Estimating prevalence for limb-girdle muscular dystrophy based on public sequencing databases
Nicole J. Lake,
Nicholas E. Johnson,
Conrad C. Weihl,
Bradley A. Williams,
Douglas E. Albrecht,
Laura E. Rufibach,
Posted 21 Dec 2018
bioRxiv DOI: 10.1101/502708 (published DOI: 10.1038/s41436-019-0544-8)
Posted 21 Dec 2018
Purpose: Limb Girdle Muscular Dystrophies (LGMD) are a genetically heterogeneous category of autosomal inherited muscle diseases. Many genes causing LGMD have been identified, and clinical trials are beginning for treatment of some genetic subtypes. However, even with the gene-level mechanisms known, it is still difficult to get a reliable and generalizable prevalence estimation for each subtype due to the limited amount of epidemiology data and the low incidence of LGMDs. Methods: Taking advantage of recently published whole exome and genome sequencing data from the general population, we used a Bayesian method to develop a reliable disease prevalence estimator. Results: This method was applied to nine recessive LGMD subtypes. The estimated disease prevalence calculated by this method were largely comparable to published estimates from epidemiological studies, however highlighted instances of possible under-diagnosis for LGMD2B and 2L. Conclusion: The increasing size of aggregated population variant databases will allow for robust and reproducible prevalence estimates of recessive disease, which is critical for the strategic design and prioritization of clinical trials.
- Downloaded 1,145 times
- Download rankings, all-time:
- Site-wide: 7,419 out of 76,820
- In epidemiology: 67 out of 1,556
- Year to date:
- Site-wide: 7,227 out of 76,820
- Since beginning of last month:
- Site-wide: 9,372 out of 76,820
Downloads over time
Distribution of downloads per paper, site-wide
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!