Depression, anxiety and PTSD symptoms before and during the COVID-19 pandemic in the UK.

BACKGROUND: The impact of the coronavirus disease 2019 (COVID-19) pandemic on mental health is still being unravelled. It is important to identify which individuals are at greatest risk of worsening symptoms. This study aimed to examine changes in depression, anxiety and post-traumatic stress disorder (PTSD) symptoms using prospective and retrospective symptom change assessments, and to find and examine the effect of key risk factors. METHOD: Online questionnaires were administered to 34 465 individuals (aged 16 years or above) in April/May 2020 in the UK, recruited from existing cohorts or via social media. Around one-third (n = 12 718) of included participants had prior diagnoses of depression or anxiety and had completed pre-pandemic mental health assessments (between September 2018 and February 2020), allowing prospective investigation of symptom change. RESULTS: Prospective symptom analyses showed small decreases in depression (PHQ-9: -0.43 points) and anxiety [generalised anxiety disorder scale - 7 items (GAD)-7: -0.33 points] and increases in PTSD (PCL-6: 0.22 points). Conversely, retrospective symptom analyses demonstrated significant large increases (PHQ-9: 2.40; GAD-7 = 1.97), with 55% reported worsening mental health since the beginning of the pandemic on a global change rating. Across both prospective and retrospective measures of symptom change, worsening depression, anxiety and PTSD symptoms were associated with prior mental health diagnoses, female gender, young age and unemployed/student status. CONCLUSIONS: We highlight the effect of prior mental health diagnoses on worsening mental health during the pandemic and confirm previously reported sociodemographic risk factors. Discrepancies between prospective and retrospective measures of changes in mental health may be related to recall bias-related underestimation of prior symptom severity.

Evidence for distinct genetic and environmental influences on fear acquisition and extinction.

BACKGROUND: Anxiety disorders are highly prevalent with an early age of onset. Understanding the aetiology of disorder emergence and recovery is important for establishing preventative measures and optimising treatment. Experimental approaches can serve as a useful model for disorder and recovery relevant processes. One such model is fear conditioning. We conducted a remote fear conditioning paradigm in monozygotic and dizygotic twins to determine the degree and extent of overlap between genetic and environmental influences on fear acquisition and extinction. METHODS: In total, 1937 twins aged 22-25 years, including 538 complete pairs from the Twins Early Development Study took part in a fear conditioning experiment delivered remotely via the Fear Learning and Anxiety Response (FLARe) smartphone app. In the fear acquisition phase, participants were exposed to two neutral shape stimuli, one of which was repeatedly paired with a loud aversive noise, while the other was never paired with anything aversive. In the extinction phase, the shapes were repeatedly presented again, this time without the aversive noise. Outcomes were participant ratings of how much they expected the aversive noise to occur when they saw either shape, throughout each phase. RESULTS: Twin analyses indicated a significant contribution of genetic effects to the initial acquisition and consolidation of fear, and the extinction of fear (15, 30 and 15%, respectively) with the remainder of variance due to the non-shared environment. Multivariate analyses revealed that the development of fear and fear extinction show moderate genetic overlap (genetic correlations 0.4-0.5). CONCLUSIONS: Fear acquisition and extinction are heritable, and share some, but not all of the same genetic influences.

Introducing the Fear Learning and Anxiety Response (FLARe) app and web portal for the remote delivery of fear conditioning experiments.

Experimental paradigms measuring key psychological constructs can enhance our understanding of mechanisms underlying human psychological well-being and mental health. Delivering such paradigms remotely affords opportunities to reach larger, more representative samples than is typically possible with in-person research. The efficiency gained from remote delivery makes it easier to test replication of previously established effects in well-powered samples. There are several challenges to the successful development and delivery of remote experimental paradigms, including use of an appropriate delivery platform, identifying feasible outcome measures, and metrics of participant compliance. In this paper, we present FLARe (Fear Learning and Anxiety Response), open-source software in the form of a smartphone app and web portal for the creation and delivery of remote fear conditioning experiments. We describe the benefits and challenges associated with the creation of a remote delivery platform for fear conditioning, before presenting in detail the resultant software suite, and one instance of deploying this using the FLARe Research infrastructure. We provide examples of the application of FLARe to several research questions which illustrate the benefits of the remote approach to experiment delivery. The FLARe smartphone app and web portal are available for use by other researchers and have been designed to be user-friendly and intuitive. We hope that FLARe will be a useful tool for those interested in conducting well-powered fear conditioning studies to inform our understanding of the development and treatment of anxiety disorders.

