Does DNA methylation influence the effects of psychiatric drugs?

Written by Alice Weatherston

The introduction, in the middle of the last century, of specific drug treatments for schizophrenia, bipolar illness and depression brought relief to many of those suffering from these disorders. Subsequently developed drugs have offered some improvements in tolerability, through changes in side effect profiles, but not more than marginal changes in efficacy. Thus severe mental illness, despite the undoubted value of current pharmacotherapy, still represents a huge economic and social burden, reflecting the limited efficacy of drug treatments. Treatment of depression achieves response rates of little more than 50%, while even lower proportions of people with schizophrenia achieve adequate symptom relief with the antipsychotic drugs.

Thus there are profound differences between individuals with severe mental illness in how they respond to drug treatments. In addition to the wide variability in symptom response mentioned above, the experience of adverse drug effects can also vary greatly between individuals. These differences in efficacy and side effects are thought to reflect, at least in part, genetic differences between patients; thus pharmacogenetics in psychiatry has much to offer in the eventual identification of risk factors for these limitations of drug treatment.

Over the past two decades, research into the pharmacogenetics of psychiatric drugs has identified several genetic variations that reliably associate with some of the effects of drug treatment, as well as many more that provide intriguing but inadequately replicated indications of gene associations. There appears to have been more success in identifying genetic factors relating to side effects of drug treatment than in finding associations with symptom response. This may be because the phenotypes related to adverse effects, such as weight gain, are often easily defined and objectively measurable, while disease severity in psychiatry is multifactorial with complex and subjective measures.

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  1. Epigenomics