Showing papers by "Rudolf Uher published in 2019"

Brain Age in Early Stages of Bipolar Disorders or Schizophrenia.

Abstract: Background The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the biological age of the brain from structural magnetic resonance imaging scans (MRI). The discrepancy between brain and chronological age could contribute to early detection and differentiation of BD and schizophrenia. Methods We estimated brain age in 2 studies focusing on early stages of schizophrenia or BD. In the first study, we recruited 43 participants with first episode of schizophrenia-spectrum disorders (FES) and 43 controls. In the second study, we included 96 offspring of bipolar parents (48 unaffected, 48 affected) and 60 controls. We used relevance vector regression trained on an independent sample of 504 controls to estimate the brain age of study participants from structural MRI. We calculated the brain-age gap estimate (BrainAGE) score by subtracting the chronological age from the brain age. Results Participants with FES had higher BrainAGE scores than controls (F(1, 83) = 8.79, corrected P = .008, Cohen's d = 0.64). Their brain age was on average 2.64 ± 4.15 years greater than their chronological age (matched t(42) = 4.36, P < .001). In contrast, participants at risk or in the early stages of BD showed comparable BrainAGE scores to controls (F(2,149) = 1.04, corrected P = .70, η2 = 0.01) and comparable brain and chronological age. Conclusions Early stages of schizophrenia, but not early stages of BD, were associated with advanced BrainAGE scores. Participants with FES showed neurostructural alterations, which made their brains appear 2.64 years older than their chronological age. BrainAGE scores could aid in early differential diagnosis between BD and schizophrenia.

Treatment response classes in major depressive disorder identified by model-based clustering and validated by clinical prediction models.

Abstract: The identification of generalizable treatment response classes (TRC[s]) in major depressive disorder (MDD) would facilitate comparisons across studies and the development of treatment prediction algorithms. Here, we investigated whether such stable TRCs can be identified and predicted by clinical baseline items. We analyzed data from an observational MDD cohort (Munich Antidepressant Response Signature [MARS] study, N = 1017), treated individually by psychopharmacological and psychotherapeutic means, and a multicenter, partially randomized clinical/pharmacogenomic study (Genome-based Therapeutic Drugs for Depression [GENDEP], N = 809). Symptoms were evaluated up to week 16 (or discharge) in MARS and week 12 in GENDEP. Clustering was performed on 809 MARS patients (discovery sample) using a mixed model with the integrated completed likelihood criterion for the assessment of cluster stability, and validated through a distinct MARS validation sample and GENDEP. A random forest algorithm was used to identify prediction patterns based on 50 clinical baseline items. From the clustering of the MARS discovery sample, seven TRCs emerged ranging from fast and complete response (average 4.9 weeks until discharge, 94% remitted patients) to slow and incomplete response (10% remitted patients at week 16). These proved stable representations of treatment response dynamics in both the MARS and the GENDEP validation sample. TRCs were strongly associated with established response markers, particularly the rate of remitted patients at discharge. TRCs were predictable from clinical items, particularly personality items, life events, episode duration, and specific psychopathological features. Prediction accuracy improved significantly when cluster-derived slopes were modelled instead of individual slopes. In conclusion, model-based clustering identified distinct and clinically meaningful treatment response classes in MDD that proved robust with regard to capturing response profiles of differently designed studies. Response classes were predictable from clinical baseline characteristics. Conceptually, model-based clustering is translatable to any outcome measure and could advance the large-scale integration of studies on treatment efficacy or the neurobiology of treatment response.

Offspring of parents with schizophrenia, bipolar disorder, and depression: a review of familial high-risk and molecular genetics studies.

Abstract: Offspring of parents with severe mental illness, including schizophrenia, bipolar disorder, and major depressive disorder, have a one-in-three risk of developing severe mental illness themselves. Over the last 60 years, three waves of familial high-risk studies examined the development of severe mental illness in offspring of affected parents. The first two waves established familial nature of schizophrenia, and demonstrated early impairment in offspring of affected parents. The most recent wave has added a focus on mood disorders and examined the transdiagnostic nature of familial risk. A synthesis of current knowledge on individuals at familial risk points to psychopathology, neurocognitive, neuroanatomical, and environmental factors involved in the familial transmission of severe mental illness. Although family history remains the single strongest predictor of illness, molecular genetic tools are becoming increasingly informative. The next decade may see family history and molecular genetics complementing each other to facilitate a transdiagnostic approach to early risk identification and prevention.

