Evidence map›Paper›PMID 30975191›Full record

ArticleClinical epigenetics2019

DNA methylome profiling of granulosa cells reveals altered methylation in genes regulating vital ovarian functions in polycystic ovary syndrome.

Pooja Sagvekar, Pankaj Kumar, Vijay Mangoli, Sadhana Desai, Srabani Mukherjee

Open access · goldAbstract read
In one paragraph

Article in Clinical epigenetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 2 pooled it
11.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

64 citing papers in PubMed, 2 syntheses or guidelines pooled it, 106 citations in OpenAlex.

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4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Pooja SagvekarDepartment of Molecular Endocrinology, ICMR-National Institute for Research in Reproductive Health, J.M. Street, Parel, Mumbai, Maharashtra, 400012, India.
Pankaj KumarColin Jamura Lab, Institute for Stem Cell Biology and Regenerative Medicine (inStem), National Centre for Biological Sciences (NCBS), GKVK, Bellary Road, Bangalore, 560065, India.
Vijay MangoliFertility Clinic and IVF Center, 12-Springfield, 19-Vachha Gandhi Road, Gamdevi, Mumbai, Maharashtra, 400007, India.
Sadhana DesaiFertility Clinic and IVF Center, 12-Springfield, 19-Vachha Gandhi Road, Gamdevi, Mumbai, Maharashtra, 400007, India.
Srabani MukherjeeDepartment of Molecular Endocrinology, ICMR-National Institute for Research in Reproductive Health, J.M. Street, Parel, Mumbai, Maharashtra, 400012, India. mukherjees@nirrh.res.in.ORCID 0000-0001-9243-4428
Bloom Fertility Centre · INNational Institute for Research in Reproductive Health · INNational Centre for Biological Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWomen with polycystic ovary syndrome (PCOS) manifest a host of ovarian defects like impaired folliculogenesis, anovulation, and poor oocyte quality, which grossly affect their reproductive health. Addressing the putative epigenetic anomalies that tightly regulate these events is of foremost importance in this disorder. We therefore aimed to carry out DNA methylome profiling of cumulus granulosa cells and assess the methylation and transcript expression profiles of a few differentially methylated genes contributing to ovarian defects in PCOS. A total of 20 controls and 20 women with PCOS were selected from a larger cohort of women undergoing IVF, after carefully screening their sera and follicular fluids for hormonal and biochemical parameters. DNA extracted from cumulus granulosa cells of three women each, from control and PCOS groups was subjected to high-throughput, next generation bisulfite sequencing, using the Illumina HiSeq 2500® platform. Remaining samples were used for the validation of methylation status of some identified genes by pyrosequencing, and the transcript expression profiles of these genes were assessed by quantitative real-time PCR.

resultsIn all, 6486 CpG sites representing 3840 genes associated with Wnt signaling, G protein receptor, endothelin/integrin signaling, angiogenesis, chemokine/cytokine-mediated inflammation, etc., showed differential methylation in PCOS. Hypomethylation was noted in 2977 CpGs representing 2063 genes while 2509 CpGs within 1777 genes showed hypermethylation. Methylation differences were also noted in noncoding RNAs regulating several ovarian functions that are dysregulated in PCOS. Few differentially methylated genes such as aldo-keto reductase family 1 member C3, calcium-sensing receptor, resistin, mastermind-like domain 1, growth hormone-releasing hormone receptor and tumor necrosis factor, which predominantly contribute to hyperandrogenism, premature luteolysis, and oocyte development defects, were explored as novel epigenetic candidates in mediating ovarian dysfunction. Methylation profiles of these genes matched with our NGS findings, and their transcript expression patterns correlated with the gene hypo- or hypermethylation status.

conclusionOur findings suggest that the epigenetic dysregulation of genes involved in important processes associated with follicular development may contribute to ovarian defects observed in women with PCOS.

Indexed as

DNA MethylationAdultCase-Control StudiesCpG IslandsEpigenesis, GeneticFemaleGene Expression ProfilingGene Expression RegulationGranulosa CellsHigh-Throughput Nucleotide SequencingHumansPolycystic Ovary SyndromeSequence Analysis, DNADNA methylationGranulosa cellsIVFMethylome profilingNGSPCOS

Identifiers

PMID30975191
PMCPMC6458760
OpenAlexW2942837101

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.