Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response.

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Pre-polycystic ovary syndrome and polymenorrhoea as new facets of polycystic ovary syndrome (PCOS): Evidences from a single centre data set.

OBJECTIVE: Polycystic ovary syndrome (PCOS) is a complex disorder with diverse metabolic implications. Diagnosis typically relies on oligo-amenorrhoea (OA), hyperandrogenism (HA), and polycystic ovarian morphology (PCOM). However, the role of polymenorrhoea in PCOS remains understudied. Additionally, limited information exists regarding metabolic disturbances in women with partial PCOS phenotypes that do not meet diagnostic criteria. This extensive database aims to provide substantial evidence on the metabolic implications of polymenorrhoea and partial PCOS phenotypes. DESIGN: Prospective observational study. PATIENTS AND MEASUREMENTS: In this single-centre study, 6463 women with PCOS-like characteristics and 3142 age-matched healthy women were included. The study compared clinical (anthropometry, modified Ferriman Gallwey [mFG] score), hormonal (serum testosterone), and metabolic (plasma glucose, serum lipids, insulin) characteristics between women diagnosed with PCOS, those with partial PCOS phenotypes, and the healthy control group RESULTS: In all, 5174 women met Rotterdam criteria for PCOS diagnosis, while 737 were classified as Pre-PCOS, including HA (n = 538), OA (n = 121), or PCOM (n = 78). Common clinical features included oligomenorrhoea (75.5%), hirsutism (82.9%), obesity (27.2%), hypertension (1.6%), metabolic syndrome (19.6%), and diabetes mellitus (5.6%). Women diagnosed with PCOS, HA only, and OA only exhibited higher average body mass index, plasma glucose levels (both fasting and 2 h after the oral glucose tolerance test), and lipid fractions in comparison to those with PCOM and the healthy controls. However, indices of insulin resistance were similar among women with PCOS, HA, PCOM, and OA, albeit higher than in the healthy controls. The polymenorrhoea subgroup (5.9%) had lower BMI and serum testosterone, but similar mFG score, plasma glucose, insulin, and lipid levels as the oligomenorrhoea subgroup. CONCLUSION: The metabolic disturbances observed in Pre-PCOS women highlight the need to reassess diagnostic criteria. Including the polymenorrhoea subcategory in PCOS criteria is recommended due to similar metabolic dysfunctions as the oligomenorrhoea group.

Cyclin-Dependent Kinase 5 Regulates cPLA2 Activity and Neuroinflammation in Parkinson's Disease.

Hyperactivation of cyclin-dependent kinase 5 (Cdk5) by p25, contributes to neuroinflammation causing neurodegeneration in Parkinson's disease (PD) and Alzheimer's disease. However, the mechanism by which Cdk5 induces neuroinflammation in the PD brain is largely unexplored. Here, we show that Cdk5 phosphorylates cytosolic phospholipase A2 (cPLA2) at Thr-268 and Ser-505 sites lead to its activation and generation of eicosanoid products. Mutational studies using site-directed mutagenesis and molecular simulations show that the architecture of the protein changes on each single-point mutation. Interestingly, double mutations also led to a severe decline in the activity of cPLA2 and to the disruption of its translocation to the plasma membrane. Further, the brain lysates of transgenic PD mouse models show hyperactivation of Cdk5, resulting in enhanced phosphorylation of Thr-268 and Ser-505 of cPLA2 and its heightened activity, confirming the findings observed in the cell culture model of PD. These phosphorylation sites of cPLA2 and Cdk5 could be explored as the future therapeutic targets against neuroinflammation in PD. Further, conjoint transcriptomic analysis of the publicly available human PD datasets strengthens the hypothesis that genes of the arachidonic acid, prostaglandin synthesis, and inflammatory pathways are significantly upregulated in the case of PD patients compared with that of healthy control subjects.

An assessment of remotely sensed environmental variables on Dengue epidemiology in Central India.

