Utility of Population-Level DNA Sequence Data in the Diagnosis of Hereditary Endocrine Disease

Paul J. Newey (Lead / Corresponding author), Jonathan N. Berg, Kaixin Zhou, Colin N. A. Palmer, Rajesh V. Thakker

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Abstract

Context: Genetic testing is increasingly employed for clinical diagnosis, although variant interpretation presents a major challenge due to high background rates of rare coding-region variation, which may contribute to inaccurate estimates of variant pathogenicity and disease penetrance.

Objective: To use the Exome Aggregation Consortium (ExAC) dataset to determine the background population frequencies of rare germline coding-region variants in genes associated with hereditary endocrine disease, and to evaluate the clinical utility of this data.

Design, Setting, Participants: Cumulative frequencies of rare non-synonymous single nucleotide variants were established for 38 endocrine disease genes in 60,706 unrelated control individuals. The utility of gene-level and variant-level metrics of tolerability was assessed and the pathogenicity and penetrance of germline variants previously associated with endocrine disease evaluated.

Results: The frequency of rare coding region variants differed markedly between genes and was correlated with the degree of evolutionary conservation. Genes associated with dominant monogenic endocrine disorders typically harbored fewer rare missense and/or loss-of-function variants than expected. In silico variant prediction tools demonstrated low clinical specificity. The frequency of several endocrine disease-associated variants in the ExAC cohort far exceeded estimates of disease prevalence, indicating either misclassification or overestimation of disease penetrance. Finally, we illustrate how rare variant frequencies may be used to anticipate expected rates of background rare variation when performing disease-targeted genetic testing.

Conclusions: Quantifying the frequency and spectrum of rare variation using population-level sequence data facilitates improved estimates of variant pathogenicity and penetrance and should be incorporated into the clinical decision-making algorithm when undertaking genetic testing.
Original languageEnglish
Pages (from-to)1507-1526
Number of pages20
JournalJournal of the Endocrine Society
Volume1
Issue number12
Early online date15 Nov 2017
DOIs
Publication statusPublished - 1 Dec 2017

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Endocrine System Diseases
Inborn Genetic Diseases
Penetrance
Genetic Testing
Exome
Virulence
Population
Genes
Computer Simulation
Nucleotides

Keywords

  • Penetrance
  • single nucleotide variant
  • ExAC
  • germline
  • genetic testing
  • mutation

Cite this

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title = "Utility of Population-Level DNA Sequence Data in the Diagnosis of Hereditary Endocrine Disease",
abstract = "Context: Genetic testing is increasingly employed for clinical diagnosis, although variant interpretation presents a major challenge due to high background rates of rare coding-region variation, which may contribute to inaccurate estimates of variant pathogenicity and disease penetrance.Objective: To use the Exome Aggregation Consortium (ExAC) dataset to determine the background population frequencies of rare germline coding-region variants in genes associated with hereditary endocrine disease, and to evaluate the clinical utility of this data.Design, Setting, Participants: Cumulative frequencies of rare non-synonymous single nucleotide variants were established for 38 endocrine disease genes in 60,706 unrelated control individuals. The utility of gene-level and variant-level metrics of tolerability was assessed and the pathogenicity and penetrance of germline variants previously associated with endocrine disease evaluated.Results: The frequency of rare coding region variants differed markedly between genes and was correlated with the degree of evolutionary conservation. Genes associated with dominant monogenic endocrine disorders typically harbored fewer rare missense and/or loss-of-function variants than expected. In silico variant prediction tools demonstrated low clinical specificity. The frequency of several endocrine disease-associated variants in the ExAC cohort far exceeded estimates of disease prevalence, indicating either misclassification or overestimation of disease penetrance. Finally, we illustrate how rare variant frequencies may be used to anticipate expected rates of background rare variation when performing disease-targeted genetic testing.Conclusions: Quantifying the frequency and spectrum of rare variation using population-level sequence data facilitates improved estimates of variant pathogenicity and penetrance and should be incorporated into the clinical decision-making algorithm when undertaking genetic testing.",
keywords = "Penetrance, single nucleotide variant, ExAC, germline, genetic testing, mutation",
author = "Newey, {Paul J.} and Berg, {Jonathan N.} and Kaixin Zhou and Palmer, {Colin N. A.} and Thakker, {Rajesh V.}",
note = "PJN holds a Scottish Senior Clinical Fellowship funded by the Chief Scientist Office (CSO)/NHS Research Scotland (NRS) and the University of Dundee [SCAF/15/01], UK. RVT holds a Wellcome Trust Investigator Award and a National Institute for Health Research (NIHR) Senior Investigator Award, and received funding from the Medical Research Council [G1000467] and NIHR Oxford Biomedical Research Centre Programme.",
year = "2017",
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doi = "10.1210/js.2017-00330",
language = "English",
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T1 - Utility of Population-Level DNA Sequence Data in the Diagnosis of Hereditary Endocrine Disease

AU - Newey, Paul J.

