Evidence map›Paper›PMID 35337356›Full record

ArticleBMC medical genomics2022

Cross-ethnic analysis of common gene variants in hemostasis show lopsided representation of global populations in genetic databases.

Abdimajid Osman, Jon Jonasson

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 41% 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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Abdimajid OsmanDepartment of Clinical Chemistry, University Hospital in Linköping, Ing. 64, Plan 11, 581 85, Linköping, Sweden. majid.osman@liu.se.
Jon JonassonDepartment of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Linköping University Hospital · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A majority of studies reporting human genetic variants were performed in populations of European ancestry whereas other global populations, and particularly many ethnolinguistic groups in other continents, are heavily underrepresented in these studies. To investigate the extent of this disproportionate representation of global populations concerning variants of significance to thrombosis and hemostasis, 845 single nucleotide polymorphisms (SNPs) in and around 34 genes associated with thrombosis and hemostasis and included in the commercial Axiom Precision Medicine Research Array (PMRA) were evaluated, using gene frequencies in 3 African (Somali and Luhya in East Africa, and Yoruba in West Africa) and 14 non-African (admixed American, East Asian, European, South Asian, and sub-groups) populations. Among the populations studied, Europeans were observed to be the best represented population by the hemostatic SNPs included in the PMRA. The European population also presented the largest number of common pharmacogenetic and pathogenic hemostatic variants reported in the ClinVar database. The number of such variants decreased the farther the genetic distance a population was from Europeans, with Yoruba and East Asians presenting the least number of clinically significant hemostatic SNPs in ClinVar while also being the two genetically most distinct populations from Europeans among the populations compared. Current study shows the lopsided representation of global populations as regards to hemostatic genetic variants listed in different commercial SNP arrays, such as the PMRA, and reported in genetic databases while also underlining the importance of inclusion of non-European ethnolinguistic populations in genomics studies designed to discover variants of significance to bleeding and thrombotic disorders.

Indexed as

EthnicityHemostaticsAsian PeopleDatabases, GeneticGene FrequencyHemostasisHumansPolymorphism, Single NucleotideHemostaticsGene frequencyHemostasisPopulation geneticsSingle nucleotide polymorphismThrombosis

Identifiers

PMID35337356
PMCPMC8957123
OpenAlexW4220716761

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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.