Genetic Markers for Later Remission in Response to Early Improvement of Antidepressants

Abstract

Planning subsequent treatment strategies based on early responses rather than waiting for delayed antidepressant action can be helpful. We identified genetic markers for later non-remission in patients exhibiting poor early improvement using whole-exome sequencing data of depressive patients treated in a naturalistic manner. Among 1000 patients, early improvement at 2 weeks (reduction in Hamilton Depression Rating Scale [HAM-D] score ≥ 20%) and remission at 12 weeks (HAM-D score ≤ 7) were evaluated. Gene- and variant-level analyses were conducted to compare patients who did not exhibit early improvement and did not eventually achieve remission (n = 126) with those who exhibited early improvement and achieved remission (n = 385). Genes predicting final non-remission in patients who exhibited poor early improvement (COMT, PRNP, BRPF3, SLC25A40, and CGREF1 in males; PPFIBPI, LZTS3, MEPCE, MAP1A, and PFAS in females; ST3GAL5 in the total population) were determined. Among the significant genes, variants in the PRNP (rs1800014), COMT (rs6267), BRPF3 (rs200565609), and SLC25A40 genes (rs3213633) were identified. However, interpretations should be made cautiously, as complex pharmacotherapy involves various genes and pathways. Early detection of poor early improvement and final non-remission based on genetic risk would be helpful for decision-making in a clinical setting.

Paired comparisons of mutational profiles before and after brachytherapy in asian uveal melanoma patients

“…If the population allele frequency of the variants is more than 1% in any subpopulation of 1000 genomes project 20 , ExAC 21 , KOVA 22 , gNomad and Korean Genome Project 23 data, the variants were excluded as germline mutations. The second exclusion criteria is that the variant were present in the Korean 1,000 depression exome data 24 , which is a panel of normal. It removes not only germline mutation but also potential platform specific artifacts.…”

Mutational Analysis of Triple-Negative Breast Cancer Using Targeted Kinome Sequencing

“…If the population allele frequency of the variants was more than 1% in any subpopulation among the 1000 Genomes Project, Exome Aggregation Consortium, Korean Variant Archive, Genome Aggregation Database, and Korean Genome Project data, the variants were excluded as germline mutations [ 13 14 15 16 17 ]. The Korean 1,000 depression exome data was also used as a normal population panel, and the variants were filtered [ 18 ]. All quality-passed variants were annotated with Sorting Intolerant from Tolerant, Polylphen2, and Combined Annotation Dependent Depletion algorithms using ANNOVAR software to evaluate the pathogenicity of each variant [ 19 20 21 22 ].…”

Investigation of genetic loci shared between bipolar disorder and risk-taking propensity: potential implications for pharmacological interventions

“…Among loci associated with risk-taking propensity, only 33% were identified when conditioning specifically on BD, while a relevant number of loci (39%) were associated with risk-taking when conditioning on all investigated psychiatric disorders and therefore show extensive pleiotropic profiles. Some of these loci might be worth of investigation as potential therapeutic targets as they were found to be located in genes part of the druggable genome (e.g CGREF1, which has been recently associated with non-response to antidepressants [99], or TET2 which has been implicated in the potential antidepressants effect of metformin in a recent preclinical study [100]). Another interesting locus associated with risk-taking propensity when conditioning on all psychiatric phenotypes was found in the NPAS3 gene, which encodes a transcription factor regulating genes involved in key neuronal processes such as postnatal hippocampal neurogenesis [101].…”