This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the mater...

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...

In this chapter, we will attempt to outline the current state of genetic knowledge for bipolar disorder and briefly summarize the main findings from genetic epidemiology studies. We then review the most recent original literature, based largely on genome-wide association study methods. We conclude with some ideas about future directions.

The decreasing cost of performing genome-wide association studies has made genomics widely accessible. However, there is a paucity of guidance for best practice in conducting such analyses. For the results of a study to be valid and replicable, multiple biases must be addressed in the course of data preparation and analysis. In addition, standardizing methods across small, independent studies w...

Genome-wide association studies (GWAS) have detected many disease associations. However, the reported variants tend to explain small fractions of risk, and there are doubts about issues such as the portability of findings over different ethnic groups or the relative roles of rare versus common variants in the genetic architecture of complex disease. Studying the degree of sharing of disease-ass...

Pathway-based analysis is rapidly emerging as an alternative but powerful approach for searching for disease causal genes from genomic datasets and has been applied to many complex diseases recently, but it is only now beginning to be applied in psychiatry. Here, we discuss critical issues in the pathway-based approach by specifically comparing the first pathway analysis of genome-wide associat...

In genome wide association studies (GWAS), family-based studies tend to have less power to detect genetic associations than population-based studies, such as case-control studies. This can be an issue when testing if genes in a family-based GWAS have a direct effect on the phenotype of interest over and above their possible indirect effect through a secondary phenotype. When multiple SNPs are t...

Most common diseases are caused by multiple genetic and environmental factors. In the last 2 years, genome-wide association studies (GWAS) have identified polymorphisms that are associated with risk to common disease, but the effect of any one risk allele is typically small. By combining information from many risk variants, will it be possible to predict accurately each individual person's gene...

AIMS Genome-wide association studies (GWAS) have identified several risk variants for prostate cancer (pCa) mainly in Europeans, which need to be further verified in other racial groups. We selected six previously identified variants as candidates and to define the association with PCa in Northern Han Chinese. METHODS 749 subjects from Beijing and Tianjin in Northern China were included. Six ...

There are errors in the ninth, tenth and eleventh sentences of the Abstract. The correct sentences are: Individual genotyping of KLF7 rs2284932 revealed that the frequency of the minor C allele was significantly increased (P = 0.00062, Pc = 0.003, OR = 2.98, 95%CI = 1.58–5.65) in group A. The minor T allele of rs4473559 in FRMD4 demonstrated a significant association in the A group (P = 0.00015...