Genetic variation at CHRNA5-CHRNA3-CHRNB4 interacts with smoking status to influence body mass index

Cigarette smoking is associated with lower body mass index (BMI), and a commonly cited reason for unwillingness to quit smoking is a concern about weight gain. Common variation in the CHRNA5-CHRNA3-CHRNB4 gene region (chromosome 15q25) is robustly associated with smoking quantity in smokers, but its association with BMI is unknown. We hypothesized that genotype would accurately reflect smoking exposure and that, if smoking were causally related to weight, it would be associated with BMI in smokers, but not in never smokers

How informative is a negative finding in a small pharmacogenetic study?

Many pharmacogenetic studies fail to yield any statistically significant associations. Such negative findings may be due to the absence of, or inadequate statistical power to test for, an effect at the genetic variants tested. In many instances, sample sizes are small, making it unclear how to interpret the absence of statistically significant findings. We demonstrate that the amount of information that can be drawn from a negative study is improved by incorporating statistical power and the added context of well-validated pharmacogenetic effects into the interpretation process. This approach permits clearer inferences to be made about the possible range of genetic effects that may be present in, or are likely absent from, small drug studies

Gene set of nuclear-encoded mitochondrial regulators is enriched for common inherited variation in obesity

There are hints of an altered mitochondrial function in obesity. Nuclear-encoded genes are relevant for mitochondrial function (3 gene sets of known relevant pathways: (1) 16 nuclear regulators of mitochondrial genes, (2) 91 genes for oxidative phosphorylation and (3) 966 nuclear-encoded mitochondrial genes). Gene set enrichment analysis (GSEA) showed no association with type 2 diabetes mellitus in these gene sets. Here we performed a GSEA for the same gene sets for obesity. Genome wide association study (GWAS) data from a case-control approach on 453 extremely obese children and adolescents and 435 lean adult controls were used for GSEA. For independent confirmation, we analyzed 705 obesity GWAS trios (extremely obese child and both biological parents) and a population-based GWAS sample (KORA F4, n = 1,743). A meta-analysis was performed on all three samples. In each sample, the distribution of significance levels between the respective gene set and those of all genes was compared using the leading-edge-fraction-comparison test (cut-offs between the 50(th) and 95(th) percentile of the set of all gene-wise corrected p-values) as implemented in the MAGENTA software. In the case-control sample, significant enrichment of associations with obesity was observed above the 50(th) percentile for the set of the 16 nuclear regulators of mitochondrial genes (p(GSEA,50) = 0.0103). This finding was not confirmed in the trios (p(GSEA,50) = 0.5991), but in KORA (p(GSEA,50) = 0.0398). The meta-analysis again indicated a trend for enrichment (p(MAGENTA,50) = 0.1052, p(MAGENTA,75) = 0.0251). The GSEA revealed that weak association signals for obesity might be enriched in the gene set of 16 nuclear regulators of mitochondrial genes

PedGenie: meta genetic association testing in mixed family and case-control designs

<p>Abstract</p> <p>Background-</p> <p>PedGenie software, introduced in 2006, includes genetic association testing of cases and controls that may be independent or related (nuclear families or extended pedigrees) or mixtures thereof using Monte Carlo significance testing. Our aim is to demonstrate that PedGenie, a unique and flexible analysis tool freely available in Genie 2.4 software, is significantly enhanced by incorporating meta statistics for detecting genetic association with disease using data across multiple study groups.</p> <p>Methods-</p> <p>Meta statistics (chi-squared tests, odds ratios, and confidence intervals) were calculated using formal Cochran-Mantel-Haenszel techniques. Simulated data from unrelated individuals and individuals in families were used to illustrate meta tests and their empirically-derived p-values and confidence intervals are accurate, precise, and for independent designs match those provided by standard statistical software.</p> <p>Results-</p> <p>PedGenie yields accurate Monte Carlo p-values for meta analysis of data across multiple studies, based on validation testing using pedigree, nuclear family, and case-control data simulated under both the null and alternative hypotheses of a genotype-phenotype association.</p> <p>Conclusion-</p> <p>PedGenie allows valid combined analysis of data from mixtures of pedigree-based and case-control resources. Added meta capabilities provide new avenues for association analysis, including pedigree resources from large consortia and multi-center studies.</p

Two New Loci for Body-Weight Regulation Identified in a Joint Analysis of Genome-Wide Association Studies for Early-Onset Extreme Obesity in French and German Study Groups

