Evidence map›Paper›PMID 38536467›Full record

ArticleHuman genetics2024

Cross-ancestry genetic architecture and prediction for cholesterol traits.

Md Moksedul Momin, Xuan Zhou, Elina Hyppönen, Beben Benyamin, S Hong Lee

Abstract read
PubMed Publisher
In one paragraph

Article in Human genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-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

6 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

5 authors at 2 institutions in 1 country.

Md Moksedul MominAustralian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia. Cvasu.Momin@gmail.com.
Xuan ZhouAustralian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
Elina HyppönenAustralian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
Beben BenyaminAustralian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
S Hong LeeAustralian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia. Hong.Lee@unisa.edu.au.
University of South Australia · AUSouth Australian Health and Medical Research Institute · AU

Funding

Australian Research Council DP190100766
6 · The paper itself

Abstract

While cholesterol is essential, a high level of cholesterol is associated with the risk of cardiovascular diseases. Genome-wide association studies (GWASs) have proven successful in identifying genetic variants that are linked to cholesterol levels, predominantly in white European populations. However, the extent to which genetic effects on cholesterol vary across different ancestries remains largely unexplored. Here, we estimate cross-ancestry genetic correlation to address questions on how genetic effects are shared across ancestries. We find significant genetic heterogeneity between ancestries for cholesterol traits. Furthermore, we demonstrate that single nucleotide polymorphisms (SNPs) with concordant effects across ancestries for cholesterol are more frequently found in regulatory regions compared to other genomic regions. Indeed, the positive genetic covariance between ancestries is mostly driven by the effects of the concordant SNPs, whereas the genetic heterogeneity is attributed to the discordant SNPs. We also show that the predictive ability of the concordant SNPs is significantly higher than the discordant SNPs in the cross-ancestry polygenic prediction. The list of concordant SNPs for cholesterol is available in GWAS Catalog. These findings have relevance for the understanding of shared genetic architecture across ancestries, contributing to the development of clinical strategies for polygenic prediction of cholesterol in cross-ancestral settings.

Indexed as

CholesterolGenome-Wide Association StudyMultifactorial InheritancePolymorphism, Single NucleotideAfrican PeopleEuropean PeopleHumansSouth Asian PeopleWhite PeopleCholesterol

Identifiers

PMID38536467
OpenAlexW4393233348

What OpenQuestion holds

Textmetadata
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.