The prevalence, genetic complexity and population-specific founder effects of human autosomal recessive disorders

Abstract Autosomal recessive (AR) disorders pose a significant burden for public health. However, despite their clinical importance, epidemiology and molecular genetics of many AR diseases remain poorly characterized. Here, we analyzed the genetic variability of 508 genes associated with AR disorder...

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Autores principales: Qingyang Xiao, Volker M. Lauschke
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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R
Acceso en línea:https://doaj.org/article/f7d08ecf18b04035bbcda70b35c01a50
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Sumario:Abstract Autosomal recessive (AR) disorders pose a significant burden for public health. However, despite their clinical importance, epidemiology and molecular genetics of many AR diseases remain poorly characterized. Here, we analyzed the genetic variability of 508 genes associated with AR disorders based on sequencing data from 141,456 individuals across seven ethnogeographic groups by integrating variants with documented pathogenicity from ClinVar, with stringent functionality predictions for variants with unknown pathogenicity. We first validated our model using 85 diseases for which population-specific prevalence data were available and found that our estimates strongly correlated with the respective clinically observed disease frequencies (r = 0.68; p < 0.0001). We found striking differences in population-specific disease prevalence with 101 AR diseases (27%) being limited to specific populations, while an additional 305 diseases (68%) differed more than tenfold across major ethnogeographic groups. Furthermore, by analyzing genetic AR disease complexity, we confirm founder effects for cystic fibrosis and Stargardt disease, and provide strong evidences for >25 additional population-specific founder mutations. The presented analyses reveal the molecular genetics of AR diseases with unprecedented resolution and provide insights into epidemiology, complexity, and population-specific founder effects. These data can serve as a powerful resource for clinical geneticists to inform population-adjusted genetic screening programs, particularly in otherwise understudied ethnogeographic groups.