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Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioral traits and the disease etiology of neuropsychiatric disorders. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits such as sleeping, smoking, feelings, alcohol intake, mental health, and psychiatric disorders. Integrating with established drug information, we validated 13 out of 13 matched combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets. This consortium effort provides a large-scale proteogenomic resource for biomedical research on human behaviors and other neuro-related phenotypes.

We performed a genome-wide association study of 143,067 highly polymorphic short tandem repeats (STRs) with MRI brain grey matter volumes (GMVs) on 10,702 UK Biobank (UKB) participants, including 8,751 in the discovery stage and 1,701 in the replication analysis. STRs’ repeat lengths were estimated from the UKB whole-genome sequencing data using Expansion Hunter software.A total of 262 STRs reached genome-wide significance in the analyses of the autosomal and sex chromosomes’ (P= 6.9 × 10−8) in association with MRI -GMVs. Replication in a second batch extraction in the UKB and linkage disequilibrium (LD) analyses confirmed 12 associations of five STRs with hippocampal, intra-calcarine cortex, and cerebellum volumes with no evidence of single nucleotide polymorphisms (SNP) in LD detected in the surrounding DNA regions. Our study highlights the importance of STR variants involved in the genetic architecture of grey matter volumes.

Observational population studies indicate that prevention of dementia and cognitive decline is being accomplished, possibly as an unintended result of better vascular prevention and healthier lifestyles. Population aging in the coming decades requires deliberate efforts to further decrease its prevalence and societal burden. Increasing evidence supports the efficacy of preventive interventions on persons with intact cognition and high dementia risk. We report recommendations for the deployment of second-generation memory clinics (Brain Health Services) whose mission is evidence-based and ethical dementia prevention in at-risk individuals. The cornerstone interventions consist of (i) assessment of genetic and potentially modifiable risk factors including brain pathology, and risk stratification, (ii) risk communication with ad-hoc protocols, (iii) risk reduction with multi-domain interventions, and (iv) cognitive enhancement with cognitive and physical training. A roadmap is proposed for concept validation and ensuing clinical deployment.

BACKGROUND: In a substantial subgroup of depressed patients, atypical, energy-related depression symptoms (e.g. increased appetite/weight, hypersomnia, loss of energy) tend to cluster with immuno-metabolic dysregulations (e.g. increased BMI and inflammatory markers). This clustering is proposed to reflect a more homogeneous depression pathology. This study examines to what extent energy-related symptoms are associated and share sociodemographic, lifestyle and clinical characteristics.METHODS: Data were available from 13,965 participants from eight Dutch cohorts with DSM-5 lifetime major depression assessed by the Lifetime Depression Assessment Self-report (LIDAS) questionnaire. Information on four energy-related depression symptoms were extracted: energy loss, increased appetite, increased weight, and hypersomnia. Tetrachoric correlations between these symptoms, and associations of these symptoms with sociodemographic (sex, age, education), lifestyle (physical activity, BMI, smoking) and clinical characteristics (age of onset, episode duration, history, treatment and recency, and self-reported comorbidity) were computed.RESULTS: Correlations between energy-related symptoms were overall higher than those with other depression symptoms and varied from 0.90 (increased appetite vs increased weight) to 0.11 (increased appetite vs energy loss). All energy-related symptoms were strongly associated with higher BMI and a more severe clinical profile. Patients with increased appetite were more often smokers, and only patients with increased appetite or weight more often had a self-reported diagnosis of PTSD (OR = 1.17, p = 2.91E-08) and eating disorder (OR = 1.40, p = 4.08E-17).CONCLUSIONS: The symptom-specific associations may have consequences for a profile integrating these symptoms, which can be used to reflect immuno-metabolic depression. They indicate the need to study immuno-metabolic depression at individual symptom resolution as a starting point.

Augmenting traditional genome wide association studies (GWAS) with advanced machine learning algorithms can allow the detection of novel signals in available cohorts by providing complementary approaches to the existing methods. We introduce “Genome wide association neural networks (GWANN)”, a novel approach that uses neural networks (NNs) to account for nonlinear and SNP-SNP interaction effects. We applied GWANN to family history of Alzheimer’s disease (AD) in the UK Biobank. Our method identified 26 known AD genes, 2 target nominations and 67 novel genes, and validated the results against brain eQTLs, AD phenotype associations, biological pathways, disease associations and differentially expressed gene sets in the AD brain. Some drugs targeting novel GWANN hits are currently in clinical trials for AD. Applying NNs for GWAS, alongside existing methods, illustrates their potential to complement existing algorithms and methods, and enable the discovery of novel and tractable targets for AD.

