Genome-wide pharmacogenomic study of citalopram-induced side effects in STAR*D

Exploratory genome-wide analyses of cortical inhibition, facilitation, and plasticity in late-life depression

Late-life depression (LLD) is a heterogenous mood disorder influenced by genetic factors. Cortical physiological processes such as cortical inhibition, facilitation, and plasticity may be markers of illness that are more strongly associated with genetic factors than the clinical phenotype. Thus, exploring the relationship between genetic factors and these physiological processes may help to characterize the biological mechanisms underlying LLD and improve diagnosis and treatment selection. Transcranial magnetic stimulation (TMS) combined with electromyography was used to measure short interval intracortical inhibition (SICI), cortical silent period (CSP), intracortical facilitation (ICF), and paired associative stimulation (PAS) in 79 participants with LLD. We used exploratory genome-wide association and gene-based analyses to assess for genetic correlations of these TMS measures. MARK4 (which encodes microtubule affinity-regulating kinase 4) and PPP1R37 (which encodes protein phosphatase 1 regulatory subunit 37) showed genome-wide significant association with SICI. EGFLAM (which encodes EGF-like fibronectin type III and laminin G domain) showed genome-wide significant association with CSP. No genes met genome-wide significant association with ICF or PAS. We observed genetic influences on cortical inhibition in older adults with LLD. Replication with larger sample sizes, exploration of clinical phenotype subgroups, and functional analysis of relevant genotypes is warranted to better characterize genetic influences on cortical physiology in LLD. This work is needed to determine whether cortical inhibition may serve as a biomarker to improve diagnostic precision and guide treatment selection in LLD.

Precision Medicine Approaches to Mental Health Care

Developing a more comprehensive understanding of the physiological underpinnings of mental illness, precision medicine has the potential to revolutionize psychiatric care. With recent breakthroughs in next-generation multi-omics technologies and data analytics, it is becoming more feasible to leverage multimodal biomarkers, from genetic variants to neuroimaging biomarkers, to objectify diagnostics and treatment decisions in psychiatry and improve patient outcomes. Ongoing work in precision psychiatry will parallel progress in precision oncology and cardiology to develop an expanded suite of blood- and neuroimaging-based diagnostic tests, empower monitoring of treatment efficacy over time, and reduce patient exposure to ineffective treatments. The emerging model of precision psychiatry has the potential to mitigate some of psychiatry's most pressing issues, including improving disease classification, lengthy treatment duration, and suboptimal treatment outcomes. This narrative-style review summarizes some of the emerging breakthroughs and recurring challenges in the application of precision medicine approaches to mental health care.

Investigating genetic variants for treatment response to selective serotonin reuptake inhibitors in syndromal factors and side effects among patients with depression in Taiwanese Han population

Major depressive disorder (MDD) is associated with high heterogeneity in clinical presentation. In addition, response to treatment with selective serotonin reuptake inhibitors (SSRIs) varies considerably among patients. Therefore, identifying genetic variants that may contribute to SSRI treatment responses in MDD is essential. In this study, we analyzed the syndromal factor structures of the Hamilton Depression Rating Scale in 479 patients with MDD by using exploratory factor analysis. All patients were followed up biweekly for 8 weeks. Treatment response was defined for all syndromal factors and total scores. In addition, a genome-wide association study was performed to investigate the treatment outcomes at week 4 and repeatedly assess all visits during follow-up by using mixed models adjusted for age, gender, and population substructure. Moreover, the role of genetic variants in suicidal and sexual side effects was explored, and five syndromal factors for depression were derived: core, insomnia, somatic anxiety, psychomotor-insight, and anorexia. Subsequently, several known genes were mapped to suggestive signals for treatment outcomes, including single-nucleotide polymorphisms (SNPs) in PRF1, UTP20, MGAM, and ENSG00000286536 for psychomotor-insight and in C4orf51 for anorexia. In total, 33 independent SNPs for treatment responses were tested in a mixed model, 12 of which demonstrated a p value <0.05. The most significant SNP was rs2182717 in the ENSR00000803469 gene located on chromosome 6 for the core syndromal factor (β = -0.638, p = 1.8 × 10^-4) in terms of symptom improvement over time. Patients with a GG or GA genotype with the rs2182717 SNP also exhibited a treatment response (β = 0.089, p = 2.0 × 10^-6) at week 4. Moreover, rs1836075352 was associated with sexual side effects (p = 3.2 × 10^-8). Pathway and network analyses using the identified SNPs revealed potential biological functions involved in treatment response, such as neurodevelopment-related functions and immune processes. In conclusion, we identified loci that may affect the clinical response to treatment with antidepressants in the context of empirically defined depressive syndromal factors and side effects among the Taiwanese Han population, thus providing novel biological targets for further investigation.

