Combining evidence from human genetic and functional screens to identify pathways altering obesity and fat distribution

Baya NA; Erdem IS; Venkatesh SS; Reibe S; Charles PD; Navarro-Guerrero E; Hill B; Lassen FH; Claussnitzer M; Palmer DS; Lindgren CM

doi:10.1530/ey.22.15.6

15.6

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ESPE Yearbook of Paediatric Endocrinology (2025) 22 15.6 | DOI: 10.1530/ey.22.15.6

ESPEYB25 15. Editors' Choice Genetics (9 abstracts)

15.6. Combining evidence from human genetic and functional screens to identify pathways altering obesity and fat distribution

Baya NA , Erdem IS , Venkatesh SS , Reibe S , Charles PD , Navarro-Guerrero E , Hill B , Lassen FH , Claussnitzer M , Palmer DS & Lindgren CM

medRxiv March2025. [Preprint]. PMID: 39371160 www.medrxiv.org/content/10.1101/2024.09.19.24313913v2

In Brief: The authors analysed whole exome-sequencing data from 402,375 UK Biobank participants to identify 19 genes in which rare, predicted loss-of-function damaging variants are associated with overall body fat or region-specific fat distribution (BMI, body fat percentage and waist-hip ratio, WHR). They performed experimental CRISPR knockdown of 14 genes in human white adipose tissue cell lines to confirm their cellular impacts on lipid accumulation.

Comment: Even with significant advances in statistical genetics and bioinformatics predictions of gene and variant function (see comment in this chapter on Blair & Risch, medRxiv 2024), experimental confirmation of the predicted functional impacts remains mandatory. The authors apply state of art cellular knock down and phenotyping to validate the findings of population-based genetics studies. The authors used the high throughput Opera Phenixcell phenotyping system to detect BODIPY staining, a marker of both lipid accumulation and adipogenesis more generally, as well as RNA sequencing to detect the impacts on expression of individual genes and gene pathways. There was statistically highly significant (P=4×10^-6), but numerically only moderate overlap (3 genes: PPARG, PLIN1, and MC4R) with the 31 genes known to cause severe monogenic obesity or lipodystrophy.

Another strength of the study was the assessment of the identified variants on detailed parameters of body fat distribution, measured by both DEXA and whole body MRI, although unfortunately these traits were measured in <10% of the full study sample. Interestingly, in sex-specific analyses, rare variants in INSR decreased WHRadjBMI in females but increased WHRadjBMI in males. Unfortunately, experimental INSR knockdown was incomplete (INSR remained partially expressed) and no impact on lipid accumulation was detected in this model.