Rare and low-frequency coding variants alter human adult height

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

Multimodal Brain Imaging Reveals Structural Differences in Alzheimer's Disease Polygenic Risk Carriers: A Study in Healthy Young Adults

BACKGROUND

Recent genome-wide association studies have identified genetic loci that jointly make a considerable contribution to risk of developing Alzheimer's disease (AD). Because neuropathological features of AD can be present several decades before disease onset, we investigated whether effects of polygenic risk are detectable by neuroimaging in young adults. We hypothesized that higher polygenic risk scores (PRSs) for AD would be associated with reduced volume of the hippocampus and other limbic and paralimbic areas. We further hypothesized that AD PRSs would affect the microstructure of fiber tracts connecting the hippocampus with other brain areas.

METHODS

We analyzed the association between AD PRSs and brain imaging parameters using T1-weighted structural (n = 272) and diffusion-weighted scans (n = 197).

RESULTS

We found a significant association between AD PRSs and left hippocampal volume, with higher risk associated with lower left hippocampal volume (p = .001). This effect remained when the APOE gene was excluded (p = .031), suggesting that the relationship between hippocampal volume and AD is the result of multiple genetic factors and not exclusively variability in the APOE gene. The diffusion tensor imaging analysis revealed that fractional anisotropy of the right cingulum was inversely correlated with AD PRSs (p = .009). We thus show that polygenic effects of AD risk variants on brain structure can already be detected in young adults.

CONCLUSIONS

This finding paves the way for further investigation of the effects of AD risk variants and may become useful for efforts to combine genotypic and phenotypic data for risk prediction and to enrich future prevention trials of AD.

Polygenic Risk of Psychosis and Ventral Striatal Activation During Reward Processing in Healthy Adolescents

IMPORTANCE

Psychotic disorders are characterized by attenuated activity in the brain's valuation system in key reward processing areas, such as the ventral striatum (VS), as measured with functional magnetic resonance imaging.

OBJECTIVE

To examine whether common risk variants for psychosis are associated with individual variation in the VS.

DESIGN, SETTING, AND PARTICIPANTS

A cross-sectional study of a large cohort of adolescents from the IMAGEN study (a European multicenter study of reinforcement sensitivity in adolescents) was performed from March 1, 2008, through December 31, 2011. Data analysis was conducted from October 1, 2015, to January 9, 2016. Polygenic risk profile scores (RPSs) for psychosis were generated for 1841 healthy adolescents. Sample size and characteristics varied across regression analyses, depending on mutual information available (N = 1524-1836).

MAIN OUTCOMES AND MEASURES

Reward-related brain function was assessed with blood oxygen level dependency (BOLD) in the VS using the monetary incentive delay (MID) task, distinguishing reward anticipation and receipt. Behavioral impulsivity, IQ, MID task performance, and VS BOLD were regressed against psychosis RPS at 4 progressive P thresholds (P < .01, P < .05, P < .10, and P < .50 for RPS models 1-4, respectively).

RESULTS

In a sample of 1841 healthy adolescents (mean age, 14.5 years; 906 boys and 935 girls), we replicated an association between increasing psychosis RPS and reduced IQ (matrix reasoning: corrected P = .003 for RPS model 2, 0.4% variance explained), supporting the validity of the psychosis RPS models. We also found a nominally significant association between increased psychosis RPS and reduced MID task performance (uncorrected P = .03 for RPS model 4, 0.2% variance explained). Our main finding was a positive association between psychosis RPS and VS BOLD during reward anticipation at all 4 psychosis RPS models and for 2 P thresholds for reward receipt (RPS models 1 and 3), correcting for the familywise error rate (0.8%-1.9% variance explained).

CONCLUSIONS AND RELEVANCE

These findings support an association between psychosis RPS and VS BOLD in adolescents. Genetic risk for psychosis may shape an individual's response to rewarding stimuli.