Genome-wide analysis suggests the importance of vascular processes and neuroinflammation in late-life antidepressant response

Antidepressant outcomes in older adults with depression is poor, possibly because of comorbidities such as cerebrovascular disease. Therefore, we leveraged multiple genome-wide approaches to understand the genetic architecture of antidepressant response. Our sample included 307 older adults (≥60 years) with current major depression, treated with venlafaxine extended-release for 12 weeks. A standard genome-wide association study (GWAS) was conducted for post-treatment remission status, followed by in silico biological characterization of associated genes, as well as polygenic risk scoring for depression, neurodegenerative and cerebrovascular disease. The top-associated variants for remission status and percentage symptom improvement were PIEZO1 rs12597726 (OR = 0.33 [0.21, 0.51], p = 1.42 × 10^-6) and intergenic rs6916777 (Beta = 14.03 [8.47, 19.59], p = 1.25 × 10^-6), respectively. Pathway analysis revealed significant contributions from genes involved in the ubiquitin-proteasome system, which regulates intracellular protein degradation with has implications for inflammation, as well as atherosclerotic cardiovascular disease (n = 25 of 190 genes, p = 8.03 × 10^-6, FDR-corrected p = 0.01). Given the polygenicity of complex outcomes such as antidepressant response, we also explored 11 polygenic risk scores associated with risk for Alzheimer's disease and stroke. Of the 11 scores, risk for cardioembolic stroke was the second-best predictor of non-remission, after being male (Accuracy = 0.70 [0.59, 0.79], Sensitivity = 0.72, Specificity = 0.67; p = 2.45 × 10^-4). Although our findings did not reach genome-wide significance, they point to previously-implicated mechanisms and provide support for the roles of vascular and inflammatory pathways in LLD. Overall, significant enrichment of genes involved in protein degradation pathways that may be impaired, as well as the predictive capacity of risk for cardioembolic stroke, support a link between late-life depression remission and risk for vascular dysfunction.

The Positive and Negative Experiences of 342 Antidepressant Users

Most efficacy and safety studies about medications adopt a quantitative approach, testing specific hypotheses with restricted samples. This online survey provides additional insights by directly asking people open questions. Thematic analysis was used to explore the responses of 342 antidepressant users to "Is there anything else you would like to tell us about your experience of taking medication". 59 (17.3%) made exclusively positive comments, 146 (42.7%) purely negative comments and 137 (40.0%) offered a mixture of positive and negative. Positive themes included: daily coping, life-changing/saving and stepping stone. Negative themes included: physical adverse effects, emotional and cognitive blunting, and withdrawal effects. Many participants also commented on relationships with prescribers. Collaboration was particularly valued. Negative sub-themes included failings in relation to information (especially about adverse effects and withdrawal), support, and alternatives. Clinicians have a duty to inform potential antidepressant users about positive and adverse effects, including withdrawal effects.

Association Between Side Effects and Blood microRNA Expression Levels and Their Targeted Pathways in Patients With Major Depressive Disorder Treated by a Selective Serotonin Reuptake Inhibitor, Escitalopram: A CAN-BIND-1 Report

INTRODUCTION

Antidepressant drugs are effective therapies for major depressive disorder; however, they are frequently associated with side effects. Although there is some evidence for a relationship between genetic variation and side effects, little is known regarding the role of dynamic molecular factors as moderators of side effects. The aim of this study was to assess microRNA (miRNA) changes associated with side effects during escitalopram treatment and their downstream effects on target gene expression.

METHODS

A total 160 patients with major depressive disorder from the CAN-BIND-1 cohort were included. Side effects were assessed with the Toronto Side Effect Scale after 2 weeks of treatment with escitalopram. We assessed the relationship between side effects and changes in peripheral expression of miRNAs between baseline and week 2. For miRNA whose expression changed, we used target prediction algorithms to identify putative messenger RNA (mRNA) targets and assessed their expression.

RESULTS

Nausea was experienced by 42.5% of patients. We identified 45 miRNAs whose expression changed on initiation of escitalopram treatment, of which 10 displayed a negative association with intensity of nausea (miR15b-5p, miR17-5p, miR20a-5p, miR20b-5p, miR103a-3p, miR103b, miR106a-5p, miR182-5p, miR185-5p, and miR660-5p). Additionally, we found negative associations between 4 microRNAs (miR20a-5p, miR106a-5p, miR185-5p, miR660-5p) and mRNA targets. The expression of the miR185-5p target, CAMK2δ was significantly decreased [log 2 mean = -0.048 (0.233)] between weeks 0 and 2 (P = .01)].

CONCLUSIONS

We identified an overexpression of miR185-5p during escitalopram treatment of major depressive disorder, which was negatively associated with intensity of nausea, and identified a potential mRNA target that may mediate this effect.

Genome-wide association analysis of autism identified multiple loci that have been reported as strong signals for neuropsychiatric disorders

Autism is a common neurodevelopmental disorder with a moderate to a high degree of heritability, but only a few common genetic variants that explain the heritability have been associated. We performed a genome-wide transmission disequilibrium test analysis of a newly genotyped autism case-parent triad samples (127 trios) in Han Chinese, identified top association signals at multiple single nucleotide polymorphisms (SNPs), including rs9839376 (OR = 2.59, P = 1.27 × 10^-05 ) at KCNMB2, rs6044680 (OR = 0.319, P = 4.82 × 10^-05 ) and rs7274133 (OR = 0.313, P = 3.22 × 10^-05 ) at PCSK2, and rs310619 (OR = 2.40, P = 7.44 × 10^-05 ) at EEF1A2. Furthermore, a genome-wide combined P-value of individual SNPs in two independent case-parent triad samples (total 402 triads, n = 1,206) identified SNPs at EGFLAM, ZDHHC2, AGBL1, and SNX29 as additional association signals for autism. While none of these signals achieved a genome-wide significance in the two samples of our study, they have been reported in a previous genome-wide association study of neuropsychiatric disorders, and the majority of these SNP have a significant cis-regulatory association with mRNA in human tissues (false discovery rate (FDR) < 0.05). Our study warrants further study or replication with additional sample for association with autism and other neuropsychiatric disorders. Autism Res 2020, 13: 382-396. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Autism is a common neurodevelopmental disorder, heritable, but only a few common genetic variants that explain the heritability have been associated. We conducted a genome-wide association study with two cohorts of autism case-parent triad samples in Han Chinese and identified multiple single nucleotide polymorphisms that were reported as strong association signals in a previous genome-wide association study of other neuropsychiatric disorders or related traits. Our study provides evidence for shared genetic variants among autism and other neuropsychiatric disorders.