In recent decades, dengue has been expanding rapidly in the tropical cities. Even though environmental factors and landscape features profoundly impact dengue vector abundance and disease epidemiology, significant gaps exist in understanding the role of local environmental heterogeneity on dengue epidemiology in India. In this study, we assessed the role of remotely sensed climatic factors (rainfall, temperature and humidity) and landscape variables (land use pattern, vegetation and built up density) on dengue incidence (2012-2019) in Bhopal city, Central India. Dengue hotspots in the city were assessed through geographical information system based spatial statistics. Dengue incidence increased from 0.59 cases in 2012 to 9.11 cases in 2019 per 10,000 inhabitants, and wards located in Southern Bhopal were found to be dengue hotspots. Distributed lag non-linear model combined with quasi Poisson regression was used to assess the exposure-response association, relative risk (RR), and delayed effects of environmental factors on dengue incidence. The analysis revealed a non-linear relationship between meteorological variables and dengue cases. The model shows that the risk of dengue cases increases with increasing mean temperature, rainfall and absolute humidity. The highest RR of dengue cases (~2.0) was observed for absolute humidity ≥60 g/m3 with a 5-15 week lag. Rapid urbanization assessed by an increase in the built-up area (a 9.1% increase in 2020 compared to 2014) could also be a key factor driving dengue incidence in Bhopal city. The study sheds important insight into the synergistic effects of both the landscape and climatic factors on the transmission dynamics of dengue. Furthermore, the study provides key baseline information on the climatic variables that can be used in the micro-level dengue prediction models in Bhopal and other cities with similar climatic conditions.

Comprehensive Assessment of Indian Variations in the Druggable Kinome Landscape Highlights Distinct Insights at the Sequence, Structure and Pharmacogenomic Stratum.

India confines more than 17% of the world's population and has a diverse genetic makeup with several clinically relevant rare mutations belonging to many sub-group which are undervalued in global sequencing datasets like the 1000 Genome data (1KG) containing limited samples for Indian ethnicity. Such databases are critical for the pharmaceutical and drug development industry where diversity plays a crucial role in identifying genetic disposition towards adverse drug reactions. A qualitative and comparative sequence and structural study utilizing variant information present in the recently published, largest curated Indian genome database (IndiGen) and the 1000 Genome data was performed for variants belonging to the kinase coding genes, the second most targeted group of drug targets. The sequence-level analysis identified similarities and differences among different populations based on the nsSNVs and amino acid exchange frequencies whereas a comparative structural analysis of IndiGen variants was performed with pathogenic variants reported in UniProtKB Humsavar data. The influence of these variations on structural features of the protein, such as structural stability, solvent accessibility, hydrophobicity, and the hydrogen-bond network was investigated. In-silico screening of the known drugs to these Indian variation-containing proteins reveals critical differences imparted in the strength of binding due to the variations present in the Indian population. In conclusion, this study constitutes a comprehensive investigation into the understanding of common variations present in the second largest population in the world and investigating its implications in the sequence, structural and pharmacogenomic landscape. The preliminary investigation reported in this paper, supporting the screening and detection of ADRs specific to the Indian population could aid in the development of techniques for pre-clinical and post-market screening of drug-related adverse events in the Indian population.

Genomic Surveillance of COVID-19 Variants With Language Models and Machine Learning.

The global efforts to control COVID-19 are threatened by the rapid emergence of novel SARS-CoV-2 variants that may display undesirable characteristics such as immune escape, increased transmissibility or pathogenicity. Early prediction for emergence of new strains with these features is critical for pandemic preparedness. We present Strainflow, a supervised and causally predictive model using unsupervised latent space features of SARS-CoV-2 genome sequences. Strainflow was trained and validated on 0.9 million sequences for the period December, 2019 to June, 2021 and the frozen model was prospectively validated from July, 2021 to December, 2021. Strainflow captured the rise in cases 2 months ahead of the Delta and Omicron surges in most countries including the prediction of a surge in India as early as beginning of November, 2021. Entropy analysis of Strainflow unsupervised embeddings clearly reveals the explore-exploit cycles in genomic feature-space, thus adding interpretability to the deep learning based model. We also conducted codon-level analysis of our model for interpretability and biological validity of our unsupervised features. Strainflow application is openly available as an interactive web-application for prospective genomic surveillance of COVID-19 across the globe.

High failure rate of ChAdOx1-nCoV19 immunization against asymptomatic infection in healthcare workers during a Delta variant surge.

