Mono- and biallelic variant effects on disease at biobank scale.
Henrike O HeyneJ KarjalainenKonrad J KarczewskiS M LemmeläWei Zhounull nullAki Samuli HavulinnaM KurkiMichael J BamshadAarno PalotieMark J DalyPublished in: Nature (2023)
Identifying causal factors for Mendelian and common diseases is an ongoing challenge in medical genetics 1 . Population bottleneck events, such as those that occurred in the history of the Finnish population, enrich some homozygous variants to higher frequencies, which facilitates the identification of variants that cause diseases with recessive inheritance 2,3 . Here we examine the homozygous and heterozygous effects of 44,370 coding variants on 2,444 disease phenotypes using data from the nationwide electronic health records of 176,899 Finnish individuals. We find associations for homozygous genotypes across a broad spectrum of phenotypes, including known associations with retinal dystrophy and novel associations with adult-onset cataract and female infertility. Of the recessive disease associations that we identify, 13 out of 20 would have been missed by the additive model that is typically used in genome-wide association studies. We use these results to find many known Mendelian variants whose inheritance cannot be adequately described by a conventional definition of dominant or recessive. In particular, we find variants that are known to cause diseases with recessive inheritance with significant heterozygous phenotypic effects. Similarly, we find presumed benign variants with disease effects. Our results show how biobanks, particularly in founder populations, can broaden our understanding of complex dosage effects of Mendelian variants on disease.
Keyphrases
- copy number
- mitochondrial dna
- electronic health record
- intellectual disability
- early onset
- healthcare
- gene expression
- type diabetes
- optical coherence tomography
- genome wide association
- cross sectional
- insulin resistance
- diabetic retinopathy
- data analysis
- clinical decision support
- polycystic ovary syndrome
- genetic diversity