[Pharmacogenetics in psychiatry: state of the art]

In this article, the current literature on pharmacogenetics of antidepressants, antipsychotics and lithium are summarized by the section of Neurobiology and Genetics of the German Society of Psychiatry, Psychotherapy and Neurology (DGPPN). The publications of international expert groups and regulatory authorities are reviewed and discussed. In Germany, a statement on pharmacogenetics was also made by the gene diagnostics committee of the Ministry of Health. The DGPPN supports two recommendations: 1) to perform CYP2D6 genetic testing prior to prescription of tricyclic antidepressants and 2) to determine the HLA-B*1502 genotype in patients of Asian origin before using carbamazepine. The main obstacle for a broad application of pharmacogenetic tests in psychiatry remains the lack of large prospective studies, for both single gene-drug pair and cobinatorial pharmacogenetic tests, to evaluate the benefits of genetic testing. Psychiatrists, geneticists and funding agencies are encouraged to increase their efforts for the future benefit of psychiatric patients.

Genetic variants in major depressive disorder: From pathophysiology to therapy

In spite of promising preclinical results there is a decreasing number of new registered medications in major depression. The main reason behind this fact is the lack of confirmation in clinical studies for the assumed, and in animals confirmed, therapeutic results. This suggests low predictive value of animal studies for central nervous system disorders. One solution for identifying new possible targets is the application of genetics and genomics, which may pinpoint new targets based on the effect of genetic variants in humans. The present review summarizes such research focusing on depression and its therapy. The inconsistency between most genetic studies in depression suggests, first of all, a significant role of environmental stress. Furthermore, effect of individual genes and polymorphisms is weak, therefore gene x gene interactions or complete biochemical pathways should be analyzed. Even genes encoding target proteins of currently used antidepressants remain non-significant in genome-wide case control investigations suggesting no main effect in depression, but rather an interaction with stress. The few significant genes in GWASs are related to neurogenesis, neuronal synapse, cell contact and DNA transcription and as being nonspecific for depression are difficult to harvest pharmacologically. Most candidate genes in replicable gene x environment interactions, on the other hand, are connected to the regulation of stress and the HPA axis and thus could serve as drug targets for depression subgroups characterized by stress-sensitivity and anxiety while other risk polymorphisms such as those related to prominent cognitive symptoms in depression may help to identify additional subgroups and their distinct treatment. Until these new targets find their way into therapy, the optimization of current medications can be approached by pharmacogenomics, where metabolizing enzyme polymorphisms remain prominent determinants of therapeutic success.

Pharmacogenetics in Psychiatry

Mental illness represents a major health issue both at the individual and at the socioeconomical level. This is partly due to the current suboptimal treatment options: existing psychotropic medications, including antidepressants, antipsychotics, and mood stabilizers, are effective only in a subset of patients or produce partial response and they are often associated with debilitating side effects that discourage adherence. Pharmacogenetics is the study of how genetic information impacts on drug response/side effects with the goal to provide tailored treatments, thereby maximizing efficacy and tolerability. The first pharmacogenetic studies focused on candidate genes, previously known to be relevant to the pharmacokinetics and pharmacodynamics of psychotropic drugs. Results were mainly inconclusive, but some replicated candidates were identified and included as pharmacogenetic biomarkers in drug labeling and in some commercial kits. With the advent of the genomic revolution, it became possible to study the genetic variation on an unprecedented scale, throughout the whole genome with no need of a priori hypothesis. This may lead to the personalized prescription of existing medications and potentially to the development of innovative ones, thanks to new insights into the genetics of mental illness. Promising findings were obtained, but methods for the generation and analysis of genome-wide and sequencing data are still in evolution. Future pharmacogenetic tests may consist of hundreds/thousands of polymorphisms throughout the genome or selected pathways in order to take into account the complex interactions across variants in a number of genes.

