Testing the expensive-tissue hypothesis’ prediction of inter-tissue competition using causal modelling with latent variables

Datos Bibliográficos

ID7989644
AutoresMeghan K Shirley (0000-0001-8800-0707, Great Ormond Street Hospital), Samuli Helle (0000-0002-6216-3759, University of Turku), Kiran Seunarine (0000-0002-2467-7716, Great Ormond Street Hospital), Owen J Arthurs (0000-0003-1213-3516, Great Ormond Street Hospital), Simon Eaton (0000-0003-0892-9204, Great Ormond Street Hospital), Jane Williams (0000-0002-0142-0299, Great Ormond Street Hospital), Chris A Clark (0000-0002-8237-6065, Great Ormond Street Hospital), J Wells (0000-0003-0411-8025, Great Ormond Street Hospital)
Año2024
Volumen6
Páginase33-e33
Fecha de publicación2024-01-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaEvolutionary Human Sciences (JOURNAL)
Identificadores de la revistaISSN: 2513-843X • E-ISSN: 2513-843X
EditorialCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/ehs.2024.26
PMID39469074
OpenAlexW4403402925
IdiomaEN
Citas recibidas2
Referencias citadas66

The expensive-tissue hypothesis (ETH) posited a brain–gut trade-off to explain how humans evolved large, costly brains. Versions of the ETH interrogating gut or other body tissues have been tested in non-human animals, but not humans. We collected brain and body composition data in 70 South Asian women and used structural equation modelling with instrumental variables, an approach that handles threats to causal inference including measurement error, unmeasured confounding and reverse causality. We tested a negative, causal effect of the latent construct ‘nutritional investment in brain tissues’ (MRI-derived brain volumes) on the construct ‘nutritional investment in lean body tissues’ (organ volume and skeletal muscle). We also predicted a negative causal effect of the brain latent on fat mass. We found negative causal estimates for both brain and lean tissue (−0.41, 95% CI, −1.13, 0.23) and brain and fat (−0.56, 95% CI, −2.46, 2.28). These results, although inconclusive, are consistent with theory and prior evidence of the brain trading off with lean and fat tissues, and they are an important step in assessing empirical evidence for the ETH in humans. Analyses using larger datasets, genetic data and causal modelling are required to build on these findings and expand the evidence base

Biology · Competition (biology · Econometrics · Latent class model · Latent variable · Machine learning · Advanced Causal Inference Techniques · Birth, Development, and Health · Computer Science · Genetic Associations and Epidemiology · Mathematics · Artificial Intelligence · Ecology