Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption.

Alcohol consumption is a moderately heritable trait, but the genetic basis in humans is largely unknown, despite its clinical and societal importance. We report a genome-wide association study meta-analysis of ∼2.5 million directly genotyped or imputed SNPs with alcohol consumption (gram per day per kilogram body weight) among 12 population-based samples of European ancestry, comprising 26,316 individuals, with replication genotyping in an additional 21,185 individuals. SNP rs6943555 in autism susceptibility candidate 2 gene (AUTS2) was associated with alcohol consumption at genome-wide significance (P = 4 × 10(-8) to P = 4 × 10(-9)). We found a genotype-specific expression of AUTS2 in 96 human prefrontal cortex samples (P = 0.026) and significant (P < 0.017) differences in expression of AUTS2 in whole-brain extracts of mice selected for differences in voluntary alcohol consumption. Down-regulation of an AUTS2 homolog caused reduced alcohol sensitivity in Drosophila (P < 0.001). Our finding of a regulator of alcohol consumption adds knowledge to our understanding of genetic mechanisms influencing alcohol drinking behavior.

A single mutation in enzyme I of the sugar phosphotransferase system confers penicillin tolerance to Streptococcus gordonii.

Tolerance is a poorly understood phenomenon that allows bacteria exposed to a bactericidal antibiotic to stop their growth and withstand drug-induced killing. This survival ability has been implicated in antibiotic treatment failures. Here, we describe a single nucleotide mutation (tol1) in a tolerant Streptococcus gordonii strain (Tol1) that is sufficient to provide tolerance in vitro and in vivo. It induces a proline-to-arginine substitution (P483R) in the homodimerization interface of enzyme I of the sugar phosphotransferase system, resulting in diminished sugar uptake. In vitro, the susceptible wild-type (WT) and Tol1 cultures lost 4.5 and 0.6 log(10) CFU/ml, respectively, after 24 h of penicillin exposure. The introduction of tol1 into the WT (WT P483R) conferred tolerance (a loss of 0.7 log(10) CFU/ml/24 h), whereas restitution of the parent sequence in Tol1 (Tol1 R483P) restored antibiotic susceptibility. Moreover, penicillin treatment of rats in an experimental model of endocarditis showed a complete inversion in the outcome, with a failure of therapy in rats infected with WT P483R and the complete disappearance of bacteria in animals infected with Tol1 R483P.

Comparative genetic analyses point to HCP5 as susceptibility locus for HCV-associated hepatocellular carcinoma.

BACKGROUND & AIMS: Recently, genetic variations in MICA (lead single nucleotide polymorphism [SNP] rs2596542) were identified by a genome-wide association study (GWAS) to be associated with hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC) in Japanese patients. In the present study, we sought to determine whether this SNP is predictive of HCC development in the Caucasian population as well. METHODS: An extended region around rs2596542 was genotyped in 1924 HCV-infected patients from the Swiss Hepatitis C Cohort Study (SCCS). Pair-wise correlation between key SNPs was calculated both in the Japanese and European populations (HapMap3: CEU and JPT). RESULTS: To our surprise, the minor allele A of rs2596542 in proximity of MICA appeared to have a protective impact on HCC development in Caucasians, which represents an inverse association as compared to the one observed in the Japanese population. Detailed fine-mapping analyses revealed a new SNP in HCP5 (rs2244546) upstream of MICA as strong predictor of HCV-related HCC in the SCCS (univariable p=0.027; multivariable p=0.0002, odds ratio=3.96, 95% confidence interval=1.90-8.27). This newly identified SNP had a similarly directed effect on HCC in both Caucasian and Japanese populations, suggesting that rs2244546 may better tag a putative true variant than the originally identified SNPs. CONCLUSIONS: Our data confirms the MICA/HCP5 region as susceptibility locus for HCV-related HCC and identifies rs2244546 in HCP5 as a novel tagging SNP. In addition, our data exemplify the need for conducting meta-analyses of cohorts of different ethnicities in order to fine map GWAS signals.

Meta-analysis of genome-wide association data identifies a risk locus for major mood disorders on 3p21.1.

