The role of common and rare genetic variation on adiposity across childhood
Kentistou, K. A.; Sundfjord, J.; Karimi, R.; Kaisinger, L. R.; Hofmeister, R. J.; Lupu, A. E.; Fragoso-Bargas, N.; Zhao, Y.; Tadross, J. A.; Steuernagel, L.; Dowsett, G. K.; Lockhart, S.; Bruening, J. C.; Liu, J.; Cortes, A.; Lo, Y.; Davitte, J.; Clement, L.; Havdahl, A.; Andreassen, O. A.; Bratland, E.; Lam, B. Y.; O'Rahilly, S.; Yeo, G. S.; Njolstad, P. R.; Kutalik, Z.; Day, F. R.; Vaudel, M.; Perry, J. R.; Ong, K. K.; Johansson, S.
Show abstract
Our understanding of the genetic architecture of obesity has primarily been shaped by observations from adult populations with relatively few studies on childhood obesity. To address this gap, we conduct a longitudinal genetic association study in up to [~]600,000 individuals with objectively measured or recalled childhood adiposity-related traits. We identify 624 common variant signals (only 7% are previously reported) associated with childhood adiposity, of which one third have no concordant association with adult BMI. Signals linked to the leptin-melanocortin pathway (BSX, GNAS, LEPR and PCSK1) and incretin-signalling genes (GIPR and GLP1R) show stronger associations in childhood than in adults, suggesting that childhood provides a more sensitive window for detecting variation in key endocrine and neuropeptide pathways regulating energy balance. This observation is further supported by integrating single-nucleus RNA sequencing data from the human hypothalamus, identifying childhood-specific adiposity-regulating cell populations in the arcuate nucleus and mammillary bodies, indicating distinct neuro-circuits that regulate adiposity only during childhood. Three signals showed parent-of-origin specific associations with childhood BMI, at KLF14 (maternal-specific), GNAS (parental-discordant) and ZDBF2 (paternal-specific). Finally, we complement these common variant analyses with DNA sequence data in 479,615 individuals, identifying rare protein-coding variation in ADCY3, CALCR, MC4R, MRAP2, POMC and MYH13, all of which demonstrate stronger adiposity associations in childhood than in adults. Collectively, our findings emphasize the value of expanding research on childhood adiposity alongside studies focused on adult obesity measures.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Whole Genome Sequencing Analysis Of Body Mass Index Identifies Novel African Ancestry-Specific Risk Allele 98%
- Rare variant associations with birth weight identify genes involved in adipose tissue regulation, placental function and insulin-like growth factor signalling 97%
- Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes 97%
Similar papers in this journal
- The extracellular vesicle transcriptome provides tissue-specific functional genomic annotation relevant to disease susceptibility in obesity 96%
- Polygenic scores capture genetic modification of the adiposity-cardiometabolic risk factor relationship 95%
- Analysis across Taiwan Biobank, Biobank Japan and UK Biobank identifies hundreds of novel loci for 36 quantitative traits 95%
Similar papers in this journal
Similar papers in this journal
- 3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity 96%
- Diet-induced loss of adipose Hexokinase 2 triggers hyperglycemia 95%
- A mouse model of human mitofusin 2-related lipodystrophy exhibits adipose-specific mitochondrial stress and reduced leptin secretion 94%
Similar papers in this journal
- Characterization of the genetic architecture of BMI in infancy and early childhood reveals age-specific effects and implicates pathways involved in Mendelian obesity 99%
- Proteome-wide Mendelian randomization implicates nephronectin as an actionable mediator of the effect of obesity on COVID-19 severity 96%
- Maternal diet disrupts the placenta-brain axis in a sex-specific manner 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.