Shantanu Sengupta

Mining literature for a comprehensive pathway analysis: A case study for retrieval of homocysteine related genes for genetic and epigenetic studies

Homocysteine is an independent risk factor for cardiovascular diseases. It is also known to be associated with a variety of complex disorders. While there are a large number of independent studies implicating homocysteine in isolated pathways, the mechanism of homocysteine induced adverse effects are not clear. Homocysteine-induced modulation of gene expression through alteration of methylation status or by hitherto unknown mechanisms is predicted to lead to several pathological conditions either directly or indirectly. In the present manuscript, using literature mining approach, we have identified the genes that are modulated directly or indirectly by an elevated level of homocysteine. These genes were then placed in appropriate pathways in an attempt to understand the molecular basis of homocysteine induced complex disorders and to provide a resource for selection of genes for polymorphism screening and analysis of mutations as well as epigenetic modifications in relation to hyperhomocysteinemia. We have identified 135 genes in 1137 abstracts that either modulate the levels of homocysteine or are modulated by elevated levels of homocysteine. Mapping the genes to their respective pathways revealed that an elevated level of homocysteine leads to the atherosclerosis either by directly affecting lipid metabolism and transport or via oxidative stress and/or Endoplasmic Reticulum (ER) stress. Elevated levels of homocysteine also decreases the bioavailability of nitric oxide and modulates the levels of other metabolites including S-adenosyl methionine and S-adenosyl homocysteine which may result in cardiovascular or neurological disorders. The ER stress emerges as the common pathway that relates to apoptosis, atherosclerosis and neurological disorders and is modulated by levels of homocysteine. The comprehensive network collated has lead to the identification of genes that are modulated by homocysteine indicating that homocysteine exerts its effect not only through modulating the substrate levels for various catalytic processes but also through regulation of expression of genes involved in complex diseases.

Detection of altered global DNA methylation in coronary artery disease patients.

Epigenetic modifications, especially alteration in DNA methylation, are increasingly being recognized as a key factor in the pathogenesis of complex disorders, including atherosclerosis. However, there are limited data on the epigenetic changes in the coronary artery disease (CAD) patients. In the present study we evaluated the methylation status of genomic DNA from peripheral lymphocytes in a cohort of 287 individuals: 137 angiographically confirmed CAD patients and 150 controls. The differential susceptibility of genomic DNA to methylation-sensitive restriction enzymes was utilized to assess the methylation status of the genome. We observed that the genomic DNA methylation in CAD patients is significantly higher than in controls (p < 0.05). Since elevated homocysteine levels are known to be an independent risk factor for CAD and a key modulator of macromolecular methylation, we investigated the probable correlation between plasma homocysteine levels and global DNA methylation. We observed a significant positive correlation of global DNA methylation with plasma homocysteine levels in CAD patients (p = 0.001). Further, within a higher range of serum homocysteine levels (>/=12-50 muM), global DNA methylation was significantly higher in CAD patients than in controls. The alteration in genomic DNA methylation associated with cardiovascular disease per se appears to be further accentuated by higher homocysteine levels.

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 × 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 Indian Genome Variation database (IGVdb): A project overview

Indian population, comprising of more than a billion people, consists of 4693 communities with several thousands of endogamous groups, 325 functioning languages and 25 scripts. To address the questions related to ethnic diversity, migrations, founder populations, predisposition to complex disorders or pharmacogenomics, one needs to understand the diversity and relatedness at the genetic level in such a diverse population. In this backdrop, six constituent laboratories of the Council of Scientific and Industrial Research (CSIR), with funding from the Government of India, initiated a network program on predictive medicine using repeats and single nucleotide polymorphisms. The Indian Genome Variation (IGV) consortium aims to provide data on validated SNPs and repeats, both novel and reported, along with gene duplications, in over a thousand genes, in 15,000 individuals drawn from Indian subpopulations. These genes have been selected on the basis of their relevance as functional and positional candidates in many common diseases including genes relevant to pharmacogenomics. This is the first large-scale comprehensive study of the structure of the Indian population with wide-reaching implications. A comprehensive platform for Indian Genome Variation (IGV) data management, analysis and creation of IGVdb portal has also been developed. The samples are being collected following ethical guidelines of Indian Council of Medical Research (ICMR) and Department of Biotechnology (DBT), India. This paper reveals the structure of the IGV project highlighting its various aspects like genesis, objectives, strategies for selection of genes, identification of the Indian subpopulations, collection of samples and discovery and validation of genetic markers, data analysis and monitoring as well as the project’s data release policy.Indian population, comprising of more than a billion people, consists of 4693 communities with several thousands of endogamous groups, 325 functioning languages and 25 scripts. To address the questions related to ethnic diversity, migrations, founder populations, predisposition to complex disorders or pharmacogenomics, one needs to understand the diversity and relatedness at the genetic level in such a diverse population. In this backdrop, six constituent laboratories of the Council of Scientific and Industrial Research (CSIR), with funding from the Government of India, initiated a network program on predictive medicine using repeats and single nucleotide polymorphisms. The Indian Genome Variation (IGV) consortium aims to provide data on validated SNPs and repeats, both novel and reported, along with gene duplications, in over a thousand genes, in 15,000 individuals drawn from Indian subpopulations. These genes have been selected on the basis of their relevance as functional and positional candidates in many common diseases including genes relevant to pharmacogenomics. This is the first large-scale comprehensive study of the structure of the Indian population with wide-reaching implications. A comprehensive platform for Indian Genome Variation (IGV) data management, analysis and creation of IGVdb portal has also been developed. The samples are being collected following ethical guidelines of Indian Council of Medical Research (ICMR) and Department of Biotechnology (DBT), India. This paper reveals the structure of the IGV project highlighting its various aspects like genesis, objectives, strategies for selection of genes, identification of the Indian subpopulations, collection of samples and discovery and validation of genetic markers, data analysis and monitoring as well as the project’s data release policy.

