Kullback-Leibler divergence for detection of rare haplotype common disease association

Detecting rare haplotypes associated with complex diseases using both population and family data: Combined logistic Bayesian Lasso

Haplotype-based association methods have been developed to understand the genetic architecture of complex diseases. Compared to single-variant-based methods, haplotype methods are thought to be more biologically relevant, since there are typically multiple non-independent genetic variants involved in complex diseases, and the use of haplotypes implicitly accounts for non-independence caused by linkage disequilibrium. In recent years, with the focus moving from common to rare variants, haplotype-based methods have also evolved accordingly to uncover the roles of rare haplotypes. One particular approach is regularization-based, with the use of Bayesian least absolute shrinkage and selection operator (Lasso) as an example. This type of methods has been developed for either case-control population data (the logistic Bayesian Lasso (LBL)) or family data (family-triad-based logistic Bayesian Lasso (famLBL)). In some situations, both family data and case-control data are available; therefore, it would be a waste of resources if only one of them could be analyzed. To make full usage of available data to increase power, we propose a unified approach that can combine both case-control and family data (combined logistic Bayesian Lasso (cLBL)). Through simulations, we characterized the performance of cLBL and showed the advantage of cLBL over existing methods. We further applied cLBL to the Framingham Heart Study data to demonstrate its utility in real data applications.

Whole-genome single nucleotide variant distribution on genomic regions and its relationship to major depression

Recent advances in DNA technologies have provided unprecedented opportunities for biological and medical research. In contrast to current popular genotyping platforms which identify specific variations, whole-genome sequencing (WGS) allows for the detection of all private mutations within an individual. Major depressive disorder (MDD) is a chronic condition with enormous medical, social and economic impacts. Genetic analysis, by identifying risk variants and thereby increasing our understanding of how MDD arises, could lead to improved prevention and the development of new and more effective treatments. Here we investigated the distributions of whole-genome single nucleotide variants (SNVs) on 12 different genomic regions for 25 human subjects using the symmetrised Kullback-Leibler divergence to measure the similarity between their SNV distributions. We performed cluster analysis for MDD patients and ethnically matched healthy controls. The results showed that Mexican-American controls grouped closer; in contrast depressed Mexican-American participants grouped away from their ethnically matched controls. This implies that whole-genome SNV distribution on the genomic regions may be related to major depression.

Glycosylation site occupancy in health, congenital disorder of glycosylation and fatty liver disease

Glycosylation is an integral part in health and disease, as emphasized by the growing number of identified glycosylation defects. In humans, proteins are modified with a diverse range of glycoforms synthesized in complex biosynthetic pathways. Glycosylation disorders have been described in congenital disorders of glycosylation (CDG) as well as in acquired disease conditions such and non-alcoholic fatty liver disease (NAFLD). A hallmark in a subset of CDG cases is the reduced glycosylation site occupancy of asparagine-linked glycans. Using an optimized method protocol, we determined the glycosylation site occupancy from four proteins of hepatic and lymphatic origin from CDG and NAFLD patients. We found variable degrees of site occupancy, depending on the tissue of origin and the disease condition. In CDG glycosylation sites of IgG2 and IgA1 were occupied to normal levels. In NAFLD haptoglobin and transferrin glycosylation sites were hyper-glycosylated, a property qualifying for its use as a potential biomarker. Furthermore, we observed, that glycosylation sites of liver-originating transferrin and haptoglobin are differentially occupied under physiological conditions, a further instance not noticed in serum proteins to date. Our findings suggest the use of serum protein hyperglycosylation as a biomarker for early stages of NAFLD.