Joint modeling of genetic linkage and association

Yang, Haiyan (2014) Joint modeling of genetic linkage and association. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Abstract

Understanding the complexities involved in identifying disease causing genes is still a monumental task. As we know, genetic variants and environmental factors can influence the risk of disease outcomes. Epidemiological studies have identified that age is one of a number of environmental risk factors for Familial Pulmonary Fibrosis (FPF), but the genetic risk factors involved identification of disease causing genes still are a problem largely unsolved. An inherited disease-causing locus occurs in the same genomic position as an ancestor who has the disease trait, and the disease genotype may be associated with a marker genotype. A joint modeling of genetic linkage and association within families having a remote common ancestor or at population level is presented in this thesis. This joint modeling uses a likelihood approach that allows the inclusion of other covariates into the model for quantitative traits and binary traits with multivariate random effects. Power studies via simulation compare the new proposed procedure with standard linkage or association procedures. The joint test is more powerful than linkage or association test alone where both sources of variation of linkage or association are present. Furthermore, the proposed method also allows testing against specific alternatives - for example, against the significance of linkage where there is no association, significance of association where there is no linkage, and significance of both linkage and association. By utilizing data from five FPF families in Newfoundland, four candidate loci were identified for the linkage or/and association with age-at-onset gene and FPF (rs4605929 in chromosome 6, rs11078200 in chromosome 7, rs1941686 in chromosome 18 and rs114682 in chromosome 22).

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