Genome-wide association study for type 2 diabetes in Indians identifies a new susceptibility locus at 2q21

Meta-AnalysisThis is the final version of the article. Available from the American Diabetes Association via the DOI in this record.Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes-associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 × 10⁻⁹). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 × 10⁻¹²) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (P < 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D.The major funding for this work comes from Council for Scientific and Industrial Research, Government of India, in the form of the grant “Diabetes mellitus—New drug discovery R&D, molecular mechanisms, and genetic and epidemiological factors” (NWP0032-19). R.T. received a postdoctoral fellowship from the Fogarty International Center and the Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health (D43-HD-065249)

pcrEfficiency: a Web tool for PCR amplification efficiency prediction

<p>Abstract</p> <p>Background</p> <p>Relative calculation of differential gene expression in quantitative PCR reactions requires comparison between amplification experiments that include reference genes and genes under study. Ignoring the differences between their efficiencies may lead to miscalculation of gene expression even with the same starting amount of template. Although there are several tools performing PCR primer design, there is no tool available that predicts PCR efficiency for a given amplicon and primer pair.</p> <p>Results</p> <p>We have used a statistical approach based on 90 primer pair combinations amplifying templates from bacteria, yeast, plants and humans, ranging in size between 74 and 907 bp to identify the parameters that affect PCR efficiency. We developed a generalized additive model fitting the data and constructed an open source Web interface that allows the obtention of oligonucleotides optimized for PCR with predicted amplification efficiencies starting from a given sequence.</p> <p>Conclusions</p> <p>pcrEfficiency provides an easy-to-use web interface allowing the prediction of PCR efficiencies prior to web lab experiments thus easing quantitative real-time PCR set-up. A web-based service as well the source code are provided freely at <url>http://srvgen.upct.es/efficiency.html</url> under the GPL v2 license.</p

Gene Ontology annotations and resources.

The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources

An International Multi-Center Evaluation of Type 5 Long QT Syndrome: A Low Penetrant Primary Arrhythmic Condition.

Background: Insight into type 5 long QT syndrome (LQT5) has been limited to case reports and small family series. Improved understanding of the clinical phenotype and genetic features associated with rare KCNE1 variants implicated in LQT5 was sought through an international multi-center collaboration. Methods: Patients with either presumed autosomal dominant LQT5 (N = 229) or the recessive Type 2 Jervell and Lange-Nielsen syndrome (JLNS2, N = 19) were enrolled from 22 genetic arrhythmia clinics and 4 registries from 9 countries. KCNE1 variants were evaluated for ECG penetrance (defined as QTc > 460ms on presenting ECG) and genotype-phenotype segregation. Multivariable Cox regression was used to compare the associations between clinical and genetic variables with a composite primary outcome of definite arrhythmic events, including appropriate implantable cardioverter-defibrillator shocks, aborted cardiac arrest, and sudden cardiac death. Results: A total of 32 distinct KCNE1 rare variants were identified in 89 probands and 140 genotype positive family members with presumed LQT5 and an additional 19 JLNS2 patients. Among presumed LQT5 patients, the mean QTc on presenting ECG was significantly longer in probands (476.9 ± 38.6ms) compared to genotype positive family members (441.8 ± 30.9ms, p<0.001). ECG penetrance for heterozygous genotype positive family members was 20.7% (29/140). A definite arrhythmic event was experienced in 16.9% (15/89) of heterozygous probands in comparison with 1.4% (2/140) of family members (adjusted hazard ratio [HR]: 11.6, 95% confidence interval [CI]: 2.6-52.2; p=0.001). Event incidence did not differ significantly for JLNS2 patients relative to the overall heterozygous cohort (10.5% [2/19]; HR: 1.7, 95% CI: 0.3-10.8, p=0.590). The cumulative prevalence of the 32 KCNE1 variants in the Genome Aggregation Database (gnomAD), which is a human database of exome and genome sequencing data from now over 140,000 individuals, was 238-fold greater than the anticipated prevalence of all LQT5 combined (0.238% vs. 0.001%). Conclusions: The present study suggests that putative/confirmed loss-of-function KCNE1 variants predispose to QT-prolongation, however the low ECG penetrance observed suggests they do not manifest clinically in the majority of individuals, aligning with the mild phenotype observed for JLNS2 patients

Genome-Wide Association Study for Type 2 Diabetes in Indians Identifies a New Susceptibility Locus at 2q21