Psychosis polyrisk score (pps) for the detection of individuals at-risk and the prediction of their outcomes

Abstract: Primary prevention in individuals at Clinical High Risk for psychosis (CHR-P) can ameliorate the course of psychotic disorders. Further advancements of knowledge have been slowed by the standstill of the field, which is mostly attributed to its epidemiological weakness. The latter, in turn, underlies the limited identification power of at-risk individuals and the modest ability of CHR-P interviews to rule-in a state of risk for psychosis. In the first part, this perspective review discusses these limitations and traces a new approach to overcome them. Theoretical concepts to support a Psychosis Polyrisk Score (PPS) integrating genetic and non-genetic risk and protective factors for psychosis are presented. The PPS hinges on recent findings indicating that risk enrichment in CHR-P samples is accounted for by the accumulation of non-genetic factors such as: parental and sociodemographic risk factors, perinatal risk factors, later risk factors and antecedents. In the second part of this perspective review we present a prototype of a PPS encompassing core predictors beyond genetics. The PPS prototype may be piloted in the next generation of CHR-P research and combined with genetic information to refine the detection of individuals at-risk of psychosis and the prediction of their outcomes, and ultimately advance clinical research in this field.

Brain age in bipolar disorders: Effects of lithium treatment:

Abstract: Objective:Bipolar disorders increase the risk of dementia and show biological and brain alterations, which resemble accelerated aging. Lithium may counter some of these processes and lower the risk...

Cognitive Performance in First-Degree Relatives of Individuals With vs Without Major Depressive Disorder: A Meta-analysis.

Abstract: Importance Findings of cognitive impairment in major depressive disorder (MDD), including remitted MDD, raise the question whether impaired cognition is part of preexisting vulnerability rather than a consequence of MDD or its treatment. To our knowledge, no meta-analyses have been published on cognitive impairment in first-degree relatives of individuals with MDD. Objective To compare cognitive performance between individuals with and without family history of MDD. Data Sources Medline/PubMed, PsycINFO, and Embase using combinations of search terms for depression, first-degree relatives, and cognition from January 1, 1980, to July 15, 2018. Study Selection Original articles that reported data on cognition in first-degree relatives of individuals with MDD compared with controls with no family history of major mental illness. Data Extraction and Synthesis Means and SDs were extracted, and standardized mean differences (SMD) between relatives and controls were calculated for each measure of cognitive performance. The relative-control differences in overall cognition and in specific cognitive domains were synthesized in random-effects meta-analyses with robust variance estimation that allows including multiple correlated measures of cognition within each study. Heterogeneity was quantified with τ2. Publication bias was assessed with funnel plots and Egger intercept. Main Outcomes and Measures Performance on cognitive tests. Results Across 284 measures of cognition in 54 nonoverlapping samples including 3246 relatives of people with MDD (mean age 15.38 years, 57.68% females) and 5222 controls (mean age 14.70 years, 55.93% females), relatives of people with MDD performed worse than controls across all measures of cognition (SMD = -0.19; 95% CI, -0.27 to -0.11; P < .001). Domain-specific meta-analyses showed similar size of relative-control difference in most domains of cognition, including Full-Scale IQ (SMD = -0.19), verbal intelligence (SMD = -0.29), perceptual intelligence (SMD = -0.23), memory (SMD = -0.20), academic performance (SMD = -0.40), and language (SMD = -0.29). Study characteristics were not significantly associated with observed between-group differences. There was no evidence of publication bias. Conclusions and Relevance A general impairment in cognition is a feature of familial disposition for MDD. Cognition may contribute to early identification of risk for depression and may be examined as potential target for early intervention.

Genome-wide association study of treatment-resistance in depression and meta-analysis of three independent samples.

