Evidence map›Paper›PMID 42896087›Full record

ArticleHuman molecular genetics2026

The monogenic forms of obesity in Saudi families.

Sultanah Turki Almolafikh, Ali A Alshatwi, Razan Orfali, Haya AlSaud

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Article in Human molecular genetics, 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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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Sultanah Turki AlmolafikhDepartment of Food Science and Nutrition, College of Food and Agricultural Sciences, King Saud University,, P.O. Box 2460, Riyadh 11451, Saudi Arabia.
Ali A AlshatwiDepartment of Food Science and Nutrition, College of Food and Agricultural Sciences, King Saud University,, P.O. Box 2460, Riyadh 11451, Saudi Arabia.
Razan OrfaliDepartment of Pharmacology, College of Medicine, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh 13317, Saudi Arabia.ORCID 0000-0002-0584-4013
Haya AlSaudKing Faisal Specialist Hospital Research Centre, Riyadh, 13458, Saudi Arabia.

Funding

Research Center in King Faisal Specialist Hospital in Riyadh
6 · The paper itself

Abstract

backgroundObesity is a multifactorial disorder with a substantial yet incompletely defined genetic component. Rare monogenic variants, particularly in consanguineous populations, may account for part of the 'missing heritability.'

objectivesTo delineate the genetic contribution to severe obesity in individuals from Saudi Arabia by pinpointing known and novel monogenic variants in families presenting with extreme phenotypes.

methodsEight multiplex Saudi families (each comprising 9 members; range: lean body weight to severe obesity) were enrolled. Adults had a BMI of ≥30 kg/m2; children exceeded the 90th percentile (overweight) or the 97th percentile (obese). Whole-exome sequencing (WES) was performed on samples collected from two children in each family, including one child with obesity and one control child without obesity. Variant calling files were filtered for quality, frequency < 1%, and predicted functional impact. Candidate loci were prioritized using Moon (Diploid) software and manual curation, then validated by Sanger sequencing.

resultsInitial filtering revealed 40 rare, potentially pathogenic variants in 35 genes shared among affected relatives. Prioritization highlighted 28 variants in 19 candidate genes, encompassing established obesity-related genes (e.g. LEPR, MC4R, BDNF) and putative novel loci linked to appetite regulation, lipid metabolism, and energy balance. Segregation analysis identified both heterozygous and homozygous variants across affected individuals, reflecting variability in inheritance patterns. Seven previously reported candidate genes did not show pathogenic variants in this cohort. Carriers of prioritized variants exhibited significantly higher BMI z-scores than non-carriers (P < 0.01), underscoring a clear genotype-phenotype correlation.

conclusionThis study broadens the catalog of genes associated with obesity in the Saudi population and demonstrates the value of studying extreme phenotypes in consanguineous families. Both previously recognized and novel variants were identified in association with severe, early-onset obesity, reflecting genetic heterogeneity across families rather than a single underlying mechanism. These findings provide a foundation for improved genetic characterization, tailored counseling, and future functional studies.

Indexed as

Genetic Predisposition to DiseaseObesityAdolescentAdultBody Mass IndexChildConsanguinityExome SequencingFemaleHumansMalePedigreePhenotypeReceptor, Melanocortin, Type 4Receptors, LeptinSaudi ArabiaLEPR protein, humanMC4R protein, humanReceptor, Melanocortin, Type 4Receptors, Leptinconsanguineous familiesheterozygosityhomozygositymonogenicobesityrare diseasesyndromic of obesity

Identifiers

PMID42896087
PMCPMC13679745

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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.