Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis.

BACKGROUND: It has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way. METHODS AND FINDINGS: The NEWMEDS consortium, an academia-industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance p<5×10(-8)). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10(-8)) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D. CONCLUSIONS: No single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study. Please see later in the article for the Editors' Summary.

Bacterial expression and simple purification of human group x secretory phospholipase A2.

Secreted group X phospholipase A2 (sPLA2-X) is one of the most effective mammalian PLA2 enzymes at hydrolyzing plasma lipoproteins and phospholipids in the membranes of intact cells, due in particular to its relatively high binding affinity to zwitterionic phospholipid substrates, such as phosphatidylcholine. The products of its enzymatic activity, lysophospholipids and free fatty acids, especially arachidonic acid, are involved in various physiological and pathological processes and currently being studied intensively. In spite of numerous studies, the biological roles of sPLA2-X have not been completely elucidated. With the aims of studying various cellular functions and designing effective enzyme inhibitors, we prepared a high amount of recombinant human sPLA2-X. Here we describe an effective Escherichia coli expression system, together with an in vitro refolding and simple purification procedure, that yields up to 10 mg of mature human sPLA2-X from a litre of culture. In contrast to the natural protein, the recombinant enzyme was produced in bacterial cells without the N-terminal propeptide, i.e. as a mature protein, and was not N-glycosylated. It however retained all the enzymatic properties for hydrolysis of vesicular substrates composed of either phosphatidylglycerol or phosphatidylcholine.

Pharmacogenetics of antidepressant response: A polygenic approach.

BACKGROUND: Major depressive disorder (MDD) has a high personal and socio-economic burden and >60% of patients fail to achieve remission with the first antidepressant. The biological mechanisms behind antidepressant response are only partially known but genetic factors play a relevant role. A combined predictor across genetic variants may be useful to investigate this complex trait. METHODS: Polygenic risk scores (PRS) were used to estimate multi-allelic contribution to: 1) antidepressant efficacy; 2) its overlap with MDD and schizophrenia. We constructed PRS and tested whether these predicted symptom improvement or remission from the GENDEP study (n=736) to the STAR*D study (n=1409) and vice-versa, including the whole sample or only patients treated with escitalopram or citalopram. Using summary statistics from Psychiatric Genomics Consortium for MDD and schizophrenia, we tested whether PRS from these disorders predicted symptom improvement in GENDEP, STAR*D, and five further studies (n=3756). RESULTS: No significant prediction of antidepressant efficacy was obtained from PRS in GENDEP/STAR*D but this analysis might have been underpowered. There was no evidence of overlap in the genetics of antidepressant response with either MDD or schizophrenia, either in individual studies or a meta-analysis. Stratifying by antidepressant did not alter the results. DISCUSSION: We identified no significant predictive effect using PRS between pharmacogenetic studies. The genetic liability to MDD or schizophrenia did not predict response to antidepressants, suggesting differences between the genetic component of depression and treatment response. Larger or more homogeneous studies will be necessary to obtain a polygenic predictor of antidepressant response.

Convergent animal and human evidence suggests a role of PPM1A gene in response to antidepressants.

BACKGROUND: Antidepressant drugs are used as first-line treatment in depression, but response has been shown to be highly heterogeneous, with drugs often failing to have the desired therapeutic effect. We report on an integrative analysis from the Genome-Based Therapeutic Drugs for Depression (GENDEP) study using gene expression from mice to inform prioritization in a human pharmacogenetic study. METHODS: The same two antidepressants were used in mice and humans: escitalopram (a serotonin reuptake inhibitor) and nortriptyline (a norepinephrine reuptake inhibitor). The animal study used four inbred strains of mice (129S1/SvlmJ, C57LB/6J, DBA/2J, and FVB/NJ). Hippocampus mRNA levels were measured in 144 animals using the Affymetrix MOE 430 v2 chip. RESULTS: Based on gene-expression analysis of strain-by-drug interactions, 17 genes differentially expressed with nortriptyline or escitalopram versus saline were prioritized in the human pharmacogenetic analysis. Single nucleotide polymorphisms tagging common sequence variation in human orthologs of these genes were tested for association with response to antidepressants in 706 participants of the GENDEP human pharmacogenetic study, treated with escitalopram or nortriptyline for 12 weeks, with available high-quality Illumina 610 quad array genotyping. Several polymorphisms in the protein phosphatase 1A gene (PPM1A) remained significantly associated with response to nortriptyline in humans after correction for multiple comparisons within the gene. PPM1A encodes a phosphatase involved in mitogen-activated protein kinase signaling and cell stress response. CONCLUSIONS: Convergent evidence from mice and humans suggests a role of the PPM1A in response to noradrenergic but not serotonergic antidepressants.

Genome-wide pharmacogenetics of antidepressant response in the GENDEP project.

OBJECTIVE: The purpose of this study was to identify genetic variants underlying the considerable individual differences in response to antidepressant treatment. The authors performed a genome-wide association analysis of improvement of depression severity with two antidepressant drugs. METHOD: High-quality Illumina Human610-quad chip genotyping data were available for 706 unrelated participants of European ancestry treated for major depression with escitalopram (N=394) or nortriptyline (N=312) over a 12-week period in the Genome-Based Therapeutic Drugs for Depression (GENDEP) project, a partially randomized open-label pharmacogenetic trial. RESULTS: Single nucleotide polymorphisms in two intergenic regions containing copy number variants on chromosomes 1 and 10 were associated with the outcome of treatment with escitalopram or nortriptyline at suggestive levels of significance and with a high posterior likelihood of true association. Drug-specific analyses revealed a genome-wide significant association between marker rs2500535 in the uronyl 2-sulphotransferase gene and response to nortriptyline. Response to escitalopram was best predicted by a marker in the interleukin-11 (IL11) gene. A set of 72 a priori-selected candidate genes did not show pharmacogenetic associations above a chance level, but an association with response to escitalopram was detected in the interleukin-6 gene, which is a close homologue of IL11. CONCLUSIONS: While limited statistical power means that a number of true associations may have been missed, these results suggest that efficacy of antidepressants may be predicted by genetic markers other than traditional candidates. Genome-wide studies, if properly replicated, may thus be important steps in the elucidation of the genetic basis of pharmacological response.

Sublethal concentrations of ciprofloxacin induce bacteriocin synthesis in Escherichia coli.

Antibiotics that interfere with DNA replication, as well as cell wall synthesis, induce the SOS response. In this report, we show that ciprofloxacin induces synthesis of colicins, narrow-spectrum antibiotics frequently produced by Escherichia coli strains, in an SOS-dependent manner.