Early weight gain trajectories in first episode anorexia: predictors of outcome for emerging adults in outpatient treatment.

BACKGROUND: Early response to treatment has been shown to be a predictor of later clinical outcomes in eating disorders (EDs). Specifically, early weight gain trajectories in anorexia nervosa (AN) have been shown to predict higher rates of later remission in inpatient treatment. However, no study has, as of yet, examined this phenomenon within outpatient treatment of first episode cases of AN or in emerging adults. METHODS: One hundred seven patients with AN, all between the ages of 16 and 25 and with an illness duration of < 3 years, received treatment via the first episode rapid early intervention in eating disorders (FREED) service pathway. Weight was recorded routinely across early treatment sessions and recovery outcomes (BMI > 18.5 kg/m2 and eating psychopathology) were assessed up to 1 year later. Early weight gain across the first 12 treatment sessions was investigated using latent growth mixture modelling to determine distinct classes of change. Follow-up clinical outcomes and remission rates were compared between classes, and individual and clinical characteristics at baseline (treatment start) were tested as potential predictors. RESULTS: Four classes of early treatment trajectory were identified. Three of these classes (n = 95), though differing in their early change trajectories, showed substantial improvement in clinical outcomes at final follow-up. One smaller class (n = 12), characterised by a 'higher' start BMI (> 17) and no early weight gain, showed negligible improvement 1 year later. Of the three treatment responding groups, levels of purging, depression, and patient reported carer expressed emotion (in the form of high expectations and low tolerance of the patient) determined class membership, although these findings were not significant after correcting for multiple testing. A higher BMI at treatment start was not sufficient to predict optimal clinical outcomes. CONCLUSION: First episode cases of AN treated via FREED fit into four distinct early response trajectory classes. These may represent subtypes of first episode AN patients. Three of these four trajectories included patients with substantial improvements 1 year later. For those in the non-response trajectory class, treatment adjustments or augmentations could be considered earlier, i.e., at treatment session 12.

A key feature of anorexia nervosa (AN) is an unhealthily low body weight. Previous studies show that more weight gained early in inpatient treatment leads to better outcomes. This study tried to see if this was also true for outpatients receiving treatment for the first time. All participants were emerging adults between the ages of 16 and 25 who had been ill for less than 3 years. Weight was recorded across the first 12 weekly treatment sessions. Statistics showed that the patients fit roughly into four different groups in early treatment, each with different starting weights and rates of weight gain in the first 12 treatment sessions. The group a patient belonged to could sometimes be predicted by vomiting behaviours, level of depression, and patients' perception of parental tolerance and expectations at the start of treatment. Out of the four groups, three did relatively well 1 year later, but one small group of patients did not. This small group had a higher starting weight than many of the other groups but did not gain any weight across the first 12 sessions. These patients could benefit from a change or increase in the amount or intensity of treatment after the first 12 treatment sessions.

Familial Influences on Neuroticism and Education in the UK Biobank.

Genome-wide studies often exclude family members, even though they are a valuable source of information. We identified parent-offspring pairs, siblings and couples in the UK Biobank and implemented a family-based DNA-derived heritability method to capture additional genetic effects and multiple sources of environmental influence on neuroticism and years of education. Compared to estimates from unrelated individuals, total heritability increased from 10 to 27% and from 17 to 56% for neuroticism and education respectively by including family-based genetic effects. We detected no family environmental influences on neuroticism. The couple similarity variance component explained 35% of the variation in years of education, probably reflecting assortative mating. Overall, our genetic and environmental estimates closely replicate previous findings from an independent sample. However, more research is required to dissect contributions to the additional heritability by rare and structural genetic effects, assortative mating, and residual environmental confounding. The latter is especially relevant for years of education, a highly socially contingent variable, for which our heritability estimate is at the upper end of twin estimates in the literature. Family-based genetic effects could be harnessed to improve polygenic prediction.

Validating the use of a smartphone app for remote administration of a fear conditioning paradigm.