Evidence of Common Genetic Overlap Between Schizophrenia and Cognition

Cognitive impairment is a core feature of schizophrenia but there is limited understanding of the genetic relationship between cognition in the general population and schizophrenia. We examine how common variants associated with schizophreniaen massecontribute to childhood cognitive ability in a population-based sample, and the extent to which common genetic variants associated with childhood cognition explain variation in schizophrenia. Schizophrenia polygenic risk scores were derived from the Psychiatric Genomics Consortium (n= 69 516) and tested for association with IQ, attention, processing speed, working memory, problem solving, and social cognition in over 5000 children aged 8 from the Avon Longitudinal Study of Parents and Children birth cohort. Polygenic scores for these cognitive domains were tested for association with schizophrenia in a large UK schizophrenia sample (n= 11 853). Bivariate genome-wide complex trait analysis (GCTA) estimated the amount of shared genetic factors between schizophrenia and cognitive domains. Schizophrenia polygenic risk score was associated with lower performance IQ (P= .001) and lower full IQ (P= .013). Polygenic score for performance IQ was associated with increased risk for schizophrenia (P= 3.56E-04). Bivariate GCTA revealed moderate genetic correlation between schizophrenia and both performance IQ (rG= -.379,P= 6.62E-05) and full IQ (rG= -.202,P= 5.00E-03), with approximately 14% of the genetic component of schizophrenia shared with that for performance IQ. Our results support the presence of shared common genetic factors between schizophrenia and childhood cognitive ability. We observe a genetic relationship between schizophrenia and performance IQ but not verbal IQ or other cognitive variables, which may have implications for studies utilizing cognitive endophenotypes for psychosis.

CACNA1C risk variant is associated with increased amygdala volume

Genome-wide association studies suggest that genetic variation within L-type calcium channel subunits confer risk to psychosis. The single nucleotide polymorphism at rs1006737 in CACNA1C has been associated with both schizophrenia and bipolar disorder and with several intermediate phenotypes that may serve as neurobiological antecedents, linking psychosis to genetic aetiology. Amongst others, it has been implicated in alterations in amygdala structure and function. In the present study, we show that the risk allele (A) is associated with increased amygdala volume in healthy individuals (n = 258). This observation reinforces a hypothesis that genetic variation may confer risk to psychosis via alterations in limbic structures. Further study of CACNA1C using intermediate phenotypes for psychosis will determine the mechanisms by which variation in this gene confers risk.

Phenotypic Manifestation of Genetic Risk for Schizophrenia During Adolescence in the General Population

IMPORTANCE

Schizophrenia is a highly heritable, polygenic condition characterized by a relatively diverse phenotype and frequent comorbid conditions, such as anxiety and depression. At present, limited evidence explains how genetic risk for schizophrenia is manifest in the general population.

OBJECTIVE

To investigate the extent to which genetic risk for schizophrenia is associated with different phenotypes during adolescence in a population-based birth cohort.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used data from the Avon Longitudinal Study of Parents and Children (ALSPAC). Of 14,062 children in the birth cohort, genetic data were available for 9912 adolescents. Data were collected periodically from September 6, 1990, and collection is ongoing. Data were analyzed from March 4 to August 13, 2015.

EXPOSURES

Polygenic risk scores (PRSs) for schizophrenia generated for individuals in the ALSPAC cohort using results of the second Psychiatric Genomics Consortium Schizophrenia genome-wide association study as a training set.

MAIN OUTCOMES AND MEASURES

Logistic regression was used to assess associations between the schizophrenia PRS and (1) psychotic experiences (Psychosis-Like Symptom Interview at 12 and 18 years of age), (2) negative symptoms (Community Assessment of Psychic Experiences at 16.5 years of age), (3) depressive disorder (Development and Well-Being Assessment at 15.5 years of age), and (4) anxiety disorder (Development and Well-Being Assessment at 15.5 years of age) in adolescence.

