Optimizing the chances of success in the search for epigenetic biomarkers: Embracing genetic variation

Abstract

The emphasis on clinical translation in biomedical research continues to grow. This focus has been particularly notable in those investigators using epigenetic approaches to decipher the biology of complex behavioral disorders. As a result of these efforts, reproducible findings for several disorders, such as smoking, have been generated, giving rise to hopes that biomarkers for other behavioral illnesses would be forthcoming. Unfortunately, that biomedical cornucopia has not yet materialized. In this editorial, we review progress to date and discuss barriers to generating epigenetic biomarkers for complex behavioral disorders. We highlight the need to incorporate information on genetic variation and develop more powerful bioinformatics tools in order to optimize the likelihood of success. We emphasize that searches should focus on clearly defined, readily distinguishable behavioral constructs and suggest that some well-intentioned methods, such as correction for cellular heterogeneity, may actually impede the identification of clinically relevant biomarkers in peripheral blood. Finally, we describe how the understanding created by the development of these biomarkers may lead to more valid animal models of neuropsychiatric illness. We conclude that the prospects for epigenetic biomarkers for complex disorders are bright, but emphasize that the journey to the clinical implementation of these findings will be a slow, iterative process.

Genome‐wide and digital polymerase chain reaction epigenetic assessments of alcohol consumption

“…Case and control approaches have long been the favorite of geneticists (Risch, ). However, for stigmatized behaviors such as heavy alcohol consumption, their skillful employment may particularly important because misclassification of subjects can have profound effects on the power of both genetic and epigenetic case and control analyses (Philibert & Glatt, ; Silverberg et al, ). The extent to which this takes place with respect to studies of alcohol consumption is not clearly established.…”

“…Correction for genome‐wide comparison was performed using the false discovery rate (FDR) method (Bortolotti, De Paoli, & Tagliaro, 1995). As per the previous recommendations for biomarker searches, analyses were not corrected for cellular heterogeneity (Bauer et al, ; Philibert & Glatt, ). Power for the meta‐analysis was calculated using the method of Valentine, Pigott, and Rothstein ().…”