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. 2020 Jan;22(1):102-111.
doi: 10.1038/s41436-019-0625-8. Epub 2019 Aug 6.

A genome-first approach to aggregating rare genetic variants in LMNA for association with electronic health record phenotypes

Affiliations

A genome-first approach to aggregating rare genetic variants in LMNA for association with electronic health record phenotypes

Joseph Park et al. Genet Med. 2020 Jan.

Abstract

Purpose: "Genome-first" approaches, in which genetic sequencing is agnostically linked to associated phenotypes, can enhance our understanding of rare variants' contributions to disease. Loss-of-function variants in LMNA cause a range of rare diseases, including cardiomyopathy.

Methods: We leveraged exome sequencing from 11,451 unselected individuals in the Penn Medicine Biobank to associate rare variants in LMNA with diverse electronic health record (EHR)-derived phenotypes. We used Rare Exome Variant Ensemble Learner (REVEL) to annotate rare missense variants, clustered predicted deleterious and loss-of-function variants into a "gene burden" (N = 72 individuals), and performed a phenome-wide association study (PheWAS). Major findings were replicated in DiscovEHR.

Results: The LMNA gene burden was significantly associated with primary cardiomyopathy (p = 1.78E-11) and cardiac conduction disorders (p = 5.27E-07). Most patients had not been clinically diagnosed with LMNA cardiomyopathy. We also noted an association with chronic kidney disease (p = 1.13E-06). Regression analyses on echocardiography and serum labs revealed that LMNA variant carriers had dilated cardiomyopathy and primary renal disease.

Conclusion: Pathogenic LMNA variants are an underdiagnosed cause of cardiomyopathy. We also find that LMNA loss of function may be a primary cause of renal disease. Finally, we show the value of aggregating rare, annotated variants into a gene burden and using PheWAS to identify novel ontologies for pleiotropic human genes.

Keywords: LMNA; electronic health records (EHRs); genome-first; phenome-wide association studies (PheWAS); rare variants.

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Conflict of interest statement

The other authors declare no conflicts of interest.

Figures

Fig. 1
Fig. 1. Phenome-wide association studies (PheWAS) of predicted deleterious LMNA variants.
Gene burden tests of association for predicted loss-of-function (pLOF) variants and predicted deleterious missense variants in LMNA. (a) Gene burden PheWAS of pLOF variants (N = 11 carriers) and missense variants predicted to be deleterious by 5/5 algorithms (SIFT, PolyPhen2 HumDiv, PolyPhen2 HumVar, MutationTaster, and LRT; N = 24). The blue line represents a p value of 0.05, and the red line represents the Bonferroni corrected significance threshold to adjust for multiple testing (p = 0.05/333). (b) Plot of p value for gene burden association with “primary/intrinsic cardiomyopathy” using pLOF variants and missense variants predicted to be deleterious per various REVEL cutoff scores as well as 5/5 algorithms. Each point is labeled with the number of exome-sequenced individuals who are carriers for missense variants in each threshold category without using a minor allele frequency threshold. (c) Venn diagram of number of exome-sequenced carriers for missense variants predicted to be deleterious by 5/5 algorithms and/or with a REVEL score ≥0.65. (d) Gene burden PheWAS of pLOF variants (N = 11) and missense variants with REVEL scores of at least 0.65 (N = 61). The blue line represents a p value of 0.05, and the red line represents the Bonferroni corrected significance threshold to adjust for multiple testing (p = 0.05/333).

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