RESULTS

Of the 8230 ALSPAC participants whose genetic data passed quality control checks (51.2% male, 48.8% female), 3676 to 5444 participated in assessments from 12 to 18 years of age. The PRSs created using single-nucleotide polymorphisms with a training-set P ≤ .05 threshold were associated with negative symptoms (odds ratio [OR] per SD increase in PRS, 1.21; 95% CI, 1.08-1.36; R(2) = 0.007) and anxiety disorder (OR per SD increase in PRS, 1.17; 95% CI, 1.06- 1.29; R(2) = 0.005). No evidence was found of an association between schizophrenia PRS and psychotic experiences (OR per SD increase in PRS, 1.08; 95% CI, 0.98-1.19; R(2) = 0.001) or depressive disorder (OR per SD increase in PRS, 1.02; 95% CI, 0.91-1.13; R(2) = 0.00005). Results were mostly consistent across different training-set P value thresholds and using different cutoffs and measures of the psychopathological outcomes.

CONCLUSIONS AND RELEVANCE

This study demonstrates polygenic overlaps between common genetic polymorphisms associated with schizophrenia and negative symptoms and anxiety disorder but not with psychotic experiences or depression. Because the genetic risk for schizophrenia appears to be manifest as anxiety and negative symptoms during adolescence, a greater focus on these phenotypes rather than on psychotic experiences might be required for prediction of transition in at-risk samples.

Phenotypic Association Analyses With Copy Number Variation in Recurrent Depressive Disorder

BACKGROUND

Defining the molecular genomic basis of the likelihood of developing depressive disorder is a considerable challenge. We previously associated rare, exonic deletion copy number variants (CNV) with recurrent depressive disorder (RDD). Sex chromosome abnormalities also have been observed to co-occur with RDD.

METHODS

In this reanalysis of our RDD dataset (N = 3106 cases; 459 screened control samples and 2699 population control samples), we further investigated the role of larger CNVs and chromosomal abnormalities in RDD and performed association analyses with clinical data derived from this dataset.

RESULTS

We found an enrichment of Turner's syndrome among cases of depression compared with the frequency observed in a large population sample (N = 34,910) of live-born infants collected in Denmark (two-sided p = .023, odds ratio = 7.76 [95% confidence interval = 1.79-33.6]), a case of diploid/triploid mosaicism, and several cases of uniparental isodisomy. In contrast to our previous analysis, large deletion CNVs were no more frequent in cases than control samples, although deletion CNVs in cases contained more genes than control samples (two-sided p = .0002).

CONCLUSIONS

After statistical correction for multiple comparisons, our data do not support a substantial role for CNVs in RDD, although (as has been observed in similar samples) occasional cases may harbor large variants with etiological significance. Genetic pleiotropy and sample heterogeneity suggest that very large sample sizes are required to study conclusively the role of genetic variation in mood disorders.

Transcriptomics and the mechanisms of antidepressant efficacy

The mechanisms by which antidepressants have their effects are not clear and the reasons for variability in treatment outcomes are also unknown. However, there is evidence from candidate gene research that indicates gene expression changes may be involved in antidepressant action. In this study, we examined antidepressant-induced alterations in gene expression on a transcriptome-wide scale, exploring associations with treatment response. Blood samples were taken from a subset of depressed patients from the GENDEP study (n=136) before and after eight weeks of treatment with either escitalopram or nortriptyline. Transcriptomic data were obtained from these samples using Illumina HumanHT-12 v4 Expression BeadChip microarrays. When analysing individual genes, we observed that changes in the expression of two genes (MMP28 and KXD1) were associated with better response to nortriptyline. Considering connectivity between genes, we identified modules of genes that were highly coexpressed. In the whole sample, changes in one of the ten identified coexpression modules showed significant correlation with treatment response (cor=0.27, p=0.0029). Using transcriptomic approaches, we have identified gene expression correlates of the therapeutic effects of antidepressants, highlighting possible molecular pathways involved in efficacious antidepressant treatment.