Delayed Ejaculation: Pathophysiology, Diagnosis, and Treatment

Delayed ejaculation (DE) is a poorly defined and uncommon form of male sexual dysfunction, characterized by a marked delay in ejaculation or an inability to achieve ejaculation. It is often quite concerning to patients and their partners, and sometimes frustrates couples' attempts to conceive. This article aims to review the pathophysiology of DE and anejaculation (AE), to explore our current understanding of the diagnosis, and to present the treatment options for this condition. Electronic databases were searched from 1966 to October 2017, including PubMed (MEDLINE) and Embase. We combined “delayed ejaculation,” “retarded ejaculation,” “inhibited ejaculation,” or “anejaculation” as Medical Subject Headings (MeSH) terms or keywords with “epidemiology,” “etiology,” “pathophysiology,” “clinical assessment,” “diagnosis,” or “treatment.” Relevant sexual medicine textbooks were searched as well. The literature suggests that the pathophysiology of DE/AE is multifactorial, including both organic and psychosocial factors. Despite the many publications on this condition, the exact pathogenesis is not yet known. There is currently no single gold standard for diagnosing DE/AE, as operationalized criteria do not exist. The history is the key to the diagnosis. Treatment should be cause-specific. There are many approaches to treatment planning, including various psychological interventions, pharmacotherapy, and specific treatments for infertile men. An approved form of drug therapy does not exist. A number of approaches can be employed for infertile men, including the collection of nocturnal emissions, prostatic massage, prostatic urethra catheterization, penile vibratory stimulation, probe electroejaculation, sperm retrieval by aspiration from either the vas deferens or the epididymis, and testicular sperm extraction.

A novel relationship for schizophrenia, bipolar and major depressive disorder Part 3: Evidence from chromosome 3 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was systematically reported (Aukes et al, Genet Med 2012, 14, 338-341) and convergent evidence from genetics, symptomatology, and psychopharmacology imply that there are intrinsic connections between these three major psychiatric disorders, for example, any two or even three of these disorders could co-exist in some families. A total of 60, 838 single-nucleotide polymorphisms (SNPs) on chromosome 3 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type-I), 177 MDD patients and 1,000 controls. The population of Shandong province was formed in 14 century and believed that it belongs to homogenous population. Associated SNPs were systematically revealed and outstanding susceptibility genes (CADPS, GRM7,KALRN, LSAMP, NLGN1, PRICKLE2, ROBO2) were identified. Unexpectedly, flanking genes for the associated SNPs distinctive for BPD and/or MDD were replicated in an enlarged cohort of 986 SCZ patients. The evidence from this chromosome 3 analysis supports the notion that both of bipolar and MDD might be subtypes of schizophrenia rather than independent disease entity. Also, a similar finding was detected on chromosome 5, 6, 7, and 8 (Chen et al. Am J Transl Res 2017;9 (5):2473-2491; Curr Mol Med 2016;16(9):840-854; Behav Brain Res 2015;293:241-251; Mol Neurobiol 2016. doi: 10.1007/s12035-016-0102-1). Furthermore, PRICKLE2 play an important role in the pathogenesis of three major psychoses in this population.

The interpersonal adverse effects reported by 1008 users of antidepressants; and the incremental impact of polypharmacy

Antidepressant drugs are being prescribed at ever increasing rates internationally, despite marginal benefit compared to placebo and a range of adverse effects. Most studies of adverse effects focus on biological phenomena. This article presents the results of an online survey of 1008 self-selected anti-depressant users in Britain, which asked about five adverse effects in the interpersonal domain. The most commonly reported among participants who took only antidepressants were: Sex Life - 43.7%, Work or Study - 27.0% and Social Life - 23.5%. These rates of interpersonal adverse effects were even higher for the 52% of participants who were also taking one or more other psychiatric drugs. Only about a half (48%) felt they had been given enough information about side effects by the prescriber. Those initially prescribed medication by a psychiatrist were more likely to be on several types of drugs and reported more adverse effects than those whose prescriber was a General Practitioner (GP). Researchers and prescribers are encouraged to pay greater attention to interpersonal adverse effects.

Pharmacogenomics in the treatment of mood disorders: Strategies and Opportunities for personalized psychiatry

Personalized medicine (personalized psychiatry in a specific setting) is a new model towards individualized care, in which knowledge from genomics and other omic pillars (microbiome, epigenomes, proteome, and metabolome) will be combined with clinical data to guide efforts to new drug development and targeted prescription of the existing treatment options. In this review, we summarize pharmacogenomic studies in mood disorders that may lay the foundation towards personalized psychiatry. In addition, we have discussed the possible strategies to integrate data from omic pillars as a future path to personalized psychiatry. So far, the progress of uncovering single nucleotide polymorphisms (SNPs) underpinning treatment efficacy in mood disorders (e.g., SNPs associated with selective serotonin re-uptake inhibitors or lithium treatment response in patients with bipolar disorder and major depressive disorder) are encouraging, but not adequate. Genetic studies have pointed to a number of SNPs located at candidate genes that possibly influence response to; (a) antidepressants COMT, HTR2A, HTR1A, CNR1, SLC6A4, NPY, MAOA, IL1B, GRIK4, BDNF, GNB3, FKBP5, CYP2D6, CYP2C19, and ABCB1 and (b) mood stabilizers (lithium) 5-HTT, TPH, DRD1, FYN, INPP1, CREB1, BDNF, GSK3β, ARNTL, TIM, DPB, NR3C1, BCR, XBP1, and CACNG2. We suggest three alternative and complementary strategies to implement knowledge gained from pharmacogenomic studies. The first strategy can be to implement diagnostic, therapeutic, or prognostic genetic testing based on candidate genes or gene products. The second alternative is an integrative analysis (systems genomics approach) to combine omics data obtained from the different pillars of omics investigation, including genomics, epigenomes, proteomics, metabolomics and microbiomes. The main goal of system genomics is an identification and understanding of biological pathways, networks, and modules underlying drug-response. The third strategy aims to the development of multivariable diagnostic or prognostic algorithms (tools) combining individual's genomic information (polygenic score) with other predictors (e.g., omics pillars, neuroimaging, and clinical characteristics) to finally predict therapeutic outcomes. An integration of molecular science with that of traditional clinical practice is the way forward to drug discoveries and novel therapeutic approaches and to characterize psychiatric disorders leading to a better predictive, preventive, and personalized medicine (PPPM) in psychiatry. With future advances in the omics technology and methodological developments for data integration, the goal of PPPM in psychiatry is promising.