The major mood disorders, which include bipolar disorder and major depressive disorder (MDD), are considered heritable traits, although previous genetic association studies have had limited success in robustly identifying risk loci. We performed a meta-analysis of five case-control cohorts for major mood disorder, including over 13,600 individuals genotyped on high-density SNP arrays. We identified SNPs at 3p21.1 associated with major mood disorders (rs2251219, P = 3.63 x 10(-8); odds ratio = 0.87; 95% confidence interval, 0.83-0.92), with supportive evidence for association observed in two out of three independent replication cohorts. These results provide an example of a shared genetic susceptibility locus for bipolar disorder and MDD.

Genome-wide association analysis identifies 20 loci that influence adult height.

Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P < 5 x 10(-7), with 10 reaching P < 1 x 10(-10)). Combined, the 20 SNPs explain approximately 3% of height variation, with a approximately 5 cm difference between the 6.2% of people with 17 or fewer 'tall' alleles compared to the 5.5% with 27 or more 'tall' alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.

Genetic and epigenetic analysis of SSAT gene dysregulation in suicidal behavior.

It has recently been proposed that the SSAT gene plays a role in the predisposition to suicidal behavior. SSAT expression was found to be down-regulated in the brain of suicide completers. In addition, a single nucleotide polymorphism (SNP) rs6526342 was associated both with variation in SSAT expression and with suicidal behavior. In this study, we aimed to characterize the relationship between SSAT dysregulation and suicide behavior. To this end, we measured SSAT expression levels in the ventral prefrontal cortex (VPFC) of suicide completers (n = 20) and controls (n = 20) and found them to be significantly down-regulated in suicide victims (P = 0.007). To identify the basis of the regulation of SSAT expression, we performed an association analysis of 309 SNPs with SSAT transcript levels in 53 lymphoblastoid cell lines from the CEPH collection. We then examined the methylation status of the SSAT promoter region in males and females suicide completers and control subjects whose SSAT brain expression had been measured. We found no evidence to support a role for SNPs in controlling the level of SSAT expression. SSAT promoter methylation levels were not different between suicide completers and controls and did not correlate with SSAT expression levels. In addition, we found no indication of a genetic association between suicidal behavior and SNPs located within the SSAT gene. Our study provides new results which show that dysregulation of SSAT expression does play a role in suicide behavior. However, our data do not support any association between rs6526342 and variation in SSAT expression or suicidal behavior.

The fine-scale architecture of structural variants in 17 mouse genomes.

BACKGROUND: Accurate catalogs of structural variants (SVs) in mammalian genomes are necessary to elucidate the potential mechanisms that drive SV formation and to assess their functional impact. Next generation sequencing methods for SV detection are an advance on array-based methods, but are almost exclusively limited to four basic types: deletions, insertions, inversions and copy number gains. RESULTS: By visual inspection of 100 Mbp of genome to which next generation sequence data from 17 inbred mouse strains had been aligned, we identify and interpret 21 paired-end mapping patterns, which we validate by PCR. These paired-end mapping patterns reveal a greater diversity and complexity in SVs than previously recognized. In addition, Sanger-based sequence analysis of 4,176 breakpoints at 261 SV sites reveal additional complexity at approximately a quarter of structural variants analyzed. We find micro-deletions and micro-insertions at SV breakpoints, ranging from 1 to 107 bp, and SNPs that extend breakpoint micro-homology and may catalyze SV formation. CONCLUSIONS: An integrative approach using experimental analyses to train computational SV calling is essential for the accurate resolution of the architecture of SVs. We find considerable complexity in SV formation; about a quarter of SVs in the mouse are composed of a complex mixture of deletion, insertion, inversion and copy number gain. Computational methods can be adapted to identify most paired-end mapping patterns.

DIP-STR: Highly Sensitive Markers for the Analysis of Unbalanced Genomic Mixtures.

Samples containing highly unbalanced DNA mixtures from two individuals commonly occur both in forensic mixed stains and in peripheral blood DNA microchimerism induced by pregnancy or following organ transplant. Because of PCR amplification bias, the genetic identification of a DNA that contributes trace amounts to a mixed sample represents a tremendous challenge. This means that standard genetic markers, namely microsatellites, also referred as short tandem repeats (STR), and single-nucleotide polymorphism (SNP) have limited power in addressing common questions of forensic and medical genetics. To address this issue, we developed a molecular marker, named DIP-STR that relies on pairing deletion-insertion polymorphisms (DIP) with STR. This novel analytical approach allows for the unambiguous genotyping of a minor component in the presence of a major component, where DIP-STR genotypes of the minor were successfully procured at ratios up to 1:1,000. The compound nature of this marker generates a high level of polymorphism that is suitable for identity testing. Here, we demonstrate the power of the DIP-STR approach on an initial set of nine markers surveyed in a Swiss population. Finally, we discuss the limitations and potential applications of our new system including preliminary tests on clinical samples and estimates of their performance on simulated DNA mixtures.