Immunization is expected to confer protection against infection and severe disease for vaccines while reducing risks to unimmunized populations by inhibiting transmission. Here, based on serial serological studies of an observational cohort of healthcare workers, we show that during a Severe Acute Respiratory Syndrome -Coronavirus 2 Delta-variant outbreak in Delhi, 25.3% (95% Confidence Interval 16.9-35.2) of previously uninfected, ChAdOx1-nCoV19 double vaccinated, healthcare workers were infected within less than two months, based on serology. Induction of anti-spike response was similar between groups with breakthrough infection (541 U/ml, Inter Quartile Range 374) and without (342 U/ml, Inter Quartile Range 497), as was the induction of neutralization activity to wildtype. This was not vaccine failure since vaccine effectiveness estimate based on infection rates in an unvaccinated cohort were about 70% and most infections were asymptomatic. We find that while ChAdOx1-nCoV19 vaccination remains effective in preventing severe infections, it is unlikely to be completely able to block transmission and provide herd immunity.

Whole Exome Sequencing in Healthy Individuals of Extreme Constitution Types Reveals Differential Disease Risk: A Novel Approach towards Predictive Medicine.

Precision medicine aims to move from traditional reactive medicine to a system where risk groups can be identified before the disease occurs. However, phenotypic heterogeneity amongst the diseased and healthy poses a major challenge for identification markers for risk stratification and early actionable interventions. In Ayurveda, individuals are phenotypically stratified into seven constitution types based on multisystem phenotypes termed "Prakriti". It enables the prediction of health and disease trajectories and the selection of health interventions. We hypothesize that exome sequencing in healthy individuals of phenotypically homogeneous Prakriti types might enable the identification of functional variations associated with the constitution types. Exomes of 144 healthy Prakriti stratified individuals and controls from two genetically homogeneous cohorts (north and western India) revealed differential risk for diseases/traits like metabolic disorders, liver diseases, and body and hematological measurements amongst healthy individuals. These SNPs differ significantly from the Indo-European background control as well. Amongst these we highlight novel SNPs rs304447 (IFIT5) and rs941590 (SERPINA10) that could explain differential trajectories for immune response, bleeding or thrombosis. Our method demonstrates the requirement of a relatively smaller sample size for a well powered study. This study highlights the potential of integrating a unique phenotyping approach for the identification of predictive markers and the at-risk population amongst the healthy.

Determinants of high-density lipoprotein (HDL) functions beyond proteome in Asian Indians: exploring the fatty acid profile of HDL phospholipids.

Impaired high-density lipoprotein (HDL) functions are associated with development of coronary artery disease. In this study, we explored the quantitative differences in HDL (i.e. HDL proteome and fatty acid profile of HDL phospholipids) underlying the functional deficits associated with acute coronary syndrome (ACS). The relationship between HDL function and composition was assessed in 65 consecutive ACS patients and 40 healthy controls. Cholesterol efflux capacity (CEC) of HDL and lecithin cholesterol acyl transferase (LCAT) activity were significantly lower in patients with ACS compared to controls. In HDL proteome analysis, HDL isolated from ACS individuals was enriched in apolipoprotein C2 (inhibitor of LCAT), apolipoprotein C4 and serum amyloid A proteins and was deficient in apolipoprotein A-I and A-II. The fatty acid profile of HDL phospholipids analyzed using gas chromatography showed significantly lower percentages of stearic acid (17.4 ± 2.4 vs 15.8 ± 2.8, p = 0.004) and omega-3 fatty acids [eicosapentaenoic acid (1.0 (0.6-1.4) vs 0.7 (0.4-1.0), p = 0.009) and docosahexaenoic acid (1.5 ± 0.7 vs 1.3 ± 0.5, p = 0.03)] in ACS patients compared to controls. Lower percentages of these fatty acids in HDL were associated with higher odds of developing ACS. Our results suggest that distinct phospholipid fatty acid profiles found in HDL from ACS patients could be one of the contributing factors to the deranged HDL functions in these patients apart from the protein content and the inflammatory conditions.

Genetics of Ataxias in Indian Population: A Collative Insight from a Common Genetic Screening Tool.

