Since 2007, GWAS have increasingly been applied to pharmacogenetics to identify loci that affect selleck chemical either drug response or susceptibility to adverse drug reactions. These studies have shown the value of this approach in many fields [18, 78-83]. However, there are limitations in conducting GWAS in pharmacogenetics. First, the variation in drug response is likely to be multifactorial, with many genes working in conjunction with the environment. Second, current GWAS are targeted at elucidating the independent effects of single genes, and may miss interactive or synergistic effects. Furthermore, the challenges in performing adequate replication studies have to be considered for

GWAS in pharmacogenetics, particularly Opaganib concentration when evaluating small cohorts, such as nonresponders to UDCA in PBC. UDCA, which is currently the only available drug in PBC, is thought to work on the downstream events of the pathogenic mechanism of the disease, through reducing the toxicity of bile and reducing bile duct cell apoptosis [84]. There are ongoing studies, focused on exploring, with a GWA approach, the mechanism(s) beyond the lack of biochemical response to UDCA treatment. A major aim of this ongoing project is to identify potential sites for therapeutic intervention in nonresponsive patients.

New therapeutic targets that may be highlighted by GWAS, as applied to pharmacogenetics, can be localized either in the upstream or downstream processes of PBC pathogenesis; from the mechanisms that lead to loss of tolerance to the fibrotic phase secondary to cholestasis. Furthermore, improved knowledge of the genetic basis of the lack of response to UDCA will allow to identify

nonresponders at an early stage and to select them for next-generation drug trials. Attempting to predict the onset and progression of disease is one of the cornerstones of epidemiology. GWAS show significant potential to identify molecular factors that enable patient stratification and might prove useful in personalized medicine. Accurate risk prediction can enable targeted preventative treatments or more intensive follow-up, particularly for patients at high risk of progression. The success of recent GWAS has rapidly changed the outlook check for genetic risk prediction. These studies have unlocked thousands of clearly validated genetic associations to complex diseases, but their generally weak effects have left their predictive value and clinical utility subject to hot debate. GWAS data might find ready application in risk prediction in PBC in those patients identified at an early stage of the disease. Risk stratification at an early stage may be important from the perspective of developing treatments that either prevent disease entirely or that improve the outcome when instituted before biliary fibrosis and cirrhosis develop.