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Identification and analysis of individuals who deviate from their genetically-predicted phenotype.

Gareth HawkesLoic YengoSailaja VedantamEirini MarouliRobin N Beaumontnull nullJessica TyrrellMichael N WeedonJoel HirschhornTimothy M FraylingAndrew R Wood
Published in: bioRxiv : the preprint server for biology (2023)
Human genetics is becoming increasingly useful to help predict human traits across a population owing to findings from large-scale genetic association studies and advances in the power of genetic predictors. This provides an opportunity to potentially identify individuals that deviate from genetic predictions for a common phenotype under investigation. For example, an individual may be genetically predicted to be tall, but be shorter than expected. It is potentially important to identify individuals who deviate from genetic predictions as this can facilitate further follow-up to assess likely causes. Using 158,951 unrelated individuals from the UK Biobank, with height and LDL cholesterol, as exemplar traits, we demonstrate that approximately 0.15% & 0.12% of individuals deviate from their genetically predicted phenotypes respectively. We observed these individuals to be enriched for a range of rare clinical diagnoses, as well as rare genetic factors that may be causal. Our analyses also demonstrate several methods for detecting individuals who deviate from genetic predictions that can be applied to a range of continuous human phenotypes.
Keyphrases
  • genome wide
  • endothelial cells
  • cross sectional