Fear conditioning models key processes related to the development, maintenance and treatment of anxiety disorders and is associated with group differences in anxiety. However, laboratory administration of tasks is time and cost intensive, precluding assessment in large samplesnecessary for the analysis of individual differences. This study introduces a newly developed smartphone app that delivers a fear conditioning paradigm remotely using a loud human scream as an aversive stimulus. Three groups of participants (total n = 152) took part in three studies involving a differential fear conditioning experiment to assess the reliability and validity of a smartphone administered fear conditioning paradigm. This comprised of fear acquisition, generalisation, extinction, and renewal phases during which online US-expectancy ratings were collected during every trial with evaluative ratings of negative affect at three time points. We show that smartphone app delivery of a fear conditioning paradigm results in a pattern of fear learning comparable to traditional laboratory delivery and is able to detect individual differences in performance that show comparable associations with anxiety to the prior group differences literature.

A genome-wide association study for extremely high intelligence.

We used a case-control genome-wide association (GWA) design with cases consisting of 1238 individuals from the top 0.0003 (~170 mean IQ) of the population distribution of intelligence and 8172 unselected population-based controls. The single-nucleotide polymorphism heritability for the extreme IQ trait was 0.33 (0.02), which is the highest so far for a cognitive phenotype, and significant genome-wide genetic correlations of 0.78 were observed with educational attainment and 0.86 with population IQ. Three variants in locus ADAM12 achieved genome-wide significance, although they did not replicate with published GWA analyses of normal-range IQ or educational attainment. A genome-wide polygenic score constructed from the GWA results accounted for 1.6% of the variance of intelligence in the normal range in an unselected sample of 3414 individuals, which is comparable to the variance explained by GWA studies of intelligence with substantially larger sample sizes. The gene family plexins, members of which are mutated in several monogenic neurodevelopmental disorders, was significantly enriched for associations with high IQ. This study shows the utility of extreme trait selection for genetic study of intelligence and suggests that extremely high intelligence is continuous genetically with normal-range intelligence in the population.

Multi-polygenic score approach to trait prediction.

A primary goal of polygenic scores, which aggregate the effects of thousands of trait-associated DNA variants discovered in genome-wide association studies (GWASs), is to estimate individual-specific genetic propensities and predict outcomes. This is typically achieved using a single polygenic score, but here we use a multi-polygenic score (MPS) approach to increase predictive power by exploiting the joint power of multiple discovery GWASs, without assumptions about the relationships among predictors. We used summary statistics of 81 well-powered GWASs of cognitive, medical and anthropometric traits to predict three core developmental outcomes in our independent target sample: educational achievement, body mass index (BMI) and general cognitive ability. We used regularized regression with repeated cross-validation to select from and estimate contributions of 81 polygenic scores in a UK representative sample of 6710 unrelated adolescents. The MPS approach predicted 10.9% variance in educational achievement, 4.8% in general cognitive ability and 5.4% in BMI in an independent test set, predicting 1.1%, 1.1%, and 1.6% more variance than the best single-score predictions. As other relevant GWA analyses are reported, they can be incorporated in MPS models to maximize phenotype prediction. The MPS approach should be useful in research with modest sample sizes to investigate developmental, multivariate and gene-environment interplay issues and, eventually, in clinical settings to predict and prevent problems using personalized interventions.

Interaction between childhood maltreatment on immunogenetic risk in depression: Discovery and replication in clinical case-control samples.