Abstract: BackgroundTreatment-resistant depression (TRD) is the most problematic outcome of depression in terms of functional impairment, suicidal thoughts and decline in physical health.AimsTo investigate the genetic predictors of TRD using a genome-wide approach to contribute to the development of precision medicine.MethodA sample recruited by the European Group for the Study of Resistant Depression (GSRD) including 1148 patients with major depressive disorder (MDD) was characterised for the occurrence of TRD (lack of response to at least two adequate antidepressant treatments) and genotyped using the Infinium PsychArray. Three clinically relevant patient groups were considered: TRD, responders and non-responders to the first antidepressant trial, thus outcomes were based on comparisons of these groups. Genetic analyses were performed at the variant, gene and gene-set (i.e. functionally related genes) level. Additive regression models of the outcomes and relevant covariates were used in the GSRD participants and in a fixed-effect meta-analysis performed between GSRD, STAR*D (n = 1316) and GENDEP (n = 761) participants.ResultsNo individual polymorphism or gene was associated with TRD, although some suggestive signals showed enrichment in cytoskeleton regulation, transcription modulation and calcium signalling. Two gene sets (GO:0043949 and GO:0000183) were associated with TRD versus response and TRD versus response and non-response to the first treatment in the GSRD participants and in the meta-analysis, respectively (corrected P = 0.030 and P = 0.027).ConclusionsThe identified gene sets are involved in cyclic adenosine monophosphate mediated signal and chromatin silencing, two processes previously implicated in antidepressant action. They represent possible biomarkers to implement personalised antidepressant treatments and targets for new antidepressants.Declaration of interestD.S. has received grant/research support from GlaxoSmithKline and Lundbeck; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen and Lundbeck. S.M. has been a consultant or served on advisory boards for: AstraZeneca, Bristol-Myers Squibb, Forest, Johnson & Johnson, Leo, Lundbeck, Medelink, Neurim, Pierre Fabre, Richter. S.K. has received grant/research support from Eli Lilly, Lundbeck, Bristol-Myers Squibb, GlaxoSmithKline, Organon, Sepracor and Servier; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, GlaxoSmithKline, Eli Lilly, Lundbeck, Pfizer, Organon, Schwabe, Sepracor, Servier, Janssen and Novartis; and has served on speakers' bureaus for AstraZeneca, Eli Lily, Lundbeck, Schwabe, Sepracor, Servier, Pierre Fabre, Janssen and Neuraxpharm. J.Z. has received grant/research support from Lundbeck, Servier, Brainsway and Pfizer, has served as a consultant or on advisory boards for Servier, Pfizer, Abbott, Lilly, Actelion, AstraZeneca and Roche and has served on speakers' bureaus for Lundbeck, Roch, Lilly, Servier, Pfizer and Abbott. J.M. is a member of the Board of the Lundbeck International Neuroscience Foundation and of Advisory Board of Servier. A.S. is or has been consultant/speaker for: Abbott, AbbVie, Angelini, Astra Zeneca, Clinical Data, Boehringer, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Innovapharma, Italfarmaco, Janssen, Lundbeck, Naurex, Pfizer, Polifarma, Sanofi and Servier. C.M.L. receives research support from RGA UK Services Limited.

Integrated genome-wide methylation and expression analyses reveal functional predictors of response to antidepressants.

Abstract: Major depressive disorder (MDD) is primarily treated with antidepressants, yet many patients fail to respond adequately, and identifying antidepressant response biomarkers is thus of clinical significance. Some hypothesis-driven investigations of epigenetic markers for treatment response have been previously made, but genome-wide approaches remain unexplored. Healthy participants (n = 112) and MDD patients (n = 211) between 18–60 years old were recruited for an 8-week trial of escitalopram treatment. Responders and non-responders were identified using differential Montgomery-Asberg Depression Rating Scale scores before and after treatment. Genome-wide DNA methylation and gene expression analyses were assessed using the Infinium MethylationEPIC Beadchip and HumanHT-12 v4 Expression Beadchip, respectively, on pre-treatment peripheral blood DNA and RNA samples. Differentially methylated positions (DMPs) located in regions of differentially expressed genes between responders (n = 82) and non-responders (n = 95) were identified, and technically validated using a targeted sequencing approach. Three DMPs located in the genes CHN2 (cg23687322, p = 0.00043 and cg06926818, p = 0.0014) and JAK2 (cg08339825, p = 0.00021) were the most significantly associated with mRNA expression changes and subsequently validated. Replication was then conducted with non-responders (n = 76) and responders (n = 71) in an external cohort that underwent a similar antidepressant trial. One CHN2 site (cg06926818; p = 0.03) was successfully replicated. Our findings indicate that differential methylation at CpG sites upstream of the CHN2 and JAK2 TSS regions are possible peripheral predictors of antidepressant treatment response. Future studies can provide further insight on robustness of our candidate biomarkers, and greater characterization of functional components.

