Evidence map›Paper›PMID 42482148›Full record

ArticleHuman genomics2026

Association of APOC2 upstream variant rs10425530 with BMI predicted to overlap with NR2C2, GCM2 and NR2C1 binding sites.

Suzanne A Al-Bustan, Babitha G Annice, Hasan Alhaddad

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Article in Human genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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3 authors.

Suzanne A Al-BustanDepartment of Biological Sciences, Faculty of Science, Kuwait University, Sabah Al Salem University City, Safat, Shadadiya, P.O. Box 5969, 13060, Kuwait, Kuwait. s.albustan@ku.edu.kw.ORCID https://orcid.org/0000-0002-1260-4632
Babitha G AnniceDepartment of Biological Sciences, Faculty of Science, Kuwait University, Sabah Al Salem University City, Safat, Shadadiya, P.O. Box 5969, 13060, Kuwait, Kuwait.
Hasan AlhaddadDepartment of Biological Sciences, Faculty of Science, Kuwait University, Sabah Al Salem University City, Safat, Shadadiya, P.O. Box 5969, 13060, Kuwait, Kuwait.

Funding

Kuwait University Research Sector SL02/19
6 · The paper itself

Abstract

backgroundLipid metabolism involves multiple genes that contribute to various diseases including metabolic disorders. Although extensive research has focused on identifying large-effect variants in coding regions, few studies have examined the effects of variations in regulatory and non-coding regions. Apolipoprotein C2 (APOC2) gene plays a central role in activating lipoprotein lipase; however, the effect of upstream variants on its transcriptional regulation remains unclear. We aimed to (1) identify genetic variants in a targeted APOC2 upstream region of, (2) annotate and characterize predicted cis-regulatory elements (CREs) in-silico, (3) map identified variants to transcription factor binding sites (TFBS), and (4) evaluate the association of selected variants with dyslipidemia and body mass index (BMI).

resultsTwelve variants were identified by sequencing of the APOC2 targeted region in a Kuwaiti cohort (n = 600). In-silico annotation using multiple tools identified 626 putative CRE within the targeted region which were prioritized into 48 predicted TFBS of functional relevance. Four variants (rs10425530, rs111782345, rs112698600, and rs2288912) met the criteria for association testing. A significant independent association, employing multivariate analysis, was observed between rs10425530 and BMI under a dominant model (β = 2.26; p = 0.022) among the Kuwaiti Arabs that requires further investigation in a large cohort. Motif-based analyses predicted that the rs10425530 A allele may alter the binding affinity of NR2C2, NR2C1, and GCM2 motifs by 21.10%, 23.80% and 20.40%, respectively.

conclusionsTwo hypothetical models have been proposed to explain the observed association between rs10425530 and increased BMI and the predicted effect on TFBS: (1) disruption of NR2C1/NR2C2 binding sites may influence APOC2 regulation via interactions with nuclear receptors involved in energy balance and/or (2) disruption of a GCM2 binding site may act via long-range regulatory effects on parathyroid hormone pathways. These findings are exploratory and require replication in larger independent cohorts and warrants further in-vitro and in-situ investigations to elucidate definitive functional assignments in regulatory activity and chromatin accessibility. The analytical framework applied in this study could provide basis for improving the interpretation of non-coding genomic variations and groundwork for future studies combining in-silico functional predictions and experimental analysis.

Indexed as

Apolipoprotein C-IIBody Mass IndexDyslipidemiasTranscription FactorsBinding SitesFemaleHumansMalePolymorphism, Single NucleotideApolipoprotein C-IITranscription FactorsApolipoprotein C2BMICREsDyslipidemiaGenetic variantsTFBSUpstream regulatory region

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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.