Cerebellar ataxias (CAs) represent a group of autosomal dominant and recessive neurodegenerative disorders affecting cerebellum with or without spinal cord. Overall, CAs have preponderance for tandem nucleotide repeat expansions as an etiological factor (10 TREs explain nearly 30-40% of ataxia cohort globally). The experience of 10 years of common genetic ataxia subtypes for ≈5600 patients' referrals (Pan-India) received at a single center is shared herein. Frequencies (in %, n) of SCA types and FRDA in the sample cohort are observed as follows: SCA12 (8.6%, 490); SCA2 (8.5%, 482); SCA1 (4.8%, 272); SCA3 (2%, 113); SCA7 (0.5%, 28); SCA6 (0.1%, 05); SCA17 (0.1%, 05), and FRDA (2.2%, 127). A significant amount of variability in TRE lengths at each locus is observed, we noted presence of biallelic expansion, co-occurrence of SCA-subtypes, and the presence of premutable normal alleles. The frequency of mutated GAA-FRDA allele in healthy controls is 1/158 (0.63%), thus an expected FRDA prevalence of 1:100 000 persons. The data of this study are relevant not only for clinical decision making but also for guidance in direction of genetic investigations, transancestral comparison of genotypes, and lastly provide insight for policy decision for the consideration of SCAs under rare disease category.

Crowdsourcing assessment of maternal blood multi-omics for predicting gestational age and preterm birth.

Identification of pregnancies at risk of preterm birth (PTB), the leading cause of newborn deaths, remains challenging given the syndromic nature of the disease. We report a longitudinal multi-omics study coupled with a DREAM challenge to develop predictive models of PTB. The findings indicate that whole-blood gene expression predicts ultrasound-based gestational ages in normal and complicated pregnancies (r = 0.83) and, using data collected before 37 weeks of gestation, also predicts the delivery date in both normal pregnancies (r = 0.86) and those with spontaneous preterm birth (r = 0.75). Based on samples collected before 33 weeks in asymptomatic women, our analysis suggests that expression changes preceding preterm prelabor rupture of the membranes are consistent across time points and cohorts and involve leukocyte-mediated immunity. Models built from plasma proteomic data predict spontaneous preterm delivery with intact membranes with higher accuracy and earlier in pregnancy than transcriptomic models (AUROC = 0.76 versus AUROC = 0.6 at 27-33 weeks of gestation).

Insights from a Pan India Sero-Epidemiological survey (Phenome-India Cohort) for SARS-CoV2.

To understand the spread of SARS-CoV2, in August and September 2020, the Council of Scientific and Industrial Research (India) conducted a serosurvey across its constituent laboratories and centers across India. Of 10,427 volunteers, 1058 (10.14%) tested positive for SARS-CoV2 anti-nucleocapsid (anti-NC) antibodies, 95% of which had surrogate neutralization activity. Three-fourth of these recalled no symptoms. Repeat serology tests at 3 (n = 607) and 6 (n = 175) months showed stable anti-NC antibodies but declining neutralization activity. Local seropositivity was higher in densely populated cities and was inversely correlated with a 30-day change in regional test positivity rates (TPRs). Regional seropositivity above 10% was associated with declining TPR. Personal factors associated with higher odds of seropositivity were high-exposure work (odds ratio, 95% confidence interval, p value: 2.23, 1.92-2.59, <0.0001), use of public transport (1.79, 1.43-2.24, <0.0001), not smoking (1.52, 1.16-1.99, 0.0257), non-vegetarian diet (1.67, 1.41-1.99, <0.0001), and B blood group (1.36, 1.15-1.61, 0.001).

Multiple Alu Exonization in 3'UTR of a Primate-Specific Isoform of CYP20A1 Creates a Potential miRNA Sponge.

