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

Park, Joseph; Levin, Michael G.; Haggerty, Christopher M.; Dn, Hartzel; Judy, Renae; Kember, Rachel L.; Reza, Nosheen; Ritchie,; At, Owens; Sm, Damrauer; Dj, Rader

doi:10.1038/s41436-019-0625-8

Cited by 51 publications

(50 citation statements)

References 39 publications

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“…The heightened MAPS score for UTC-introducing variants suggests that they are also likely to be functional. To explore the possibility that uORF UTC and stop-strengthening variants might contribute functionally to human disease susceptibility, we performed a phenome-wide association study (PheWAS) of predicted uORF-disrupting variants using the Penn Medicine Biobank (PMBB) -a large academic biobank with exome sequencing linked to EHR data for 10,900 individuals 36 .…”

Section: Uorf-disrupting Variants Associate Genes With New Disease Phmentioning

confidence: 99%

“…These studies could confirm that predicted loss-of-function in the protein coding sequence of the uORF-regulated gene causes the same phenotype as the uORF UTC or stop-strengthening variants. Indeed, similar loss-of-function gene burden approaches using rare protein-coding variants have successfully been applied to identify both known and new gene-disease associations in studies that utilized these two datasets 36,39 .…”

Section: Disease-associated Uorf Variants Change Expressionmentioning

confidence: 99%

“…These sequences were mapped to GRCh37 as previously described 36 For UKB, we used the provided ICD-10 disease diagnosis codes for replication studies, and individuals were determined to have a certain disease phenotype if they had one or more encounters for the corresponding ICD diagnosis given the lack of individuals with more than two encounters per diagnosis, while phenotypic controls consisted of individuals who never had the ICD code. Individuals under control exclusion criteria based on PheWAS phenotype mapping protocols were not considered in statistical analyses.…”

Section: Genetic Sequencingmentioning

confidence: 99%

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Disrupting upstream translation in mRNAs leads to loss-of-function associated with human disease

Lee

Park

Kromer

et al. 2020

Preprint

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Ribosome-profiling has uncovered pervasive translation in 5'UTRs, however the biological significance of this phenomenon remains unclear. Using genetic variation from 71,702 human genomes, we assess patterns of selection in translated upstream open reading frames (uORFs) in 5'UTRs. We show that uORF variants introducing new stop codons, or strengthening existing stop codons, are under strong negative selection comparable to protein-coding missense variants. Using these variants, we map and validate new gene-disease associations in two independent biobanks containing exome sequencing from 10,900 and 32,268 individuals respectively, and demonstrate their impact on gene expression in human cells. Our results establish new mechanisms relating uORF variation to loss-of-function of downstream genes, and demonstrate that translated uORFs are genetically constrained regulatory elements in 40% of human genes.

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Section: Uorf-disrupting Variants Associate Genes With New Disease Phmentioning

confidence: 99%

Section: Disease-associated Uorf Variants Change Expressionmentioning

confidence: 99%

Section: Genetic Sequencingmentioning

confidence: 99%

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Disrupting upstream translation in mRNAs leads to loss-of-function associated with human disease

Lee

Park

Kromer

et al. 2020

Preprint

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“…These sequences were mapped to GRCh37 as previously described. 7 Furthermore, for subsequent phenotypic analyses, we removed samples with low exome sequencing coverage (i.e. less than 75% of targeted bases achieving 20x coverage), high missingness (i.e.…”

Section: Exome Sequencingmentioning

confidence: 99%

“…6 Previously, we leveraged the Penn Medicine Biobank (PMBB, University of Pennsylvania), a large academic biobank with whole exome sequencing (WES) data linked to EHR data, to show that aggregating rare, loss-of-function variants in a single gene or targeted sets of genes to conduct gene burden PheWAS has the potential to uncover novel pleiotropic relationships between the gene and human disease. [7][8][9] This approach has not yet been applied on an exome-wide scale, and the clinical ontologies of loss-of-function variants in many genes have yet to be described. Thus, we applied gene burden PheWAS on an exome-wide scale utilizing WES data to conduct exome-byphenome-wide association studies (ExoPheWAS) to evaluate in detail the phenotypes (i.e.…”

Section: Introductionmentioning

confidence: 99%

Exome-by-phenome-wide rare variant gene burden association with electronic health record phenotypes