An Analysis of Two Genome-wide Association Meta-analyses Identifies a New Locus for Broad Depression Phenotype

BACKGROUND

The genetics of depression has been explored in genome-wide association studies that focused on either major depressive disorder or depressive symptoms with mostly negative findings. A broad depression phenotype including both phenotypes has not been tested previously using a genome-wide association approach. We aimed to identify genetic polymorphisms significantly associated with a broad phenotype from depressive symptoms to major depressive disorder.

METHODS

We analyzed two prior studies of 70,017 participants of European ancestry from general and clinical populations in the discovery stage. We performed a replication meta-analysis of 28,328 participants. Single nucleotide polymorphism (SNP)-based heritability and genetic correlations were calculated using linkage disequilibrium score regression. Discovery and replication analyses were performed using a p-value-based meta-analysis. Lifetime major depressive disorder and depressive symptom scores were used as the outcome measures.

RESULTS

The SNP-based heritability of major depressive disorder was 0.21 (SE = 0.02), the SNP-based heritability of depressive symptoms was 0.04 (SE = 0.01), and their genetic correlation was 1.001 (SE = 0.2). We found one genome-wide significant locus related to the broad depression phenotype (rs9825823, chromosome 3: 61,082,153, p = 8.2 × 10^-9) located in an intron of the FHIT gene. We replicated this SNP in independent samples (p = .02) and the overall meta-analysis of the discovery and replication cohorts (1.0 × 10^-9).

CONCLUSIONS

This large study identified a new locus for depression. Our results support a continuum between depressive symptoms and major depressive disorder. A phenotypically more inclusive approach may help to achieve the large sample sizes needed to detect susceptibility loci for depression.

Identification of EGFLAM, SPATC1L and RNASE13 as novel susceptibility loci for aortic aneurysm in Japanese individuals by exome-wide association studies

We performed an exome-wide association study (EWAS) to identify genetic variants - in particular, low‑frequency or rare variants with a moderate to large effect size - that confer susceptibility to aortic aneurysm with 8,782 Japanese subjects (456 patients with aortic aneurysm, 8,326 control individuals) and with the use of Illumina HumanExome-12 DNA Analysis BeadChip or Infinium Exome-24 BeadChip arrays. The correlation of allele frequencies for 41,432 single nucleotide polymorphisms (SNPs) that passed quality control to aortic aneurysm was examined with Fisher's exact test. Based on Bonferroni's correction, a P-value of <1.21x10-6 was considered statistically significant. The EWAS revealed 59 SNPs that were significantly associated with aortic aneurysm. None of these SNPs was significantly (P<2.12x10-4) associated with aortic aneurysm by multivariable logistic regression analysis with adjustment for age, gender and hypertension, although 8 SNPs were related (P<0.05) to this condition. Examination of the correlation of these latter 8 SNPs to true or dissecting aortic aneurysm separately showed that rs1465567 [T/C (W229R)] of the EGF-like, fibronectin type III, and laminin G domains gene (EGFLAM) (dominant model; P=0.0014; odds ratio, 1.63) was significantly (P<0.0016) associated with true aortic aneurysm. We next performed EWASs for true or dissecting aortic aneurysm separately and found that 45 and 19 SNPs were significantly associated with these conditions, respectively. Multivariable logistic regression analysis with adjustment for covariates revealed that rs113710653 [C/T (E231K)] of the spermatogenesis- and centriole associated 1-like gene (SPATC1L) (dominant model; P=0.0002; odds ratio, 5.32) and rs143881017 [C/T (R140H)] of the ribonuclease A family member 13 gene (RNASE13) (dominant model; P=0.0006; odds ratio, 5.77) were significantly (P<2.78x10-4 or P<6.58x10-4, respectively) associated with true or dissecting aortic aneurysm, respectively. EGFLAM and SPATC1L may thus be susceptibility loci for true aortic aneurysm and RNASE13 may be such a locus for dissecting aneurysm in Japanese individuals.