Alu repeats contribute to phylogenetic novelties in conserved regulatory networks in primates. Our study highlights how exonized Alus could nucleate large-scale mRNA-miRNA interactions. Using a functional genomics approach, we characterize a transcript isoform of an orphan gene, CYP20A1 (CYP20A1_Alu-LT) that has exonization of 23 Alus in its 3'UTR. CYP20A1_Alu-LT, confirmed by 3'RACE, is an outlier in length (9 kb 3'UTR) and widely expressed. Using publically available data sets, we demonstrate its expression in higher primates and presence in single nucleus RNA-seq of 15,928 human cortical neurons. miRanda predicts ∼4,700 miRNA recognition elements (MREs) for ∼1,000 miRNAs, primarily originated within these 3'UTR-Alus. CYP20A1_Alu-LT could be a potential multi-miRNA sponge as it harbors ≥10 MREs for 140 miRNAs and has cytosolic localization. We further tested whether expression of CYP20A1_Alu-LT correlates with mRNAs harboring similar MRE targets. RNA-seq with conjoint miRNA-seq analysis was done in primary human neurons where we observed CYP20A1_Alu-LT to be downregulated during heat shock response and upregulated in HIV1-Tat treatment. In total, 380 genes were positively correlated with its expression (significantly downregulated in heat shock and upregulated in Tat) and they harbored MREs for nine expressed miRNAs which were also enriched in CYP20A1_Alu-LT. MREs were significantly enriched in these 380 genes compared with random sets of differentially expressed genes (P = 8.134e-12). Gene ontology suggested involvement of these genes in neuronal development and hemostasis pathways thus proposing a novel component of Alu-miRNA-mediated transcriptional modulation that could govern specific physiological outcomes in higher primates.

Role of VapBC12 Toxin-Antitoxin Locus in Cholesterol-Induced Mycobacterial Persistence.

The worldwide increase in the frequency of multidrug-resistant and extensively drug-resistant cases of tuberculosis is mainly due to therapeutic noncompliance associated with a lengthy treatment regimen. Depending on the drug susceptibility profile, the treatment duration can extend from 6 months to 2 years. This protracted regimen is attributed to a supposedly nonreplicating and metabolically inert subset of the Mycobacterium tuberculosis population, called "persisters." The mechanism underlying stochastic generation and enrichment of persisters is not fully known. We have previously reported that the utilization of host cholesterol is essential for mycobacterial persistence. In this study, we have demonstrated that cholesterol-induced activation of a RNase toxin (VapC12) inhibits translation by targeting proT tRNA in M. tuberculosis This results in cholesterol-specific growth modulation that increases the frequency of generation of the persisters in a heterogeneous M. tuberculosis population. Also, a null mutant strain of this toxin (ΔvapC12) demonstrated an enhanced growth phenotype in a guinea pig model of M. tuberculosis infection, depicting its role in disease persistence. Thus, we have identified a novel strategy through which cholesterol-specific activation of a toxin-antitoxin module in M. tuberculosis enhances persister formation during infection. The current findings provide an opportunity to target persisters, a new paradigm facilitating tuberculosis drug development.IMPORTANCE The current TB treatment regimen involves a combination of drugs administered for an extended duration that could last for 6 months to 2 years. This could lead to noncompliance and the emergence of newer drug resistance strains. It is widely perceived that the major culprits are the so-called nonreplicating and metabolically inactive "persister" bacteria. The importance of cholesterol utilization during the persistence stage of M. tuberculosis infection and its potential role in the generation of persisters is very intriguing. We explored the mechanism involved in the cholesterol-mediated generation of persisters in mycobacteria. In this study, we have identified a toxin-antitoxin (TA) system essential for the generation of persisters during M. tuberculosis infection. This study verified that M. tuberculosis strain devoid of the VapBC12 TA system failed to persist and showed a hypervirulent phenotype in a guinea pig infection model. Our studies indicate that the M. tuberculosis VapBC12 TA system acts as a molecular switch regulating persister generation during infection. VapBC12 TA system as a drug target offers opportunities to develop shorter and more effective treatment regimens against tuberculosis.

Downregulation of peripheral PTGS2/COX-2 in response to valproate treatment in patients with epilepsy.