Early change in reward and punishment sensitivity as a predictor of response to antidepressant treatment for major depressive disorder: a CAN-BIND-1 report.

Abstract: BACKGROUND In an effort to optimize patient outcomes, considerable attention is being devoted to identifying patient characteristics associated with major depressive disorder (MDD) and its responsiveness to treatment In the current study, we extend this work by evaluating whether early change in these sensitivities is associated with response to antidepressant treatment for MDD METHODS Participants included 210 patients with MDD who were treated with 8 weeks of escitalopram and 112 healthy comparison participants Of the original 210 patients, 90 non-responders received adjunctive aripiprazole for an additional 8 weeks Symptoms of depression and anhedonia were assessed at the beginning of treatment and 8 weeks later in both samples Reward and punishment sensitivity were assessed using the BIS/BAS scales measured at the initiation of treatment and 2 weeks later RESULTS Individuals with MDD exhibited higher punishment sensitivity and lower reward sensitivity compared with healthy comparison participants Change in reward sensitivity during the first 2 weeks of treatment was associated with improved depressive symptoms and anhedonia following 8 weeks of treatment with escitalopram Similarly, improvement in reward responsiveness during the first 2 weeks of adjunctive therapy with aripiprazole was associated with fewer symptoms of depression at post-treatment CONCLUSIONS Findings highlight the predictive utility of early change in reward sensitivity during antidepressant treatment for major depression In a clinical setting, a lack of change in early reward processing may signal a need to modify a patient's treatment plan with alternative or augmented treatment approaches

Larger right inferior frontal gyrus volume and surface area in participants at genetic risk for bipolar disorders

Abstract: Background Larger grey matter volume of the inferior frontal gyrus (IFG) is among the most replicated biomarkers of genetic risk for bipolar disorders (BD). However, the IFG is a heterogeneous prefrontal region, and volumetric findings can be attributable to changes in cortical thickness (CT), surface area (SA) or gyrification. Here, we investigated the morphometry of IFG in participants at genetic risk for BD. Methods We quantified the IFG cortical grey matter volume in 29 affected, 32 unaffected relatives of BD probands, and 42 controls. We then examined SA, CT, and cortical folding in subregions of the IFG. Results We found volumetric group differences in the right IFG, with the largest volumes in unaffected high-risk and smallest in control participants (F2,192 = 3.07, p = 0.01). The volume alterations were localized to the pars triangularis of the IFG (F2,97 = 4.05, p = 0.02), with no differences in pars opercularis or pars orbitalis. Pars triangularis volume was highly correlated with its SA [Pearson r(101) = 0.88, p l 0.001], which significantly differed between the groups (F2,97 = 4.45, p = 0.01). As with volume, the mean SA of the pars triangularis was greater in unaffected (corrected p = 0.02) and affected relatives (corrected p = 0.05) compared with controls. We did not find group differences in pars triangularis CT or gyrification. Conclusions These findings strengthen prior knowledge about the volumetric findings in this region and provide a new insight into the localization and topology of IFG alterations. The unique nature of rIFG morphology in BD, with larger volume and SA early in the course of illness, could have practical implications for detection of participants at risk for BD.

Predicting Worsening Suicidal Ideation With Clinical Features and Peripheral Expression of Messenger RNA and MicroRNA During Antidepressant Treatment