Indians undergoing socioeconomic and lifestyle transitions will be maximally affected by epidemic of type 2 diabetes (T2D). We conducted a two-stage genome-wide association study of T2D in 12,535 Indians, a less explored but high-risk group. We identified a new type 2 diabetes–associated locus at 2q21, with the lead signal being rs6723108 (odds ratio 1.31; P = 3.32 3 1029 ). Imputation analysis refined the signal to rs998451 (odds ratio 1.56; P = 6.3 3 10212) within TMEM163 that encodes a probable vesicular transporter in nerve terminals. TMEM163 variants also showed association with decreased fasting plasma insulin and homeostatic model assessment of insulin resistance, indicating a plausible effect through impaired insulin secretion. The 2q21 region also harbors RAB3GAP1 and ACMSD; those are involved in neurologic disorders. Forty-nine of 56 previously reported signals showed consistency in direction with similar effect sizes in Indians and previous studies, and 25 of them were also associated (P , 0.05). Known loci and the newly identified 2q21 locus altogether explained 7.65% variance in the risk of T2D in Indians. Our study suggests that common susceptibility variants for T2D are largely the same across populations, but also reveals a population-specific locus and provides further insights into genetic architecture and etiology of T2D

Mathematical models for immunology:current state of the art and future research directions

The advances in genetics and biochemistry that have taken place over the last 10 years led to significant advances in experimental and clinical immunology. In turn, this has led to the development of new mathematical models to investigate qualitatively and quantitatively various open questions in immunology. In this study we present a review of some research areas in mathematical immunology that evolved over the last 10 years. To this end, we take a step-by-step approach in discussing a range of models derived to study the dynamics of both the innate and immune responses at the molecular, cellular and tissue scales. To emphasise the use of mathematics in modelling in this area, we also review some of the mathematical tools used to investigate these models. Finally, we discuss some future trends in both experimental immunology and mathematical immunology for the upcoming years

Rescue of Photoreceptor Degeneration by Curcumin in Transgenic Rats with P23H Rhodopsin Mutation

The P23H mutation in the rhodopsin gene causes rhodopsin misfolding, altered trafficking and formation of insoluble aggregates leading to photoreceptor degeneration and autosomal dominant retinitis pigmentosa (RP). There are no effective therapies to treat this condition. Compounds that enhance dissociation of protein aggregates may be of value in developing new treatments for such diseases. Anti-protein aggregating activity of curcumin has been reported earlier. In this study we present that treatment of COS-7 cells expressing mutant rhodopsin with curcumin results in dissociation of mutant protein aggregates and decreases endoplasmic reticulum stress. Furthermore we demonstrate that administration of curcumin to P23H-rhodopsin transgenic rats improves retinal morphology, physiology, gene expression and localization of rhodopsin. Our findings indicate that supplementation of curcumin improves retinal structure and function in P23H-rhodopsin transgenic rats. This data also suggest that curcumin may serve as a potential therapeutic agent in treating RP due to the P23H rhodopsin mutation and perhaps other degenerative diseases caused by protein trafficking defects

Urinary Exosomal microRNA-451-5p Is a Potential Early Biomarker of Diabetic Nephropathy in Rats

Non-invasive renal signatures can help in serial monitoring of diabetic patients. We tested whether urinary exosomal (UE) microRNA (miR) analysis could non-invasively predict renal pathology in diabetic rats during the course of diabetes. Diabetes mellitus (DM) was induced in male Wistar rats by a single intraperitoneal injection of streptozotocin (STZ, 50 mg/kg body weight). Non-diabetic control (CTRL) rats were injected with vehicle. Insulin (INS) treatment (5U/d, s.c.) was provided to 50% of the DM rats. Urine samples were collected at weeks 3, 6, and 9 following injections and UE prepared. An increase in miR-451-5p and miR-16, observed by pilot small RNA sequencing of UE RNA, was confirmed by quantitative real-time polymerase chain reaction (qPCR) and selected for further study. Subsets of rats were euthanized after 3, 6, and 9 weeks of diabetes for renal pathology analysis, including determination of the tubulointerstitial fibrotic index (TFI) and glomerulosclerotic index (GI) scores. qPCR showed a substantial rise in miR-451-5p in UE from DM rats during thecourse of diabetes, with a significant rise (median fold change >1000) between 3 and 6 weeks. Moreover, UE miR-451-5p at 6 weeks predicted urine albumin at 9 weeks (r = 0.76). A delayed but significant rise was also observed for miR-16. In contrast, mean urine albumin only increased 21% between 3 and 6 weeks (non-significant rise), and renal TFI and GI were unchanged till 9 weeks. Renal expression of miR-451-5p and miR-16 (at 10 weeks) did not correlate with urine levels, and moreover, was negatively associated with indices of renal pathology (r�-0.70, p = 0.005 for TFI and r�-0.6, p�0.02 for GI). Overall, a relative elevation in renal miR-451-5p and miR-16 in diabetes appeared protective against diabetes- induced kidney fibrosis; while UE miR-451-5p may hold prognostic value as an earlyand sensitive non-invasive indicator of renal diseas

Using graph theory to analyze biological networks

Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system