This document describes the contribution of clinical criteria to the interpretation of genetic variants using heritable Mendelian cardiomyopathies as an example. The aim is to assist cardiologists in defining the clinical contribution to a genetic diagnosis and the interpretation of molecular genetic reports. The identification of a genetic variant of unknown or uncertain significance is a limitation of genetic testing, but current guidelines for the interpretation of genetic variants include essential contributions from clinical family screening that can establish a de novo assignment of the variant or its segregation with the phenotype in the family. A partnership between clinicians and patients helps to solve major uncertainties and provides reliable and clinically actionable information.

Using genome-wide association data, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s (PD) or Alzheimer’s (AD) disease versus controls across ancestry groups. A shared genetic association was observed across diseases at rs601945 (PD: odds ratio (OR)=0.84; 95% confidence interval, [0.80; 0.88]; p=2.2x10-13; AD: OR=0.91[0.89; 0.93]; p=1.8x10-22), and with a protective HLA association recently reported in amyotrophic lateral sclerosis (ALS). Hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03, and absent for HLA-DRB1*04:05. The same signal was associated with decreased neurofibrillary tangles (but not neuritic plaque density) in postmortem brains and was more strongly associated with tau levels than Aβ42 levels in the cerebrospinal fluid. Finally, protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, but only when acetylated at K311, a modification central to aggregation. An HLA-DRB1*04-mediated adaptive immune response, potentially against tau, decreases PD, AD and ALS risk, offering the possibility of new therapeutic avenues.

Hypertension is a leading cause of premature death affecting more than a billion individuals worldwide. Here we report on the genetic determinants of blood pressure (BP) traits (systolic, diastolic, and pulse pressure) in the largest single-stage genome-wide analysis to date (N = 1,028,980 European-descent individuals). We identified 2,103 independent genetic signals (P − 8) for BP traits, including 113 novel loci. These associations explain ~ 40% of common SNP heritability of systolic and diastolic BP. Comparison of top versus bottom deciles of polygenic risk scores (PRS) based on these results reveal clinically meaningful differences in BP (12.9 mm Hg for systolic BP, 95% CI 11.5–14.2 mm Hg, p = 9.08×10− 73) and hypertension risk (OR 5.41; 95% CI 4.12 to 7.10; P = 9.71×10− 33) in an independent dataset. Compared with the area under the curve (AUC) for hypertension discrimination for a model with sex, age, BMI, and genetic ancestry, adding systolic and diastolic BP PRS increased discrimination from 0.791 (95% CI = 0.781–0.801) to 0.814 (95% CI = 0.805–0.824, ∆AUC = 0.023, P = 2.27x10− 22). Our transcriptome-wide association study detected 2,793 BP colocalized associations with genetically-predicted expression of 1,070 genes in five cardiovascular tissues, of which 500 are previously unreported for BP traits. These findings represent an advance in our understanding of hypertension and highlight the role of increasingly large genomic studies for development of more accurate PRS, which may inform precision health research.

There is a growing body of evidence highlighting there are significant changes in the gut microbiota composition and relative abundance in various neurological disorders. We performed a systematic review of the different microbiota altered in a wide range of neurological disorders (Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis, and stroke). Fifty-two studies were included representing 5496 patients. At the genus level, the most frequently involved microbiota are Akkermansia, Faecalibacterium, and Prevotella. The overlap between the pathologies was strongest for MS and PD, sharing eight genera (Akkermansia, Butyricicoccus, Bifidobacterium, Coprococcus, Dorea, Faecalibacterium, Parabacteroides, and Prevotella) and PD and stroke, sharing six genera (Enterococcus, Faecalibacterium, Lactobacillus, Parabacteroides, Prevotella, and Roseburia). The identification signatures overlapping for AD, PD, and MS raise the question of whether these reflect a common etiology or rather common consequence of these diseases. The interpretation is hampered by the low number and low power for AD, ALS, and stroke with ample opportunity for false positive and false negative findings.