Major depressive disorder (MDD) is a prevalent disorder with moderate heritability. Both MDD and interpersonal adversity, including childhood maltreatment, have been consistently associated with elevated inflammatory markers. We investigated interaction between exposure to childhood maltreatment and extensive genetic variation within the inflammation pathway (CRP, IL1b, IL-6, IL11, TNF, TNFR1, and TNFR2) in relation to depression diagnosis. The discovery RADIANT sample included 262 cases with recurrent DSM-IV/ICD-10 MDD, and 288 unaffected controls. The replication Münster cohort included 277 cases with DSM-IV MDD, and 316 unaffected controls. We identified twenty-five single nucleotide polymorphisms (SNPs) following multiple testing correction that interacted with childhood maltreatment to predict depression in the discovery cohort. Seven SNPs representing independent signals (rs1818879, rs1041981, rs4149576, rs616645, rs17882988, rs1061622, and rs3093077) were taken forward for replication. Meta-analyses of the two samples presented evidence for interaction with rs1818879 (IL6) (RD=0.059, SE=0.016, p<0.001), with the replication Münster sample approaching statistical significance in analyses restricted to recurrent MDD and controls following correction for multiple testing (q=0.066). The CRP locus (rs3093077) showed a similar level of evidence for interaction in the meta-analysis (RD=0.092, SE=0.029, p=0.002), but less compelling evidence in the replication sample alone (recurrent MDD q=0.198; all MDD q=0.126). Here we present evidence suggestive of interaction with childhood maltreatment for novel loci in IL-6 (rs1818879) and CRP (rs3093077), increasing risk of depression. Replication is needed by independent groups, targeting these specific variants and interaction with childhood maltreatment on depression risk.

New insights into the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation.

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (P=1.80e-08, ITGA9 (integrin α9)) and rs76191705 (P=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P=0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role.

Drug enrichment and discovery from schizophrenia genome-wide association results: an analysis and visualisation approach.

Using successful genome-wide association results in psychiatry for drug repurposing is an ongoing challenge. Databases collecting drug targets and gene annotations are growing and can be harnessed to shed a new light on psychiatric disorders. We used genome-wide association study (GWAS) summary statistics from the Psychiatric Genetics Consortium (PGC) Schizophrenia working group to build a drug repositioning model for schizophrenia. As sample size increases, schizophrenia GWAS results show increasing enrichment for known antipsychotic drugs, selective calcium channel blockers, and antiepileptics. Each of these therapeutical classes targets different gene subnetworks. We identify 123 Bonferroni-significant druggable genes outside the MHC, and 128 FDR-significant biological pathways related to neurons, synapses, genic intolerance, membrane transport, epilepsy, and mental disorders. These results suggest that, in schizophrenia, current well-powered GWAS results can reliably detect known schizophrenia drugs and thus may hold considerable potential for the identification of new therapeutic leads. Moreover, antiepileptics and calcium channel blockers may provide repurposing opportunities. This study also reveals significant pathways in schizophrenia that were not identified previously, and provides a workflow for pathway analysis and drug repurposing using GWAS results.

Widespread covariation of early environmental exposures and trait-associated polygenic variation.

Although gene-environment correlation is recognized and investigated by family studies and recently by SNP-heritability studies, the possibility that genetic effects on traits capture environmental risk factors or protective factors has been neglected by polygenic prediction models. We investigated covariation between trait-associated polygenic variation identified by genome-wide association studies (GWASs) and specific environmental exposures, controlling for overall genetic relatedness using a genomic relatedness matrix restricted maximum-likelihood model. In a UK-representative sample (n = 6,710), we find widespread covariation between offspring trait-associated polygenic variation and parental behavior and characteristics relevant to children's developmental outcomes-independently of population stratification. For instance, offspring genetic risk for schizophrenia was associated with paternal age (R2 = 0.002; P = 1e-04), and offspring education-associated variation was associated with variance in breastfeeding (R2 = 0.021; P = 7e-30), maternal smoking during pregnancy (R2 = 0.008; P = 5e-13), parental smacking (R2 = 0.01; P = 4e-15), household income (R2 = 0.032; P = 1e-22), watching television (R2 = 0.034; P = 5e-47), and maternal education (R2 = 0.065; P = 3e-96). Education-associated polygenic variation also captured covariation between environmental exposures and children's inattention/hyperactivity, conduct problems, and educational achievement. The finding that genetic variation identified by trait GWASs partially captures environmental risk factors or protective factors has direct implications for risk prediction models and the interpretation of GWAS findings.

Genome-wide expression and response to exposure-based psychological therapy for anxiety disorders.

