Joint linkage and association analysis using GENEHUNTER-MODSCORE with an application to familial pancreatic cancer
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Abstract
Introduction: Joint linkage and association (JLA) analysis combines two disease gene mapping strategies: linkage information contained in families and association information contained in populations. Such a JLA analysis can in crease mapping power, especially when the evidence for
both linkage and association is low to moderate. Similarly, an
association analysis based on haplotypes instead of single
markers can increase mapping power when the association
pattern is complex. Methods: In this paper, we present an
extension to the GENEHUNTER-MODSCORE software package that enables a JLA analysis based on haplotypes and uses information from arbitrary pedigree types and unre lated individuals. Our new JLA method is an extension of the MOD score approach for linkage analysis, which allows the
estimation of trait-model and linkage disequilibrium (LD)
parameters, i.e., penetrance, disease-allele frequency, and
haplotype frequencies. LD is modeled between alleles at a
single diallelic disease locus and up to three diallelic test
markers. Linkage information is contributed by additional
multi-allelic flanking markers. We investigated the statistical
properties of our JLA implementation using extensive
simulations, and we compared our approach to another
commonly used single-marker JLA test. To demonstrate the
applicability of our new method in practice, we analyzed
pedigree data from the German National Case Collection for Familial Pancreatic Cancer (FaPaCa). Results: Based on the
simulated data, we demonstrated the validity of our JLA MOD score analysis implementation and identified scenarios in which haplotype-based tests outperformed the single marker test. The estimated trait-model and LD parameters were in good accordance with the simulated values. Our
method outperformed another commonly used JLA single-marker test when the LD pattern was complex. The exploratory analysis of the FaPaCa families led to the identification of a promising genetic region on chromosome
22q13.33, which can serve as a starting point for future
mutation analysis and molecular research in pancreatic
cancer. Conclusion: Our newly proposed JLA-MOD score ethod proves to be a valuable gene mapping and characterization tool, especially when either linkage or association information alone provide insufficient power to
identify the disease-causing genetic variants.Keywords
Association analysis · Familial pancreatic cancer · Haplotype
frequency estimation · Linkage analysis · MOD scores