Association between genetic risk scoring for schizophrenia and bipolar disorder with regional subcortical volumes

Previous research has shown coincident abnormal regional brain volume in patients with schizophrenia (SCZ) and bipolar disorder (BD) compared with controls. Whether these abnormalities are genetically driven or explained by secondary effects of the disorder or environmental factors is unknown. We aimed to investigate the association between genetic risk scoring (GRS) for SCZ and BD with volume of brain areas previously shown to be different between these clinical groups and healthy controls. We obtained subcortical brain volume measures and GRS for SCZ and BD from a sample of 274 healthy volunteers (71.4% females, mean age 24.7 (s.d. 6.9)). Volume of the globus pallidus was associated with the shared GRS between SCZ and BD, and also with the independent GRS for each of these disorders. Volume of the amygdala was associated with the non-shared GRS between SCZ and BD, and with the independent GRS for BD. Our results for volume of the globus pallidus support the idea of SCZ and BD sharing a common underlying neurobiological abnormality associated with a common genetic risk for both these disorders. Results for volume of the amygdala, though, would suggest the existence of a distinct mechanism only associated with genetic risk for BD. Finally, the lack of association between genetic risk and volume of most subcortical structures suggests that the volumetric differences reported in patient-control comparisons may not be genetically driven, but a consequence of the disorder or co-occurring environmental factors.

Associations between polygenic risk for schizophrenia and brain function during probabilistic learning in healthy individuals

A substantial proportion of schizophrenia liability can be explained by additive genetic factors. Risk profile scores (RPS) directly index risk using a summated total of common risk variants weighted by their effect. Previous studies suggest that schizophrenia RPS predict alterations to neural networks that support working memory and verbal fluency. In this study, we apply schizophrenia RPS to fMRI data to elucidate the effects of polygenic risk on functional brain networks during a probabilistic‐learning neuroimaging paradigm. The neural networks recruited during this paradigm have previously been shown to be altered to unmedicated schizophrenia patients and relatives of schizophrenia patients, which may reflect genetic susceptibility. We created schizophrenia RPS using summary data from the Psychiatric Genetic Consortium (Schizophrenia Working Group) for 83 healthy individuals and explore associations between schizophrenia RPS and blood oxygen level dependency (BOLD) during periods of choice behavior (switch–stay) and reflection upon choice outcome (reward–punishment). We show that schizophrenia RPS is associated with alterations in the frontal pole (P_{WHOLE‐BRAIN‐CORRECTED} = 0.048) and the ventral striatum (P_{ROI‐CORRECTED} = 0.036), during choice behavior, but not choice outcome. We suggest that the common risk variants that increase susceptibility to schizophrenia can be associated with alterations in the neural circuitry that support the processing of changing reward contingencies. Hum Brain Mapp 37:491–500, 2016. © 2015 Wiley Periodicals, Inc.

Schizophrenia risk variants modulate white matter volume across the psychosis spectrum: evidence from two independent cohorts

Polygenic risk scores, based on risk variants identified in genome-wide-association-studies (GWAS), explain a considerable portion of the heritability for schizophrenia (SZ) and bipolar disorder (BD). However, little is known about the combined effects of these variants, although polygenic neuroimaging has developed into a powerful tool of translational neuroscience. In this study, we used genome wide significant SZ risk variants to test the predictive capacity of the polygenic model and explored potential associations with white matter volume, a key candidate in imaging phenotype for psychotic disorders. By calculating the combined additive schizophrenia risk of seven SNPs (significant hits from a recent schizophrenia GWAS study), we show that increased additive genetic risk for SZ was associated with reduced white matter volume in a group of participants (n = 94) consisting of healthy individuals, SZ first-degree relatives, SZ patients and BD patients. This effect was also seen in a second independent sample of healthy individuals (n = 89). We suggest that a moderate portion of variance (~4%) of white matter volume can be explained by the seven hits from the recent schizophrenia GWAS. These results provide evidence for associations between cumulative genetic risk for schizophrenia and intermediate neuroimaging phenotypes in models of psychosis. Our work contributes to a growing body of literature suggesting that polygenic risk may help to explain white matter alterations associated with familial risk for psychosis.

