Evidence map›Paper›PMID 27895139›Full record

ArticleMolecular & cellular proteomics : MCP2017

Human Spermatozoa Quantitative Proteomic Signature Classifies Normo- and Asthenozoospermia.

Mayank Saraswat, Sakari Joenväärä, Tushar Jain, Anil Kumar Tomar, Ashima Sinha, Sarman Singh, Savita Yadav, Risto Renkonen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed
–field-weighted citation impact
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

43 citing papers in PubMed.

  1. Article
  2. Review
  3. Age-Associated Proteomic Changes in Human Spermatozoa.International journal of molecular sciences · 2025
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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.

Mayank SaraswatFrom the ‡Transplantation laboratory, Haartmaninkatu 3, PO Box 21, FI-00014 University of Helsinki, Finland.
Sakari Joenväärä§HUSLAB, Helsinki University Hospital, Helsinki, Finland.
Tushar Jain¶School of Computing and Electrical Engineering, Indian Institute of Technology Mandi, Kamand-175005, Himachal Pradesh, India.
Anil Kumar Tomar‖Department of Biophysics, All India Institute of Medical Sciences, New Delhi 110029, India.
Ashima Sinha‖Department of Biophysics, All India Institute of Medical Sciences, New Delhi 110029, India.
Sarman Singh**Division of Clinical Microbiology & Molecular Medicine, Department of Laboratory Medicine, All India Institute of Medical Sciences, New Delhi-110029, India.
Savita Yadav‖Department of Biophysics, All India Institute of Medical Sciences, New Delhi 110029, India.
Risto RenkonenFrom the ‡Transplantation laboratory, Haartmaninkatu 3, PO Box 21, FI-00014 University of Helsinki, Finland; risto.renkonen@helsinki.fi.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Scarcely understood defects lead to asthenozoospermia, which results in poor fertility outcomes. Incomplete knowledge of these defects hinders the development of new therapies and reliance on interventional therapies, such as in vitro fertilization, increases. Sperm cells, being transcriptionally and translationally silent, necessitate the proteomic approach to study the sperm function. We have performed a differential proteomics analysis of human sperm and seminal plasma and identified and quantified 667 proteins in sperm and 429 proteins in seminal plasma data set, which were used for further analysis. Statistical and mathematical analysis combined with pathway analysis and self-organizing maps clustering and correlation was performed on the data set.It was found that sperm proteomic signature combined with statistical analysis as opposed to the seminal plasma proteomic signature can differentiate the normozoospermic versus the asthenozoospermic sperm samples. This is despite the results that some of the seminal plasma proteins have big fold changes among classes but they fall short of statistical significance. S-Plot of the sperm proteomic data set generated some high confidence targets, which might be implicated in sperm motility pathways. These proteins also had the area under the curve value of 0.9 or 1 in ROC curve analysis.Various pathways were either enriched in these proteomic data sets by pathway analysis or they were searched by their constituent proteins. Some of these pathways were axoneme activation and focal adhesion assembly, glycolysis, gluconeogenesis, cellular response to stress and nucleosome assembly among others. The mass spectrometric data is available via ProteomeXchange with identifier PXD004098.

Indexed as

Area Under CurveAsthenozoospermiaCluster AnalysisGene Expression RegulationGene Regulatory NetworksHumansMalePrincipal Component AnalysisProtein Interaction MapsProteomicsSemenSpermatozoa

Identifiers

PMID27895139
PMCPMC5217782

What OpenQuestion holds

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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.