The common p.R114W <i>HNF4A </i>mutation causes a distinct clinical subtype of monogenic diabetes

HNF4A mutations cause increased birth weight, transient neonatal hypoglycaemia and maturity onset diabetes of the young (MODY). The most frequently reported HNF4A mutation is p.R114W (previously p.R127W) but functional studies have shown inconsistent results, there is lack of co-segregation in some pedigrees and an unexpectedly high frequency in public variant databases. We confirm that p.R114W is a pathogenic mutation with an odds ratio of 30.4 (95% CI: 9.79 - 125, P=2x10(-21)) for diabetes in our MODY cohort compared to controls. p.R114W heterozygotes do not have the increased birth weight of patients with other HNF4A mutations (3476g vs. 4147g, P=0.0004) and fewer patients responded to sulfonylurea treatment (48% vs. 73%, P=0.038). p.R114W has reduced penetrance; only 54% of heterozygotes developed diabetes by age 30 compared to 71% for other HNF4A mutations. We re-define p.R114W as a pathogenic mutation causing a distinct clinical subtype of HNF4A MODY with reduced penetrance, reduced sensitivity to sulfonylurea treatment and no effect on birth weight. This has implications for diabetes treatment, management of pregnancy and predictive testing of at-risk relatives. The increasing availability of large-scale sequence data is likely to reveal similar examples of rare, low-penetrance MODY mutations.</p

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW ($\textit{P}$  < 5 × 10$^{-8}$). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure ($\textit{R}$ $_{g}$ = -0.22, $\textit{P}$  = 5.5 × 10$^{-13}$), T2D ($\textit{R}$ $_{g}$ = -0.27, $\textit{P}$  = 1.1 × 10$^{-6}$) and coronary artery disease ($\textit{R}$ $_{g}$ = -0.30, $\textit{P}$  = 6.5 × 10$^{-9}$). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions ($\textit{P}$ = 1.9 × 10$^{-4}$). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.For a full list of the funders pelase visit the publisher's website and look at the supplemetary material provided. Some of the funders are: British Heart Foundation, Cancer Research UK, Medical Research Council, National Institutes of Health, Royal Society and Wellcome Trust

Genome-wide and fine-resolution association analysis of malaria in West Africa

We report a genome-wide association (GWA) study of severe malaria in The Gambia. The initial GWA scan included 2,500 children genotyped on the Affymetrix 500K GeneChip, and a replication study included 3,400 children. We used this to examine the performance of GWA methods in Africa. We found considerable population stratification, and also that signals of association at known malaria resistance loci were greatly attenuated owing to weak linkage disequilibrium (LD). To investigate possible solutions to the problem of low LD, we focused on the HbS locus, sequencing this region of the genome in 62 Gambian individuals and then using these data to conduct multipoint imputation in the GWA samples. This increased the signal of association, from P = 4 × 10(-7) to P = 4 × 10(-14), with the peak of the signal located precisely at the HbS causal variant. Our findings provide proof of principle that fine-resolution multipoint imputation, based on population-specific sequencing data, can substantially boost authentic GWA signals and enable fine mapping of causal variants in African populations