Pharmacogenetics and Imaging-Pharmacogenetics of Antidepressant Response: Towards Translational Strategies

Genetic variation underlies both the response to antidepressant treatment and the occurrence of side effects. Over the past two decades, a number of pharmacogenetic variants, among these the SCL6A4, BDNF, FKBP5, GNB3, GRIK4, and ABCB1 genes, have come to the forefront in this regard. However, small effects sizes, mixed results in independent samples, and conflicting meta-analyses results led to inherent difficulties in the field of pharmacogenetics translating these findings into clinical practice. Nearly all antidepressant pharmacogenetic variants have potentially pleiotropic effects in which they are associated with major depressive disorder, intermediate phenotypes involved in emotional processes, and brain areas affected by antidepressant treatment. The purpose of this article is to provide a comprehensive review of the advances made in the field of pharmacogenetics of antidepressant efficacy and side effects, imaging findings of antidepressant response, and the latest results in the expanding field of imaging-pharmacogenetics studies. We suggest there is mounting evidence that genetic factors exert their impact on treatment response by influencing brain structural and functional changes during antidepressant treatment, and combining neuroimaging and genetic methods may be a more powerful way to detect biological mechanisms of response than either method alone. The most promising imaging-pharmacogenetics findings exist for the SCL6A4 gene, with converging associations with antidepressant response, frontolimbic predictors of affective symptoms, and normalization of frontolimbic activity following antidepressant treatment. More research is required before imaging-pharmacogenetics informed personalized medicine can be applied to antidepressant treatment; nevertheless, inroads have been made towards assessing genetic and neuroanatomical liability and potential clinical application.

Insight gained from genome-wide interaction and enrichment analysis on weight gain during citalopram treatment

Weight gain is a possible side effect of the pharmacological antidepressant treatments. Defining antidepressant prescriptions based on personal genetic makeups would decrease the risk of weight gain and increase the quality of the current antidepressant pharmacological treatments. 643 depressed, citalopram treated individuals with available clinical and genome-wide genetic information were investigated to identify the molecular pathways associated with weight gain. 111 individuals experienced weight gain during citalopram treatment. The axon guidance (p.adjust=0.005) and the developmental biology pathway (p.adjust=0.01) were enriched in variations associated with weight gain. The developmental biology pathway includes molecular cascades involved in the regulation of beta-cell development, and the transcriptional regulation of white adipocyte differentiation. A number of variations were harbored by genes whose products are involved in the synthesis of collagen (COL4A3, COL5A1 and ITGA1), activity of the thyroid-hormones (NCOR1 and NCOR2), energy metabolism (ADIPOQ, PPARGC1A) and myogenic differentiation (CDON). A molecular pathway analysis conducted in a sample of depressed patients identified new candidate genes whose future investigation may provide insights in the molecular events that drive weight gain during antidepressant treatment.

Targeted Re-Sequencing Approach of Candidate Genes Implicates Rare Potentially Functional Variants in Tourette Syndrome Etiology

Although the genetic basis of Tourette Syndrome (TS) remains unclear, several candidate genes have been implicated. Using a set of 382 TS individuals of European ancestry we investigated four candidate genes for TS (HDC, SLITRK1, BTBD9, and SLC6A4) in an effort to identify possibly causal variants using a targeted re-sequencing approach by next generation sequencing technology. Identification of possible disease causing variants under different modes of inheritance was performed using the algorithms implemented in VAAST. We prioritized variants using Variant ranker and validated five rare variants via Sanger sequencing in HDC and SLITRK1, all of which are predicted to be deleterious. Intriguingly, one of the identified variants is in linkage disequilibrium with a variant that is included among the top hits of a genome-wide association study for response to citalopram treatment, an antidepressant drug with off-label use also in obsessive compulsive disorder. Our findings provide additional evidence for the implication of these two genes in TS susceptibility and the possible role of these proteins in the pathobiology of TS should be revisited.

Toward a Global Roadmap for Precision Medicine in Psychiatry: Challenges and Opportunities

Mental disorders represent a major public health burden worldwide. This is likely to rise in the next decade, with the highest increases predicted to occur in low- and middle-income countries. Current psychotropic medication treatment guidelines focus on uniform approaches to the treatment of heterogeneous disorders and achieve only partial therapeutic success. Developing a global precision medicine approach in psychiatry appears attractive, given the value of this approach in other fields of medicine, such as oncology and infectious diseases. In this horizon scanning analysis, we review the salient opportunities and challenges for precision medicine in psychiatry over the next decade. Variants within numerous genes involved in a range of pathways have been implicated in psychotropic drug response and might ultimately be used to guide choice of pharmacotherapy. Multipronged approaches such as multi-omics (genomics, proteomics, metabolomics) analyses and systems diagnostics together with high-throughput sequencing and genotyping technologies hold promise for identifying precise and targeted treatments in mental disorders. To date, however, the vast majority of pharmacogenomics work has been undertaken in high-income countries on a relatively small proportion of the global population, and many other challenges face the field. Opportunities and challenges for establishing a global roadmap for precision medicine in psychiatry are discussed in this article.

Pharmacogenomics: A focus on antidepressants and atypical antipsychotics

The study of pharmacogenomics is rapidly growing, particularly in the field of mental health. Understanding pharmacogenomic principles can be a challenge for many clinicians. Most mental health genomic data concentrates on variability (response, side effects) with antidepressants and atypical antipsychotics. Current pharmacogenomic practice and research primarily focuses on two areas: pharmacodynamics and pharmacokinetics. Based on the current literature, genetic polymorphisms of pharmacodynamics and pharmacokinetics parameters likely influence medication efficacy, therefore affecting the therapeutic benefit. Additionally, certain pharmacodynamic and pharmacokinetic polymorphisms have been linked to an elevated risk of side effects and adverse events with these medications. In this review, specific pharmacodynamic and pharmacokinetic polymorphisms related to antidepressants and atypical antipsychotics will be discussed, as well as the potential clinical effect these genomic abnormalities have within psychiatric care.