BACKGROUND: Depression has been associated with metabolic alterations, which adversely impact cardiometabolic health. Here, a comprehensive set of metabolic markers, predominantly lipids, was compared between depressed and nondepressed persons.METHODS: Nine Dutch cohorts were included, comprising 10,145 control subjects and 5283 persons with depression, established with diagnostic interviews or questionnaires. A proton nuclear magnetic resonance metabolomics platform provided 230 metabolite measures: 51 lipids, fatty acids, and low-molecular-weight metabolites; 98 lipid composition and particle concentration measures of lipoprotein subclasses; and 81 lipid and fatty acids ratios. For each metabolite measure, logistic regression analyses adjusted for gender, age, smoking, fasting status, and lipid-modifying medication were performed within cohort, followed by random-effects meta-analyses.RESULTS: Of the 51 lipids, fatty acids, and low-molecular-weight metabolites, 21 were significantly related to depression (false discovery rate q < .05). Higher levels of apolipoprotein B, very-low-density lipoprotein cholesterol, triglycerides, diglycerides, total and monounsaturated fatty acids, fatty acid chain length, glycoprotein acetyls, tyrosine, and isoleucine and lower levels of high-density lipoprotein cholesterol, acetate, and apolipoprotein A1 were associated with increased odds of depression. Analyses of lipid composition indicators confirmed a shift toward less high-density lipoprotein and more very-low-density lipoprotein and triglyceride particles in depression. Associations appeared generally consistent across gender, age, and body mass index strata and across cohorts with depressive diagnoses versus symptoms.CONCLUSIONS: This large-scale meta-analysis indicates a clear distinctive profile of circulating lipid metabolites associated with depression, potentially opening new prevention or treatment avenues for depression and its associated cardiometabolic comorbidity.

We conducted a large multi-ethnic meta-analysis of genome-wide association studies for primary open-angle glaucoma (POAG) on a total of 34,179 cases vs 349,321 controls, and identified 127 independent risk loci, almost doubling the number of known loci for POAG. The majority of loci have broadly consistent effect across European, Asian and African ancestries. We identify a link, both genome-wide and at specific loci, between POAG and Alzheimer’s disease. Gene expression data and bioinformatic functional analyses provide further support for the functional relevance of the POAG risk genes. Several drug compounds target these risk genes and may be potential candidates for developing novel POAG treatments.

Supplemental Digital Content is available in the text., Background: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D). Methods: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D). Results: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background. Conclusions: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.

Introduction The genetic architecture of Alzheimer's disease (AD) is only partially understood. Methods We conducted an association study for AD using whole sequence data from 507 genetically enriched AD cases (i.e., cases having close relatives affected by AD) and 4917 cognitively healthy controls of European ancestry (EA) and 172 enriched cases and 179 controls of Caribbean Hispanic ancestry. Confirmation of top findings from stage 1 was sought in two family-based genome-wide association study data sets and in a whole genome–sequencing data set comprising members from 42 EA and 115 Caribbean Hispanic families. Results We identified associations in EAs with variants in 12 novel loci. The most robust finding is a rare CASP7 missense variant (rs116437863; P = 2.44 × 10−10) which improved when combined with results from stage 2 data sets (P = 1.92 × 10−10). Discussion Our study demonstrated that an enriched case design can strengthen genetic signals, thus allowing detection of associations that would otherwise be missed in a traditional case-control study.

The Glu to Lys change at codon 200 (E200K) of theWe searched for other genes by performing genome-wide analyses (GWA) on 19 patients with genetic CJD and 18 healthy subjects carrying the E200K mutation ofWe identified two single nucleotide polymorphisms on the

Contains fulltext : 153490.pdf (Publisher’s version ) (Closed access) Our objective was to design a genotyping platform that would allow rapid genetic characterization of samples in the context of genetic mutations and risk factors associated with common neurodegenerative diseases. The platform needed to be relatively affordable, rapid to deploy, and use a common and accessible technology. Central to this project, we wanted to make the content of the platform open to any investigator without restriction. In designing this array we prioritized a number of types of genetic variability for inclusion, such as known risk alleles, disease-causing mutations, putative risk alleles, and other functionally important variants. The array was primarily designed to allow rapid screening of samples for disease-causing mutations and large population studies of risk factors. Notably, an explicit aim was to make this array widely available to facilitate data sharing across and within diseases. The resulting array, NeuroX, is a remarkably cost and time effective solution for high-quality genotyping. NeuroX comprises a backbone of standard Illumina exome content of approximately 240,000 variants, and over 24,000 custom content variants focusing on neurologic diseases. Data are generated at approximately $50-$60 per sample using a 12-sample format chip and regular Infinium infrastructure; thus, genotyping is rapid and accessible to many investigators. Here, we describe the design of NeuroX, discuss the utility of NeuroX in the analyses of rare and common risk variants, and present quality control metrics and a brief primer for the analysis of NeuroX derived data.

