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Exploring the effect of ascertainment bias on genetic studies that use clinical pedigrees.

ABSTRACT: Recent studies have reported novel cancer risk associations with incidentally tested genes on cancer risk panels using clinically ascertained cohorts. Clinically ascertained pedigrees may have unknown ascertainment biases for both patients and relatives. We used a method to assess gene and variant risk and ascertainment bias based on comparing the number of observed disease instances in a pedigree given the sex and ages of individuals with those expected given established population incidence. We assessed the performance characteristics of the method by simulating families with varying genetic risk and proportion of individuals genotyped. We implemented this method using SEER cancer incidence data to assess clinical ascertainment bias in a set of 42 pedigrees with clinical testing ordered for either breast/ovarian cancer or colorectal/endometrial cancer at the University of Washington and negative sequencing results. In addition to expected biases consistent with the stated testing purpose, there were trends suggesting increased colorectal and endometrial cancer in pedigrees tested for breast cancer risk and trends suggesting increased breast cancer in families tested for colon cancer risk. There was no observed selection bias for prostate cancer in this set of families. This analysis illustrates that clinically ascertained data sets may have subtle biases. In the future, researchers seeking to explore risk associations with clinical data sets could assess potential ascertainment bias by comparing incidence of disease in families that test negative under given ordering criteria to expected population disease frequencies. Failure to assess for ascertainment bias increases the risk of false genetic associations.

SUBMITTER: Ranola JMO

PROVIDER: S-EPMC6871527 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Exploring the effect of ascertainment bias on genetic studies that use clinical pedigrees.

Ranola John Michael O JMO Tsai Ginger J GJ Shirts Brian H BH

European journal of human genetics : EJHG 20190711 12

Recent studies have reported novel cancer risk associations with incidentally tested genes on cancer risk panels using clinically ascertained cohorts. Clinically ascertained pedigrees may have unknown ascertainment biases for both patients and relatives. We used a method to assess gene and variant risk and ascertainment bias based on comparing the number of observed disease instances in a pedigree given the sex and ages of individuals with those expected given established population incidence. W ...[more]

PMID: 31296927

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Project description:BACKGROUND:Single nucleotide polymorphism (SNP) panels have been widely used to study genomic variations within and between populations. Methods of SNP discovery have been a matter of debate for their potential of introducing ascertainment bias, and genetic diversity results obtained from the SNP genotype data can be misleading. We used a total of 42 chicken populations where both individual genotyped array data and pool whole genome resequencing (WGS) data were available. We compared allele frequency distributions and genetic diversity measures (expected heterozygosity (H e ), fixation index (F ST ) values, genetic distances and principal components analysis (PCA)) between the two data types. With the array data, we applied different filtering options (SNPs polymorphic in samples of two Gallus gallus wild populations, linkage disequilibrium (LD) based pruning and minor allele frequency (MAF) filtering, and combinations thereof) to assess their potential to mitigate the ascertainment bias. RESULTS:Rare SNPs were underrepresented in the array data. Array data consistently overestimated H e compared to WGS data, however, with a similar ranking of the breeds, as demonstrated by Spearman's rank correlations ranging between 0.956 and 0.985. LD based pruning resulted in a reduced overestimation of H e compared to the other filters and slightly improved the relationship with the WGS results. The raw array data and those with polymorphic SNPs in the wild samples underestimated pairwise F ST values between breeds which had low F ST (<0.15) in the WGS, and overestimated this parameter for high WGS F ST (>0.15). LD based pruned data underestimated F ST in a consistent manner. The genetic distance matrix from LD pruned data was more closely related to that of WGS than the other array versions. PCA was rather robust in all array versions, since the population structure on the PCA plot was generally well captured in comparison to the WGS data. CONCLUSIONS:Among the tested filtering strategies, LD based pruning was found to account for the effects of ascertainment bias in the relatively best way, producing results which are most comparable to those obtained from WGS data and therefore is recommended for practical use.

Dataset Information

Exploring the effect of ascertainment bias on genetic studies that use clinical pedigrees.

Publications

Exploring the effect of ascertainment bias on genetic studies that use clinical pedigrees.

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