Antidepressants in Older People

Project Details

Description

Major depressive disorder (MDD) in older people is a relatively common, yet hard to treat problem. In this study, we aimed to establish if a single nucleotide polymorphism in the 5-HT1A receptor gene (rs6295) determines antidepressant response in patients aged > 80 years (the oldest old) with MDD.
Nineteen patients aged at least 80 years with a new diagnosis of MDD were monitored for response to citalopram 20 mg daily over 4 weeks and genotyped for the rs6295 allele. Both a frequentist and Bayesian analysis was performed on the data. Bayesian analysis answered the clinically relevant question: ‘What is the probability that an older patient would enter remission after commencing selective serotonin reuptake inhibitor (SSRI) treatment, conditional on their rs6295 genotype?’
Individuals with a CC (cytosine–cytosine) genotype showed a significant improvement in their Geriatric Depression Score (p = 0.020) and cognition (p = 0.035) compared with other genotypes. From a Bayesian perspective, we updated reports of antidepressant efficacy in older people with our data and calculated that the 4-week relative risk of entering remission, given a CC genotype, is 1.9 [95% highest-density interval (HDI) 0.7–3.5], compared with 0.52 (95% HDI 0.1–1.0) for the CG (cytosine–guanine) genotype. 
The sample size of n = 19 is too small to draw any firm conclusions, however, the data suggest a trend indicative of a relationship between the rs6295 genotype and response to citalopram in older patients, which requires further investigation.

Layman's description

This project explored a population of patients over the age of 80 years and whether there was a link between changes in the type of 5-HT1A receptor people have and their response to antidepressants.

Key findings

The data suggested a possible link between the rs6295 genotype and response to citalopram in older patients, which requires further investigation.
StatusFinished
Effective start/end date1/09/1031/03/16

Funding

  • NIHR

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.