Obesity and Multiple Sclerosis: A Mendelian Randomization Study.

BACKGROUND: Observational studies have reported an association between obesity, as measured by elevated body mass index (BMI), in early adulthood and risk of multiple sclerosis (MS). However, bias potentially introduced by confounding and reverse causation may have influenced these findings. Therefore, we elected to perform Mendelian randomization (MR) analyses to evaluate whether genetically increased BMI is associated with an increased risk of MS. METHODS AND FINDINGS: Employing a two-sample MR approach, we used summary statistics from the Genetic Investigation of Anthropometric Traits (GIANT) consortium and the International MS Genetics Consortium (IMSGC), the largest genome-wide association studies for BMI and MS, respectively (GIANT: n = 322,105; IMSGC: n = 14,498 cases and 24,091 controls). Seventy single nucleotide polymorphisms (SNPs) were genome-wide significant (p < 5 x 10-8) for BMI in GIANT (n = 322,105) and were investigated for their association with MS risk in the IMSGC. The effect of each SNP on MS was weighted by its effect on BMI, and estimates were pooled to provide a summary measure for the effect of increased BMI upon risk of MS. Our results suggest that increased BMI influences MS susceptibility, where a 1 standard deviation increase in genetically determined BMI (kg/m2) increased odds of MS by 41% (odds ratio [OR]: 1.41, 95% CI 1.20-1.66, p = 2.7 x 10-5, I2 = 0%, 95% CI 0-29). Sensitivity analyses, including MR-Egger regression, and the weighted median approach provided no evidence of pleiotropic effects. The main study limitations are that, while these sensitivity analyses reduce the possibility that pleiotropy influenced our results, residual pleiotropy is difficult to exclude entirely. CONCLUSION: Genetically elevated BMI is associated with risk of MS, providing evidence for a causal role for obesity in MS etiology. While obesity has been associated with many late-life outcomes, these findings suggest an important consequence of childhood and/or early adulthood obesity.National Institute for Health Research Cambridge Biomedical Research CentreThis is the final version of the article. It first appeared from Public Library of Science via http://dx.doi.org/10.1371/journal.pmed.1002053

The Empirical Power of Rare Variant Association Methods: Results from Sanger Sequencing in 1,998 Individuals

The role of rare genetic variation in the etiology of complex disease remains unclear. However, the development of next-generation sequencing technologies offers the experimental opportunity to address this question. Several novel statistical methodologies have been recently proposed to assess the contribution of rare variation to complex disease etiology. Nevertheless, no empirical estimates comparing their relative power are available. We therefore assessed the parameters that influence their statistical power in 1,998 individuals Sanger-sequenced at seven genes by modeling different distributions of effect, proportions of causal variants, and direction of the associations (deleterious, protective, or both) in simulated continuous trait and case/control phenotypes. Our results demonstrate that the power of recently proposed statistical methods depend strongly on the underlying hypotheses concerning the relationship of phenotypes with each of these three factors. No method demonstrates consistently acceptable power despite this large sample size, and the performance of each method depends upon the underlying assumption of the relationship between rare variants and complex traits. Sensitivity analyses are therefore recommended to compare the stability of the results arising from different methods, and promising results should be replicated using the same method in an independent sample. These findings provide guidance in the analysis and interpretation of the role of rare base-pair variation in the etiology of complex traits and diseases

An Efficient Paradigm for Genetic Epidemiology Cohort Creation

Development of novel methodologies to efficiently create large genetic epidemiology cohorts is needed. Here we describe a rapid, precise and cost-efficient method for collection of DNA from cases previously experiencing an osteoporotic fracture by identifying cases using and administrative health-care databases. Over the course of 14 months we collected DNA from 1,130 women experiencing an osteoporotic fracture, at a cost of $54 per sample. This cohort is among the larger DNA osteoporotic fracture collections in the world. The novel method described addresses a major unmet health care research need and is widely applicable to any disease that can be identified accurately through administrative data

Little evidence for an effect of smoking on multiple sclerosis risk:A Mendelian Randomization study

The causes of multiple sclerosis (MS) remain unknown. Smoking has been associated with MS in observational studies and is often thought of as an environmental risk factor. We used two-sample Mendelian randomization (MR) to examine whether this association is causal using genetic variants identified in genome-wide association studies (GWASs) as associated with smoking. We assessed both smoking initiation and lifetime smoking behaviour (which captures smoking duration, heaviness, and cessation). There was very limited evidence for a meaningful effect of smoking on MS susceptibility as measured using summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) meta-analysis, including 14,802 cases and 26,703 controls. There was no clear evidence for an effect of smoking on the risk of developing MS (smoking initiation: odds ratio [OR] 1.03, 95% confidence interval [CI] 0.92-1.61; lifetime smoking: OR 1.10, 95% CI 0.87-1.40). These findings suggest that smoking does not have a detrimental consequence on MS susceptibility. Further work is needed to determine the causal effect of smoking on MS progression

Vitamin D levels and risk of type 1 diabetes:A Mendelian randomization study

[This corrects the article DOI: 10.1371/journal.pmed.1003536.]

Genome-wide Association Study for Vitamin D Levels Reveals 69 Independent Loci.

We aimed to increase our understanding of the genetic determinants of vitamin D levels by undertaking a large-scale genome-wide association study (GWAS) of serum 25 hydroxyvitamin D (25OHD). To do so, we used imputed genotypes from 401,460 white British UK Biobank participants with available 25OHD levels, retaining single-nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) > 0.1% and imputation quality score > 0.3. We performed a linear mixed model GWAS on standardized log-transformed 25OHD, adjusting for age, sex, season of measurement, and vitamin D supplementation. These results were combined with those from a previous GWAS including 42,274 Europeans. In silico functional follow-up of the GWAS results was undertaken to identify enrichment in gene sets, pathways, and expression in tissues, and to investigate the partitioned heritability of 25OHD and its shared heritability with other traits. Using this approach, the SNP heritability of 25OHD was estimated to 16.1%. 138 conditionally independent SNPs were detected (p value < 6.6 × 10-9) among which 53 had MAF < 5%. Single variant association signals mapped to 69 distinct loci, among which 63 were previously unreported. We identified enrichment in hepatic and lipid metabolism gene pathways and enriched expression of the 25OHD genes in liver, skin, and gastrointestinal tissues. We observed partially shared heritability between 25OHD and socio-economic traits, a feature which may be mediated through time spent outdoors. Therefore, through a large 25OHD GWAS, we identified 63 loci that underline the contribution of genes outside the vitamin D canonical metabolic pathway to the genetic architecture of 25OHD