Evidence map›Paper›PMID 33506367›Full record

ArticleJournal of endocrinological investigation2021

Conceptualization of functional single nucleotide polymorphisms of polycystic ovarian syndrome genes: an in silico approach.

B N Prabhu, S H Kanchamreddy, A R Sharma, S K Bhat, P V Bhat, S P Kabekkodu, K Satyamoorthy, P S Rai

Open access · hybridAbstract read
In one paragraph

Article in Journal of endocrinological investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.5field-weighted citation impact, top 8% 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

12 citing papers in PubMed, 23 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

B N PrabhuDepartment of Biotechnology, Manipal School of Life Sciences, MAHE, Manipal, Karnataka, India.
S H KanchamreddyDepartment of Biotechnology, Manipal School of Life Sciences, MAHE, Manipal, Karnataka, India.
A R SharmaDepartment of Biotechnology, Manipal School of Life Sciences, MAHE, Manipal, Karnataka, India.
S K BhatDepartment of Obstetrics and Gynaecology, Dr. T.M.A Pai Hospital, MMMC, MAHE, Manipal, Karnataka, India.
P V BhatDepartment of Obstetrics and Gynaecology, Dr. T.M.A Pai Hospital, MMMC, MAHE, Manipal, Karnataka, India.
S P KabekkoduDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, MAHE, Manipal, Karnataka, India.
K SatyamoorthyDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, MAHE, Manipal, Karnataka, India.
P S RaiDepartment of Biotechnology, Manipal School of Life Sciences, MAHE, Manipal, Karnataka, India. padmalatha.rai@manipal.edu.ORCID http://orcid.org/0000-0001-7159-0560
Manipal Academy of Higher Education · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposePolycystic ovarian syndrome (PCOS) is a multi-faceted endocrinopathy frequently observed in reproductive-aged females, causing infertility. Cumulative evidence revealed that genetic and epigenetic variations, along with environmental factors, were linked with PCOS. Deciphering the molecular pathways of PCOS is quite complicated due to the availability of limited molecular information. Hence, to explore the influence of genetic variations in PCOS, we mapped the GWAS genes and performed a computational analysis to identify the SNPs and their impact on the coding and non-coding sequences.

methodsThe causative genes of PCOS were searched using the GWAS catalog, and pathway analysis was performed using ClueGO. SNPs were extracted using an Ensembl genome browser, and missense variants were shortlisted. Further, the native and mutant forms of the deleterious SNPs were modeled using I-TASSER, Swiss-PdbViewer, and PyMOL. MirSNP, PolymiRTS, miRNASNP3, and SNP2TFBS, SNPInspector databases were used to find SNPs in the miRNA binding site and transcription factor binding site (TFBS), respectively. EnhancerDB and HaploReg were used to characterize enhancer SNPs. Linkage Disequilibrium (LD) analysis was performed using LDlink.

results25 PCOS genes showed interaction with 18 pathways. 7 SNPs were predicted to be deleterious using different pathogenicity predictions. 4 SNPs were found in the miRNA target site, TFBS, and enhancer sites and were in LD with reported PCOS GWAS SNPs.

conclusionComputational analysis of SNPs residing in PCOS genes may provide insight into complex molecular interactions among genes involved in PCOS pathophysiology. It may also aid in determining the causal variants and consequently contributing to predicting disease strategies.

Indexed as

Databases, GeneticFemaleGenetic Predisposition to DiseaseGenetic VariationGenome-Wide Association StudyHumansMicroRNAsPolycystic Ovary SyndromePolymorphism, Single NucleotideSignal TransductionTranscription FactorsMicroRNAsTranscription FactorsEnhancersmiRNAsPolycystic ovarian syndromeSingle nucleotide polymorphismsTranscription factors

Identifiers

PMID33506367
PMCPMC8285346
OpenAlexW3121374377

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LicenceCC BY
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Registered trials

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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.