Abstract
Congenital disorders of glycosylation (CDG) are a widely acknowledged group of metabolic diseases. PMM2-CDG is the most frequently diagnosed CDG with a prevalence as high as one in 20,000. In contrast, the prevalence of other CDG types remains unknown. This study aimed to analyze the estimated prevalence of different N-linked protein glycosylation disorders. We extracted allele frequencies for diverse populations from The Genome Aggregation Database (gnomAD), encompassing variant frequency information from 141,456 individuals. To identify pathogenic variants, we used the ClinVar database as a primary source. High confidence loss-of-function variants as defined by the LOFTEE algorithm were also classified as pathogenic. After summing up population frequencies for pathogenic alleles, estimated disease birth prevalence values with confidence intervals were calculated using the Bayesian method. We first validated our approach using two more common recessive disorders (cystic fibrosis and phenylketonuria) by showing that the estimated prevalences calculated from population allele frequencies were in accordance with previously published epidemiological studies. Among assessed 27 autosomal recessive N-glycosylation disorders, the only disease with estimated birth prevalence higher than one in 100,000 was PMM2-CDG (in both, all gnomAD individuals and those with European ancestry). The combined prevalence of 27 different N-glycosylation disorders was around one in 22,000 Europeans but varied considerably across populations. We will show estimated prevalence data from diverse populations and explain the possible pitfalls of this analysis. Still, we are confident that these data will guide CDG research and clinical care to identify CDG across populations.