempt to improve the understanding of the genetic regulation of serum IgA levels, the heritability was estimated in over 12 000 Swedish twins, and a genome-wide association study was conducted in a subsample of 9617. Using the classical twin model the heritability was found to be significantly larger among females (61%) compared with males (21%), while contribution from shared environment (20%) was only seen for males. By modeling the genetic relationship matrix with IgA levels, we estimate that a substantial proportion (31%) of variance in IgA levels can ultimately be explained by the investigated SNPs. The genome-wide association study revealed significant association to two loci: (i) rs6928791 located on chromosome 6, 22 kb upstream of the gene SAM and SH3 domain containing 1 (SASH1) and (ii) rs13300483 on chromosome 9, situated 12 kb downstream the CD30 ligand (CD30L) encoding gene. The association to rs13300483 was replicated in two additional independent Swedish materials. The heritability of IgA levels is moderate and can partly be attributable to common variation in the CD30L locus.

Association study of common polymorphisms in MSRA, TFAP2B, MC4R, NRXN3, PPARGC1A, TMEM18, SEC16B, HOXB5 and OLFM4 genes with obesity-related traits among Portuguese children

At least 52 genetic loci were associated with obesity-related traits. However, little is known about the genetic basis of obesity among children. This study aims to test whether 10 polymorphisms in obesity-related genes methionine sulfoxide reductase A (MSRA), transcription factor AP-2 beta (TFAP2B), melanocortin 4 receptor (MC4R), neurexin 3 (NRXN3), peroxisome proliferator-activated receptor gamma coactivator 1 alpha (PPARGC1A), transmembrane protein 18 (TMEM18), homolog of S. cerevisiae Sec16 (SEC16B), homeobox B5 (HOXB5) and olfactomedin 4 (OLFM4) are associated with the risk of obesity in Portuguese children. A total of 730 children aging from 6 to 12 years old, recruited randomly from public schools in Portugal, were analysed. Anthropometric measurements were obtained and children were classified into three phenotypic groups, normal weight (n=256), overweight (n=320) and obese (n=154), according to the International Obesity Task Force cutoffs. Polymorphisms were genotyped by allelic discrimination TaqMan assays. The MC4R rs12970134 polymorphism was nominally associated with body mass index (BMI) (P=0.035), BMI Z-score (P=0.043) and waist circumference (P=0.020), and borderline associated with weight (P=0.053). Near nominal associations were also found for the PPARGC1A rs8192678 polymorphism with weight (P=0.061), and for the MSRA rs545854 polymorphism with BMI (P=0.055) and BMI Z-score (P=0.056). Furthermore, logistic regression showed that MC4R rs12970134 and TFAP2B rs987237 were nominally, respectively, associated (P=0.029) and borderline associated (P=0.056) with the obese phenotype. This study highlighted the possible association of MC4R, PPARGC1A, MSRA and TFAP2B polymorphisms with several obesity-related traits in a sample of Portuguese children. The two significant associated TFAP2B rs987237 and MC4R rs12970134 polymorphisms showed an opposite direction of effect to that in the original reports.

Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci

Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ~50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.

An excess of risk-increasing low-frequency variants can be a signal of polygenic inheritance in complex diseases

In most complex diseases, much of the heritability remains unaccounted for by common variants. It has been postulated that lower-frequency variants contribute to the remaining heritability. Here, we describe a method to test for polygenic inheritance from lower-frequency variants by using GWAS summary association statistics. We explored scenarios with many causal low-frequency variants and showed that there is more power to detect risk variants than to detect protective variants, resulting in an increase in the ratio of detected risk to protective variants (R/P ratio). Such an excess can also occur if risk variants are present and kept at lower frequencies because of negative selection. The R/P ratio can be falsely elevated because of reasons unrelated to polygenic inheritance, such as uneven sample sizes or asymmetric population stratification, so precautions to correct for these confounders are essential. We tested our method on published GWAS results and observed a strong signal in some diseases (schizophrenia and type 2 diabetes) but not others. We also explored the shared genetic component in overlapping phenotypes related to inflammatory bowel disease (Crohn disease [CD] and ulcerative colitis [UC]) and diabetic nephropathy (macroalbuminuria and end-stage renal disease [ESRD]). Although the signal was still present when both CD and UC were jointly analyzed, the signal was lost when macroalbuminuria and ESRD were jointly analyzed, suggesting that these phenotypes should best be studied separately. Thus, our method may also help guide the design of future genetic studies of various traits and diseases.