The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio (WHR) adjusted for body mass index. These loci are wide and narrowingthe signalsremains necessary. Twelve of 14 loci identified inGIANTEA samples retained strong associations with WHR in our joint EA/individuals of African Ancestry (AA) analysis (log-Bayes factor >6.1). Transethnic analysesatfiveloci (TBX15-WARS2, LYPLAL1, ADAMTS9, LY86andITPR2-SSPN)substantially narrowed the signals to smaller sets of variants, some of which are in regions that have evidence of regulatory activity. By leveraging varying linkage disequilibrium structures across different populations, single-nucleotide polymorphisms (SNPs) with strong signals and narrower credible sets from trans-ethnic meta-analysis of central obesity provide more precise localizations of potential functional variants and suggest a possible regulatory role. Meta-analysis results for WHR were obtained from 77 167 EA participants from GIANT and 23 564 AA participants from the AfricanAncestry Anthropometry Genetics Consortium. For fine mapping we interrogatedSNPs within ±250 kbflanking regionsof 14 previously reported indexSNPsfrom loci discovered in EApopulations by performing trans-ethnic meta-analysis of results from the EA and AA meta-analyses. We applied a Bayesian approach that leverages allelic heterogeneity across populations to combine meta-analysis results and aids in fine-mapping shared variants at these locations. We annotated variants using information from the ENCODE Consortium and Roadmap Epigenomics Project to prioritize variants for possible functionality. © The Author 2014. Published by Oxford University Press. All rights reserved.

Objective A large body of epidemiologic data strongly suggests an association between excess adiposity and coronary artery disease (CAD). Low adiponectin levels, a hormone secreted only from adipocytes, have been associated with an increased risk of CAD in observational studies. However, these associations cannot clarify whether this relationship is causal or due to a shared set of causal factors or even confounding. Genome-wide association studies have identified common variants that influence adiponectin levels, providing valuable tools to examine the genetic relationship between adiponectin and CAD. Methods Using 145 genome wide significant SNPs for adiponectin from the ADIPOGen consortium ( n = 49,891), we tested whether adiponectin-decreasing alleles influenced risk of CAD in the CARDIoGRAM consortium ( n = 85,274). Results In single-SNP analysis, 5 variants among 145 SNPs were associated with increased risk of CAD after correcting for multiple testing ( P −4 ). Using a multi-SNP genotypic risk score to test whether adiponectin levels and CAD have a shared genetic etiology, we found that adiponectin-decreasing alleles increased risk of CAD ( P = 5.4 × 10 −7 ). Conclusion These findings demonstrate that adiponectin levels and CAD have a shared allelic architecture and provide rationale to undertake a Mendelian randomization studies to understand if this relationship is causal.

Aims/hypothesis Tobacco smoking, a risk factor for diabetes, is an established modifier of DNA methylation. We hypothesised that tobacco smoking modifies DNA methylation of genes previously identified for diabetes. Methods We annotated CpG sites available on the Illumina Human Methylation 450K array to diabetes genes previously identified by genome-wide association studies (GWAS), and investigated them for an association with smoking by comparing current to never smokers. The discovery study consisted of 630 individuals (Bonferroni-corrected p = 1.4 × 10−5), and we sought replication in an independent sample of 674 individuals. The replicated sites were tested for association with nearby genetic variants and gene expression and fasting glucose and insulin levels. Results We annotated 3,620 CpG sites to the genes identified in the GWAS on type 2 diabetes. Comparing current smokers to never smokers, we found 12 differentially methylated CpG sites, of which five replicated: cg23161492 within ANPEP (p = 1.3 × 10−12); cg26963277 (p = 1.2 × 10−9), cg01744331 (p = 8.0 × 10−6) and cg16556677 (p = 1.2 × 10−5) within KCNQ1 and cg03450842 (p = 3.1 × 10−8) within ZMIZ1. The effect of smoking on DNA methylation at the replicated CpG sites attenuated after smoking cessation. Increased DNA methylation at cg23161492 was associated with decreased gene expression levels of ANPEP (p = 8.9 × 10−5). rs231356-T, which was associated with hypomethylation of cg26963277 (KCNQ1), was associated with a higher odds of diabetes (OR 1.06, p = 1.3 × 10−5). Additionally, hypomethylation of cg26963277 was associated with lower fasting insulin levels (p = 0.04). Conclusions/interpretation Tobacco smoking is associated with differential DNA methylation of the diabetes risk genes ANPEP, KCNQ1 and ZMIZ1. Our study highlights potential biological mechanisms connecting tobacco smoking to excess risk of type 2 diabetes. Electronic supplementary material The online version of this article (doi:10.1007/s00125-016-3872-0) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

