Karim Malki

Genetic relationships between suicide attempts, suicidal ideation and major psychiatric disorders: a genome-wide association and polygenic scoring study.

Epidemiological studies have recognized a genetic diathesis for suicidal behavior, which is independent of other psychiatric disorders. Genome‐wide association studies (GWAS) on suicide attempt (SA) and ideation have failed to identify specific genetic variants. Here, we conduct further GWAS and for the first time, use polygenic score analysis in cohorts of patients with mood disorders, to test for common genetic variants for mood disorders and suicide phenotypes. Genome‐wide studies for SA were conducted in the RADIANT and GSK‐Munich recurrent depression samples and London Bipolar Affective Disorder Case‐Control Study (BACCs) then meta‐analysis was performed. A GWAS on suicidal ideation during antidepressant treatment had previously been conducted in the Genome Based Therapeutic Drugs for Depression (GENDEP) study. We derived polygenic scores from each sample and tested their ability to predict SA in the mood disorder cohorts or ideation status in the GENDEP study. Polygenic scores for major depressive disorder, bipolar disorder and schizophrenia from the Psychiatric Genomics Consortium were used to investigate pleiotropy between psychiatric disorders and suicide phenotypes. No significant evidence for association was detected at any SNP in GWAS or meta‐analysis. Polygenic scores for major depressive disorder significantly predicted suicidal ideation in the GENDEP pharmacogenetics study and also predicted SA in a combined validation dataset. Polygenic scores for SA showed no predictive ability for suicidal ideation. Polygenic score analysis suggests pleiotropy between psychiatric disorders and suicidal ideation whereas the tendency to act on such thoughts may have a partially independent genetic diathesis.

Biomarkers predicting treatment outcome in depression: what is clinically significant?

AIM To extend to biomarker studies the consensus clinical significance criterion of a three-point difference in Hamilton Rating Scale for Depression. MATERIALS & METHODS We simulated datasets modeled on large clinical trials. RESULTS In a typical clinical trial comparing active treatment and placebo, a difference of three Hamilton Rating Scale for Depression (HRSD) points at the end of treatment corresponds to 6.3% of variance in outcome explained. To achieve a similar explanatory power, genotypes with minor allele frequencies of 5, 10, 20, 30 and 50% need to attain a per allele difference of 4.7, 3.6, 2.8, 2.4 and 2.2 HRSD points, respectively. A normally distributed continuous biomarker will need an effect size of 1.5 HRSD points per standard deviation. A number needed to assess of three suggests that with this effect size, a biomarker will significantly improve the prediction of outcome in one out of every three patients assessed. CONCLUSION This report provides guidance on assessing clinical significance of biomarkers predictive of outcome in depression treatment.

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.

The endogenous and reactive depression subtypes revisited: integrative animal and human studies implicate multiple distinct molecular mechanisms underlying major depressive disorder

BackgroundTraditional diagnoses of major depressive disorder (MDD) suggested that the presence or absence of stress prior to onset results in either ‘reactive’ or ‘endogenous’ subtypes of the disorder, respectively. Several lines of research suggest that the biological underpinnings of ‘reactive’ or ‘endogenous’ subtypes may also differ, resulting in differential response to treatment. We investigated this hypothesis by comparing the gene-expression profiles of three animal models of ‘reactive’ and ‘endogenous’ depression. We then translated these findings to clinical samples using a human post-mortem mRNA study.MethodsAffymetrix mouse whole-genome oligonucleotide arrays were used to measure gene expression from hippocampal tissues of 144 mice from the Genome-based Therapeutic Drugs for Depression (GENDEP) project. The study used four inbred mouse strains and two depressogenic ‘stress’ protocols (maternal separation and Unpredictable Chronic Mild Stress) to model ‘reactive’ depression. Stress-related mRNA differences in mouse were compared with a parallel mRNA study using Flinders Sensitive and Resistant rat lines as a model of ‘endogenous’ depression. Convergent genes differentially expressed across the animal studies were used to inform candidate gene selection in a human mRNA post-mortem case control study from the Stanley Brain Consortium.ResultsIn the mouse ‘reactive’ model, the expression of 350 genes changed in response to early stresses and 370 in response to late stresses. A minimal genetic overlap (less than 8.8%) was detected in response to both stress protocols, but 30% of these genes (21) were also differentially regulated in the ‘endogenous’ rat study. This overlap is significantly greater than expected by chance. The VAMP-2 gene, differentially expressed across the rodent studies, was also significantly altered in the human study after correcting for multiple testing.ConclusionsOur results suggest that ‘endogenous’ and ‘reactive’ subtypes of depression are associated with largely distinct changes in gene-expression. However, they also suggest that the molecular signature of ‘reactive’ depression caused by early stressors differs considerably from that of ‘reactive’ depression caused by late stressors. A small set of genes was consistently dysregulated across each paradigm and in post-mortem brain tissue of depressed patients suggesting a final common pathway to the disorder. These genes included the VAMP-2 gene, which has previously been associated with Axis-I disorders including MDD, bipolar depression, schizophrenia and with antidepressant treatment response. We also discuss the implications of our findings for disease classification, personalized medicine and case-control studies of MDD.