Whole genome expression and biochemical correlates of extreme constitutional types defined in Ayurveda.

BackgroundAyurveda is an ancient system of personalized medicine documented and practiced in India since 1500 B.C. According to this system an individuals basic constitution to a large extent determines predisposition and prognosis to diseases as well as therapy and life-style regime. Ayurveda describes seven broad constitution types (Prakriti s) each with a varying degree of predisposition to different diseases. Amongst these, three most contrasting types, Vata, Pitta, Kapha, are the most vulnerable to diseases. In the realm of modern predictive medicine, efforts are being directed towards capturing disease phenotypes with greater precision for successful identification of markers for prospective disease conditions. In this study, we explore whether the different constitution types as described in Ayurveda has molecular correlates.MethodsNormal individuals of the three most contrasting constitutional types were identified following phenotyping criteria described in Ayurveda in Indian population of Indo-European origin. The peripheral blood samples of these individuals were analysed for genome wide expression levels, biochemical and hematological parameters. Gene Ontology (GO) and pathway based analysis was carried out on differentially expressed genes to explore if there were significant enrichments of functional categories among Prakriti types.ResultsIndividuals from the three most contrasting constitutional types exhibit striking differences with respect to biochemical and hematological parameters and at genome wide expression levels. Biochemical profiles like liver function tests, lipid profiles, and hematological parameters like haemoglobin exhibited differences between Prakriti types. Functional categories of genes showing differential expression among Prakriti types were significantly enriched in core biological processes like transport, regulation of cyclin dependent protein kinase activity, immune response and regulation of blood coagulation. A significant enrichment of housekeeping, disease related and hub genes were observed in these extreme constitution types.ConclusionAyurveda based method of phenotypic classification of extreme constitutional types allows us to uncover genes that may contribute to system level differences in normal individuals which could lead to differential disease predisposition. This is a first attempt towards unraveling the clinical phenotyping principle of a traditional system of medicine in terms of modern biology. An integration of Ayurveda with genomics holds potential and promise for future predictive medicine.

Homocysteine levels are associated with MTHFR A1298C polymorphism in Indian population.

AbstractAn elevated level of homocysteine is an independent risk factor for cardiovascular diseases and is associated with other complex disorders. Homocysteine levels can be elevated due to dietary and/or genetic factors. A majority of Indian population have a low level of vitamin B12 (presumably due to vegetarian diet)—a critical nutritional factor, deficiency of which results in hyperhomocysteinemia. Hence, polymorphisms in the genes responsible for homocysteine metabolism can be perceived to have a greater impact in relation to hyperhomocysteinemia in Indian population. For this reason, the effects of diet and/or methylenetetrahydrofolate reductase (MTHFR) polymorphism were assessed in 200 individuals having varying homocysteine levels. Homocysteine levels were significantly elevated in individuals adhering to a vegetarian diet (P=0.019) or having MTHFR A1298C polymorphism (P=0.006). The minor allele frequency (MAF) of MTHFR C677T and A1298C was 0.15 and 0.44 respectively in this cohort. Since the MAF of these polymorphisms differed considerably from Caucasian and other Asian populations, frequencies of these polymorphisms were also determined in more than 400 individuals from different ethnic populations, selected from the entire country based on their geographical location and linguistic lineage, and was found to be similar to that of our cohort. The fact that MTHFR A1298C polymorphism is significantly associated with homocysteine levels, and that the CC genotype is present at a higher frequency in the Indian population, makes it extremely relevant in terms of its potential impact on hyperhomocysteinemia.