Schizophrenia genetics: emerging themes for a complex disorder

After two decades of frustration, genetic studies of schizophrenia have entered an era of spectacular success. Advances in genotyping technologies and high throughput sequencing, increasing analytic rigour and collaborative efforts on a global scale have generated a profusion of new findings. The broad conclusions from these studies are threefold: (1) schizophrenia is a highly polygenic disorder with a complex array of contributing risk loci across the allelic frequency spectrum; (2) many psychiatric illnesses share risk genes and alleles, specifically, schizophrenia has substantial overlaps with bipolar disorder, intellectual disability, major depressive disorder and autism spectrum disorders; and (3) some convergent biological themes are emerging from studies of schizophrenia and related disorders. In this commentary, we focus on the very recent findings that have emerged in the past 12 months, and in particular, the areas of convergence that are beginning to emerge from multiple study designs.

Alzheimer's disease risk variant in CLU is associated with neural inefficiency in healthy individuals

INTRODUCTION

Genome-wide association studies identify rs11136000 in the CLU gene, which codes for Apolipoprotein J/Clusterin, as a significant risk variant for Alzheimer's disease (AD). However, the mechanisms by which this variant confers susceptibility remain relatively unknown.

METHODS

Eighty-five healthy Caucasian participants underwent functional magnetic resonance imaging during a working memory (WM) task and were genotyped for CLU rs11136000/APOE loci.

RESULTS

Here we show that young individuals with the CLU rs11136000 risk variant (C) have higher activation levels in memory-related prefrontal and limbic areas during a WM task. We also found subtle reductions in gray matter in the right hippocampal formation in carriers of the risk variant.

DISCUSSION

We suggest that this pattern of multimodal imaging results may reflect incipient structural differences and inefficient functional activation. This study supports accumulating evidence suggesting that genetic risk for AD affects the neural networks associated with memory in healthy individuals.

An inflammatory biomarker as a differential predictor of outcome of depression treatment with escitalopram and nortriptyline

OBJECTIVE

Major depressive disorder has been linked with inflammatory processes, but it is unclear whether individual differences in levels of inflammatory biomarkers could help match patients to treatments that are most likely to be beneficial. The authors tested the hypothesis that C-reactive protein (CRP), a commonly available marker of systemic inflammation, predicts differential response to escitalopram (a serotonin reuptake inhibitor) and nortriptyline (a norepinephrine reuptake inhibitor).

METHOD

The hypothesis was tested in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study, a multicenter open-label randomized clinical trial. CRP was measured with a high-sensitivity method in serum samples from 241 adult men and women with major depressive disorder randomly allocated to 12-week treatment with escitalopram (N=115) or nortriptyline (N=126). The primary outcome measure was the score on the Montgomery-Åsberg Depression Rating Scale (MADRS), administered weekly.

RESULTS

CRP level at baseline differentially predicted treatment outcome with the two antidepressants (CRP-drug interaction: β=3.27, 95% CI=1.65, 4.89). For patients with low levels of CRP (<1 mg/L), improvement on the MADRS score was 3 points higher with escitalopram than with nortriptyline. For patients with higher CRP levels, improvement on the MADRS score was 3 points higher with nortriptyline than with escitalopram. CRP and its interaction with medication explained more than 10% of individual-level variance in treatment outcome.

CONCLUSIONS

An easily accessible peripheral blood biomarker may contribute to improvement in outcomes of major depressive disorder by personalizing treatment choice.

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.

Functional polymorphism in the brain-derived neurotrophic factor gene interacts with stressful life events but not childhood maltreatment in the etiology of depression

BACKGROUND

We test the hypothesis that the functional Val66Met polymorphism of BDNF interacts with recent life events to produce onset of new depressive episodes. We also explore the possibility that the Met allele of this polymorphism interacts with childhood maltreatment to increase the risk of chronic depression.

METHODS

In a risk-enriched combined sample of unrelated women, childhood maltreatment and current life events were measured with the Childhood Experience of Care and Abuse, and Life Events and Difficulties Schedule interviews. Chronic episodes of depression (12 months or longer) during adulthood and onset of a major depressive episode during a 12-month follow-up were established with the Schedules for Clinical Assessment in Neuropsychiatry interview.

