Evidence map›Paper›PMID 34831407›Full record

ReviewCells2021

Bench Research Informed by GWAS Results.

Nikolay V Kondratyev, Margarita V Alfimova, Arkadiy K Golov, Vera E Golimbet

Abstract readReview
In one paragraph

Review in Cells, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Identifying Candidate Genes for Grape (Journal of agricultural and food chemistry · 2025
    Article
  2. Article
  3. Article
  4. Article
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

4 authors.

Nikolay V KondratyevMental Health Research Center, 115522 Moscow, Russia.ORCID 0000-0002-5134-6007
Margarita V AlfimovaMental Health Research Center, 115522 Moscow, Russia.
Arkadiy K GolovMental Health Research Center, 115522 Moscow, Russia.
Vera E GolimbetMental Health Research Center, 115522 Moscow, Russia.

Funding

Russian Science Foundation 21-15-00124
6 · The paper itself

Abstract

Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.

Indexed as

Biomedical ResearchGenome-Wide Association StudyFollow-Up StudiesHumansMolecular Sequence AnnotationMultifactorial InheritancePublicationscomplex traitsGWASpolygenic scores

Identifiers

PMID34831407
PMCPMC8623533

What Socratic 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 Socratic graph.