Abstract: OBJECTIVE To investigate how the combination of clinical and molecular biomarkers can predict worsening of suicidal ideation during antidepressant treatment. METHODS Samples were obtained from 237 patients with major depressive disorder (DSM-IV criteria) treated with either duloxetine or placebo in an 8-week randomized controlled trial. Data were collected between 2007 and 2011. The relationship between treatment-worsening suicidal ideation (TWSI) and a number of clinical variables, as well as peripheral expression of messenger RNA (mRNA) and microRNA (miRNA), was assessed at baseline. We generated 4 predictive models for TWSI: clinical, mRNA, miRNA, and a combined model comprising the best predictive variables from clinical, mRNA, and miRNA data. RESULTS Eleven patients (9.8%) presented with TWSI in the duloxetine group. Among the clinical variables, only baseline depressive severity was found to be mildly predictive of TWSI. Two mRNAs (stathmin 1 [STMN1] and protein phosphatase 1 regulatory subunit 9B [PPP1R9B]) and 2 miRNAs (miR-3688 and miR-5695) were identified that were significantly predictive of TWSI when mRNA and miRNA were assessed separately (P = .002, .044, .004, and .005, respectively). The best model included baseline depression severity and expression of STMN1 and miR-5695 and predicted TWSI with area under the curve = 0.94 (P < .001). Additionally, the combined model did not significantly predict TWSI in the placebo group. CONCLUSIONS This study generated a predictive tool for TWSI that combines both biological and clinical variables. These biological variables can be easily quantified in peripheral tissues, thus rendering them viable targets to be used in both clinical practice and future studies of suicidal behaviors. TRIAL REGISTRATION ClinicalTrials.gov identifiers: NCT00635219, NCT00599911, and NCT01140906.

Sleep in Offspring of Parents With Mood Disorders.

Abstract: Background: Sleep problems in childhood are an early predictor of mood disorders among individuals at high familial risk. However, the majority of the research has focused on sleep disturbances in already diagnosed individuals and has largely neglected investigating potential differences between weeknight and weekend sleep in high-risk offspring. This study examined sleep parameters in offspring of parents with major depressive disorder or bipolar disorder during both weeknights and weekends. Methods: We used actigraphy, sleep diaries, and questionnaires to measure several sleep characteristics in 73 offspring aged 4-19 years: 23 offspring of a parent with major depressive disorder, 22 offspring of a parent with bipolar disorder, and 28 control offspring. Results: Offspring of parents with major depressive disorder slept, on average, 26 min more than control offspring on weeknights (95% confidence interval, 3 to 49 min, p = 0.027). Offspring of parents with bipolar disorder slept, on average, 27 min more on weekends than on weeknights compared to controls, resulting in a significant family history × weekend interaction (95% confidence interval, 7 to 47 min, p = 0.008). Conclusions: Sleep patterns in children and adolescents were related to the psychiatric diagnosis of their parent(s). Future follow-up of these results may clarify the relations between early sleep differences and the risk of developing mood disorders in individuals at high familial risk.

Basic symptoms in offspring of parents with mood and psychotic disorders.

Abstract: Background Basic symptoms, defined as subjectively perceived disturbances in thought, perception and other essential mental processes, have been established as a predictor of psychotic disorders. However, the relationship between basic symptoms and family history of a transdiagnostic range of severe mental illness, including major depressive disorder, bipolar disorder and schizophrenia, has not been examined. Aims We sought to test whether non-severe mood disorders and severe mood and psychotic disorders in parents is associated with increased basic symptoms in their biological offspring. Method We measured basic symptoms using the Schizophrenia Proneness Instrument – Child and Youth Version in 332 youth aged 8–26 years, including 93 offspring of control parents, 92 offspring of a parent with non-severe mood disorders, and 147 offspring of a parent with severe mood and psychotic disorders. We tested the relationships between parent mental illness and offspring basic symptoms in mixed-effects linear regression models. Results Offspring of a parent with severe mood and psychotic disorders ( B = 0.69, 95% CI 0.22–1.16, P = 0.004) or illness with psychotic features ( B = 0.68, 95% CI 0.09–1.27, P = 0.023) had significantly higher basic symptom scores than control offspring. Offspring of a parent with non-severe mood disorders reported intermediate levels of basic symptoms, that did not significantly differ from control offspring. Conclusions Basic symptoms during childhood are a marker of familial risk of psychopathology that is related to severity and is not specific to psychotic illness. Declaration of interest None.

Effect of antidepressant switching between nortriptyline and escitalopram after a failed first antidepressant treatment among patients with major depressive disorder.

