Association of CAPN10 SNPs and Haplotypes with Polycystic Ovary Syndrome among South Indian Women

Polycystic Ovary Syndrome (PCOS) is known to be characterized by metabolic disorder in which hyperinsulinemia and peripheral insulin resistance are central features. Given the physiological overlap between PCOS and type-2 diabetes (T2DM), and calpain 10 gene (CAPN10) being a strong candidate for T2DM, a number of studies have analyzed CAPN10 SNPs among PCOS women yielding contradictory results. Our study is first of its kind to investigate the association pattern of CAPN10 polymorphisms (UCSNP-44, 43, 56, 19 and 63) with PCOS among Indian women. 250 PCOS cases and 299 controls from Southern India were recruited for this study. Allele and genotype frequencies of the SNPs were determined and compared between the cases and controls. Results show significant association of UCSNP-44 genotype CC with PCOS (p = 0.007) with highly significant odds ratio when compared to TC (OR = 2.51, p = 0.003, 95% CI = 1.37–4.61) as well as TT (OR = 1.94, p = 0.016, 95% CI = 1.13–3.34). While the haplotype carrying the SNP-44 and SNP-19 variants (21121) exhibited a 2 fold increase in the risk for PCOS (OR = 2.37, p = 0.03), the haplotype containing SNP-56 and SNP-19 variants (11221) seems to have a protective role against PCOS (OR = 0.20, p = 0.004). Our results support the earlier evidence for a possible role of UCSNP-44 of the CAPN10 gene in the manifestation of PCOS

The role of height-associated loci identified in genome wide association studies in the determination of pediatric stature

<p>Abstract</p> <p>Background</p> <p>Human height is considered highly heritable and correlated with certain disorders, such as type 2 diabetes and cancer. Despite environmental influences, genetic factors are known to play an important role in stature determination. A number of genetic determinants of adult height have already been established through genome wide association studies.</p> <p>Methods</p> <p>To examine 51 single nucleotide polymorphisms (SNPs) corresponding to the 46 previously reported genomic loci for height in 8,184 European American children with height measurements. We leveraged genotyping data from our ongoing GWA study of height variation in children in order to query the 51 SNPs in this pediatric cohort.</p> <p>Results</p> <p>Sixteen of these SNPs yielded at least nominally significant association to height, representing fifteen different loci including <it>EFEMP1-PNPT1, GPR126, C6orf173, SPAG17</it>, Histone class 1, HLA class III and <it>GDF5-UQCC</it>. Other loci revealed no evidence for association, including <it>HMGA1 and HMGA2</it>. For the 16 associated variants, the genotype score explained 1.64% of the total variation for height z-score.</p> <p>Conclusion</p> <p>Among 46 loci that have been reported to associate with adult height to date, at least 15 also contribute to the determination of height in childhood.</p

TEAD and YAP regulate the enhancer network of human embryonic pancreatic progenitors.

The genomic regulatory programmes that underlie human organogenesis are poorly understood. Pancreas development, in particular, has pivotal implications for pancreatic regeneration, cancer and diabetes. We have now characterized the regulatory landscape of embryonic multipotent progenitor cells that give rise to all pancreatic epithelial lineages. Using human embryonic pancreas and embryonic-stem-cell-derived progenitors we identify stage-specific transcripts and associated enhancers, many of which are co-occupied by transcription factors that are essential for pancreas development. We further show that TEAD1, a Hippo signalling effector, is an integral component of the transcription factor combinatorial code of pancreatic progenitor enhancers. TEAD and its coactivator YAP activate key pancreatic signalling mediators and transcription factors, and regulate the expansion of pancreatic progenitors. This work therefore uncovers a central role for TEAD and YAP as signal-responsive regulators of multipotent pancreatic progenitors, and provides a resource for the study of embryonic development of the human pancreas

Genome-wide association analysis of self-reported daytime sleepiness identifies 42 loci that suggest biological subtypes

