Evidence map›Paper›PMID 32902719›Full record

ArticleHuman genetics2021

Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population.

Prashantha Hebbar, Jehad Ahmed Abubaker, Mohamed Abu-Farha, Osama Alsmadi, Naser Elkum, Fadi Alkayal, Sumi Elsa John, Arshad Channanath, Rasheeba Iqbal, Janne Pitkaniemi and 4 more

Abstract read
In one paragraph

Article in Human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
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  6. Journal of diabetes research · 2025
    Article
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  9. Article
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  11. Genes · 2022
    Article
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  13. Review
  14. 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

14 authors.

Prashantha HebbarDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
Jehad Ahmed AbubakerDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
Mohamed Abu-FarhaDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
Osama AlsmadiKing Hussein Cancer Center, Amman, Jordan.
Naser ElkumSidra Medical and Research Center, Doha, Qatar.
Fadi AlkayalDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
Sumi Elsa JohnDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
Arshad ChannanathDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
Rasheeba IqbalDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait.
Janne PitkaniemiDepartment of Public Health, University of Helsinki, Helsinki, Finland.
Jaakko TuomilehtoDepartment of Public Health, University of Helsinki, Helsinki, Finland.
Robert SladekMcGill University and Genome Quebec Innovation Centre, Montreal, Canada.
Fahd Al-MullaDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait. fahd.almulla@dasmaninstitute.org.
Thangavel Alphonse ThanarajDasman Diabetes Institute, P.O. Box 1180, 15462, Dasman, Kuwait. alphonse.thangavel@dasmaninstitute.org.ORCID http://orcid.org/0000-0002-4574-5343

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified 'novel' risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyAdultArabsCohort StudiesFemaleHumansMaleMetabolic DiseasesMiddle AgedPolymorphism, Single Nucleotide

Identifiers

PMID32902719
PMCPMC7889551

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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.