Evidence map›Paper›PMID 34363073›Full record

ArticleDatabase : the journal of biological databases and curation2021

Male Infertility Knowledgebase: decoding the genetic and disease landscape.

Shaini Joseph, Smita D Mahale

Open access · goldAbstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 16 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

2 authors at 1 institution in 1 country.

Shaini JosephGenetic Research Center, ICMR-National Institute for Research in Reproductive Health, J.M. Street, Parel, Mumbai 400012, India.
Smita D MahaleEmeritus Scientist, ICMR-National Institute for Research in Reproductive Health, J.M. Street, Parel, Mumbai 400012, India.ORCID 0000-0002-4164-7455
National Institute for Research in Reproductive Health · IN

Funding

Indian Council of Medical Research and National Institute for Research in Reproductive Health (NIRRH) RA/997/11-2020
6 · The paper itself

Abstract

Male infertility is a multifactorial condition that contributes to around one-third of cases of infertility worldwide. Several chromosomal aberrations, single-gene and polygenic associations with male factor defects have been reported. These defects manifest as sperm number or sperm quality defects leading to infertility. However, in almost 40% of cases, the genetic etiology of male infertility remains unexplained. Understanding the causal genetic factors is crucial for effective patient management and counseling. Integrating the vast amount of available omics data on male infertility is a first step towards understanding, delineating and prioritizing genes associated with the different male reproductive disorders. The Male Infertility Knowledgebase (MIK) is a manually curated repository developed to boost research on the elusive genetic etiology of male infertility. It integrates information on ∼17 000 genes, their associated pathways, gene ontology, diseases and gene and sequence-based analysis tools. In addition, it also incorporates information on reported chromosomal aberrations and syndromic associations with male infertility. Disease enrichment of genes in MIK indicate a shared genetic etiology between cancer, male and female infertility disorders. While the genes involved in cancer pathways were found to be common causal factors for sperm number and sperm quality defects, the interleukin pathways were found to be shared and enriched between male factor defects and non-reproductive conditions like cardiovascular diseases, metabolic diseases, etc. Disease information in MIK can be explored further to identify high-risk conditions associated with male infertility and delineate shared genetic etiology. Utility of the knowledgebase in predicting novel genes is illustrated by identification of 149 novel candidates for cryptorchidism using gene prioritization and network analysis. MIK will serve as a platform for review of genetic information on male infertility, identification pleiotropic genes, prediction of novel candidate genes for the different male infertility diseases and for portending future high-risk diseases associated with male infertility. Database URL: http://mik.bicnirrh.res.in/.

Indexed as

Infertility, MaleFemaleHumansKnowledge BasesMaleSpermatozoa

Identifiers

PMID34363073
PMCPMC8346693
OpenAlexW3191099839

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.