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Medientyp:
E-Artikel
Titel:
Calculating variant penetrance from family history of disease and average family size in population-scale data
Beteiligte:
Spargo, Thomas P.;
Opie-Martin, Sarah;
Bowles, Harry;
Lewis, Cathryn M.;
Iacoangeli, Alfredo;
Al-Chalabi, Ammar
Erschienen:
Springer Science and Business Media LLC, 2022
Erschienen in:Genome Medicine
Sprache:
Englisch
DOI:
10.1186/s13073-022-01142-7
ISSN:
1756-994X
Entstehung:
Anmerkungen:
Beschreibung:
<jats:title>Abstract
</jats:title><jats:sec>
<jats:title>Background</jats:title>
<jats:p>Genetic penetrance is the probability of a phenotype when harbouring a particular pathogenic variant. Accurate penetrance estimates are important across biomedical fields including genetic counselling, disease research, and gene therapy. However, existing approaches for penetrance estimation require, for instance, large family pedigrees or availability of large databases of people affected and not affected by a disease.</jats:p>
</jats:sec><jats:sec>
<jats:title>Methods</jats:title>
<jats:p>We present a method for penetrance estimation in autosomal dominant phenotypes. It examines the distribution of a variant among people affected (cases) and unaffected (controls) by a phenotype within population-scale data and can be operated using cases only by considering family disease history. It is validated through simulation studies and candidate variant-disease case studies.</jats:p>
</jats:sec><jats:sec>
<jats:title>Results</jats:title>
<jats:p>Our method yields penetrance estimates which align with those obtained via existing approaches in the Parkinson’s disease <jats:italic>LRRK2</jats:italic> gene and pulmonary arterial hypertension <jats:italic>BMPR2</jats:italic> gene case studies. In the amyotrophic lateral sclerosis case studies, examining penetrance for variants in the <jats:italic>SOD1</jats:italic> and <jats:italic>C9orf72</jats:italic> genes, we make novel penetrance estimates which correspond closely to understanding of the disease.</jats:p>
</jats:sec><jats:sec>
<jats:title>Conclusions</jats:title>
<jats:p>The present approach broadens the spectrum of traits for which reliable penetrance estimates can be obtained. It has substantial utility for facilitating the characterisation of disease risks associated with rare variants with an autosomal dominant inheritance pattern. The yielded estimates avoid any kinship-specific effects and can circumvent ascertainment biases common when sampling rare variants among control populations.</jats:p>
</jats:sec>