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DOI 10.1002/mgg3.245

Медицинская библиотека · Molecular genetics & genomic medicine · 2016

Analyses of more than 60,000 exomes questions the role of numerous genes previously associated with dilated cardiomyopathy.

Nouhravesh Nina, Ahlberg Gustav, Ghouse Jonas, Andreasen Charlotte, Svendsen Jesper H, Haunsø Stig, Bundgaard Henning, Weeke Peter E, Olesen Morten S

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Аннотация

BACKGROUND

Hundreds of genetic variants have been described as disease causing in dilated cardiomyopathy (DCM). Some of these associations are now being questioned. We aimed to identify the prevalence of previously DCM associated variants in the Exome Aggregation Consortium (ExAC), in order to identify potentially false-positive DCM variants.

METHODS

Variants listed as DCM disease-causing variants in the Human Gene Mutation Database were extracted from ExAC. Pathogenicity predictions for these variants were mined from dbNSFP v 2.9 database.

RESULTS

Of the 473 DCM variants listed in HGMD, 148 (31%) were found in ExAC. The expected number of individuals with DCM in ExAC is 25 based on the prevalence in the general population. Yet, 35 variants were found in more than 25 individuals. In 13 genes, we identified all variants previously associated with DCM; four genes contained variants above our estimated cut-off. Prediction tools found ExAC variants to be significantly more tolerated when compared to variants not found in ExAC (P = 0.004).

CONCLUSION

In ExAC, we identified a higher genotype prevalence of variants considered disease-causing than expected. More importantly, we found 13 genes in which all variants previously associated with DCM were identified in ExAC, questioning the association of these genes with the monogenic form of DCM.

Для цитирования: Nouhravesh Nina, Ahlberg Gustav, Ghouse Jonas, Andreasen Charlotte, Svendsen Jesper H, Haunsø Stig, Bundgaard Henning, Weeke Peter E, Olesen Morten S. Analyses of more than 60,000 exomes questions the role of numerous genes previously associated with dilated cardiomyopathy.. Molecular genetics & genomic medicine. 2016. DOI: 10.1002/mgg3.245.
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