Imperial College London

Dr Nicky Whiffin

Faculty of MedicineNational Heart & Lung Institute

Research Fellow
 
 
 
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Contact

 

n.whiffin

 
 
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Location

 

Hammersmith HospitalHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Walsh:2019:10.1186/s13073-019-0616-z,
author = {Walsh, R and Mazzarotto, F and Whiffin, N and Buchan, R and Midwinter, W and Wilk, A and Li, N and Felkin, L and Ingold, N and Govind, R and Ahmad, M and Mazaika, E and Allouba, M and Zhang, X and de, Marvao A and Day, SM and Ashley, E and Colan, SD and Michels, M and Pereira, AC and Jacoby, D and Ho, CY and Thomson, KL and Watkins, H and Barton, PJR and Olivotto, I and Cook, SA and Ware, JS},
doi = {10.1186/s13073-019-0616-z},
journal = {Genome Medicine},
title = {Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: The case of hypertrophic cardiomyopathy},
url = {http://dx.doi.org/10.1186/s13073-019-0616-z},
volume = {11},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - BackgroundInternational guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false-positive rate over test sensitivity and diagnostic yield. Genetic testing is also more likely informative in individuals with well-characterised variants from extensively studied European-ancestry populations. Inherited cardiomyopathies are relatively common Mendelian diseases that allow empirical calibration and assessment of this framework.MethodsWe compared rare variants in large hypertrophic cardiomyopathy (HCM) cohorts (up to 6179 cases) to reference populations to identify variant classes with high prior likelihoods of pathogenicity, as defined by etiological fraction (EF). We analysed the distribution of variants using a bespoke unsupervised clustering algorithm to identify gene regions in which variants are significantly clustered in cases.ResultsAnalysis of variant distribution identified regions in which variants are significantly enriched in cases and variant location was a better discriminator of pathogenicity than generic computational functional prediction algorithms. Non-truncating variant classes with an EF ≥ 0.95 were identified in five established HCM genes. Applying this approach leads to an estimated 14–20% increase in cases with actionable HCM variants, i.e. variants classified as pathogenic/likely pathogenic that might be used for predictive testing in probands’ relatives.ConclusionsWhen found in a patient confirmed to have disease, novel variants in some genes and regions are empirically shown to have a sufficiently high probability of pathogenicity to support a “likely pathogenic” classification, even without additional segregation or functional data. This could increase the yield of high confidence actionable variants, consistent with the framework and recommendations of current guidelines. The techniques outlined offer a consisten
AU - Walsh,R
AU - Mazzarotto,F
AU - Whiffin,N
AU - Buchan,R
AU - Midwinter,W
AU - Wilk,A
AU - Li,N
AU - Felkin,L
AU - Ingold,N
AU - Govind,R
AU - Ahmad,M
AU - Mazaika,E
AU - Allouba,M
AU - Zhang,X
AU - de,Marvao A
AU - Day,SM
AU - Ashley,E
AU - Colan,SD
AU - Michels,M
AU - Pereira,AC
AU - Jacoby,D
AU - Ho,CY
AU - Thomson,KL
AU - Watkins,H
AU - Barton,PJR
AU - Olivotto,I
AU - Cook,SA
AU - Ware,JS
DO - 10.1186/s13073-019-0616-z
PY - 2019///
SN - 1756-994X
TI - Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: The case of hypertrophic cardiomyopathy
T2 - Genome Medicine
UR - http://dx.doi.org/10.1186/s13073-019-0616-z
UR - http://hdl.handle.net/10044/1/66905
VL - 11
ER -