The methylome is subject to genetic and environmental effects. Their impact may depend on sex and age, resulting in sex- and age-related physiological variation and disease susceptibility. Here we estimate the total heritability of DNA methylation levels in whole blood and estimate the variance explained by common single nucleotide polymorphisms at 411,169 sites in 2,603 individuals from twin families, to establish a catalogue of between-individual variation in DNA methylation. Heritability estimates vary across the genome (mean=19%) and interaction analyses reveal thousands of sites with sex-specific heritability as well as sites where the environmental variance increases with age. Integration with previously published data illustrates the impact of genome and environment across the lifespan at methylation sites associated with metabolic traits, smoking and ageing. These findings demonstrate that our catalogue holds valuable information on locations in the genome where methylation variation between people may reflect disease-relevant environmental exposures or genetic variation., Differential impact of genetic and environmental influences on DNA methylation may result in sex- and age-related physiological variation and disease susceptibility. By analysing DNA methylome of 2,603 individuals from twin families, here, the authors establish a catalogue of between-individual variation in DNA methylation.

It has recently been suggested that the low-frequency c.136–14_136–13insC variant in high-mobility group A1 (HMGA1) may strongly contribute to insulin resistance and type 2 diabetes risk. In our study, we attempted to confirm that HMGA1 is a novel type 2 diabetes locus in French Caucasians. The gene was sequenced in 368 type 2 diabetic case subjects with a family history of type 2 diabetes and 372 normoglycemic control subjects without a family history of type 2 diabetes. None of the 41 genetic variations identified were associated with type 2 diabetes. The lack of association between the c.136–14_136–13insC variant and type 2 diabetes was confirmed in an independent French group of 4,538 case subjects and 4,015 control subjects and in a large meta-analysis of 16,605 case subjects and 46,179 control subjects. Finally, this variant had no effects on metabolic traits and was not involved in variations of HMGA1 and insulin receptor (INSR) expressions. The c.136–14_136–13insC variant was not associated with type 2 diabetes in individuals of European descent. Our study emphasizes the need to analyze a large number of subjects to reliably assess the association of low-frequency variants with the disease.

Background Despite extensive research on the genetic determinants of glaucoma, the genes identified to date explain only a small proportion of cases in the general population. Methods Genome-wide linkage and association analyses of quantitative traits related to glaucoma were performed: intraocular pressure, size and morphology of the optic disc (individual and combined by method of principal components) and thickness of the retinal nerve fibre layer (RNFL), in a large pedigree from a genetically isolated Dutch population. Results For the size of the optic disc, the study demonstrated a significant linkage signal (logarithm of odds (LOD) = 3.6) at the LRP1B region on chromosome 2q21.2-q22.2 and significant association (p = 8.95 x 10(-12)) with the previously reported CDC7/TGFBR3 locus at 1p22. For parameters describing morphology of the optic disc, the study obtained significant linkage signal (LOD = 4.6) at regions SIRPA and RNF24/PANK2 at 20p13 (false discovery rate (FDR) based q value < 0.05) and genome-wide significant association (p = 2.38 x 10(-9)) with a common variant in the RERE gene at 1p36. Suggestive linkage and association signals indicated loci for morphology of the optic disc at 2q31-q33 (IGFBP2 locus) and for RNFL thickness at 3p22.2 (DCLK3 locus) and 14q22-q23 (SIX1 locus). Conclusion This study identified new linkage regions at 20p13 (SIRPA and RNF24/PANK2 loci) and 2q33-q34 (IGFBP2 locus) for parameters describing morphology of the optic disc. The results of the study also suggested common genetic control of these parameters and RNFL thickness by SIX1 and doublecotin family genes. Finally, association signals for the recently reported RERE and LRP1B loci and the well known CDC7, TGFBR3, and ATOH7 loci were replicated.