Genome-wide analysis reveals distinct patterns of epigenetic features in long non-coding RNA loci

A major fraction of the transcriptome of higher organisms comprised an extensive repertoire of long non-coding RNA (lncRNA) which express in a cell type and development stage-specific manner. While lncRNAs are a proven component of epigenetic gene expression modulation, epigenetic regulation of lncRNA itself remains poorly understood. Here we have analysed pan-genomic DNA methylation and histone modification marks (H3K4me3, H3K9me3, H3K27me3 and H3K36me3) associated with transcription start site (TSS) of lncRNA in four different cell types and three different tissue types representing various cellular stages. We observe that histone marks associated with active transcription H3K4me3 and H3K36me3 along with the repressive histone mark H3K27me3 have similar distribution pattern around TSS irrespective of cell types. Also, the density of these marks correlates well with expression of protein-coding and lncRNA genes. In contrast, the lncRNA genes harbour higher methylation density around TSS than protein-coding genes regardless of their expression status. Furthermore, we found that DNA methylation along with the other repressive histone mark H3K9me3 does not seem to play a role in lncRNA expression. Thus, our observation suggests that epigenetic regulation of lncRNA shares common features with mRNA except the role of DNA methylation which is markedly dissimilar.

lncRNome: a comprehensive knowledgebase of human long noncoding RNAs

The advent of high-throughput genome scale technologies has enabled us to unravel a large amount of the previously unknown transcriptionally active regions of the genome. Recent genome-wide studies have provided annotations of a large repertoire of various classes of noncoding transcripts. Long noncoding RNAs (lncRNAs) form a major proportion of these novel annotated noncoding transcripts, and presently known to be involved in a number of functionally distinct biological processes. Over 18 000 transcripts are presently annotated as lncRNA, and encompass previously annotated classes of noncoding transcripts including large intergenic noncoding RNA, antisense RNA and processed pseudogenes. There is a significant gap in the resources providing a stable annotation, cross-referencing and biologically relevant information. lncRNome has been envisioned with the aim of filling this gap by integrating annotations on a wide variety of biologically significant information into a comprehensive knowledgebase. To the best of our knowledge, lncRNome is one of the largest and most comprehensive resources for lncRNAs. Database URL: http://genome.igib.res.in/lncRNome

A Systematic Analysis of Eluted Fraction of Plasma Post Immunoaffinity Depletion: Implications in Biomarker Discovery

Plasma is the most easily accessible source for biomarker discovery in clinical proteomics. However, identifying potential biomarkers from plasma is a challenge given the large dynamic range of proteins. The potential biomarkers in plasma are generally present at very low abundance levels and hence identification of these low abundance proteins necessitates the depletion of highly abundant proteins. Sample pre-fractionation using immuno-depletion of high abundance proteins using multi-affinity removal system (MARS) has been a popular method to deplete multiple high abundance proteins. However, depletion of these abundant proteins can result in concomitant removal of low abundant proteins. Although there are some reports suggesting the removal of non-targeted proteins, the predominant view is that number of such proteins is small. In this study, we identified proteins that are removed along with the targeted high abundant proteins. Three plasma samples were depleted using each of the three MARS (Hu-6, Hu-14 and Proteoprep 20) cartridges. The affinity bound fractions were subjected to gelC-MS using an LTQ-Orbitrap instrument. Using four database search algorithms including MassWiz (developed in house), we selected the peptides identified at <1% FDR. Peptides identified by at least two algorithms were selected for protein identification. After this rigorous bioinformatics analysis, we identified 101 proteins with high confidence. Thus, we believe that for biomarker discovery and proper quantitation of proteins, it might be better to study both bound and depleted fractions from any MARS depleted plasma sample.

High resolution methylome map of rat indicates role of intragenic DNA methylation in identification of coding region.

DNA methylation is crucial for gene regulation and maintenance of genomic stability. Rat has been a key model system in understanding mammalian systemic physiology, however detailed rat methylome remains uncharacterized till date. Here, we present the first high resolution methylome of rat liver generated using Methylated DNA immunoprecipitation and high throughput sequencing (MeDIP-Seq) approach. We observed that within the DNA/RNA repeat elements, simple repeats harbor the highest degree of methylation. Promoter hypomethylation and exon hypermethylation were common features in both RefSeq genes and expressed genes (as evaluated by proteomic approach). We also found that although CpG islands were generally hypomethylated, about 6% of them were methylated and a large proportion (37%) of methylated islands fell within the exons. Notably, we obeserved significant differences in methylation of terminal exons (UTRs); methylation being more pronounced in coding/partially coding exons compared to the non-coding exons. Further, events like alternate exon splicing (cassette exon) and intron retentions were marked by DNA methylation and these regions are retained in the final transcript. Thus, we suggest that DNA methylation could play a crucial role in marking coding regions thereby regulating alternative splicing. Apart from generating the first high resolution methylome map of rat liver tissue, the present study provides several critical insights into methylome organization and extends our understanding of interplay between epigenome, gene expression and genome stability.