ProbABEL package for genome-wide association analysis of imputed data

Background: Over the last few years, genome-wide association (GWA) studies became a tool of choice for the identification of loci associated with complex traits. Currently, imputed single nucleotide polymorphisms (SNP) data are frequently used in GWA analyzes. Correct analysis of imputed data calls for the implementation of specific methods which take genotype imputation uncertainty into account.Results: We developed the ProbABEL software package for the analysis of genome-wide imputed SNP data and quantitative, binary, and time-till-event outcomes under linear, logistic, and Cox proportional hazards models, respectively. For quantitative traits, the package also implements a fast two-step mixed model-based score test for association in samples with differential relationships, facilitating analysis in family-based studies, studies performed in human genetically isolated populations and outbred animal populations.Conclusions: ProbABEL package provides fast efficient way to analyze imputed data in genome-wide context and will facilitate future identification of complex trait loci

A Genome-Wide Association Study on Obesity and Obesity-Related Traits

Large-scale genome-wide association studies (GWAS) have identified many loci associated with body mass index (BMI), but few studies focused on obesity as a binary trait. Here we report the results of a GWAS and candidate SNP genotyping study of obesity, including extremely obese cases and never overweight controls as well as families segregating extreme obesity and thinness. We first performed a GWAS on 520 cases (BMI>35 kg/m2) and 540 control subjects (BMI<25 kg/m2), on measures of obesity and obesity-related traits. We subsequently followed up obesity-associated signals by genotyping the top ∼500 SNPs from GWAS in the combined sample of cases, controls and family members totaling 2,256 individuals. For the binary trait of obesity, we found 16 genome-wide significant signals within the FTO gene (strongest signal at rs17817449, P = 2.5×10−12). We next examined obesity-related quantitative traits (such as total body weight, waist circumference and waist to hip ratio), and detected genome-wide significant signals between waist to hip ratio and NRXN3 (rs11624704, P = 2.67×10−9), previously associated with body weight and fat distribution. Our study demonstrated how a relatively small sample ascertained through extreme phenotypes can detect genuine associations in a GWAS

Implications of Central Obesity-Related Variants in LYPLAL1, NRXN3, MSRA, and TFAP2B on Quantitative Metabolic Traits in Adult Danes

Two meta-analyses of genome-wide association studies (GWAS) have suggested that four variants: rs2605100 in lysophospholipase-like 1 (LYPLAL1), rs10146997 in neuroxin 3 (NRXN3), rs545854 in methionine sulfoxide reductase A (MSRA), and rs987237 in transcription factor activating enhancer-binding protein 2 beta (TFAP2B) associate with measures of central obesity. To elucidate potential underlying phenotypes we aimed to investigate whether these variants associated with: 1) quantitative metabolic traits, 2) anthropometric measures (waist circumference (WC), waist-hip ratio, and BMI), or 3) type 2 diabetes, and central and general overweight and obesity.The four variants were genotyped in Danish individuals using KASPar®. Quantitative metabolic traits were examined in a population-based sample (n = 6,038) and WC and BMI were furthermore analyzed in a combined study sample (n = 13,507). Case-control studies of diabetes and adiposity included 15,326 individuals. The major G-allele of LYPLAL1 rs2605100 associated with increased fasting serum triglyceride concentrations (per allele effect (β) = 3%(1;5(95%CI)), p(additive) = 2.7×10(-3)), an association driven by the male gender (p(interaction) = 0.02). The same allele associated with increased fasting serum insulin concentrations (β = 3%(1;5), p(additive) = 2.5×10(-3)) and increased insulin resistance (HOMA-IR) (β = 4%(1;6), p(additive) = 1.5×10(-3)). The minor G-allele of rs10146997 in NRXN3 associated with increased WC among women (β = 0.55cm (0.20;0.89), p(additive) = 1.7×10(-3), p(interaction) = 1.0×10(-3)), but showed no associations with obesity related metabolic traits. The MSRA rs545854 and TFAP2B rs987237 showed nominal associations with central obesity; however, no underlying metabolic phenotypes became obvious, when investigating quantitative metabolic traits. None of the variants influenced the prevalence of type 2 diabetes.We demonstrate that several of the central obesity-associated variants in LYPLAL1, NRXN3, MSRA, and TFAP2B associate with metabolic and anthropometric traits in Danish adults. However, analyses were made without adjusting for multiple testing, and further studies are needed to confirm the putative role of LYPLAL1, NRXN3, MSRA, and TFAP2B in the pathophysiology of obesity