Park

Katz

Zhang

et al. 2019

Preprint

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Background: By coupling large-scale DNA sequencing with electronic health records (EHR), "genome-first" approaches can enhance our understanding of the contribution of rare genetic variants to disease. Aggregating rare, loss-of-function variants in a candidate gene into a "gene burden" to test for association with EHR phenotypes can identify both known and novel clinical implications for the gene in human disease. However, this methodology has not yet been applied on both an exome-wide and phenome-wide scale, and the clinical ontologies of rare loss-offunction variants in many genes have yet to be described. Methods: We leveraged whole exome sequencing (WES) data in participants (N=11,451) in the Penn Medicine Biobank (PMBB) to address on an exome-wide scale the association of a burden of rare loss-of-function variants in each gene with diverse EHR phenotypes using a phenomewide association study (PheWAS) approach. For discovery, we collapsed rare (minor allele frequency (MAF) ≤ 0.1%) predicted loss-of-function (pLOF) variants (i.e. frameshift insertions/deletions, gain/loss of stop codon, or splice site disruption) per gene to perform a gene burden PheWAS. Subsequent evaluation of the significant gene burden associations was done by collapsing rare (MAF ≤ 0.1%) missense variants with Rare Exonic Variant Ensemble Learner (REVEL) scores ≥ 0.5 into corresponding yet distinct gene burdens, as well as interrogation of individual low-frequency to common (MAF > 0.1%) pLOF variants and missense variants with REVEL≥ 0.5. We replicated our findings using the UK Biobank's (UKBB) whole exome sequence dataset (N=49,960).Results: From the pLOF-based discovery phase, we identified 106 gene burdens with phenotype associations at p<10 -6 from our exome-by-phenome-wide association studies. Positive-control associations included TTN (cardiomyopathy, p=7.83E-13), MYBPC3 (hypertrophic cardiomyopathy, p=3.48E-15), CFTR (cystic fibrosis, p=1.05E-15), CYP2D6 (adverse effects due to opiates/narcotics, p=1.50E-09), and BRCA2 (breast cancer, p=1.36E-07). Of the 106 genes, 12 gene-phenotype relationships were also detected by REVEL-informed missense-based gene burdens and 19 by single-variant analyses, demonstrating the robustness of these gene-phenotype relationships. Three genes showed evidence of association using both additional methods (BRCA1, CFTR, TGM6), leading to a total of 28 robust gene-phenotype associations within PMBB. Furthermore, replication studies in UKBB validated 30 of 106 gene burden associations, of which 12 demonstrated robustness in PMBB.Conclusion: Our study presents 12 exome-by-phenome-wide robust gene-phenotype associations, which include three proof-of-concept associations and nine novel findings. We show the value of aggregating rare pLOF variants into gene burdens on an exome-wide scale for unbiased association with EHR phenotypes to identify novel clinical ontologies of human genes. Furthermore, we show the significance of evaluating gene burden associations through complementary, yet non-overlapping genetic ...

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Bidirectional Risk Modulator and Modifier Variant of Dilated and Hypertrophic Cardiomyopathy in BAG3

Park,

Levin,

Zhang

et al. 2024

JAMA Cardiol

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ImportanceThe genetic factors that modulate the reduced penetrance and variable expressivity of heritable dilated cardiomyopathy (DCM) are largely unknown. BAG3 genetic variants have been implicated in both DCM and hypertrophic cardiomyopathy (HCM), nominating BAG3 as a gene that harbors potential modifier variants in DCM.ObjectiveTo interrogate the clinical traits and diseases associated with BAG3 coding variation.Design, Setting, and ParticipantsThis was a cross-sectional study in the Penn Medicine BioBank (PMBB) enrolling patients of the University of Pennsylvania Health System’s clinical practice sites from 2014 to 2023. Whole-exome sequencing (WES) was linked to electronic health record (EHR) data to associate BAG3 coding variants with EHR phenotypes. This was a health care population-based study including individuals of European and African genetic ancestry in the PMBB with WES linked to EHR phenotypes, with replication studies in BioVU, UK Biobank, MyCode, and DCM Precision Medicine Study.ExposuresCarrier status for BAG3 coding variants.Main Outcomes and MeasuresAssociation of BAG3 coding variation with clinical diagnoses, echocardiographic traits, and longitudinal outcomes.ResultsIn PMBB (n = 43 731; median [IQR] age, 65 [50-76] years; 21 907 female [50.1%]), among 30 324 European and 11 198 African individuals, the common C151R variant was associated with decreased risk for DCM (odds ratio [OR], 0.85; 95% CI, 0.78-0.92) and simultaneous increased risk for HCM (OR, 1.59; 95% CI, 1.25-2.02), which was confirmed in the replication cohorts. C151R carriers exhibited improved longitudinal outcomes compared with noncarriers as assessed by age at death (hazard ratio [HR], 0.85; 95% CI, 0.74-0.96; median [IQR] age, 71.8 [63.1-80.7] in carriers and 70.3 [61.6-79.2] in noncarriers) and heart transplant (HR, 0.81; 95% CI, 0.66-0.99; median [IQR] age, 56.7 [46.1-63.1] in carriers and 55.6 [45.2-62.9] in noncarriers). C151R was associated with reduced risk of DCM (OR, 0.42; 95% CI, 0.24-0.74) and heart failure (OR, 0.27; 95% CI, 0.14-0.50) among individuals harboring truncating TTN variants in exons with high cardiac expression (n = 358).Conclusions and RelevanceBAG3 C151R was identified as a bidirectional modulator of risk along the DCM-HCM spectrum, as well as an important genetic modifier variant in TTN-mediated DCM. This work expands on the understanding of the etiology and penetrance of DCM, suggesting that BAG3 C151R is an important genetic modifier variant contributing to the variable expressivity of DCM, warranting further exploration of its mechanisms and of genetic modifiers in DCM more broadly.

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

Cited by 51 publications

References 39 publications

Disrupting upstream translation in mRNAs leads to loss-of-function associated with human disease

Disrupting upstream translation in mRNAs leads to loss-of-function associated with human disease

Exome-by-phenome-wide rare variant gene burden association with electronic health record phenotypes

Bidirectional Risk Modulator and Modifier Variant of Dilated and Hypertrophic Cardiomyopathy in BAG3

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