Relating pathogenic loss-of-function mutations in humans to their evolutionary fitness costs.
Elife
; 122023 01 17.
Article
in En
| MEDLINE
| ID: mdl-36648429
Causal loss-of-function (LOF) variants for Mendelian and severe complex diseases are enriched in 'mutation intolerant' genes. We show how such observations can be interpreted in light of a model of mutation-selection balance and use the model to relate the pathogenic consequences of LOF mutations at present to their evolutionary fitness effects. To this end, we first infer posterior distributions for the fitness costs of LOF mutations in 17,318 autosomal and 679 X-linked genes from exome sequences in 56,855 individuals. Estimated fitness costs for the loss of a gene copy are typically above 1%; they tend to be largest for X-linked genes, whether or not they have a Y homolog, followed by autosomal genes and genes in the pseudoautosomal region. We compare inferred fitness effects for all possible de novo LOF mutations to those of de novo mutations identified in individuals diagnosed with one of six severe, complex diseases or developmental disorders. Probands carry an excess of mutations with estimated fitness effects above 10%; as we show by simulation, when sampled in the population, such highly deleterious mutations are typically only a couple of generations old. Moreover, the proportion of highly deleterious mutations carried by probands reflects the typical age of onset of the disease. The study design also has a discernible influence: a greater proportion of highly deleterious mutations is detected in pedigree than case-control studies, and for autism, in simplex than multiplex families and in female versus male probands. Thus, anchoring observations in human genetics to a population genetic model allows us to learn about the fitness effects of mutations identified by different mapping strategies and for different traits.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Autistic Disorder
/
Loss of Function Mutation
Type of study:
Health_economic_evaluation
/
Observational_studies
Limits:
Female
/
Humans
/
Male
Language:
En
Journal:
Elife
Year:
2023
Document type:
Article
Affiliation country:
United States
Country of publication:
United kingdom