Cohort Profile: Estonian Biobank of the Estonian Genome Center, University of Tartu

The Estonian Biobank cohort is a volunteer-based sample of the Estonian resident adult population (aged ≥18 years). The current number of participants-close to 52000--represents a large proportion, 5%, of the Estonian adult population, making it ideally suited to population-based studies. General practitioners (GPs) and medical personnel in the special recruitment offices have recruited participants throughout the country. At baseline, the GPs performed a standardized health examination of the participants, who also donated blood samples for DNA, white blood cells and plasma tests and filled out a 16-module questionnaire on health-related topics such as lifestyle, diet and clinical diagnoses described in WHO ICD-10. A significant part of the cohort has whole genome sequencing (100), genome-wide single nucleotide polymorphism (SNP) array data (20 000) and/or NMR metabolome data (11 000) available (http://www.geenivaramu.ee/for-scientists/data-release/). The data are continuously updated through periodical linking to national electronic databases and registries. A part of the cohort has been re-contacted for follow-up purposes and resampling, and targeted invitations are possible for specific purposes, for example people with a specific diagnosis. The Estonian Genome Center of the University of Tartu is actively collaborating with many universities, research institutes and consortia and encourages fellow scientists worldwide to co-initiate new academic or industrial joint projects with us.

Genetic modifiers of obesity and bariatric surgery outcomes

Obesity is a highly heritable trait. While acute and chronic changes in body weight or obesity-related comorbidities are heavily influenced by environmental factors, there are still strong genomic modifiers that help account for inter-subject variability in baseline traits and in response to interventions. This review is intended to provide an up-to-date overview of our current understanding of genetic influences on obesity, with emphasis on genetic modifiers of baseline traits and responses to intervention. We begin by reviewing how genetic variants can influence obesity. We then examine genetic modifiers of weight loss via different intervention strategies, focusing on known and potential modifiers of surgical weight loss outcomes. We will pay particular attention to the effects of patient age on outcomes, addressing the risks and benefits of adopting early intervention strategies. Finally, we will discuss how the field of bariatric surgery can leverage knowledge of genetic modifiers to adopt a personalized medicine approach for optimal outcomes across this widespread and diverse patient population.

Novel association of the obesity risk-allele near Fas Apoptotic Inhibitory Molecule 2 (FAIM2) gene with heart rate and study of its effects on myocardial infarction in diabetic participants of the PREDIMED trial

BACKGROUND

The Fas apoptotic pathway has been implicated in type 2 diabetes and cardiovascular disease. Although a polymorphism (rs7138803; G > A) near the Fas apoptotic inhibitory molecule 2 (FAIM2) locus has been related to obesity, its association with other cardiovascular risk factors and disease remains uncertain.

METHODS

We analyzed the association between the FAIM2-rs7138803 polymorphism and obesity, blood pressure and heart rate in 7,161 participants (48.3% with type 2 diabetes) in the PREDIMED study at baseline. We also explored gene-diet interactions with adherence to the Mediterranean diet (MedDiet) and examined the effects of the polymorphism on cardiovascular disease incidence per diabetes status after a median 4.8-year dietary intervention (MedDiet versus control group) follow-up.

RESULTS

We replicated the association between the FAIM2-rs7138803 polymorphism and greater obesity risk (OR: 1.08; 95% CI: 1.01-1.16; P = 0.011; per-A allele). Moreover, we detected novel associations of this polymorphism with higher diastolic blood pressure (DBP) and heart rate at baseline (B = 1.07; 95% CI: 0.97-1.28 bmp in AA vs G-carriers for the whole population), that remained statistically significant even after adjustment for body mass index (P = 0.012) and correction for multiple comparisons. This association was greater and statistically significant in type-2 diabetic subjects (B = 1.44: 95% CI: 0.23-2.56 bmp; P = 0.010 for AA versus G-carriers). Likewise, these findings were also observed longitudinally over 5-year follow-up. Nevertheless, we found no statistically significant gene-diet interactions with MedDiet for this trait. On analyzing myocardial infarction risk, we detected a nominally significant (P = 0.041) association in type-2 diabetic subjects (HR: 1.86; 95% CI:1.03-3.37 for AA versus G-carriers), although this association did not remain statistically significant following correction for multiple comparisons.

CONCLUSIONS

We confirmed the FAIM2-rs7138803 relationship with obesity and identified novel and consistent associations with heart rate in particular in type 2 diabetic subjects. Furthermore, our results suggest a possible association of this polymorphism with higher myocardial infarction risk in type-2 diabetic subjects, although this result needs to be replicated as it could represent a false positive.

The bigger picture of FTO: the first GWAS-identified obesity gene

Single nucleotide polymorphisms (SNPs) that cluster in the first intron of fat mass and obesity associated (FTO) gene are associated obesity traits in genome-wide association studies. The minor allele increases BMI by 0.39 kg/m(2) (or 1,130 g in body weight) and risk of obesity by 1.20-fold. This association has been confirmed across age groups and populations of diverse ancestry; the largest effect is seen in young adulthood. The effect of FTO SNPs on obesity traits in populations of African and Asian ancestry is similar or somewhat smaller than in European ancestry populations. However, the BMI-increasing allele in FTO is substantially less prevalent in populations with non-European ancestry. FTO SNPs do not influence physical activity levels; yet, in physically active individuals, FTO's effect on obesity susceptibility is attenuated by approximately 30%. Evidence from epidemiological and functional studies suggests that FTO confers an increased risk of obesity by subtly changing food intake and preference. Moreover, emerging data suggest a role for FTO in nutrient sensing, regulation of mRNA translation and general growth. In this Review, we discuss the genetic epidemiology of FTO and discuss how its complex biology might link to the regulation of body weight.