This is the final version. Available from the publisher via the DOI in this record.UK Biobank Sleep Traits GWAS summary statistics are available at the Sleep Disorder Knowledge Portal (SDKP) website (http://www.sleepdisordergenetics.org). All other data are contained within the article and its supplementary information or available upon request.Excessive daytime sleepiness (EDS) affects 10–20% of the population and is associated with substantial functional deficits. Here, we identify 42 loci for self-reported daytime sleepiness in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirm the aggregate effect of a genetic risk score of 42 SNPs on daytime sleepiness in independent Scandinavian cohorts and on other sleep disorders (restless legs syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). However, individual daytime sleepiness signals vary in their associations with objective short vs long sleep, and with markers of sleep continuity. The 42 sleepiness variants primarily cluster into two predominant composite biological subtypes - sleep propensity and sleep fragmentation. Shared genetic links are also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing.Medical Research Council (MRC

The genetic susceptibility to type 2 diabetes may be modulated by obesity status: implications for association studies

<p>Abstract</p> <p>Background</p> <p>Considering that a portion of the heterogeneity amongst previous replication studies may be due to a variable proportion of obese subjects in case-control designs, we assessed the association of genetic variants with type 2 diabetes (T2D) in large groups of obese and non-obese subjects.</p> <p>Methods</p> <p>We genotyped <it>RETN</it>, <it>KCNJ11</it>, <it>HNF4A</it>, <it>HNF1A</it>, <it>GCK</it>, <it>SLC30A8</it>, <it>ENPP1</it>, <it>ADIPOQ</it>, <it>PPARG</it>, and <it>TCF7L2 </it>polymorphisms in 1,283 normoglycemic (NG) and 1,581 T2D obese individuals as well as in 3,189 NG and 1,244 T2D non-obese subjects of European descent, allowing us to examine T2D risk over a wide range of BMI.</p> <p>Results</p> <p>Amongst non-obese individuals, we observed significant T2D associations with <it>HNF1A </it>I27L [odds ratio (OR) = 1.14, <it>P </it>= 0.04], <it>GCK </it>-30G>A (OR = 1.23, <it>P </it>= 0.01), <it>SLC30A8 </it>R325W (OR = 0.87, <it>P </it>= 0.04), and <it>TCF7L2 </it>rs7903146 (OR = 1.89, <it>P </it>= 4.5 × 10^-23), and non-significant associations with <it>PPARG </it>Pro12Ala (OR = 0.85, <it>P </it>= 0.14), <it>ADIPOQ </it>-11,377C>G (OR = 1.00, <it>P </it>= 0.97) and <it>ENPP1 </it>K121Q (OR = 0.99, <it>P </it>= 0.94). In obese subjects, associations with T2D were detected with <it>PPARG </it>Pro12Ala (OR = 0.73, <it>P </it>= 0.004), <it>ADIPOQ </it>-11,377C>G (OR = 1.26, <it>P </it>= 0.02), <it>ENPP1 </it>K121Q (OR = 1.30, <it>P </it>= 0.003) and <it>TCF7L2 </it>rs7903146 (OR = 1.30, <it>P </it>= 1.1 × 10^-4), and non-significant associations with <it>HNF1A </it>I27L (OR = 0.96, <it>P </it>= 0.53), <it>GCK </it>-30G>A (OR = 1.15, <it>P </it>= 0.12) and <it>SLC30A8 </it>R325W (OR = 0.95, <it>P </it>= 0.44). However, a genotypic heterogeneity was only found for <it>TCF7L2 </it>rs7903146 (<it>P </it>= 3.2 × 10^-5) and <it>ENPP1 </it>K121Q (<it>P </it>= 0.02). No association with T2D was found for <it>KCNJ11</it>, <it>RETN</it>, and <it>HNF4A </it>polymorphisms in non-obese or in obese individuals.</p> <p>Conclusion</p> <p>Genetic variants modulating insulin action may have an increased effect on T2D susceptibility in the presence of obesity, whereas genetic variants acting on insulin secretion may have a greater impact on T2D susceptibility in non-obese individuals.</p

Combined Effect of Hemostatic Gene Polymorphisms and the Risk of Myocardial Infarction in Patients with Advanced Coronary Atherosclerosis

