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bioRxiv · 10.1101/2022.07.06.499037

Estimating the prevalence of LAMA2 congenital muscular dystrophy using population genetic databases

Lake, N. J.·Phua, J.·Liu, W.·Moors, T.·Axon, S.·Lek, M.
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Abstract

BACKGROUNDRecessive pathogenic variants in LAMA2 resulting in complete or partial loss of laminin 2 protein cause congenital muscular dystrophy (LAMA2 CMD). The prevalence of LAMA2 CMD has been estimated by epidemiological studies to lie between 1.36 - 20 cases per million. However, prevalence estimates from epidemiological studies are vulnerable to inaccuracies owing to challenges with studying rare diseases. Population genetic databases offer an alternative method for estimating prevalence. OBJECTIVEWe aim to use population allele frequency data for reported and predicted pathogenic variants to estimate the birth prevalence of LAMA2 CMD. METHODSA list of reported pathogenic LAMA2 variants was compiled from public databases, and supplemented with predicted loss of function (LoF) variants in genome aggregation database (gnomAD). gnomAD allele frequencies for 273 reported pathogenic and predicted LoF LAMA2 variants were used to calculate disease prevalence using a Bayesian methodology. RESULTSThe world-wide birth prevalence of LAMA2 CMD was estimated to be 8.3 per million (95% confidence interval (CI) 6.27 - 10.5 per million). The prevalence estimates for each population in gnomAD varied, ranging from 1.79 per million in East Asians (95% CI 0.63 - 3.36) to 10.1 per million in Europeans (95% CI 6.74 - 13.9). These estimates were generally consistent with those from epidemiological studies, where available. CONCLUSIONSWe provide robust world-wide and population-specific birth prevalence estimates for LAMA2 CMD, including for non-European populations in which LAMA2 CMD prevalence hadnt been studied. This work will inform the design and prioritization of clinical trials for promising LAMA2 CMD treatments.

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Lake, N. J., Phua, J., Liu, W., Moors, T., Axon, S., Lek, M.. 2022-07-10. Estimating the prevalence of LAMA2 congenital muscular dystrophy using population genetic databases. https://doi.org/10.1101/2022.07.06.499037

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