Genome-wide association studies in pharmacogenomics of antidepressants

Major depressive disorder (MDD) is one of the most common psychiatric disorders worldwide. Doctors must prescribe antidepressants based on educated guesses due to the fact that it is unmanageable to predict the effectiveness of any particular antidepressant in an individual patient. With the recent advent of scientific research, the genome-wide association study (GWAS) is extensively employed to analyze hundreds of thousands of single nucleotide polymorphisms by high-throughput genotyping technologies. In addition to the candidate-gene approach, the GWAS approach has recently been utilized to investigate the determinants of antidepressant response to therapy. In this study, we reviewed GWAS studies, their limitations and future directions with respect to the pharmacogenomics of antidepressants in MDD.

Placental DNA Methylation Related to Both Infant Toenail Mercury and Adverse Neurobehavioral Outcomes

BACKGROUND

Prenatal mercury (Hg) exposure is associated with adverse child neurobehavioral outcomes. Because Hg can interfere with placental functioning and cross the placenta to target the fetal brain, prenatal Hg exposure can inhibit fetal growth and development directly and indirectly.

OBJECTIVES

We examined potential associations between prenatal Hg exposure assessed through infant toenail Hg, placental DNA methylation changes, and newborn neurobehavioral outcomes.

METHODS

The methylation status of > 485,000 CpG loci was interrogated in 192 placental samples using Illumina's Infinium HumanMethylation450 BeadArray. Hg concentrations were analyzed in toenail clippings from a subset of 41 infants; neurobehavior was assessed using the NICU Network Neurobehavioral Scales (NNNS) in an independent subset of 151 infants.

RESULTS

We identified 339 loci with an average methylation difference > 0.125 between any two toenail Hg tertiles. Variation among these loci was subsequently found to be associated with a high-risk neurodevelopmental profile (omnibus p-value = 0.007) characterized by the NNNS. Ten loci had p < 0.01 for the association between methylation and the high-risk NNNS profile. Six of 10 loci reside in the EMID2 gene and were hypomethylated in the 16 high-risk profile infants' placentas. Methylation at these loci was moderately correlated (correlation coefficients range, -0.33 to -0.45) with EMID2 expression.

CONCLUSIONS

EMID2 hypomethylation may represent a novel mechanism linking in utero Hg exposure and adverse infant neurobehavioral outcomes.

Progress in understanding the genomic basis for adverse drug reactions: a comprehensive review and focus on the role of ethnicity

A major goal of the field of pharmacogenomics is to identify the genomic causes of serious adverse drug reactions (ADRs). Increasingly, genome-wide association studies (GWAS) have been used to achieve this goal. In this article, we review recent progress in the identification of genetic variants associated with ADRs using GWAS and discuss emerging themes from these studies. We also compare aspects of GWAS for ADRs to GWAS for common diseases. In the second part of the article, we review progress in performing pharmacogenomic research in multi-ethnic populations and discuss the challenges and opportunities of investigating genetic causes of ADRs in ethnically diverse patient populations.

Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease

Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.

Towards the clinical implementation of pharmacogenetics in bipolar disorder

BACKGROUND

Bipolar disorder (BD) is a psychiatric illness defined by pathological alterations between the mood states of mania and depression, causing disability, imposing healthcare costs and elevating the risk of suicide. Although effective treatments for BD exist, variability in outcomes leads to a large number of treatment failures, typically followed by a trial and error process of medication switches that can take years. Pharmacogenetic testing (PGT), by tailoring drug choice to an individual, may personalize and expedite treatment so as to identify more rapidly medications well suited to individual BD patients.

DISCUSSION

A number of associations have been made in BD between medication response phenotypes and specific genetic markers. However, to date clinical adoption of PGT has been limited, often citing questions that must be answered before it can be widely utilized. These include: What are the requirements of supporting evidence? How large is a clinically relevant effect? What degree of specificity and sensitivity are required? Does a given marker influence decision making and have clinical utility? In many cases, the answers to these questions remain unknown, and ultimately, the question of whether PGT is valid and useful must be determined empirically. Towards this aim, we have reviewed the literature and selected drug-genotype associations with the strongest evidence for utility in BD.

SUMMARY

Based upon these findings, we propose a preliminary panel for use in PGT, and a method by which the results of a PGT panel can be integrated for clinical interpretation. Finally, we argue that based on the sufficiency of accumulated evidence, PGT implementation studies are now warranted. We propose and discuss the design for a randomized clinical trial to test the use of PGT in the treatment of BD.

Adverse emotional and interpersonal effects reported by 1829 New Zealanders while taking antidepressants

In the context of rapidly increasing antidepressant use internationally, and recent reviews raising concerns about efficacy and adverse effects, this study aimed to survey the largest sample of AD recipients to date. An online questionnaire about experiences with, and beliefs about, antidepressants was completed by 1829 adults who had been prescribed antidepressants in the last five years (53% were first prescribed them between 2000 and 2009, and 52% reported taking them for more than three years). Eight of the 20 adverse effects studied were reported by over half the participants; most frequently Sexual Difficulties (62%) and Feeling Emotionally Numb (60%). Percentages for other effects included: Feeling Not Like Myself - 52%, Reduction In Positive Feelings - 42%, Caring Less About Others - 39%, Suicidality - 39% and Withdrawal Effects - 55%. Total Adverse Effect scores were related to younger age, lower education and income, and type of antidepressant, but not to level of depression prior to taking antidepressants. The adverse effects of antidepressants may be more frequent than previously reported, and include emotional and interpersonal effects.

