The type 2 diabetes risk allele of TMEM154-rs6813195 associates with decreased beta cell function in a study of 6,486 Danes

A trans-ethnic meta-analysis of type 2 diabetes genome-wide association studies has identified seven novel susceptibility variants in or near TMEM154, SSR1/RREB1, FAF1, POU5F1/TCF19, LPP, ARL15 and ABCB9/MPHOSPH9. The aim of our study was to investigate associations between these novel risk variants and type 2 diabetes and pre-diabetic traits in a Danish population-based study with measurements of plasma glucose and serum insulin after an oral glucose tolerance test in order to elaborate on the physiological impact of the variants.Case-control analyses were performed in up to 5,777 patients with type 2 diabetes and 7,956 individuals with normal fasting glucose levels. Quantitative trait analyses were performed in up to 5,744 Inter99 participants naïve to glucose-lowering medication. Significant associations between TMEM154-rs6813195 and the beta cell measures insulinogenic index and disposition index and between FAF1-rs17106184 and 2-hour serum insulin levels were selected for further investigation in additional Danish studies and results were combined in meta-analyses including up to 6,486 Danes.We confirmed associations with type 2 diabetes for five of the seven SNPs (TMEM154-rs6813195, FAF1-rs17106184, POU5F1/TCF19-rs3130501, ARL15-rs702634 and ABCB9/MPHOSPH9-rs4275659). The type 2 diabetes risk C-allele of TMEM154-rs6813195 associated with decreased disposition index (n=5,181, β=-0.042, p=0.012) and insulinogenic index (n=5,181, β=-0.032, p=0.043) in Inter99 and these associations remained significant in meta-analyses including four additional Danish studies (disposition index n=6,486, β=-0.042, p=0.0044; and insulinogenic index n=6,486, β=-0.037, p=0.0094). The type 2 diabetes risk G-allele of FAF1-rs17106184 associated with increased levels of 2-hour serum insulin (n=5,547, β=0.055, p=0.017) in Inter99 and also when combining effects with three additional Danish studies (n=6,260, β=0.062, p=0.0040).Studies of type 2 diabetes intermediary traits suggest the diabetogenic impact of the C-allele of TMEM154-rs6813195 is mediated through reduced beta cell function. The impact of the diabetes risk G-allele of FAF1-rs17106184 on increased 2-hour insulin levels is however unexplained

Predicting species abundances in a grassland biodiversity experiment: Trade‐offs between model complexity and generality

Models of natural processes necessarily sacrifice some realism for the sake of tractability. Detailed, parameter‐rich models often provide accurate estimates of system behaviour but can be data‐hungry and difficult to operationalize. Moreover, complexity increases the danger of ‘over‐fitting’, which leads to poor performance when models are applied to novel conditions. This challenge is typically described in terms of a trade‐off between bias and variance (i.e. low accuracy vs. low precision). In studies of ecological communities, this trade‐off often leads to an argument about the level of detail needed to describe interactions among species. Here, we used data from a grassland biodiversity experiment containing nine locally abundant plant species (the Jena ‘dominance experiment’) to parameterize models representing six increasingly complex hypotheses about interactions. For each model, we calculated goodness‐of‐fit across different subsets of the data based on sown species richness levels, and tested how performance changed depending on whether or not the same data were used to parameterize and test the model (i.e. within vs. out‐of‐sample), and whether the range of diversity treatments being predicted fell inside or outside of the range used for parameterization. As expected, goodness‐of‐fit improved as a function of model complexity for all within‐sample tests. In contrast, the best out‐of‐sample performance generally resulted from models of intermediate complexity (i.e. with only two interaction coefficients per species—an intraspecific effect and a single pooled interspecific effect), especially for predictions that fell outside the range of diversity treatments used for parameterization. In accordance with other studies, our results also demonstrate that commonly used selection methods based on AIC of models fitted to the full dataset correspond more closely to within‐sample than out‐of‐sample performance. Synthesis. Our results demonstrate that models which include only general intra and interspecific interaction coefficients can be sufficient for estimating species‐level abundances across a wide range of contexts and may provide better out‐of‐sample performance than do more complex models. These findings serve as a reminder that simpler models may often provide a better trade‐off between bias and variance in ecological systems, particularly when applying models beyond the conditions used to parameterize them

Meta-analysis of the effect of the G-allele of <i>FAF1</i>-rs17106184 on 2-hour serum insulin in 6,260 individuals from the Inter99 study (n = 5,547), ADIGEN controls (n = 246), ADIGEN obese cases (n = 165) and Danish Family study (n = 302).

<p>Gray diamond represents combined change per risk allele and the 95% confidence interval. Gray squares represent effects size estimates (beta coefficients) in single studies sized according to their weight in the meta-analyses. The horizontal lines through the gray squares represent the 95% confidence interval. ob, obese. <i>p</i>, <i>P</i>-value. CI, confidence interval. W(fixed), study weight in the fixed effect meta-analysis.</p

Meta-analysis of the effect of the C-allele of <i>TMEM154</i>-rs6813195 on insulinogenic index in 6,486 individuals from the Inter99 study (n = 5,181), Health 2008 study (n = 592), ADIGEN controls (n = 246), ADIGEN obese cases (n = 165) and Danish Family study (n = 302).

<p>Gray diamond represents combined change per risk allele and the 95% confidence interval. Gray squares represent effects size estimates (beta coefficients) in single studies sized according to their weight in the meta-analyses. The horizontal lines through the gray squares represent the 95% confidence interval. ob, obese. <i>p</i>, <i>P</i>-value. CI, confidence interval. W(fixed), study weight in the fixed effect meta-analysis.</p

T2D case-control analyses of up to 5,777 patients from Inter99 (n = 320), Health 2006 (n = 166), Health 2008 (n = 18), Steno Diabetes Center (n = 1,424), ADDITION (n = 1,870) and Vejle Biobank (n = 1,979) and up to 7,956 individuals with normal fasting glucose from Inter99 (n = 4,590), Health 2006 (n = 2,412), Health 2008 (n = 528) and Vejle Biobank (n = 426).

<p>Number of cases vs. number of controls is shown as 0/1/2 risk alleles. Odds ratios (OR) and <i>P</i>-values (<i>P</i>) are adjusted for age and sex. OR_adjBMI and <i>P</i>_adjBMI are adjusted for age, sex and BMI. SNP, single nucleotide polymorphism. RA, risk allele. RAF, risk allele frequency. CI, confidence interval.</p><p>T2D case-control analyses of up to 5,777 patients from Inter99 (n = 320), Health 2006 (n = 166), Health 2008 (n = 18), Steno Diabetes Center (n = 1,424), ADDITION (n = 1,870) and Vejle Biobank (n = 1,979) and up to 7,956 individuals with normal fasting glucose from Inter99 (n = 4,590), Health 2006 (n = 2,412), Health 2008 (n = 528) and Vejle Biobank (n = 426).</p