RESULTS

Met alleles of BDNF moderated the relationship between recent life events and adult onsets of depression in a significant gene-environment interaction (interaction risk difference 0.216, 95% CI 0.090-0.342; P =.0008). BDNF did not significantly influence the effect of childhood maltreatment on chronic depression in the present sample.

CONCLUSIONS

The Met allele of BDNF increases the risk of a new depressive episode following a severe life event. The BDNF and the serotonin transporter gene length polymorphism (5-HTTLPR) and BDNF may contribute to depression through distinct mechanisms involving interactions with childhood and adulthood adversity respectively, which may, in combination, be responsible for a substantial proportion of depression burden in the general population.

Putative transcriptomic biomarkers in the inflammatory cytokine pathway differentiate major depressive disorder patients from control subjects and bipolar disorder patients

Mood disorders consist of two etiologically related, but distinctly treated illnesses, major depressive disorder (MDD) and bipolar disorder (BPD). These disorders share similarities in their clinical presentation, and thus show high rates of misdiagnosis. Recent research has revealed significant transcriptional differences within the inflammatory cytokine pathway between MDD patients and controls, and between BPD patients and controls, suggesting this pathway may possess important biomarker properties. This exploratory study attempts to identify disorder-specific transcriptional biomarkers within the inflammatory cytokine pathway, which can distinguish between control subjects, MDD patients and BPD patients. This is achieved using RNA extracted from subject blood and applying synthesized complementary DNA to quantitative PCR arrays containing primers for 87 inflammation-related genes. Initially, we use ANOVA to test for transcriptional differences in a 'discovery cohort' (total n = 90) and then we use t-tests to assess the reliability of any identified transcriptional differences in a 'validation cohort' (total n = 35). The two most robust and reliable biomarkers identified across both the discovery and validation cohort were Chemokine (C-C motif) ligand 24 (CCL24) which was consistently transcribed higher amongst MDD patients relative to controls and BPD patients, and C-C chemokine receptor type 6 (CCR6) which was consistently more lowly transcribed amongst MDD patients relative to controls. Results detailed here provide preliminary evidence that transcriptional measures within inflammation-related genes might be useful in aiding clinical diagnostic decision-making processes. Future research should aim to replicate findings detailed in this exploratory study in a larger medication-free sample and examine whether identified biomarkers could be used prospectively to aid clinical diagnosis.

The inflammatory cytokines: molecular biomarkers for major depressive disorder?

Cytokines are pleotropic cell signaling proteins that, in addition to their role as inflammatory mediators, also affect neurotransmitter systems, brain functionality and mood. Here we explore the potential utility of cytokine biomarkers for major depressive disorder. Specifically, we explore how genetic, transcriptomic and proteomic information relating to the cytokines might act as biomarkers, aiding clinical diagnosis and treatment selection processes. We advise future studies to investigate whether cytokine biomarkers might differentiate major depressive disorder patients from other patient groups with overlapping clinical characteristics. Furthermore, we invite future pharmacogenetic studies to investigate whether early antidepressant-induced changes to cytokine mRNA or protein levels precede behavioral changes and act as longer-term predictors of clinical antidepressant response.

Interaction between stress and the BDNF Val66Met polymorphism in depression: a systematic review and meta-analysis

BACKGROUND

Major depression is a disabling psychiatric illness with complex origins. Life stress (childhood adversity and recent stressful events) is a robust risk factor for depression. The relationship between life stress and Val66Met polymorphism in the brain-derived neurotrophic factor (BDNF) gene has received much attention. The aim of the present work was to review and conduct a meta-analysis on the results from published studies examining this interaction.

METHODS

A literature search was conducted using PsychINFO and PubMed databases until 22 November 2013. A total of 22 studies with a pooled total of 14,233 participants met the inclusion criteria, the results of which were combined and a meta-analysis performed using the Liptak-Stouffer z-score method.