Antidepressants and the resilience to early-life stress in inbred mouse strains

Rationale Selecting an effective treatment for patients with major depressive disorder is a perpetual problem for psychiatrists. It is of particular interest to explore the interaction between genetic predisposition and environmental factors. Objectives Mouse inbred strains vary in baseline performance in depression-related behaviour tests, which were originally validated as tests of antidepressant response. Therefore, we investigated interactions between environmental stress, genotype, and drug response in a multifactorial behaviour study. Method Our study design included four inbred mouse strains (129S1/SvlmJ, C57LB/6J, DBA/2J and FVB/NJ) of both sexes, two subjected to environmental manipulations (maternal separation and unpredictable chronic mild stress) and two representative of treatment with antidepressants (escitalopram and nortryptiline vs. vehicle). The mice treated with antidepressants were further divided into those administered acute (1 day) and subchronic (14 days) regimes, giving 144 experimental groups in all, each with at least seven animals. All animals were tested using the Porsolt forced-swim test (FST) and the hole-board test. Results Despite a 24-h maternal separation (MS) or a 14-day unpredictable chronic mild stress protocol, most animals seemed to be resilient to the stress induced. One compelling finding is the long-lasting, strain-specific effect of MS resulting in an increased depression-like behaviour in the Porsolt FST and elevated anxiety-related behaviour in the hole-board test seen in 129S1/SvImJ mice. Nortriptyline was effective in reversing the effect of MS in the FST in 129S1/SvlmJ male mice. Conclusion A single 24-h maternal separation of pups from their mother on postnatal day 9 is a sufficient insult to result in a depression-like phenotype in adult 129S1/SvImJ mice but not in C57LB/6 J, DBA/2 J, and FVB/NJ mice.

Combining clinical variables to optimize prediction of antidepressant treatment outcomes

The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug.

Antidepressant-dependent mRNA changes in mouse associated with hippocampal neurogenesis in a mouse model of depression

Rationale Monoaminergic imbalances play a role in the pathogenesis of depression and most common antidepressant drugs act on monoamine neurotransmitters. However, the lag time between restoring neurochemical balance and symptom improvement suggests that the response to drugs involves complex biological events downstream of primary targets that have not yet been fully characterized. Here, we report a mouse mRNA expression study to evaluate the effect of escitalopram (a serotonergic antidepressant) and nortriptyline (a noradrenergic antidepressant) on genes that are involved in the pathogenesis of depression and to assess the similarities and differences between two drugs on gene expression levels. Methods Genome-wide RNA expression data from the hippocampal tissues of four inbred mouse strains (129S1/SvlmJ, C57LB/6J, DBA/2J and FVB/NJ) were treated with varying doses of either nortriptyline (NRI) or escitalopram (SSRI) and subjected to two different depressogenic protocols. Following robust multichip average normalization, we applied the nonparametric RankProd approach to identify differentially expressed genes in response to drugs across the four strains. Pathway analysis was subsequently carried out on top-ranking genes to gain further biological insights. Results A total of 371 genes were significantly differentially expressed in response to nortriptyline, whereas 383 were altered by escitalopram. Genes involved in the pathways of integrin signalling (Fnlb, Mapk1, Mapk8), synaptic transmission (Cacnb1, Dnajc5, Kcnma1, Slc1a2) or Huntington disease (Crebbp, Dlg4, Ncor1) were altered by both nortriptyline and escitalopram. Several biological processes and pathways were identified, which could explain the divergence between the molecular mechanisms of nortriptyline and escitalopram. Conclusion From a large-scale animal study, we obtain gene sets comprised of commonly and differentially expressed genes in response to different antidepressant drug treatments. The results may help to characterize the response to antidepressant treatment, shed further light on the neurobiology of depressive disorders and inform future animal and human studies. Finally, the top-ranking pathways from Ingenuity provide further evidence for the hippocampal neurogenesis hypothesis of major depressive disorders.