Antidepressant pharmacogenetics

PURPOSE OF REVIEW

This article reviews recent literature published over the period March 2012-August 2013 on antidepressant pharmacogenetics, with a focus on clinical translation and methodological challenges.

RECENT FINDINGS

Recently, various polymorphisms associated with differential antidepressant efficacy, tolerability, and safety have emerged in association studies, but mixed findings, limited effect sizes, and poor control of confounders have prevented findings translating to practice. Although promising steps have been made, empirically robust clinically translatable pharmacogenetic tests are not yet established. The complex neurobiology of major depressive disorder (MDD) together with the evolving understanding of genetic processes present research challenges for clinical translation.

SUMMARY

Early reports of clinical utility are published. The current evidence base for antidepressant pharmacogenetics is, however, not yet empirically robust enough to inform routine prescribing guidelines. Over the coming years, genetically guided versus unguided trials will help determine if antidepressant pharmacogenetics merits more widespread application.

Impact of antidepressants on cytokine production of depressed patients in vitro

The interplay between immune and nervous systems plays a pivotal role in the pathophysiology of depression. In depressive episodes, patients show increased production of pro-inflammatory cytokines such as interleukin (IL)-1β and tumor necrosis factor (TNF)-α. There is limited information on the effect of antidepressant drugs on cytokines, most studies report on a limited sample of cytokines and none have reported effects on IL-22. We systematically investigated the effect of three antidepressant drugs, citalopram, escitalopram and mirtazapine, on secretion of cytokines IL-1β, IL-2, IL-4, IL-6, IL-17, IL-22 and TNF-α in a whole blood assay in vitro, using murine anti-human CD3 monoclonal antibody OKT3, and 5C3 monoclonal antibody against CD40, to stimulate T and B cells respectively. Citalopram increased production of IL-1β, IL-6, TNF-α and IL-22. Mirtazapine increased IL-1β, TNF-α and IL-22. Escitalopram decreased IL-17 levels. The influence of antidepressants on IL-2 and IL-4 levels was not significant for all three drugs. Compared to escitalopram, citalopram led to higher levels of IL-1β, IL-6, IL-17 and IL-22; and mirtazapine to higher levels of IL-1β, IL-17, IL-22 and TNF-α. Mirtazapine and citalopram increased IL-22 production. The differing profile of cytokine production may relate to differences in therapeutic effects, risk of relapse and side effects.

Pharmacogenetics of antidepressant drugs: an update after almost 20 years of research

Major depressive disorder (MDD) is an emergent cause of personal and socio-economic burden, both for the high prevalence of the disorder and the unsatisfying response rate of the available antidepressant treatments. No reliable predictor of treatment efficacy and tolerance in the single patient is available, thus drug choice is based on a trial and error principle with poor clinical efficiency. Among modulators of treatment outcome, genetic polymorphisms are thought to explain a significant share of the inter-individual variability. The present review collected the main pharmacogenetic findings primarily about antidepressant response and secondly about antidepressant induced side effects, and discussed the main strengths and limits of both candidate and genome-wide association studies and the most promising methodological opportunities and challenges of the field. Despite clinical applications of antidepressant pharmacogenetics are not available yet, previous findings suggest that genotyping may be applied in the clinical practice. In order to reach this objective, further rigorous pharmacogenetic studies (adequate sample size, study of better defined clinical subtypes of MDD, adequate covering of the genetic variability), their combination with the results obtained through complementary methodologies (e.g., pathway analysis, epigenetics, transcriptomics, and proteomics), and finally cost-effectiveness trials are required.

Genotype-based ancestral background consistently predicts efficacy and side effects across treatments in CATIE and STAR*D

Only a subset of patients will typically respond to any given prescribed drug. The time it takes clinicians to declare a treatment ineffective leaves the patient in an impaired state and at unnecessary risk for adverse drug effects. Thus, diagnostic tests robustly predicting the most effective and safe medication for each patient prior to starting pharmacotherapy would have tremendous clinical value. In this article, we evaluated the use of genetic markers to estimate ancestry as a predictive component of such diagnostic tests. We first estimated each patient’s unique mosaic of ancestral backgrounds using genome-wide SNP data collected in the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) (n = 765) and the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) (n = 1892). Next, we performed multiple regression analyses to estimate the predictive power of these ancestral dimensions. For 136/89 treatment-outcome combinations tested in CATIE/STAR*D, results indicated 1.67/1.84 times higher median test statistics than expected under the null hypothesis assuming no predictive power (p<0.01, both samples). Thus, ancestry showed robust and pervasive correlations with drug efficacy and side effects in both CATIE and STAR*D. Comparison of the marginal predictive power of MDS ancestral dimensions and self-reported race indicated significant improvements to model fit with the inclusion of MDS dimensions, but mixed evidence for self-reported race. Knowledge of each patient’s unique mosaic of ancestral backgrounds provides a potent immediate starting point for developing algorithms identifying the most effective and safe medication for a wide variety of drug-treatment response combinations. As relatively few new psychiatric drugs are currently under development, such personalized medicine offers a promising approach toward optimizing pharmacotherapy for psychiatric conditions.