Serum uric acid and adiposity: deciphering causality using a bidirectional Mendelian randomization approach.

Although the relationship between serum uric acid (SUA) and adiposity is well established, the direction of the causality is still unclear in the presence of conflicting evidences. We used a bidirectional Mendelian randomization approach to explore the nature and direction of causality between SUA and adiposity in a population-based study of Caucasians aged 35 to 75 years. We used, as instrumental variables, rs6855911 within the SUA gene SLC2A9 in one direction, and combinations of SNPs within the adiposity genes FTO, MC4R and TMEM18 in the other direction. Adiposity markers included weight, body mass index, waist circumference and fat mass. We applied a two-stage least squares regression: a regression of SUA/adiposity markers on our instruments in the first stage and a regression of the response of interest on the fitted values from the first stage regression in the second stage. SUA explained by the SLC2A9 instrument was not associated to fat mass (regression coefficient [95% confidence interval]: 0.05 [-0.10, 0.19] for fat mass) contrasting with the ordinary least square estimate (0.37 [0.34, 0.40]). By contrast, fat mass explained by genetic variants of the FTO, MC4R and TMEM18 genes was positively and significantly associated to SUA (0.31 [0.01, 0.62]), similar to the ordinary least square estimate (0.27 [0.25, 0.29]). Results were similar for the other adiposity markers. Using a bidirectional Mendelian randomization approach in adult Caucasians, our findings suggest that elevated SUA is a consequence rather than a cause of adiposity.

Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile.

Genome-wide association studies have identified 32 loci influencing body mass index, but this measure does not distinguish lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ∼2.5 million SNPs and body fat percentage from 36,626 individuals and followed up the 14 most significant (P < 10(-6)) independent loci in 39,576 individuals. We confirmed a previously established adiposity locus in FTO (P = 3 × 10(-26)) and identified two new loci associated with body fat percentage, one near IRS1 (P = 4 × 10(-11)) and one near SPRY2 (P = 3 × 10(-8)). Both loci contain genes with potential links to adipocyte physiology. Notably, the body-fat-decreasing allele near IRS1 is associated with decreased IRS1 expression and with an impaired metabolic profile, including an increased visceral to subcutaneous fat ratio, insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.

Defining the role of common variation in the genomic and biological architecture of adult human height.

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Association analysis of urotensin II gene (UTS2) and flanking regions with biochemical parameters related to insulin resistance.

Background. Urotensin II (UII) is a potent vasoconstrictor peptide, which signals through a G-protein coupled receptor (GPCR) known as GPR14 or urotensin receptor (UTR). UII exerts a broad spectrum of actions in several systems such as vascular cell, heart muscle or pancreas, where it inhibits insulin release. Objective. Given the reported role of UII in insulin secretion, we have performed a genetic association analysis of the UTS2 gene and flanking regions with biochemical parameters related to insulin resistance (fasting glucose, glucose 2 hours after a glucose overload, fasting insulin and insulin resistance estimated as HOMA). Results and Conclusions. We have identified several polymorphisms associated with the analysed clinical traits, not only at the UTS2 gene, but also in thePER3 gene, located upstream from UTS2. Our results are compatible with a role for UII in glucose homeostasis and diabetes although we cannot rule out the possibility that PER3 gene may underlie the reported associations.