Exposure-based psychological treatments for anxiety have high efficacy. However, a substantial proportion of patients do not respond to therapy. Research examining the potential biological underpinnings of therapy response is still in its infancy, and most studies have focussed on candidate genes. To our knowledge, this study represents the first investigation of genome-wide expression profiles with respect to treatment outcome. Participants (n=102) with panic disorder or specific phobia received exposure-based cognitive behavioural therapy. Treatment outcome was defined as percentage reduction from baseline in clinician-rated severity of their primary anxiety diagnosis at post treatment and 6 month follow-up. Gene expression was determined from whole blood samples at three time points using the Illumina HT-12v4 BeadChip microarray. Linear regression models tested the association between treatment outcome and changes in gene expression from pre-treatment to post treatment, and pre-treatment to follow-up. Network analysis was conducted using weighted gene co-expression network analysis, and change in the detected modules from pre-treatment to post treatment and follow-up was tested for association with treatment outcome. No changes in gene expression were significantly associated with treatment outcomes when correcting for multiple testing (q<0.05), although a small number of genes showed a suggestive association with treatment outcome (q<0.5, n=20). Network analysis showed no association between treatment outcome and change in gene expression for any module. We report suggestive evidence for the role of a small number of genes in treatment outcome. Although preliminary, these findings contribute to a growing body of research suggesting that response to psychological therapies may be associated with changes at a biological level.

Genetic effects influencing risk for major depressive disorder in China and Europe.

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

Exome chip analyses in adult attention deficit hyperactivity disorder.

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable childhood-onset neuropsychiatric condition, often persisting into adulthood. The genetic architecture of ADHD, particularly in adults, is largely unknown. We performed an exome-wide scan of adult ADHD using the Illumina Human Exome Bead Chip, which interrogates over 250 000 common and rare variants. Participants were recruited by the International Multicenter persistent ADHD CollaboraTion (IMpACT). Statistical analyses were divided into 3 steps: (1) gene-level analysis of rare variants (minor allele frequency (MAF)<1%); (2) single marker association tests of common variants (MAF⩾1%), with replication of the top signals; and (3) pathway analyses. In total, 9365 individuals (1846 cases and 7519 controls) were examined. Replication of the most associated common variants was attempted in 9847 individuals (2077 cases and 7770 controls) using fixed-effects inverse variance meta-analysis. With a Bonferroni-corrected significance level of 1.82E-06, our analyses of rare coding variants revealed four study-wide significant loci: 6q22.1 locus (P=4.46E-08), where NT5DC1 and COL10A1 reside; the SEC23IP locus (P=6.47E-07); the PSD locus (P=7.58E-08) and ZCCHC4 locus (P=1.79E-06). No genome-wide significant association was observed among the common variants. The strongest signal was noted at rs9325032 in PPP2R2B (odds ratio=0.81, P=1.61E-05). Taken together, our data add to the growing evidence of general signal transduction molecules (NT5DC1, PSD, SEC23IP and ZCCHC4) having an important role in the etiology of ADHD. Although the biological implications of these findings need to be further explored, they highlight the possible role of cellular communication as a potential core component in the development of both adult and childhood forms of ADHD.

Blood metabolite markers of neocortical amyloid-ß burden: discovery and enrichment using candidate proteins.

We believe this is the first study to investigate associations between blood metabolites and neocortical amyloid burden (NAB) in the search for a blood-based biomarker for Alzheimer's disease (AD). Further, we present the first multi-modal analysis of blood markers in this field. We used blood plasma samples from 91 subjects enrolled in the University of California, San Francisco Alzheimer's Disease Research Centre. Non-targeted metabolomic analysis was used to look for associations with NAB using both single and multiple metabolic feature models. Five metabolic features identified subjects with high NAB, with 72% accuracy. We were able to putatively identify four metabolites from this panel and improve the model further by adding fibrinogen gamma chain protein measures (accuracy=79%). One of the five metabolic features was studied in the Alzheimer's Disease Neuroimaging Initiative cohort, but results were inconclusive. If replicated in larger, independent studies, these metabolic features and proteins could form the basis of a blood test with potential for enrichment of amyloid pathology in anti-amyloid trials.

Phenome-wide analysis of genome-wide polygenic scores.

