Background Diabetes is an increasingly important risk factor for ischemic stroke and worsens stroke prognosis. Yet a large proportion of stroke patients who are eventually diabetic are undiagnosed. Therefore, it is important to have sensitive assessment of unrecognized hyperglycaemia in stroke patients. Design Secondary outcome analysis of a randomized controlled trial focussing on parameters of glucose metabolism and detection of diabetes and prediabetes in patients with acute ischemic stroke (AIS). Methods A total of 130 consecutively admitted patients with AIS without previously known type 2 diabetes mellitus (T2DM) were screened for diabetes or prediabetes as part of secondary outcome analysis of a randomized controlled trial that tested lifestyle intervention to prevent post-stroke cognitive decline. Patients had the oral glucose tolerance test (OGTT) and glycated hemoglobin (HbA1c) measurements in the second week after stroke onset and after 1 year. The detection rates of diabetes and prediabetes based on the OGTT or HbA1c values were compared. Results By any of the applied tests at the second week after stroke onset 62 of 130 patients (48%) had prediabetes or T2DM. Seventy-five patients had results from both tests available, the OGTT and HbA1c; according to the OGTT 40 (53.3%) patients had normal glucose metabolism, 33 (44%) had prediabetes, two (2.7%) T2DM. In 50 (66.7%) patients the HbA1c results were normal, 24 (32%) in the prediabetic and one (1.3%) in the diabetic range. The detection rate for disorders of glucose metabolism was 10% higher (absolute difference; relative difference 29%) with the OGTT compared with HbA1c. After 1 year the detection rate for prediabetes or T2DM was 7% higher with the OGTT (26% relative difference). The study intervention led to a more favourable evolution of glycemic status after 1 year. Conclusion The OGTT is a more sensitive screening tool than HbA1c for the detection of previously unrecognized glycemic disorders in patients with acute stroke with an at least a 25% relative difference in detection rate. Therefore, an OGTT should be performed in all patients with stroke with no history of diabetes. Trial registration. Unique identifier: NCT01109836.

Obesity is highly heritable. Genetic variants showing robust associationswith obesity traits have been identified through genome wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. Totally, 32 body mass index (BMI)- and 14 waist-hip ratio (WHR)-associated single nucleotide polymorphismswere genotyped, and genetic risk scores (GRS) were calculated in 18 cohorts of European ancestry (n = 68 317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages and fried potatoes (unfavorable). Multivariable adjusted, linear regression within each cohort followed by inverse variance-weighted, fixed-effects meta-analysis was used to characterize: (a) associations of each GRS with BMI and BMI-adjustedWHR and (b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P = 0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567) and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjustedWHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

Genome-wide association studies of birth weight have focused on fetal genetics, whereas relatively little is known about the role of maternal genetic variation. We aimed to identify maternal genetic variants associated with birth weight that could highlight potentially relevant maternal determinants of fetal growth. We meta-analysed data on up to 8.7 million SNPs in up to 86 577 women of European descent from the Early Growth Genetics (EGG) Consortium and the UK Biobank. We used structural equation modelling (SEM) and analyses of mother-child pairs to quantify the separate maternal and fetal genetic effects. Maternal SNPs at 10 loci (MTNR1B, HMGA2, SH2B3, KCNAB1, L3MBTL3, GCK, EBF1, TCF7L2, ACTL9, CYP3A7) were associated with offspring birth weight at P<5 x 10(-8). In SEM analyses, at least 7 of the 10 associations were consistent with effects of the maternal genotype acting via the intrauterine environment, rather than via effects of shared alleles with the fetus. Variants, or correlated proxies, at many of the loci had been previously associated with adult traits, including fasting glucose (MTNR1B, GCK and TCF7L2) and sex hormone levels (CYP3A7), and one (EBF1) with gestational duration. The identified associations indicate that genetic effects on maternal glucose, cytochrome P450 activity and gestational duration, and potentially on maternal blood pressure and immune function, are relevant for fetal growth. Further characterization of these associations in mechanistic and causal analyses will enhance understanding of the potentially modifiable maternal determinants of fetal growth, with the goal of reducing the morbidity and mortality associated with low and high birth weights.