Genetics of Response to ECT, TMS, Ketamine and Esketamine.
American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics – June 17, 2025
Source: PubMed
Summary
Imagine tailoring mental health treatment to your unique genetic makeup! While intensive therapies like ECT, TMS, ketamine, and esketamine effectively treat severe mood disorders, understanding how genetics influences individual response is crucial. Early genetic explorations are paving the way to identify specific genetic markers. This will empower clinicians to recommend the most effective intervention for each patient's unique genetic profile, ensuring optimal outcomes and truly personalized care.
Abstract
Treatment-resistant mood disorders are often managed with intensive interventions that include electroconvulsive therapy (ECT), transcranial magnetic stimulation (TMS), ketamine, and esketamine, but the role of genetics in clinical response to those interventions is yet to be clearly determined. Here, we review the current literature on the genetics of response to these treatment modalities. To date, the limited number of studies done to investigate genetic predictors of treatment response have primarily focused on single variants in candidate genes, and none of these have been consistently reproducible. The majority of candidate gene studies examine the effect of variants in the COMT and BDNF genes on treatment response. There are a limited number of genome-wide association studies (GWAS) looking at treatment response, though they are almost all underpowered, with only one study including a sample size > 1000. As a result, there have been few single nucleotide polymorphisms (SNPs) found to be associated with treatment response at a statistically significant level, all in genes other than COMT and BDNF. The challenge is now to generate data from a large group of patients undergoing these therapies in order to more robustly assess the genetic factors affecting treatment response. This will not only help establish genetic predictors of response, but also potentially develop differential predictors of response to available treatments, which could provide clinicians with critical information to aid in deciding which treatment modality to recommend for treatment-resistant depression. We are currently pursuing such a strategy in our 50-site worldwide Gen-ECT-ic consortium.