In order to meaningfully analyze common and rare genetic variants, results from genome-wide association studies (GWASASs) of multiple cohorts need to be combined in a meta-analysis in order to obtain enough power. This requires all cohorts to have the same single-nucleotide polymorphisms (SNPSNPSNPs) in their GWASASs. To this end, genotypes that have not been measured in a given cohort can be imputed on the basis of a set of reference haplotypes. This protocol provides guidelines for performing imputations with two widely used tools: minimac and IMPUTEPUTEPUTEPUTE2. These guidelines were developed and used by the Genome of the Netherlands (GoNL) consortium, which has created a population-specific reference panel for genetic imputations and used this reference to impute various Dutch biobanks. We also describe several factors that might influence the final imputation quality. This protocol, which has been used by the largest Dutch biobanks, should take approximately several days, depending on the sample size of the biobank and the computer resources available.

Background: Individuals with exceptional longevity and their offspring have significantly larger high-density lipoprotein concentrations (HDL-C) particle sizes due to the increased homozygosity for the I405V variant in the cholesteryl ester transfer protein (CETP) gene. In this study, we investigate the association of CETP and HDL-C further to identify novel, independent CETP variants associated with HDL-C in humans. Methods: We performed a meta-analysis of HDL-C within the CETP region using 59,432 individuals imputed with 1000 Genomes data. We performed replication in an independent sample of 47,866 individuals and validation was done by Sanger sequencing. Results: The meta-analysis of HDL-C within the CETP region identified five independent variants, including an exonic variant and a common intronic insertion. We replicated these 5 variants significantly in an independent sample of 47,866 individuals. Sanger sequencing of the insertion within a single family confirmed segregation of this variant. The strongest reported association between HDL-C and CETP variants, was rs3764261; however, after conditioning on the five novel variants we identified the support for rs3764261 was highly reduced (βunadjusted=3.179 mg/dl (P value=5.25×10−509), βadjusted=0.859 mg/dl (P value=9.51×10−25)), and this finding suggests that these five novel variants may partly explain the association of CETP with HDL-C. Indeed, three of the five novel variants (rs34065661, rs5817082, rs7499892) are independent of rs3764261. Conclusions: The causal variants in CETP that account for the association with HDL-C remain unknown. We used studies imputed to the 1000 Genomes reference panel for fine mapping of the CETP region. We identified and validated five variants within this region that may partly account for the association of the known variant (rs3764261), as well as other sources of genetic contribution to HDL-C.

Background Brain‐derived neurotrophic factor ( BDNF ) is a pleiotropic peptide involved in maintaining endothelial integrity. It is unknown if circulating BDNF levels are associated with risk of cardiovascular disease ( CVD ). Methods and Results We prospectively investigated the association of circulating BDNF levels with cardiovascular events and mortality in 3687 participants (mean age 65 years, 2068 women) from the Framingham Heart Study ( FHS ). Using a common nonsynonomous single nucleotide polymorphism ( SNP ) in the BDNF gene (rs6265), we then performed a Mendelian randomization experiment in the CARDIoGRAM (Coronary ARtery DIsease Genome‐Wide Replication And Meta‐Analysis) consortium (>22 000 coronary artery disease [ CAD ] cases, >60 000 controls) to investigate whether SNP rs6265 was associated with CAD in CARDIoGRAM and, if so, whether the effect estimate differed from that predicted based on FHS data. On follow‐up (median 8.9 years), 467 individuals (261 women) in FHS experienced a CVD event, and 835 (430 women) died. In multivariable‐adjusted Cox regression, serum BDNF was associated inversely with CVD risk (hazard ratio [ HR ] per 1‐ SD increase 0.88, 95% CI 0.80 to 0.97, P =0.01) and with mortality ( HR 0.87, 95% CI 0.80 to 0.93, P =0.0002). SNP rs6265 was associated with BDNF concentrations (0.772 ng/mL increase per minor allele copy) in FHS . In CARDIoGRAM, SNP rs6265 was associated with CAD (odds ratio 0.957, 95% CI 0.923 to 0.992), a magnitude consistent with the predicted effect ( HR per minor allele copy 0.99, 95% CI 0.98 to 1.0; P =0.06 for difference between predicted and observed effect). Conclusion Higher serum BDNF is associated with a decreased risk of CVD and mortality. Mendelian randomization suggests a causal protective role of BDNF in the pathogenesis of CVD .