Antiepileptic drug therapy has significant inter-patient variability in response towards it. The current study aims to understand this variability at the molecular level using microarray-based analysis of peripheral blood gene expression profiles of patients receiving valproate (VA) monotherapy. Only 10 unique genes were found to be differentially expressed in VA responders (n = 15) and 6 genes in the non-responders (n = 8) (fold-change >2, p < 0.05). PTGS2 which encodes cyclooxygenase-2, COX-2, showed downregulation in the responders compared to the non-responders. PTGS2/COX-2 mRNA profiles in the two groups corresponded to their plasma profiles of the COX-2 product, prostaglandin E2 (PGE2). Since COX-2 is believed to regulate P-glycoprotein (P-gp), a multidrug efflux transporter over-expressed at the blood-brain barrier (BBB) in drug-resistant epilepsy, the pathway connecting COX-2 and P-gp was further explored in vitro. Investigation of the effect of VA upon the brain endothelial cells (hCMEC/D3) in hyperexcitatory conditions confirmed suppression of COX-2-dependent P-gp upregulation by VA. Our findings suggest that COX-2 downregulation by VA may suppress seizure-mediated P-gp upregulation at the BBB leading to enhanced drug delivery to the brain in the responders. Our work provides insight into the association of peripheral PTGS2/COX-2 expression with VA efficacy and the role of COX-2 as a potential therapeutic target for developing efficacious antiepileptic treatment.

Telomere repeat-binding factor 2 binds extensively to extra-telomeric G-quadruplexes and regulates the epigenetic status of several gene promoters.

The role of the telomere repeat-binding factor 2 (TRF2) in telomere maintenance is well-established. However, recent findings suggest that TRF2 also functions outside telomeres, but relatively little is known about this function. Herein, using genome-wide ChIP-Seq assays of TRF2-bound chromatin from HT1080 fibrosarcoma cells, we identified thousands of TRF2-binding sites within the extra-telomeric genome. In light of this observation, we asked how TRF2 occupancy is organized within the genome. Interestingly, we found that extra-telomeric TRF2 sites throughout the genome are enriched in potential G-quadruplex-forming DNA sequences. Furthermore, we validated TRF2 occupancy at several promoter G-quadruplex motifs, which did adopt quadruplex forms in solution. TRF2 binding altered expression and the epigenetic state of several target promoters, indicated by histone modifications resulting in transcriptional repression of eight of nine genes investigated here. Furthermore, TRF2 occupancy and target gene expression were also sensitive to the well-known intracellular G-quadruplex-binding ligand 360A. Together, these results reveal an extensive genome-wide association of TRF2 outside telomeres and that it regulates gene expression in a G-quadruplex-dependent fashion.

Investigating Coronary Artery Disease methylome through targeted bisulfite sequencing.

BACKGROUND: Gene environment interactions leading to epigenetic alterations play pivotal role in the pathogenesis of Coronary Artery Disease (CAD). Altered DNA methylation is one such epigenetic factor that could lead to altered disease etiology. In this study, we comprehensively identified methylation sites in several genes that have been previously associated with young CAD patients. METHODS: The study population consisted of 42 healthy controls and 33 young CAD patients (age group <50 years). We performed targeted bisulfite sequencing of promoter as well as gene body regions of several genes in various pathways like cholesterol synthesis and metabolism, endothelial dysfunction, apoptosis, which are implicated in the development of CAD. RESULTS: We observed that the genes like GALNT2, HMGCR were hypermethylated in the promoter whereas LDLR gene promoter was hypomethylated indicating that intracellular LDL uptake was higher in CAD patients. Although APOA1 did not show significant change in methylation but APOC3 and APOA5 showed variation in methylation in promoter and exonic regions. Glucokinase (GCK) and endothelial nitric oxide synthase 3 (NOS3) were hyper methylated in the promoter. Genes involved in apoptosis (BAX/BCL2/AKT2) and inflammation (PHACTR1/LCK) also showed differential methylation between controls and CAD patients. A combined analysis of the methylated CpG sites using machine learning tool revealed 14 CpGs in 11 genes that could discriminate CAD cases from controls with over 93% accuracy. CONCLUSIONS: This study is unique because it highlights important gene methylation alterations which might predict the risk of young CAD in Indian population. Large scale studies in different populations would be important for validating our findings and understanding the epigenetic events associated with CAD.

Quantitative Lipid Droplet Proteomics Reveals Mycobacterium tuberculosis Induced Alterations in Macrophage Response to Infection.