The IFN-³+874T/A gene polymorphism is associated with retinochoroiditis toxoplasmosis susceptibility

Toxoplasmosis is a worldwide zoonosis that generally produces an asymptomatic infection. In some cases, however, toxoplasmosis infection can lead to ocular damage. The immune system has a crucial role in both the course of the infection and in the evolution of toxoplasmosis disease. In particular, IFN-³ plays an important role in resistance to toxoplasmosis. Polymorphisms in genes encoding cytokines have been shown to have an association with susceptibility to parasitic diseases. The aim of this work was to analyse the occurrence of polymorphisms in the gene encoding IFN-³ (+874T/A) among Toxoplasma gondii seropositive individuals, including those with ocular lesions caused by the parasite, from a rural population of Santa Rita de Cássia, Barra Mansa, state of Rio de Janeiro, Brazil. Further, we verified which of these polymorphisms could be related to susceptibility to the development of ocular toxoplasmosis. This study included 34 individuals with ocular toxoplasmosis (ocular group) and 134 without ocular lesions (control group). The differences between A and T allele distributions were not statistically significant between the two groups. However, we observed that a higher frequency of individuals from the ocular group possessed the A/A genotype, when compared with the control group, suggesting that homozygocity for the A allele could enhance susceptibility to ocular toxoplasmosis in T. gondii infection.

Hardy-Weinberg Equilibrium and the Ternary Plot

The Hardy-Weinberg law, formulated about 100 years ago, states that under certainassumptions, the three genotypes AA, AB and BB at a bi-allelic locus are expected to occur inthe proportions p2, 2pq, and q2 respectively, where p is the allele frequency of A, and q = 1-p.There are many statistical tests being used to check whether empirical marker data obeys theHardy-Weinberg principle. Among these are the classical xi-square test (with or withoutcontinuity correction), the likelihood ratio test, Fisher's Exact test, and exact tests in combinationwith Monte Carlo and Markov Chain algorithms. Tests for Hardy-Weinberg equilibrium (HWE)are numerical in nature, requiring the computation of a test statistic and a p-value.There is however, ample space for the use of graphics in HWE tests, in particular for the ternaryplot. Nowadays, many genetical studies are using genetical markers known as SingleNucleotide Polymorphisms (SNPs). SNP data comes in the form of counts, but from the countsone typically computes genotype frequencies and allele frequencies. These frequencies satisfythe unit-sum constraint, and their analysis therefore falls within the realm of compositional dataanalysis (Aitchison, 1986). SNPs are usually bi-allelic, which implies that the genotypefrequencies can be adequately represented in a ternary plot. Compositions that are in exactHWE describe a parabola in the ternary plot. Compositions for which HWE cannot be rejected ina statistical test are typically “close" to the parabola, whereas compositions that differsignificantly from HWE are “far". By rewriting the statistics used to test for HWE in terms ofheterozygote frequencies, acceptance regions for HWE can be obtained that can be depicted inthe ternary plot. This way, compositions can be tested for HWE purely on the basis of theirposition in the ternary plot (Graffelman & Morales, 2008). This leads to nice graphicalrepresentations where large numbers of SNPs can be tested for HWE in a single graph. Severalexamples of graphical tests for HWE (implemented in R software), will be shown, using SNPdata from different human populations

ELOVL6 Genetic Variation Is Related to Insulin Sensitivity: A New Candidate Gene in Energy Metabolism

BACKGROUND: The elongase of long chain fatty acids family 6 (ELOVL6) is an enzyme that specifically catalyzes the elongation of saturated and monounsaturated fatty acids with 12, 14 and 16 carbons. ELOVL6 is expressed in lipogenic tissues and it is regulated by sterol regulatory element binding protein 1 (SREBP-1). OBJECTIVE: We investigated whether ELOVL6 genetic variation is associated with insulin sensitivity in a population from southern Spain. DESIGN: We undertook a prospective, population-based study collecting phenotypic, metabolic, nutritional and genetic information. Measurements were made of weight and height and the body mass index (BMI) was calculated. Insulin resistance was measured by homeostasis model assessment. The type of dietary fat was assessed from samples of cooking oil taken from the participants' kitchens and analyzed by gas chromatography. Five SNPs of the ELOVL6 gene were analyzed by SNPlex. RESULTS: Carriers of the minor alleles of the SNPs rs9997926 and rs6824447 had a lower risk of having high HOMA_IR, whereas carriers of the minor allele rs17041272 had a higher risk of being insulin resistant. An interaction was detected between the rs6824447 polymorphism and the intake of oil in relation with insulin resistance, such that carriers of this minor allele who consumed sunflower oil had lower HOMA_IR than those who did not have this allele (P = 0.001). CONCLUSIONS: Genetic variations in the ELOVL6 gene were associated with insulin sensitivity in this population-based study.