Search

Purpose: a population-based study in the region of Augsburg (Germany, KORA) was used to identify the prevalence of eye diseases and their risk factors in a sample of aged individuals. Methods: data originated from the KORA-Age study collected in 2012 and 822 participants (49.6% women, 50.4% men, aged 68-96 years) were asked standardised questions about eye diseases. Positive answers were validated and specified by treating ophthalmologists. Additional information came from laboratory data. Polymorphic markers were tested for candidate genes. Results: we received validations and specifications for 339 participants. The most frequent eye diseases were cataracts (299 cases, 36%), dry eyes (120 cases, 15%), glaucoma (72 cases, 9%) and age-related macular degeneration (AMD) (68 cases, 8%). Almost all participants suffering from glaucoma or from AMD also had cataracts. Cataract surgery was associated with diabetes (in men; OR = 2.24; 95% confidence interval [CI] 1.11-4.53; P = 0.025) and smoking (in women; OR = 6.77; CI 1.62-28.35; P = 0.009). In men, treatments in airway diseases was associated with cataracts (glucocorticoids: OR = 5.29, CI 1.20-23.37; P = 0.028; sympathomimetics: OR = 4.57, CI 1.39-15.00; P = 0.012). Polymorphisms in two genes were associated with AMD (ARMS2: OR = 2.28, CI 1.48-3.51; P = 0.005; CFH: OR = 2.03, CI 1.35-3.06; P = 0.010). Conclusion: combinations of eye diseases were frequent at old age. The importance of classical risk factors like diabetes, hypertension and airway diseases decreased either due to a survivor bias leaving healthier survivors in the older age group, or due to an increased influence of other up to now unknown risk factors. [ABSTRACT FROM AUTHOR]

Genome-wide association studies identified numerous disease risk loci. Delineating molecular mechanisms influenced by cis-regulatory variants is essential to understand gene regulation and ultimately disease pathophysiology. Combining bioinformatics and public domain chromatin information with quantitative proteomics supports prediction of cis-regulatory variants and enabled identification of allele-dependent binding of both, transcription factors and coregulators at the type 2 diabetes associated PPARG locus. We found rs7647481A nonrisk allele binding of Yin Yang 1 (YY1), confirmed by allele-specific chromatin immunoprecipitation in primary adipocytes. Quantitative proteomics also found the coregulator RING1 and YY1 binding protein (RYBP) whose mRNA levels correlate with improved insulin sensitivity in primary adipose cells carrying the rs7647481A nonrisk allele. Our findings support a concept with diverse cis-regulatory variants contributing to disease pathophysiology at one locus. Proteome-wide identification of both, transcription factors and coregulators, can profoundly improve understanding of mechanisms underlying genetic associations.

Aims/hypothesis: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes., Methods: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case-control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders., Results: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p < 9.2 × 10 -7 ). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10 -3 ) and prevalent type 2 diabetes (OR Val&#95;PC ae C32:2 2.64 [β 0.97 ± 0.09], p = 1.0 × 10 -27 ). Furthermore, Val&#95;PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HR Val&#95;PC ae C32:2 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10 -15 ), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose)., Conclusions/interpretation: In this study we have shown that the Val&#95;PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.