The next-generation sequencing revolution and its impact on genomics

Genomics is a relatively new scientific discipline, having DNA sequencing as its core technology. As technology has improved the cost and scale of genome characterization over sequencing's 40-year history, the scope of inquiry has commensurately broadened. Massively parallel sequencing has proven revolutionary, shifting the paradigm of genomics to address biological questions at a genome-wide scale. Sequencing now empowers clinical diagnostics and other aspects of medical care, including disease risk, therapeutic identification, and prenatal testing. This Review explores the current state of genomics in the massively parallel sequencing era.

An obesity genetic risk score is associated with metabolic syndrome in Chinese children

Recent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with body mass index (BMI)/obesity. In this study, we aim to examine the associations of obesity related loci with risk of metabolic syndrome (MetS) in a children population from China. A total of 431 children with MetS and 3046 controls were identified based on the modified ATPIII definition. 11 SNPs (FTO rs9939609, MC4R rs17782313, GNPDA2 rs10938397, BDNF rs6265, FAIM2 rs7138803, NPC1 rs1805081, SEC16B rs10913469, SH2B1 rs4788102, PCSK1rs6235, KCTD15 rs29941, BAT2 rs2844479) were genotyped by TaqMan 7900. Of 11 SNPs, GNPDA2 rs10938397, BDNF rs6265, and FAIM2 rs7138803 were nominally associated with risk of MetS (GNPDA2 rs10938397: odds ratio (OR)=1.21, 95% confidence interval (CI)=1.04-1.40, P=0.016; BDNF rs6265: OR=1.19, 95% CI=1.03-1.39, P=0.021; FAIM2 rs7138803: OR=1.20, 95% CI=1.02-1.40, P=0.025); genetic risk score (GRS) was significantly associated with risk of MetS (OR=1.09, 95% CI=1.04-1.15, P=5.26×10(-4)). After further adjustment for BMI, none of SNPs were associated with risk of MetS (all P>0.05); the association between GRS and risk of MetS remained nominally (OR=1.02, 95%CI=0.96-1.08, P=0.557). However, after correction for multiple testing, only GRS was statistically associated with risk of MetS in the model without adjustment for BMI. The present study demonstrated that there were nominal associations of GNPDA2 rs10938397, BDNF rs6265, and FAIM2 rs7138803 with risk of MetS. The SNPs in combination have a significant effect on risk of MetS among Chinese children. These associations above were mediated by adiposity.

Novel insights from genetic and epigenetic studies in understanding the complex uraemic phenotype

Like in many other common complex disorders, studies of chronic kidney disease (CKD) can now make use of the increasing knowledge of the human genome, its variations and impact on disease susceptibility, initiation, progression and complications. Such studies are facilitated by novel readily available high through-put genotyping methods and sophisticated analytical approaches to scan the genome for DNA variations and epigenetic modifications. Here, we review some of the recent discoveries that have emerged from these studies and expanded our knowledge of genetic risk loci and epigenetic markers in CKD pathophysiology. Obstacles and practical issues in this field are discussed.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

Contribution of 32 GWAS-identified common variants to severe obesity in European adults referred for bariatric surgery

The prevalence of severe obesity, defined as body mass index (BMI) ≥ 35.0 kg/m(2), is rising rapidly. Given the disproportionately high health burden and healthcare costs associated with this condition, understanding the underlying aetiology, including predisposing genetic factors, is a biomedical research priority. Previous studies have suggested that severe obesity represents an extreme tail of the population BMI variation, reflecting shared genetic factors operating across the spectrum. Here, we sought to determine whether a panel of 32 known common obesity-susceptibility variants contribute to severe obesity in patients (n = 1,003, mean BMI 48.4 ± 8.1 kg/m(2)) attending bariatric surgery clinics in two European centres. We examined the effects of these 32 common variants on obesity risk and BMI, both as individual markers and in combination as a genetic risk score, in a comparison with normal-weight controls (n = 1,809, BMI 18.0-24.9 kg/m(2)); an approach which, to our knowledge, has not been previously undertaken in the setting of a bariatric clinic. We found strong associations with severe obesity for SNP rs9939609 within the FTO gene (P = 9.3 × 10(-8)) and SNP rs2815752 near the NEGR1 gene (P = 3.6 × 10(-4)), and directionally consistent nominal associations (P<0.05) for 12 other SNPs. The genetic risk score associated with severe obesity (P = 8.3 × 10(-11)) but, within the bariatric cohort, this score did not associate with BMI itself (P = 0.264). Our results show significant effects of individual BMI-associated common variants within a relatively small sample size of bariatric patients. Furthermore, the burden of such low-penetrant risk alleles contributes to severe obesity in this population. Our findings support that severe obesity observed in bariatric patients represents an extreme tail of the population BMI variation. Moreover, future genetic studies focused on bariatric patients may provide valuable insights into the pathogenesis of obesity at a population level.