The Genetic Architecture of the Human Immune System:A Bioresource for Autoimmunity and Disease Pathogenesis

SummaryDespite recent discoveries of genetic variants associated with autoimmunity and infection, genetic control of the human immune system during homeostasis is poorly understood. We undertook a comprehensive immunophenotyping approach, analyzing 78,000 immune traits in 669 female twins. From the top 151 heritable traits (up to 96% heritable), we used replicated GWAS to obtain 297 SNP associations at 11 genetic loci, explaining up to 36% of the variation of 19 traits. We found multiple associations with canonical traits of all major immune cell subsets and uncovered insights into genetic control for regulatory T cells. This data set also revealed traits associated with loci known to confer autoimmune susceptibility, providing mechanistic hypotheses linking immune traits with the etiology of disease. Our data establish a bioresource that links genetic control elements associated with normal immune traits to common autoimmune and infectious diseases, providing a shortcut to identifying potential mechanisms of immune-related diseases

Effects of age on genetic influence on bone loss over 17 years in women:the Healthy Ageing Twin Study (HATS)

The rate of bone loss varies across the aging period via multiple complex mechanisms. Therefore, the role of genetic factors on bone loss may also change similarly. In this study, we investigated the effect of age on the genetic component of bone loss in a large twin-based longitudinal study. During 17 years of follow-up in TwinsUK and Healthy Ageing Twin Study (HATS), 15,491 hip and lumbar spine dual-energy X-ray absorptiometry (DXA) scans were performed in 7056 twins. Out of these subjects, 2716 female twins aged >35 years with at least two scans separated for >4 years (mean follow-up 9.7 years) were included in this analysis. We used a mixed-effects random-coefficients regression model to predict hip and spine bone mineral density (BMD) values for exact ages of 40, 45, 50, 55, 60, 65, 70, 75, and 80 years, with adjustment for baseline age, weight, height, and duration of hormone replacement therapy. We then estimated heritability of the changes in BMD measures between these age ranges. Heritability estimates for cross-sectional hip and spine BMD were high (ranging between 69% and 88%) at different ages. Heritability of change of BMD was lower and more variable, generally ranging from 0% to 40% for hip and 0% to 70% for spine; between age 40 and 45 years genetic factors explained 39.9% (95% confidence interval [CI], 25%-53%) of variance of BMD loss for total hip, 46.4% (95% CI, 32%-58%) for femoral neck, and 69.5% (95% CI, 59%-77%) for lumbar spine. These estimates decreased with increasing age, and there appeared to be no heritability of BMD changes after the age of 65 years. There was some evidence at the spine for shared genetic effects between cross-sectional and longitudinal BMD. Whereas genetic factors appear to have an important role in bone loss in early postmenopausal women, nongenetic mechanisms become more important determinants of bone loss with advanced age

Targeted metabolomics profiles are strongly correlated with nutritional patterns in women

Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targeted metabolomic analyses of serum samples using the Biocrates Absolute-IDQ™ Kit p150 (163 metabolites). We analyzed seven nutritional parameters: coffee intake, garlic intake and nutritional scores derived from the FFQs summarizing fruit and vegetable intake, alcohol intake, meat intake, hypo-caloric dieting and a "traditional English" diet. We studied the correlation between metabolite levels and dietary intake patterns in the larger population and identified for each trait between 14 and 20 independent monozygotic twins pairs discordant for nutritional intake and replicated results in this set. Results from both analyses were then meta-analyzed. For the metabolites associated with nutritional patterns, we calculated heritability using structural equation modelling. 42 metabolite nutrient intake associations were statistically significant in the discovery samples (Bonferroni