Background Migraine is a common comorbidity among individuals with bipolar disorder, but the underlying mechanisms for this co-occurrence are poorly understood. The aim of this study was to investigate the genetic background of bipolar patients with and without migraine. Methods We performed a genome-wide association analysis contrasting 460 bipolar migraneurs with 914 bipolar patients without migraine from the Bipolar Genome Study (BiGS). Results We identified one genome-wide significant association between migraine in bipolar disorder patients and rs1160720, an intronic single nucleotide polymorphism (SNP) in the NBEA gene ( P =2.97×10 −8 , OR: 1.82, 95% CI: 1.47–2.25), although this was not replicated in a smaller sample of 289 migraine cases. Limitations Our study is based on self-reported migraine. Conclusions NBEA encodes neurobeachin, a scaffolding protein primarily expressed in the brain and involved in trafficking of vesicles containing neurotransmitter receptors. This locus has not previously been implicated in migraine per se. We found no evidence of association in data from the GWAS migraine meta-analysis consortium ( n =118,710 participants) suggesting that the association might be specific to migraine co-morbid with bipolar disorder.

Background Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) that associate with clinical phenotypes, but these SNPs usually explain just a small part of the heritability and have relatively modest effect sizes. In contrast, SNPs that associate with metabolite levels generally explain a higher percentage of the genetic variation and demonstrate larger effect sizes. Still, the discovery of SNPs associated with metabolite levels is challenging since testing all metabolites measured in typical metabolomics studies with all SNPs comes with a severe multiple testing penalty. We have developed an automated workflow approach that utilizes prior knowledge of biochemical pathways present in databases like KEGG and BioCyc to generate a smaller SNP set relevant to the metabolite. This paper explores the opportunities and challenges in the analysis of GWAS of metabolomic phenotypes and provides novel insights into the genetic basis of metabolic variation through the re-analysis of published GWAS datasets. Results Re-analysis of the published GWAS dataset from Illig et al. (Nature Genetics, 2010) using a pathway-based workflow (http://www.myexperiment.org/packs/319.html), confirmed previously identified hits and identified a new locus of human metabolic individuality, associating Aldehyde dehydrogenase family1 L1 (ALDH1L1) with serine/glycine ratios in blood. Replication in an independent GWAS dataset of phospholipids (Demirkan et al., PLoS Genetics, 2012) identified two novel loci supported by additional literature evidence: GPAM (Glycerol-3 phosphate acyltransferase) and CBS (Cystathionine beta-synthase). In addition, the workflow approach provided novel insight into the affected pathways and relevance of some of these gene-metabolite pairs in disease development and progression. Conclusions We demonstrate the utility of automated exploitation of background knowledge present in pathway databases for the analysis of GWAS datasets of metabolomic phenotypes. We report novel loci and potential biochemical mechanisms that contribute to our understanding of the genetic basis of metabolic variation and its relationship to disease development and progression.

Summary Background Vascular disorders have been implicated in dementia, but whether atherosclerosis is related to the most frequent type of dementia, Alzheimer's disease, is not known. The apolipoprotein-E genotype has been associated with Alzheimer's disease, and we postulate that it plays a part, together with atherosclerosis, in the aetiology of Alzheimer's disease. We investigated the frequency of dementia and its subtypes in relation to atherosclerosis and apolipoprotein E. Methods We did a population-based study of 284 patients with dementia, 207 of whom had Alzheimer's disease, and 1698 individuals who were not demented. Indicators of atherosclerosis included vessel wall thickness and plaques of the carotid arteries, assessed by ultrasonography, and the ratio of ankle-to-brachial systolic blood pressure as a measure of generalised atherosclerosis. Based on these indicators participants were scored from 0 (no atherosclerosis) to 3 (severe atherosclerosis) for degree of atherosclerosis. Apolipoprotein-E polymorphisms were assessed in 246 patients and in 928 controls. Findings All indicators of atherosclerosis were associated with dementia (odds ratios ranging from 1·3 to 1·9) and its major subtypes Alzheimer's disease (odds ratios 1·3–1·8) and vascular dementia (odds ratios 1·9–3·2). The frequencies of all dementia, Alzheimer's disease, and vascular dementia increased with the degree of atherosclerosis. The odds ratio for Alzheimer's disease in those with severe atherosclerosis compared with those without atherosclerosis was 3·0 (95% CI 1·5–6·0; p=0·001). In participants with the apolipoprotein-E e4 genotype and an atherosclerosis score of 2 or 3 the odds ratio for all dementia was 4·5 (2·0–10·1; p≤0·001), for Alzheimer's disease was 3·9 (1·6–9·6; p=0·002), and for vascular dementia was 19·8 (4·1–95·0; p Interpretation These findings suggest that dementia and its two major subtypes Alzheimer's disease and vascular dementia are associated with atherosclerosis and that there is an interaction between apolipoprotein E and atherosclerosis in the aetiology of Alzheimer's disease.