Do Gene Variants Influencing Adult Adiposity Affect Birth Weight? A Population-Based Study of 24 Loci in 4,744 Danish Individuals

Several obesity risk alleles affecting adult adiposity have been identified by the recent wave of genome wide association studies. We aimed to examine the potential effect of these variants on fetal body composition by investigating the variants in relation to birth weight and ponderal index of the newborn.Midwife records from the Danish State Archives provided information on mother's age, parity, as well as birth weight, birth length and prematurity of the newborn in 4,744 individuals of the population-based Inter99 study. Twenty-four risk alleles showing genome-wide associations with adult BMI and/or waist circumference were genotyped. None of the 24 risk variants tested showed an association with birth weight or ponderal index after correction for multiple testing. Birth weight was divided into three categories low (≤10(th) percentile), normal (10(th)-90(th) percentile) and high birth weight (≥90th percentile) to allow for non-linear associations. There was no difference in the number of risk alleles between the groups (p = 0.57). No interactions between each risk allele and birth weight in the prediction of adult BMI were observed. An obesity risk score was created by summing up risk alleles. The risk score did not associate with fetal body composition. Moreover there was no interaction between the risk score and birth weight/ponderal index in the prediction of adult BMI.24 common variants associated with adult adiposity did not affect or interact with birth weight among Danes suggesting that the effects of these variants predominantly arise in the post-natal life

Silencing hepatic MCJ attenuates non-alcoholic fatty liver disease (NAFLD) by increasing mitochondrial fatty acid oxidation

Nonalcoholic fatty liver disease (NAFLD) is considered the next major health epidemic with an estimated 25% worldwide prevalence. No drugs have yet been approved and NAFLD remains a major unmet need. Here, we identify MCJ (Methylation-Controlled J protein) as a target for non-alcoholic steatohepatitis (NASH), an advanced phase of NAFLD. MCJ is an endogenous negative regulator of the respiratory chain Complex I that acts to restrain mitochondrial respiration. We show that therapeutic targeting of MCJ in the liver with nanoparticle- and GalNAc-formulated siRNA efficiently reduces liver lipid accumulation and fibrosis in multiple NASH mouse models. Decreasing MCJ expression enhances the capacity of hepatocytes to mediate beta -oxidation of fatty acids and minimizes lipid accumulation, which results in reduced hepatocyte damage and fibrosis. Moreover, MCJ levels in the liver of NAFLD patients are elevated relative to healthy subjects. Thus, inhibition of MCJ emerges as an alternative approach to treat NAFLD. Non-alcoholic fatty liver (NAFLD) disease causes degeneration of the liver, affects about 25% of people globally, and has no approved treatment. Here, the authors show that the therapeutic siRNA-driven silencing of MCJ in the liver is an effective and safe treatment for NAFLD in multiple mouse models.We thank Douglas Taatjes and Nicole Bouffard for help with confocal microscopy analysis (Microscopy Imaging Center) at the University of Vermont. We also thank the University of Vermont Medical Center's Department of Pathology and Laboratory Medicine Histology and Clinical Laboratories for assistance with liver section staining and AST/ALT measurement, respectively. This work was supported by NIH STTR R41DK112429 (M.R.), NIH PO GM103496 (M.R.), Mitotherapeutix LLC (M.R., K.F, and M.L.M.-C.), MINECO/Feder SAF2015-65327-R and RTI2018-096494-B-100 (J.A.), MINECO/Feder SAF2017-87301-R (M.L.M-C.), BIOEF (M.L.M.-C.), EITB Maratoia BIO15/CA/014 (M.L.M-C), BBVA (M.L.M.-C.), La Caixa Foundation (M.L.M.-C.), Basque Country Health Department 2013111114 (M.L.M-C), MINECO/Feder SAF2015-64352-R (P.A.) and MINECO-Feder RTI2018-095134-B-100 (P.A.). ISCIII-Feder PI17/00535 (C.G.-M.), ISCIII-Feder CP14/00181, and PI16/00823 (A.G-R.), and Francisco Cobos Foundation (A.G.-R.). CIC bioGUNE is the recipient of a Severo Ochoa Excellence Accreditation (SEV-2016-0644) by the Ministry of Science, Innovation and Universities

