Genome-wide association (GWA) studies are a powerful tool for understanding the genetic underpinnings of human disease. In this article, we briefly review the role and findings of GWA studies in type 1 diabetes, stature, pubertal timing, obesity, and vitamin D deficiency. We then discuss the present and future implications of these findings with regards to disease prediction, uncovering basic b...

Over the last few years, many new genetic associations have been identified by genome-wide association studies (GWAS). There are potentially many uses of these identified variants: a better understanding of disease etiology, personalized medicine, new leads for studying underlying biology, and risk prediction. Recently, there has been some skepticism regarding the prospects of risk prediction u...

Genome-wide association studies (GWAS) are widely used to discover genetic variants associated with diseases. To control false positives, all findings from GWAS need to be verified with additional evidences, even for associations discovered from a high power study. Replication study is a common verification method by using independent samples. An association is regarded as true positive with a ...

This thesis focus on various statistical methods for analyzing Genome Wide Association data. The thesis include four papers, three of them considers the analysis of complex traits, and the last one a method for analyzing mendelian traits. Although GWAS have identified many associated regions in the genome for many complex diseases, there is still much of the genetic heritability that remains un...

In the last 2 years, the effort to identify genes affecting common diseases and complex traits has been accelerated through the use of genome-wide association studies (GWAS). The availability of existing large collections of linkage data paved the way for the use of family-based GWAS. Although most published GWAS used population-based designs, family-based designs have played an important role,...

The genetics of Alzheimer disease (AD) to date support an age-dependent dichotomous model whereby earlier age of disease onset (< 60 years) is explained by 3 fully penetrant genes (APP [NCBI Entrez gene 351], PSEN1 [NCBI Entrez gene 5663], and PSEN2 [NCBI Entrez gene 5664]), whereas later age of disease onset (> or = 65 years) representing most cases of AD has yet to be explained by a purely ge...