Evidence map›Paper›PMID 35207567›Full record

ReviewLife (Basel, Switzerland)2022

Omics and Male Infertility: Highlighting the Application of Transcriptomic Data.

Temidayo S Omolaoye, Victor A Omolaoye, Richard K Kandasamy, Mahmood Yaseen Hachim, Stefan S Du Plessis

Open access · goldAbstract readReview
In one paragraph

Review in Life (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
6.8field-weighted citation impact, top 3% 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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 39 citations in OpenAlex.

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  6. Development of a Novel 11-Gene Signature Related to Immune Subtypes for FibromyalgiaEndocrine, metabolic & immune disorders drug targets · 2026
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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

5 authors at 4 institutions in 4 countries.

Temidayo S OmolaoyeDepartment of Basic Sciences, College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates.
Victor A OmolaoyeDepartment of Artificial Intelligence and Intelligent Systems, Faculty of Digital Engineering, University of Potsdam, 14469 Potsdam, Germany.
Richard K KandasamyDepartment of Basic Sciences, College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates.
Mahmood Yaseen HachimDepartment of Basic Sciences, College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates.ORCID 0000-0002-7096-0731
Stefan S Du PlessisDepartment of Basic Sciences, College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai 505055, United Arab Emirates.
Mohammed Bin Rashid University of Medicine and Health Sciences · AENorwegian University of Science and Technology · NOStellenbosch University · ZAUniversity of Potsdam · DE

Funding

Al Jalila Foundation MBRU-CM-PD2020-06
6 · The paper itself

Abstract

Male infertility is a multifaceted disorder affecting approximately 50% of male partners in infertile couples. Over the years, male infertility has been diagnosed mainly through semen analysis, hormone evaluations, medical records and physical examinations, which of course are fundamental, but yet inefficient, because 30% of male infertility cases remain idiopathic. This dilemmatic status of the unknown needs to be addressed with more sophisticated and result-driven technologies and/or techniques. Genetic alterations have been linked with male infertility, thereby unveiling the practicality of investigating this disorder from the "omics" perspective. Omics aims at analyzing the structure and functions of a whole constituent of a given biological function at different levels, including the molecular gene level (genomics), transcript level (transcriptomics), protein level (proteomics) and metabolites level (metabolomics). In the current study, an overview of the four branches of omics and their roles in male infertility are briefly discussed; the potential usefulness of assessing transcriptomic data to understand this pathology is also elucidated. After assessing the publicly obtainable transcriptomic data for datasets on male infertility, a total of 1385 datasets were retrieved, of which 10 datasets met the inclusion criteria and were used for further analysis. These datasets were classified into groups according to the disease or cause of male infertility. The groups include non-obstructive azoospermia (NOA), obstructive azoospermia (OA), non-obstructive and obstructive azoospermia (NOA and OA), spermatogenic dysfunction, sperm dysfunction, and Y chromosome microdeletion. Findings revealed that 8 genes (

Indexed as

genomicsmale infertilitymetabolomicsomicsproteomicstranscriptomics

Identifiers

PMID35207567
PMCPMC8875138
OpenAlexW4213081917

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.