PedHunter 2.0 and its usage to characterize the founder structure of the Old Order Amish of Lancaster County

<p>Abstract</p> <p>Background</p> <p>Because they are a closed founder population, the Old Order Amish (OOA) of Lancaster County have been the subject of many medical genetics studies. We constructed four versions of Anabaptist Genealogy Database (AGDB) using three sources of genealogies and multiple updates. In addition, we developed PedHunter, a suite of query software that can solve pedigree-related problems automatically and systematically.</p> <p>Methods</p> <p>We report on how we have used new features in PedHunter to quantify the number and expected genetic contribution of founders to the OOA. The queries and utility of PedHunter programs are illustrated by examples using AGDB in this paper. For example, we calculated the number of founders expected to be contributing genetic material to the present-day living OOA and estimated the mean relative founder representation for each founder. New features in PedHunter also include pedigree trimming and pedigree renumbering, which should prove useful for studying large pedigrees.</p> <p>Results</p> <p>With PedHunter version 2.0 querying AGDB version 4.0, we identified 34,160 presumed living OOA individuals and connected them into a 14-generation pedigree descending from 554 founders (332 females and 222 males) after trimming. From the analysis of cumulative mean relative founder representation, 128 founders (78 females and 50 males) accounted for over 95% of the mean relative founder contribution among living OOA descendants.</p> <p>Discussion/Conclusions</p> <p>The OOA are a closed founder population in which a modest number of founders account for the genetic variation present in the current OOA population. Improvements to the PedHunter software will be useful in future studies of both the OOA and other populations with large and computerized genealogies.</p

The Genetics of Obesity

Obesity is a result of excess body fat accumulation. This excess is associated with adverse health effects such as CVD, type 2 diabetes, and cancer. The development of obesity has an evident environmental contribution, but as shown by heritability estimates of 40% to 70%, a genetic susceptibility component is also needed. Progress in understanding the etiology has been slow, with findings largely restricted to monogenic, severe forms of obesity. However, technological and analytical advances have enabled detection of more than 20 obesity susceptibility loci. These contain genes suggested to be involved in the regulation of food intake through action in the central nervous system as well as in adipocyte function. These results provide plausible biological pathways that may, in the future, be targeted as part of treatment or prevention strategies. Although the proportion of heritability explained by these genes is small, their detection heralds a new phase in understanding the etiology of common obesity

Linkage analysis of obesity phenotypes in pre- and post-menopausal women from a United States mid-western population

