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How many cases of disease in a pedigree imply familial disease?

Overview of attention for article published in Annals of Human Genetics, October 2017
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Title
How many cases of disease in a pedigree imply familial disease?
Published in
Annals of Human Genetics, October 2017
DOI 10.1111/ahg.12222
Pubmed ID
Authors

Frank Dudbridge, Suzanne J. Brown, Lynley Ward, Scott G. Wilson, John P. Walsh

Abstract

The ability to perform whole-exome and, increasingly, whole-genome sequencing on large numbers of individuals has led to increased efforts to identify rare genetic variants that affect the risk of both common and rare diseases. In such applications, it is important to identify families that are segregating the rare variants of interest. For rare diseases or rare familial forms of common diseases, pedigrees with multiple affected members are clearly harbouring risk variants. For more common diseases, however, it may be unclear whether a family with a few affected members is segregating a familial disease, is the result of multiple sporadic cases, or is a mixture of familial cases and phenocopies. We provide calculations for the probability that a family is harbouring familial disease, presented in general terms that admit working guidelines for selecting families for current sequencing studies. Using examples motivated by our own studies of thyroid cancer and published studies of colorectal cancer, we show that for common diseases, families with exactly two affected first-degree relatives have only a moderate probability of segregating familial disease, but this probability is higher for families with three or more affected relatives, and those families should therefore be prioritised in sequencing studies.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 19%
Researcher 3 19%
Student > Bachelor 2 13%
Student > Postgraduate 2 13%
Other 2 13%
Other 1 6%
Unknown 3 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 31%
Medicine and Dentistry 4 25%
Biochemistry, Genetics and Molecular Biology 3 19%
Nursing and Health Professions 1 6%
Unknown 3 19%