Identification of genes and gene pathways associated with major depressive disorder by integrative brain analysis of rat and human prefrontal cortex transcriptomes

Despite moderate heritability estimates, progress in uncovering the molecular substrate underpinning major depressive disorder (MDD) has been slow. In this study, we used prefrontal cortex (PFC) gene expression from a genetic rat model of MDD to inform probe set prioritization in PFC in a human post-mortem study to uncover genes and gene pathways associated with MDD. Gene expression differences between Flinders sensitive (FSL) and Flinders resistant (FRL) rat lines were statistically evaluated using the RankProd, non-parametric algorithm. Top ranking probe sets in the rat study were subsequently used to prioritize orthologous selection in a human PFC in a case–control post-mortem study on MDD from the Stanley Brain Consortium. Candidate genes in the human post-mortem study were then tested against a matched control sample using the RankProd method. A total of 1767 probe sets were differentially expressed in the PFC between FSL and FRL rat lines at (q⩽0.001). A total of 898 orthologous probe sets was found on Affymetrix’s HG-U95A chip used in the human study. Correcting for the number of multiple, non-independent tests, 20 probe sets were found to be significantly dysregulated between human cases and controls at q⩽0.05. These probe sets tagged the expression profile of 18 human genes (11 upregulated and seven downregulated). Using an integrative rat–human study, a number of convergent genes that may have a role in pathogenesis of MDD were uncovered. Eighty percent of these genes were functionally associated with a key stress response signalling cascade, involving NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells), AP-1 (activator protein 1) and ERK/MAPK, which has been systematically associated with MDD, neuroplasticity and neurogenesis.

Integrative mouse and human mRNA studies using WGCNA nominates novel candidate genes involved in the pathogenesis of major depressive disorder

AIM This study aims to identify novel genes associated with major depressive disorder and pharmacological treatment response using animal and human mRNA studies. MATERIALS & METHODS Weighted gene coexpression network analysis was used to uncover genes associated with stress factors in mice and to inform mRNA probe set selection in a post-mortem study of depression. RESULTS A total of 171 genes were found to be differentially regulated in response to both early and late stress protocols in a mouse study. Ten human genes, orthologous to mouse genes differentially expressed by stress, were also found to be dysregulated in depressed cases in a human post-mortem brain study from the Stanley Foundation Brain Collection. CONCLUSION Several novel genes associated with depression were uncovered, including NOVA1 and USP9X. Moreover, we found further evidence in support of hippocampal neurogenesis and peripheral inflammation in major depressive disorder.

Genes and gene networks implicated in aggression related behaviour

Aggressive behaviour is a major cause of mortality and morbidity. Despite of moderate heritability estimates, progress in identifying the genetic factors underlying aggressive behaviour has been limited. There are currently three genetic mouse models of high and low aggression created using selective breeding. This is the first study to offer a global transcriptomic characterization of the prefrontal cortex across all three genetic mouse models of aggression. A systems biology approach has been applied to transcriptomic data across the three pairs of selected inbred mouse strains (Turku Aggressive (TA) and Turku Non-Aggressive (TNA), Short Attack Latency (SAL) and Long Attack Latency (LAL) mice and North Carolina Aggressive (NC900) and North Carolina Non-Aggressive (NC100)), providing novel insight into the neurobiological mechanisms and genetics underlying aggression. First, weighted gene co-expression network analysis (WGCNA) was performed to identify modules of highly correlated genes associated with aggression. Probe sets belonging to gene modules uncovered by WGCNA were carried forward for network analysis using ingenuity pathway analysis (IPA). The RankProd non-parametric algorithm was then used to statistically evaluate expression differences across the genes belonging to modules significantly associated with aggression. IPA uncovered two pathways, involving NF-kB and MAPKs. The secondary RankProd analysis yielded 14 differentially expressed genes, some of which have previously been implicated in pathways associated with aggressive behaviour, such as Adrbk2. The results highlighted plausible candidate genes and gene networks implicated in aggression-related behaviour.