<p>Abstract</p> <p>Background</p> <p>Obesity has a strong genetic influence, with some variants showing stronger associations among women than men. Women are also more likely to distribute weight in the abdomen following menopause. We investigated whether genetic loci link with obesity-related phenotypes differently by menopausal status.</p> <p>Methods</p> <p>We performed univariate and bivariate linkage analysis for the phenotypes of body mass index (BMI), waist (W) and hip (H) circumferences (WC, HC), and WH ratio (WHR) separately among 172 pre-menopausal and 405 post-menopausal women from 90 multigenerational families using a genome scan with 403 microsatellite markers. Bivariate analysis used pair-wise combinations of obesity phenotypes to detect linkage at loci with pleiotropic effects for genetically correlated traits. BMI was adjusted in models of WC, HC and WHR.</p> <p>Results</p> <p>Pre-menopausal women, compared to post-menopausal women, had higher heritability for BMI (<it>h</it>²= 94% versus <it>h</it>²= 39%, respectively) and for HC (<it>h</it>²= 99% versus <it>h</it>²= 43%, respectively), and lower heritability for WC (<it>h</it>²= 29% versus <it>h</it>²= 61%, respectively) and for WHR (<it>h</it>²= 39% versus <it>h</it>²= 57%, respectively). Among pre-menopausal women, the strongest evidence for linkage was for the combination of BMI and HC traits at 3p26 (bivariate LOD = 3.65) and at 13q13-q14 (bivariate LOD = 3.59). Among post-menopausal women, the highest level of evidence for genetic linkage was for HC at 4p15.3 (univariate LOD = 2.70) and 14q13 (univariate LOD = 2.51). WC was not clearly linked to any locus.</p> <p>Conclusions</p> <p>These results support a genetic basis for fat deposition that differs by menopausal status, and suggest that the same loci encode genes that influence general obesity (BMI) and HC, specifically, among pre-menopausal women. However, lower heritability among pre-menopausal women for WC and WHR suggests that pre-menopausal waist girth may be influenced to a greater extent by controllable environmental factors than post-menopausal waist girth. Possibly, targeted interventions for weight control among pre-menopausal women may prevent or attenuate post-menopausal abdominal weight deposition.</p

Association of genetic variation in FTO with risk of obesity and type 2 diabetes with data from 96,551 East and South Asians

Aims/hypothesis: $FTO$ harbours the strongest known obesity-susceptibility locus in Europeans. While there is growing evidence for a role for $FTO$ in obesity risk in Asians, its association with type 2 diabetes, independently of BMI, remains inconsistent. To test whether there is an association of the $FTO$ locus with obesity and type 2 diabetes, we conducted a meta-analysis of 32 populations including 96,551 East and South Asians. Methods: All studies published on the association between $FTO$-rs9939609 (or proxy [r$^2$ > 0.98]) and BMI, obesity or type 2 diabetes in East or South Asians were invited. Each study group analysed their data according to a standardised analysis plan. Association with type 2 diabetes was also adjusted for BMI. Random-effects meta-analyses were performed to pool all effect sizes. Results: The $FTO$-rs9939609 minor allele increased risk of obesity by 1.25-fold/allele (p = 9.0 × 10$^{−19}$), overweight by 1.13-fold/allele (p = 1.0 × 10$^{−11}$) and type 2 diabetes by 1.15-fold/allele (p = 5.5 × 10$^{−8}$). The association with type 2 diabetes was attenuated after adjustment for BMI (OR 1.10-fold/allele, p = 6.6 × 10$^{−5}$). The $FTO$-rs9939609 minor allele increased BMI by 0.26 kg/m2 per allele (p = 2.8 × 10$^{−17}$), WHR by 0.003/allele (p = 1.2 × 10$^{−6}$), and body fat percentage by 0.31%/allele (p = 0.0005). Associations were similar using dominant models. While the minor allele is less common in East Asians (12–20%) than South Asians (30–33%), the effect of $FTO$ variation on obesity-related traits and type 2 diabetes was similar in the two populations. Conclusions/interpretation: $FTO$ is associated with increased risk of obesity and type 2 diabetes, with effect sizes similar in East and South Asians and similar to those observed in Europeans. Furthermore, $FTO$ is also associated with type 2 diabetes independently of BMI. Electronic supplementary material The online version of this article (doi:10.1007/s00125-011-2370-7) contains peer-reviewed but unedited supplementary material, which is available to authorised users