Meta-analyses of population-based genome-wide association studies (GWAS) in adults have recently led to the detection of new genetic loci for obesity. Here we aimed to discover additional obesity loci in extremely obese children and adolescents. We also investigated if these results generalize by estimating the effects of these obesity loci in adults and in population-based samples including both children and adults. We jointly analysed two GWAS of 2,258 individuals and followed-up the best, according to lowest p-values, 44 single nucleotide polymorphisms (SNP) from 21 genomic regions in 3,141 individuals. After this DISCOVERY step, we explored if the findings derived from the extremely obese children and adolescents (10 SNPs from 5 genomic regions) generalized to (i) the population level and (ii) to adults by genotyping another 31,182 individuals (GENERALIZATION step). Apart from previously identified FTO, MC4R, and TMEM18, we detected two new loci for obesity: one in SDCCAG8 (serologically defined colon cancer antigen 8 gene; p = 1.85610 x 10(-8) in the DISCOVERY step) and one between TNKS (tankyrase, TRF1-interacting ankyrin-related ADP-ribose polymerase gene) and MSRA (methionine sulfoxide reductase A gene; p = 4.84 x 10(-7)), the latter finding being limited to children and adolescents as demonstrated in the GENERALIZATION step. The odds ratios for early-onset obesity were estimated at similar to 1.10 per risk allele for both loci. Interestingly, the TNKS/MSRA locus has recently been found to be associated with adult waist circumference. In summary, we have completed a meta-analysis of two GWAS which both focus on extremely obese children and adolescents and replicated our findings in a large followed-up data set. We observed that genetic variants in or near FTO, MC4R, TMEM18, SDCCAG8, and TNKS/MSRA were robustly associated with early-onset obesity. We conclude that the currently known major common variants related to obesity overlap to a substantial degree between children and adults

An Integrated Meta-Analysis of Two Variants in HOXA1/HOXB1 and Their Effect on the Risk of Autism Spectrum Disorders

BACKGROUND: HOXA1 and HOXB1 have been strongly posed as candidate genes for autism spectrum disorders (ASD) given their important role in the development of hindbrain. The A218G (rs10951154) in HOXA1 and the insertion variant in HOXB1 (nINS/INS, rs72338773) were of special interest for ASD but with inconclusive results. Thus, we conducted a meta-analysis integrating case-control and transmission/disequilibrium test (TDT) studies to clearly discern the effect of these two variants in ASD. METHODS AND FINDINGS: Multiple electronic databases were searched to identify studies assessing the A218G and/or nINS/INS variant in ASD. Data from case-control and TDT studies were analyzed in an allelic model using the Catmap software. A total of 10 and 7 reports were found to be eligible for meta-analyses of A218G and nINS/INS variant, respectively. In overall meta-analysis, the pooled OR for the 218G allele and the INS allele was 0.97 (95% CI = 0.76-1.25, P(heterogeneity) = 0.029) and 1.14 (95% CI = 0.97-1.33, P(heterogeneity) = 0.269), respectively. No significant association was also identified between these two variants and ASD risk in stratified analysis. Further, cumulative meta-analysis in chronologic order showed the inclination toward null-significant association for both variants with continual adding studies. Additionally, although the between-study heterogeneity regarding the A218G is not explained by study design, ethnicity, and sample size, the sensitive analysis indicated the stability of the result. CONCLUSIONS: This meta-analysis suggests the HOXA1 A218G and HOXB1 nINS/INS variants may not contribute significantly to ASD risk

Genome-Wide Meta-Analysis of Five Asian Cohorts Identifies PDGFRA as a Susceptibility Locus for Corneal Astigmatism

Corneal astigmatism refers to refractive abnormalities and irregularities in the curvature of the cornea, and this interferes with light being accurately focused at a single point in the eye. This ametropic condition is highly prevalent, influences visual acuity, and is a highly heritable trait. There is currently a paucity of research in the genetic etiology of corneal astigmatism. Here we report the results from five genome-wide association studies of corneal astigmatism across three Asian populations, with an initial discovery set of 4,254 Chinese and Malay individuals consisting of 2,249 cases and 2,005 controls. Replication was obtained from three surveys comprising of 2,139 Indians, an additional 929 Chinese children, and an independent 397 Chinese family trios. Variants in PDGFRA on chromosome 4q12 (lead SNP: rs7677751, allelic odds ratio = 1.26 (95% CI: 1.16–1.36), Pmeta = 7.87×10−9) were identified to be significantly associated with corneal astigmatism, exhibiting consistent effect sizes across all five cohorts. This highlights the potential role of variants in PDGFRA in the genetic etiology of corneal astigmatism across diverse Asian populations

Genome-wide association study of serious blistering skin rash caused by drugs.

Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are rare but severe, potentially life threatening adverse drug reactions characterized by skin blistering. Previous studies have identified drug-specific and population-specific genetic risk factors with large effects. In this study, we report the first genome-wide association study (GWAS) of SJS/TEN induced by a variety of drugs. Our aim was to identify common genetic risk factors with large effects on SJS/TEN risk. We conducted a genome-wide analysis of 96 retrospective cases and 198 controls with a panel of over one million single-nucleotide polymorphisms (SNPs). We further improved power with about 4000 additional controls from publicly available datasets. No genome-wide significant associations with SNPs or copy number variants were observed, although several genomic regions were suggested that may have a role in predisposing to drug-induced SJS/TEN. Our GWAS did not find common, highly penetrant genetic risk factors responsible for SJS/TEN events in the cases selected