Growing evidence suggests the importance of lipid metabolism in pathogenesis of tuberculosis. Neutral lipids form the majority of lipids in a caseous granuloma, a pathology characteristic of tuberculosis. Cytosolic lipid droplets (LDs) of macrophages form the store house of these lipids and have been demonstrated to contribute to the inflammatory response to infection. The proteome of lipid droplets reflects the mechanisms of lipid metabolism active under a condition. However, infection induced changes in the proteome of these dynamic organelles remains elusive. Here, we employed quantitative proteomics to identify alterations induced upon infection with live Mycobacterium tuberculosis (Mtb) in comparison with heat killed bacilli or uninfected macrophages. We found increased abundance of proteins coupled with lipid metabolism, protein synthesis, and vesicular transport function in LDs upon infection with live Mtb. Using biochemical methods and microscopy, we validated ADP-ribosyltransferase (Arf)-like 8 (ARL8B) to be increased on the lipid droplet surface of live Mtb infected macrophages and that ARL8B is a bonafide LD protein. This study provides the first proteomic evidence that the dynamic responses to infection also encompass changes at the level of LDs. This information will be important in understanding how Mtb manipulates lipid metabolism and defense mechanisms of the host macrophage.

First Degree Relatives of Patients with Celiac Disease Harbour an Intestinal Transcriptomic Signature that Might Protect them from Enterocyte Damage.

INTRODUCTION: Celiac disease (CeD) is an autoimmune enteropathy which affects approximately 0.7% of the global population. While first-degree relatives (FDR) of patients with CeD have a 7.5% risk of developing enteropathy, many remain protected. Therefore, intestinal mucosa of FDR might have protective compensatory mechanisms against immunological injury. We have explored the protective mechanisms that may be active in intestinal mucosa of FDR. METHODS: Intestinal mucosal biopsies (4-5 pieces) from treatment naïve patients with CeD (n = 12), FDR (n = 12) (anti-tTG negative) and controls (n = 12) (anti-tTG negative) were obtained from each individual and subjected to microarray analysis using HT-12-v4 Human Expression BeadChips (Illumina). Differential gene expression analysis was carried out among CeD, FDR and controls; and resulting gene lists were analyzed using gene ontology and pathway enrichment tools. RESULTS: Patients with CeD, FDR and control groups displayed significant differential gene expression. Thirty seven genes were upregulated and 372 were downregulated in the intestinal mucosa of FDR in comparison to CeD and controls. Pseudogenes constituted about 18% (315/1751) of FDR differentially expressed genes, and formed "clusters" that associated uniquely with individual study groups. The three study groups segregated into distinct clusters in unsupervised (PCA) and supervised (random forests) modelling approaches. Pathways analysis revealed an emphasis on crypt-villous maintenance and immune regulation in the intestinal mucosa of FDR. CONCLUSIONS: Our analysis suggests that the intestinal mucosa of celiac FDR consist of a unique molecular phenotype that is distinct from CeD and controls. The transcriptomic landscape of FDR promotes maintenance of crypt-villous axis and modulation of immune mechanisms. These differences clearly demonstrate the existence of compensatory protective mechanisms in the FDR intestinal mucosa.

Exhaled breath condensate metabolome clusters for endotype discovery in asthma.

BACKGROUND: Asthma is a complex, heterogeneous disorder with similar presenting symptoms but with varying underlying pathologies. Exhaled breath condensate (EBC) is a relatively unexplored matrix which reflects the signatures of respiratory epithelium, but is difficult to normalize for dilution. METHODS: Here we explored whether internally normalized global NMR spectrum patterns, combined with machine learning, could be useful for diagnostics or endotype discovery. Nuclear magnetic resonance (NMR) spectroscopy of EBC was performed in 89 asthmatic subjects from a prospective cohort and 20 healthy controls. A random forest classifier was built to differentiate between asthmatics and healthy controls. Clustering of the spectra was done using k-means to identify potential endotypes. RESULTS: NMR spectra of the EBC could differentiate between asthmatics and healthy controls with 80% sensitivity and 75% specificity. Unsupervised clustering within the asthma group resulted in three clusters (n = 41,11, and 9). Cluster 1 patients had lower long-term exacerbation scores, when compared with other two clusters. Cluster 3 patients had lower blood eosinophils and higher neutrophils, when compared with other two clusters with a strong family history of asthma. CONCLUSION: Asthma clusters derived from NMR spectra of EBC show important clinical and chemical differences, suggesting this as a useful tool in asthma endotype-discovery.