Dataset Information

Comparative assessment of different familial aggregation methods in the context of large and unstructured pedigrees.

ABSTRACT:

Motivation

Familial aggregation analysis is an important early step for characterizing the genetic determinants of phenotypes in epidemiological studies. To facilitate this analysis, a collection of methods to detect familial aggregation in large pedigrees has been made available recently. However, efficacy of these methods in real world scenarios remains largely unknown. Here, we assess the performance of five aggregation methods to identify individuals or groups of related individuals affected by a Mendelian trait within a large set of decoys. We investigate method performance under a representative set of combinations of causal variant penetrance, trait prevalence and number of affected generations in the pedigree. These methods are then applied to assess familial aggregation of familial hypercholesterolemia and stroke, in the context of the Cooperative Health Research in South Tyrol (CHRIS) study.

Results

We find that in some situations statistical hypothesis testing with a binomial null distribution achieves performance similar to methods that are based on kinship information, while kinship based methods perform better when information is available on fewer generations. Potential case families from the CHRIS study are reported and the results are discussed taking into account insights from the performance assessment.

Availability and implementation

The familial aggregation analysis package is freely available at the Bioconductor repository, http://www.bioconductor.org/packages/FamAgg.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Weichenberger CX

PROVIDER: S-EPMC6298062 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Comparative assessment of different familial aggregation methods in the context of large and unstructured pedigrees.

Weichenberger Christian X CX Rainer Johannes J Pattaro Cristian C Pramstaller Peter P PP Domingues Francisco S FS

Bioinformatics (Oxford, England) 20190101 1

<h4>Motivation</h4>Familial aggregation analysis is an important early step for characterizing the genetic determinants of phenotypes in epidemiological studies. To facilitate this analysis, a collection of methods to detect familial aggregation in large pedigrees has been made available recently. However, efficacy of these methods in real world scenarios remains largely unknown. Here, we assess the performance of five aggregation methods to identify individuals or groups of related individuals ...[more]

PMID: 30010787

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Project description:This research examined the familial aggregation of migraine, depression, and their co-occurrence.Diagnoses of migraine and depression were determined in a sample of 5,319 Australian twins. Migraine was diagnosed by either self-report, the ID migraine™ Screener, or International Headache Society (IHS) criteria. Depression was defined by fulfilling either major depressive disorder (MDD) or minor depressive disorder (MiDD) based on the Diagnostic and Statistical Manual of Mental Disorders (DSM) criteria. The relative risks (RR) for migraine and depression were estimated in co-twins of twin probands reporting migraine or depression to evaluate their familial aggregation and co-occurrence.An increased RR of both migraine and depression in co-twins of probands with the same trait was observed, with significantly higher estimates within monozygotic (MZ) twin pairs compared to dizygotic (DZ) twin pairs. For cross-trait analysis, the RR for migraine in co-twins of probands reporting depression was 1.36 (95% CI: 1.24-1.48) in MZ pairs and 1.04 (95% CI: 0.95-1.14) in DZ pairs; and the RR for depression in co-twins of probands reporting migraine was 1.26 (95% CI: 1.14-1.38) in MZ pairs and 1.02 (95% CI: 0.94-1.11) in DZ pairs. The RR for strict IHS migraine in co-twins of probands reporting MDD was 2.23 (95% CI: 1.81-2.75) in MZ pairs and 1.55 (95% CI: 1.34-1.79) in DZ pairs; and the RR for MDD in co-twins of probands reporting IHS migraine was 1.35 (95% CI: 1.13-1.62) in MZ pairs and 1.06 (95% CI: 0.93-1.22) in DZ pairs.We observed significant evidence for a genetic contribution to familial aggregation of migraine and depression. Our findings suggest a bi-directional association between migraine and depression, with an increased risk for depression in relatives of probands reporting migraine, and vice versa. However, the observed risk for migraine in relatives of probands reporting depression was considerably higher than the reverse. These results add further support to previous studies suggesting that patients with comorbid migraine and depression are genetically more similar to patients with only depression than patients with only migraine.

Dataset Information

Comparative assessment of different familial aggregation methods in the context of large and unstructured pedigrees.

Motivation

Results

Availability and implementation

Supplementary information

Publications

Comparative assessment of different familial aggregation methods in the context of large and unstructured pedigrees.

Similar Datasets

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