BACKGROUND: Relative little attention has been devoted until now to the combined effects of gene polymorphisms of the hemostatic pathway as risk factors for Myocardial Infarction (MI), the main thrombotic complication of Coronary Artery Disease (CAD). The aim of this study was to evaluate the combined effect of ten common prothrombotic polymorphisms as a determinant of MI. METHODOLOGY/PRINCIPAL FINDINGS: We studied a total of 804 subjects, 489 of whom with angiographically proven severe CAD, with or without MI (n = 307; n = 182; respectively). An additive model considering ten common polymorphisms [Prothrombin 20210G>A, PAI-1 4G/5G, Fibrinogen beta -455G>A, FV Leiden and "R2", FVII -402G>A and -323 del/ins, Platelet ADP Receptor P2Y12 -744T>C, Platelet Glycoproteins Ia (873G>A), and IIIa (1565T>C)] was tested. The prevalence of MI increased linearly with an increasing number of unfavorable alleles (chi(2) for trend = 10.68; P = 0.001). In a multiple logistic regression model, the number of unfavorable alleles remained significantly associated with MI after adjustment for classical risk factors. As compared to subjects with 3-7 alleles, those with few (/=8) alleles had an increased MI risk (OR 2.49, 95%CIs 1.03-6.01). The number of procoagulant alleles correlated directly (r = 0.49, P = 0.006) with endogenous thrombin potential. CONCLUSIONS: The combination of prothrombotic polymorphisms may help to predict MI in patients with advanced CAD

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Glucokinase Gene Mutations: Structural and Genotype-Phenotype Analyses in MODY Children from South Italy

BACKGROUND: Maturity onset diabetes of the young type 2 (or GCK MODY) is a genetic form of diabetes mellitus provoked by mutations in the glucokinase gene (GCK). METHODOLOGY/PRINCIPAL FINDINGS: We screened the GCK gene by direct sequencing in 30 patients from South Italy with suspected MODY. The mutation-induced structural alterations in the protein were analyzed by molecular modeling. The patients' biochemical, clinical and anamnestic data were obtained. Mutations were detected in 16/30 patients (53%); 9 of the 12 mutations identified were novel (p.Glu70Asp, p.Phe123Leu, p.Asp132Asn, p.His137Asp, p.Gly162Asp, p.Thr168Ala, p.Arg392Ser, p.Glu290X, p.Gln106_Met107delinsLeu) and are in regions involved in structural rearrangements required for catalysis. The prevalence of mutation sites was higher in the small domain (7/12: approximately 59%) than in the large (4/12: 33%) domain or in the connection (1/12: 8%) region of the protein. Mild diabetic phenotypes were detected in almost all patients [mean (SD) OGTT = 7.8 mMol/L (1.8)] and mean triglyceride levels were lower in mutated than in unmutated GCK patients (p = 0.04). CONCLUSIONS: The prevalence of GCK MODY is high in southern Italy, and the GCK small domain is a hot spot for MODY mutations. Both the severity of the GCK mutation and the genetic background seem to play a relevant role in the GCK MODY phenotype. Indeed, a partial genotype-phenotype correlation was identified in related patients (3 pairs of siblings) but not in two unrelated children bearing the same mutation. Thus, the molecular approach allows the physician to confirm the diagnosis and to predict severity of the mutation

The CAPN10 Gene Is Associated with Insulin Resistance Phenotypes in the Spanish Population

Cardiovascular disease is the leading cause of morbidity and mortality in the industrialized world. Familial aggregation of cardiovascular risk factors is a frequent finding, but genetic factors affecting its presentation are still poorly understood. The calpain 10 gene (CAPN10) has been associated with type 2 diabetes (T2DM), a complex metabolic disorder with increased risk of cardiovascular disease. Moreover, the CAPN10 gene has been associated with the presence of metabolic syndrome (MS) in T2DM and in polycystic ovary syndrome (PCOS). In this work, we have analysed whether the polymorphisms UCSNP44, -43, -19 and -63 are related to several cardiovascular risk factors in the context of MS. Molecular analysis of CAPN10 gene was performed in 899 individuals randomly chosen from a cross-sectional population-based epidemiological survey. We have found that CAPN10 gene in our population is mainly associated with two indicators of the presence of insulin resistance: glucose levels two hours after a 75-g oral glucose tolerance test (OGTT) and HOMA values, although cholesterol levels and blood pressure values are also influenced by CAPN10 variants. In addition, the 1221/1121 haplogenotype is under-represented in individuals that fulfil the International Diabetes Federation (IDF) diagnostic criteria for MS. Our results suggest that CAPN10 gene is associated with insulin resistance phenotypes in the Spanish population