Background/Aims The development of type 2 diabetes (T2D) is influenced both by environmental and by genetic determinants. Obesity is an important risk factor for T2D, mostly mediated by obesity-related insulin resistance. Obesity and insulin resistance are also modulated by the genetic milieu; thus, genes affecting risk of obesity and insulin resistance might also modulate risk of T2D. Recently, 32 loci have been associated with body mass index (BMI) by genome-wide studies, including one locus on chromosome 16p11 containing the SH2B1 gene. Animal studies have suggested that SH2B1 is a physiological enhancer of the insulin receptor and humans with rare deletions or mutations at SH2B1 are obese with a disproportionately high insulin resistance. Thus, the role of SH2B1 in both obesity and insulin resistance makes it a strong candidate for T2D. However, published data on the role of SH2B1 variability on the risk for T2D are conflicting, ranging from no effect at all to a robust association. Methods The SH2B1 tag SNP rs4788102 (SNP, single nucleotide polymorphism) was genotyped in 6978 individuals from six studies for abnormal glucose homeostasis (AGH), including impaired fasting glucose, impaired glucose tolerance or T2D, from the GENetics of Type 2 Diabetes in Italy and the United States (GENIUS T2D) consortium. Data from these studies were then meta-analyzed, in a Bayesian fashion, with those from DIAGRAM+ ( n = 47,117) and four other published studies ( n = 39,448). Results Variability at the SH2B1 obesity locus was not associated with AGH either in the GENIUS consortium (overall odds ratio (OR) = 0.96; 0.89–1.04) or in the meta-analysis (OR = 1.01; 0.98–1.05). Conclusion Our data exclude a role for the SH2B1 obesity locus in the modulation of AGH.

A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity., Background Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. Methods and Findings We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). Conclusions On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency. Please see later in the article for the Editors' Summary, Editors' Summary Background Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements. Why Was This Study Done? Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations. What Did the Researchers Do and Find? The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium. What Do These Findings Mean? These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383. The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population The World Health Organization provides information on obesity (in several languages) The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D The International Obesity Taskforce provides information about the global obesity epidemic The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish) The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish) MedlinePlus has links to further information about obesity and about vitamin D (in English and Spanish) Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages) Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits

Background\ud Disruption of endogenous circadian rhythms has been shown to increase the risk of developing type 2 diabetes, suggesting that circadian genes might play a role in determining disease susceptibility. We present the results of a pilot study investigating the association between type 2 diabetes and selected single nucleotide polymorphisms (SNPs) in/near nine circadian genes. The variants were chosen based on their previously reported association with prostate cancer, a disease that has been suggested to have a genetic link with type 2 diabetes through a number of shared inherited risk determinants.\ud \ud Methodology/Principal Findings\ud The pilot study was performed using two genetically homogeneous Punjabi cohorts, one resident in the United Kingdom and one indigenous to Pakistan. Subjects with (N = 1732) and without (N = 1780) type 2 diabetes were genotyped for thirteen circadian variants using a competitive allele-specific polymerase chain reaction method. Associations between the SNPs and type 2 diabetes were investigated using logistic regression. The results were also combined with in silico data from other South Asian datasets (SAT2D consortium) and white European cohorts (DIAGRAM+) using meta-analysis. The rs7602358G allele near PER2 was negatively associated with type 2 diabetes in our Punjabi cohorts (combined odds ratio [OR] = 0.75 [0.66–0.86], p = 3.18×10−5), while the BMAL1 rs11022775T allele was associated with an increased risk of the disease (combined OR = 1.22 [1.07–1.39], p = 0.003). Neither of these associations was replicated in the SAT2D or DIAGRAM+ datasets, however. Meta-analysis of all the cohorts identified disease associations with two variants, rs2292912 in CRY2 and rs12315175 near CRY1, although statistical significance was nominal (combined OR = 1.05 [1.01–1.08], p = 0.008 and OR = 0.95 [0.91–0.99], p = 0.015 respectively).\ud \ud Conclusions/significance\ud None of the selected circadian gene variants was associated with type 2 diabetes with study-wide significance after meta-analysis. The nominal association observed with the CRY2 SNP, however, complements previous findings and confirms a role for this locus in disease susceptibility.