Browsing by Author "Saumya Sarkar"

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Array-based DNA methylation profiling reveals peripheral blood differential methylation in male infertility
(Elsevier Inc., 2019) Saumya Sarkar; Kumar Mohanty Sujit; Vertika Singh; Rajesh Pandey; Sameer Trivedi; Kiran Singh; Gopal Gupta; Singh Rajender
Objective: To study peripheral blood DNA differential methylation in oligozoospermic infertile men in comparison with normozoospermic fertile controls. Design: Case-control study. Setting: Reproductive biology laboratory. Patients(s): Azoospermic and oligozoospermic infertile patients (n = 6) and normozoospermic fertile controls (n = 6) in the discovery phase, and oligo/asthenozoospermic infertile men (n = 11) and normozoospermic fertile controls (n = 10) in the validation phase. Intervention(s): Blood samples drawn from all participants, DNA isolation and methylation analysis. Main Outcome Measure(s): DNA methylation values analyzed using genomewide methylation 450K BeadChip array, followed by deep sequencing of selected regions for methylation analysis in the neighborhood regions of differentially methylated CpGs. Result(s): We found 329 differentially methylated CpG spots, out of which 245 referred to the genes, representing 170 genes. Deep-sequencing analysis confirmed the methylation pattern suggested by 450K array. A thorough literature search suggested that 38 genes play roles in spermatogenesis (PDHA2, PARP12, FHIT, RPTOR, GSTM1, GSTM5, MAGI2, BCAN, DDB2, KDM4C, AGPAT3, CAMTA1, CCR6, CUX1, DNAH17, ELMO1, FNDC3B, GNRHR, HDAC4, IRS2, LIF, SMAD3, SOD3, TALDO1, TRIM27, GAA, PAX8, RNF39, HLA-C, HLA-DRB6), are testis enriched (NFATC1, NMNAT3, PIAS2, SRPK2, WDR36, WWP2), or show methylation differences between infertile cases and controls (PTPRN2, RPH3AL). Conclusion(s): We found a statistically significant correlation between peripheral blood DNA methylation and male infertility, raising the hope that epigenome-based blood markers can be used for screening male infertility risk. The study also identified new candidates for spermatogenesis and fertility. © 2019 American Society for Reproductive Medicine
Genome-wide differential methylation analyses identifies methylation signatures of male infertility
(Oxford University Press, 2018) Kumar Mohanty Sujit; Saumya Sarkar; Vertika Singh; Rajesh Pandey; Neeraj Kumar Agrawal; Sameer Trivedi; Kiran Singh; Gopal Gupta; Singh Rajender
STUDY QUESTION: Do methylation changes in sperm DNA correlate with infertility? STUDY ANSWER: Loss of spermatogenesis and fertility was correlated with 1680 differentially-methylated CpGs (DMCs) across 1052 genes. WHAT IS KNOWN ALREADY: Methylation changes in a number of genes have been correlated with reduced sperm count and motility. STUDY DESIGN, SIZE, DURATION: This case-control study used spermatozoal DNA from 38 oligo-/oligoastheno-zoospermic infertile patients and 26 normozoospermic fertile men. PARTICIPANTS/MATERIALS, SETTINGS, METHODS: Genome-wide methylation analysis was undertaken using 450 K BeadChip on spermatozoal DNA from six infertile and six fertile men to identify DMCs. This was followed by deep sequencing of spermatozoal DNA from 32 infertile patients and 20 fertile controls. MAIN RESULTS AND THE ROLE OF CHANCE: A total of 1680 DMCs were identified, out of which 1436 were hypermethylated and 244 were hypomethylated. Classification of DMCs according to the genes identified BCAN, CTNNA3, DLGAP2, GATA3, MAGI2 and TP73 among imprinted genes, SPATA5, SPATA7, SPATA16 and SPATA22 among spermatogenesis-associated genes, KDM4C and JMJD1C, EZH2 and HDAC4 among genes which regulate methylation and gene expression, HLA-C, HLA-DRB6 and HLA-DQA1 among complementation and immune response genes, and CRISPLD1, LPHN3 and CPEB2 among other genes. Genes showing significant differential methylation in deep sequencing, i.e. HOXB1, GATA3, EBF3, BCAN and TCERG1L, are strong candidates for further investigations. The role of chance was ruled out by deep sequencing of select genes. LARGE-SCALE DATA: N/A. LIMITATIONS, REASON FOR CAUTION: Genome-wide analyses are fairly accurate, but may not be exactly validated in replication studies across all DMCs. We used the 't' test in the genome-wide methylation analysis, whereas other tests could provide a more robust and powerful analysis. WIDER IMPLICATIONS OF THE FINDINGS: DMCs can serve as markers for inclusion in infertility screening panels, particularly those in the genes showing differential methylation consistent with previous studies. The genes validated by deep sequencing are strong candidates for investigations of their roles in spermatogenesis.STUDY FUNDING/COMPETING INTEREST(S): The study was funded by the Council of Scientific and Industrial Research (CSIR), Govt. of India with grant number BSC0101 awarded to Rajender Singh. None of the authors has any competing interest to declare. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved.
Is MTHFR 677 C>T polymorphism clinically important in Polycystic Ovarian Syndrome (PCOS)? A case-control study, meta-analysis and trial sequential analysis
(Public Library of Science, 2016) S. Justin Carlus; Saumya Sarkar; Sandeep Kumar Bansal; Vertika Singh; Kiran Singh; Rajesh Kumar Jha; Nirmala Sadasivam; Sri Revathy Sadasivam; P.S. Gireesha; Kumarasamy Thangaraj; Singh Rajender
Background: Optimum efficiency of the folate pathway is considered essential for adequate ovarian function. 677 C>T substitution in the 5, 10-methylene tertrahydrofolatereductase (MTHFR) gene compromises activity of the MTHFR enzyme by about 50%. The significance of correlation between 677C>T substitution and PCOS remains dubious due to the low power of published studies. Methods and Results: We analyzed MTHFR 677 C>T site in ethnically two different PCOS case-control groups (total 261 cases and 256 controls) from India. The data analysis revealed a lack of association between this polymorphism and PCOS [OR = 1.11 (95%CI = 0.71-1.72), P = 0.66]. Group-wise analysis on the basis of ethnicity also revealed no association in any of the ethnic groups [Indo-Europeans, P = 1; Dravidians, P = 0.70]. Homocysteine levels did not differ significantly between cases (15.51 μmol/L, SD = 2.89) and controls (15.89 μmol/L, SD = 2.23). We also undertook a meta-analysis on 960 cases and 1028 controls, which suggested a significant association of the substitution with PCOS in the dominant model of analysis (OR = 1.47 (95%CI = 1.04-2.09), P = 0.032]. Trial sequential analysis corroborated findings of the traditional meta-analysis. However, we found that the conclusions of meta-analysis were strongly influenced by studies that deviated from the Hardy Weinberg equilibrium. A careful investigation of each study and a trial sequential analysis suggested that 677 C>T substitution holds no clinical significance in PCOS in most of the populations. Conclusion: In conclusion, MTHFR 677 C>T polymorphism does not affect PCOS risk in India. The association seen in the meta-analysis is due to an outlier study and studies showing deviation from the Hardy Weinberg equilibrium. © 2016 Carlus et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.