RESULTS

The results suggest that the Met allele of BDNF Val66Met significantly moderates the relationship between life stress and depression (P = 0.03). When the studies were stratified by type of environmental stressor, the evidence was stronger for an interaction with stressful life events (P = 0.01) and weaker for interaction of BDNF Val66Met with childhood adversity (P = 0.051).

CONCLUSIONS

The interaction between BDNF and life stress in depression is stronger for stressful life events rather than childhood adversity. Methodological limitations of existing studies include poor measurement of life stress.

Genetic susceptibility for bipolar disorder and response to antidepressants in major depressive disorder

The high heterogeneity of response to antidepressant treatment in major depressive disorder (MDD) makes individual treatment outcomes currently unpredictable. It has been suggested that resistance to antidepressant treatment might be due to undiagnosed bipolar disorder or bipolar spectrum features. Here, we investigate the relationship between genetic susceptibility for bipolar disorder and response to treatment with antidepressants in MDD. Polygenic scores indexing risk for bipolar disorder were derived from the Psychiatric Genomics Consortium Bipolar Disorder whole genome association study. Linear regressions tested the effect of polygenic risk scores for bipolar disorder on proportional reduction in depression severity in two large samples of individuals with MDD, treated with antidepressants, NEWMEDS (n=1,791) and STAR*D (n=1,107). There was no significant association between polygenic scores for bipolar disorder and response to treatment with antidepressants. Our data indicate that molecular measure of genetic susceptibility to bipolar disorder does not aid in understanding non-response to antidepressants.

Whole-exome sequencing identifies a polymorphism in the BMP5 gene associated with SSRI treatment response in major depression

Although antidepressants are widely used in the pharmacotherapy of major depressive disorder (MDD), their efficacy is still insufficient as approximately one-third of the patients do not fully recover even after several treatment trials. Inter-individual genetic differences are thought to contribute to the variability in antidepressant response; however, current findings from pharmacogenetic studies are uncertain or not clearly replicated. Here we report the first application of full exome sequencing for the analysis of pharmacogenomics on antidepressant treatment. After 12 weeks of treatment with the selective serotonin re-uptake inhibitor escitalopram, we selected five clear responders and five clear non-responders for exome sequencing. By comparing the allele counts of previously known single nucleotide polymorphisms and novel polymorphisms we selected 38 markers for further genotyping in two independent patient samples treated with escitalopram (n=116 and n=394). The A allele, carried by approximately 30% of the patients with MDD, of rs41271330 in the bone morphogenetic protein (BMP5) gene showed strong association with worse treatment response in both sample sets (p=0.001), indicating that this is an promising pharmacogenetic marker for prediction of antidepressant therapeutic outcome.

ATP-binding cassette sub-family F member 1 (ABCF1) is identified as a putative therapeutic target of escitalopram in the inflammatory cytokine pathway

The inflammatory cytokine pathway may be a potential therapeutic target for major depressive disorder (MDD). Previous reports suggest that antidepressants have anti-inflammatory properties and can cause a reduction in proinflammatory cytokines. Recent evidence suggests this might be mediated at the level of the transcriptome. The current study investigated the transcription of 86 genes in the inflammatory cytokine pathway both at baseline and after eight weeks of escitalopram treatment in MDD patients who were either clinical responders (n=25) or non-responders (n=21), using a subset of samples in the Genome-Based Therapeutic Drugs for Depression project (GENDEP). Changes in expression between baseline and eight weeks of treatment were assessed using two-tailed t-tests. To establish if any significant expression changes related to clinical response, the magnitude of the relative expression change between baseline and eight weeks of treatment was established and binary logistic regressions were used to compare differences between responders and non-responders. ATP-binding cassette sub-family F member 1 (ABCF1), a translational regulator of the inflammatory cytokine pathway showed a significant increase in expression after escitalopram treatment which was significantly greater in responders compared to non-responders, suggesting that ABCF1 may play a role in mediating antidepressant response.

A mega-analysis of genome-wide association studies for major depressive disorder

Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.