AU - Berg, Jonathan N.

AU - Zhou, Kaixin

AU - Palmer, Colin N. A.

AU - Thakker, Rajesh V.

N1 - PJN holds a Scottish Senior Clinical Fellowship funded by the Chief Scientist Office (CSO)/NHS Research Scotland (NRS) and the University of Dundee [SCAF/15/01], UK. RVT holds a Wellcome Trust Investigator Award and a National Institute for Health Research (NIHR) Senior Investigator Award, and received funding from the Medical Research Council [G1000467] and NIHR Oxford Biomedical Research Centre Programme.

PY - 2017/12/1

Y1 - 2017/12/1

N2 - Context: Genetic testing is increasingly employed for clinical diagnosis, although variant interpretation presents a major challenge due to high background rates of rare coding-region variation, which may contribute to inaccurate estimates of variant pathogenicity and disease penetrance.Objective: To use the Exome Aggregation Consortium (ExAC) dataset to determine the background population frequencies of rare germline coding-region variants in genes associated with hereditary endocrine disease, and to evaluate the clinical utility of this data.Design, Setting, Participants: Cumulative frequencies of rare non-synonymous single nucleotide variants were established for 38 endocrine disease genes in 60,706 unrelated control individuals. The utility of gene-level and variant-level metrics of tolerability was assessed and the pathogenicity and penetrance of germline variants previously associated with endocrine disease evaluated.Results: The frequency of rare coding region variants differed markedly between genes and was correlated with the degree of evolutionary conservation. Genes associated with dominant monogenic endocrine disorders typically harbored fewer rare missense and/or loss-of-function variants than expected. In silico variant prediction tools demonstrated low clinical specificity. The frequency of several endocrine disease-associated variants in the ExAC cohort far exceeded estimates of disease prevalence, indicating either misclassification or overestimation of disease penetrance. Finally, we illustrate how rare variant frequencies may be used to anticipate expected rates of background rare variation when performing disease-targeted genetic testing.Conclusions: Quantifying the frequency and spectrum of rare variation using population-level sequence data facilitates improved estimates of variant pathogenicity and penetrance and should be incorporated into the clinical decision-making algorithm when undertaking genetic testing.

AB - Context: Genetic testing is increasingly employed for clinical diagnosis, although variant interpretation presents a major challenge due to high background rates of rare coding-region variation, which may contribute to inaccurate estimates of variant pathogenicity and disease penetrance.Objective: To use the Exome Aggregation Consortium (ExAC) dataset to determine the background population frequencies of rare germline coding-region variants in genes associated with hereditary endocrine disease, and to evaluate the clinical utility of this data.Design, Setting, Participants: Cumulative frequencies of rare non-synonymous single nucleotide variants were established for 38 endocrine disease genes in 60,706 unrelated control individuals. The utility of gene-level and variant-level metrics of tolerability was assessed and the pathogenicity and penetrance of germline variants previously associated with endocrine disease evaluated.Results: The frequency of rare coding region variants differed markedly between genes and was correlated with the degree of evolutionary conservation. Genes associated with dominant monogenic endocrine disorders typically harbored fewer rare missense and/or loss-of-function variants than expected. In silico variant prediction tools demonstrated low clinical specificity. The frequency of several endocrine disease-associated variants in the ExAC cohort far exceeded estimates of disease prevalence, indicating either misclassification or overestimation of disease penetrance. Finally, we illustrate how rare variant frequencies may be used to anticipate expected rates of background rare variation when performing disease-targeted genetic testing.Conclusions: Quantifying the frequency and spectrum of rare variation using population-level sequence data facilitates improved estimates of variant pathogenicity and penetrance and should be incorporated into the clinical decision-making algorithm when undertaking genetic testing.

KW - Penetrance

KW - single nucleotide variant

KW - ExAC

KW - germline

KW - genetic testing

KW - mutation

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DO - 10.1210/js.2017-00330

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JO - Journal of the Endocrine Society

JF - Journal of the Endocrine Society

SN - 2472-1972

IS - 12

ER -