Genome-wide polygenic scores (GPS), which aggregate the effects of thousands of DNA variants from genome-wide association studies (GWAS), have the potential to make genetic predictions for individuals. We conducted a systematic investigation of associations between GPS and many behavioral traits, the behavioral phenome. For 3152 unrelated 16-year-old individuals representative of the United Kingdom, we created 13 GPS from the largest GWAS for psychiatric disorders (for example, schizophrenia, depression and dementia) and cognitive traits (for example, intelligence, educational attainment and intracranial volume). The behavioral phenome included 50 traits from the domains of psychopathology, personality, cognitive abilities and educational achievement. We examined phenome-wide profiles of associations for the entire distribution of each GPS and for the extremes of the GPS distributions. The cognitive GPS yielded stronger predictive power than the psychiatric GPS in our UK-representative sample of adolescents. For example, education GPS explained variation in adolescents' behavior problems (~0.6%) and in educational achievement (~2%) but psychiatric GPS were associated with neither. Despite the modest effect sizes of current GPS, quantile analyses illustrate the ability to stratify individuals by GPS and opportunities for research. For example, the highest and lowest septiles for the education GPS yielded a 0.5 s.d. difference in mean math grade and a 0.25 s.d. difference in mean behavior problems. We discuss the usefulness and limitations of GPS based on adult GWAS to predict genetic propensities earlier in development.

Polygenic interactions with environmental adversity in the aetiology of major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene-environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD. METHOD: The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them. RESULTS: PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10(-6)). SLEs and CT were also associated with MDD status (p = 2.19 × 10(-4) and p = 5.12 × 10(-20), respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples. CONCLUSIONS: CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene-environment interactions in complex traits.

Convergent evidences from human and animal studies implicate angiotensin I-converting enzyme activity in cognitive performance in schizophrenia.

In schizophrenia (SCZ), higher angiotensin I-converting enzyme (ACE) levels have been reported in patient's blood and cerebrospinal fluid (CSF). Hereby, we propose to explore whether the ACE activity levels are associated to cognitive performance in SCZ. Seventy-two patients with SCZ or schizoaffective disorder diagnosis, and 69 healthy controls (HCs) underwent a cognitive battery with parallel collection of peripheral blood samples to measure ACE activity. Significant higher ACE activity levels were confirmed in the plasma of SCZ patients compared with HCs (Student's t=-5.216; P<0.001). ACE activity significantly correlated to Hopkins delayed recall measures (r=-0.247; P=0.004) and Hopkins total (r=-0.214; P=0.012). Subjects grouped as high ACE activity (above average) had worse performance compared with low ACE activity level group for Hopkins delayed recall measure, even after correction for clinical condition, age, gender and years of education (P=0.029). The adjusted R squared for this final model was 0.343. This result was evident only comparing extreme groups for ACE activity, when splitting the sample in three groups with similar number of subjects. To clarify this finding, we performed an evaluation of the cognitive performance of transgenic mice with three copies of ACE gene in novel object recognition (NOR) test, which showed that such animals presented impairment in NOR (P<0.05) compared with two copies of wild-type animals. The results observed in SCZ patients and animal model suggest both the association of ACE to cognitive deficits in SCZ. This finding may support the evaluation of novel treatment protocols and/or of innovative drugs for specific intervention of cognitive deficits in SCZ envisioning concomitant ACE activity and behavior evaluations.

Plasma protein biomarkers of Alzheimer's disease endophenotypes in asymptomatic older twins: early cognitive decline and regional brain volumes.

There is great interest in blood-based markers of Alzheimer's disease (AD), especially in its pre-symptomatic stages. Therefore, we aimed to identify plasma proteins whose levels associate with potential markers of pre-symptomatic AD. We also aimed to characterise confounding by genetics and the effect of genetics on blood proteins in general. Panel-based proteomics was performed using SOMAscan on plasma samples from TwinsUK subjects who are asymptomatic for AD, measuring the level of 1129 proteins. Protein levels were compared with 10-year change in CANTAB-paired associates learning (PAL; n = 195), and regional brain volumes (n = 34). Replication of proteins associated with regional brain volumes was performed in 254 individuals from the AddNeuroMed cohort. Across all the proteins measured, genetic factors were found to explain ~26% of the variability in blood protein levels on average. The plasma level of the mitogen-activated protein kinase (MAPK) MAPKAPK5 protein was found to positively associate with the 10-year change in CANTAB-PAL in both the individual and twin difference context. The plasma level of protein MAP2K4 was found to suggestively associate negatively (Q < 0.1) with the volume of the left entorhinal cortex. Future studies will be needed to assess the specificity of MAPKAPK5 and MAP2K4 to eventual conversion to AD.