Abstract: BackgroundFor patients with major depressive disorder (MDD) experiencing side-effects or non-response to their first antidepressant, little is known regarding the effect of switching between a tricyclic antidepressant (TCA) and a selective serotonin reuptake inhibitor (SSRI).AimsTo compare the switch between the TCA nortriptyline and the SSRI escitalopram.MethodAmong 811 adults with MDD treated with nortriptyline or escitalopram for up to 12 weeks, 108 individuals switched from nortriptyline to escitalopram or vice versa because of side-effects or non-response (trial registration: EudraCT No.2004-001723-38 (https://eudract.ema.europa.eu/) and ISRCTN No.03693000 (http://www.controlled-trials.com)). Patients were followed for up to 26 weeks after switching and response was measured with the Montgomery–Asberg Depression Rating scale (MADRS). We performed adjusted mixed-effects linear regression models with full information maximum likelihood estimation reporting β-coefficients with 95% CIs.ResultsSwitching antidepressants resulted in a significant decrease in MADRS scores. This was present for switchers from escitalopram to nortriptyline (n = 36, β = −0.38, 95% CI −0.51 to −0.25, P<0.001) and from nortriptyline to escitalopram (n = 72, β = −0.34, 95% CI −0.41 to −0.26, P<0.001). Both switching options resulted in significant improvement among individuals who switched because of non-response or side-effects. The results were supported by analyses on other rating scales and symptom dimensions.ConclusionsThese results suggest that switching from a TCA to an SSRI or vice versa after non-response or side-effects to the first antidepressant may be a viable approach to achieve response among patients with MDD.Declarations of interestK.J.A. holds an Alberta Centennial Addiction and Mental Health Research Chair, funded by the Government of Alberta. K.J.A. has been a member of various advisory boards, received consultancy fees and honoraria, and has received research grants from various companies including Johnson and Johnson Pharmaceuticals Research and Development and Bristol-Myers Squibb Pharmaceuticals Limited. D.S. has served on advisory boards for, and received unrestricted grants from, Lundbeck and AstraZeneca. A.F. and P.M. have received honoraria for participating in expert panels for Lundbeck and GlaxoSmithKline.

Trajectories of Suicidal Ideation During 12 Weeks of Escitalopram or Nortriptyline Antidepressant Treatment Among 811 Patients With Major Depressive Disorder.

Abstract: Background Suicidal ideation is a frequent and difficult-to-treat clinical challenge among patients with major depressive disorder (MDD). However, little is known regarding the differential development during antidepressant treatment and whether some patients may suffer from persistent suicidal ideation. Methods Among 811 patients with Schedules for Clinical Assessment in Neuropsychiatry (SCAN)-verified MDD from 2004-2007 assessed weekly for 12 weeks of escitalopram or nortriptyline antidepressant treatment, we applied item response theory to integrate a suicidality score based on 3 rating scales. We performed latent growth mixture modeling analysis to empirically identify trajectories. Multinomial logistic regression analyses estimated associations with potential predictors. Results We identified 5 distinct classes of suicidal ideation. The Persistent-low class (53.7%) showed no suicidal ideation whereas the Persistent-high class (9.8%) had high suicidal ideation throughout 12 weeks. Two classes showed a fluctuating course: the Fluctuating class (5.2%) ended at a low level of suicidal ideation, whereas the Slow-response-relapse class (4.8%) initially responded slowly but then experienced a large increase to a high level of suicidal ideation after 12 weeks. The Fast-response class (26.5%) had a high baseline severity similar to the Persistent-high class but responded quickly within a few weeks and remained at a low level. Previous suicide attempts and higher mood symptom severity were associated with worse suicidal ideation trajectories, whereas living with a partner showed a trend toward better response. Conclusion Approximately 1 of 5 patients with MDD showed high or fluctuating suicidal ideation despite antidepressant treatment. Studies should investigate whether suicidal ideation may persist for longer periods and more targeted treatment possibilities. Trial registration ISRCTN​​ identifier: ISRCTN03693000​​​​.

Clinical course predicts long-term outcomes in bipolar disorder.

Abstract: Background The long-term outcomes of bipolar disorder range from lasting remission to chronic course or frequent recurrences requiring admissions. The distinction between bipolar I and II disorders has limited utility in outcome prediction. It is unclear to what extent the clinical course of bipolar disorder predicts long-term outcomes. Methods A representative sample of 191 individuals diagnosed with bipolar I or II disorder was recruited and followed for up to 5 years using a life-chart method. We previously described the clinical course over the first 18 months with dimensional course characteristics and latent classes. Now we test if these course characteristics predict long-term outcomes, including time ill (time with any mood symptoms) and hospital admissions over a second non-overlapping follow-up period in 111 individuals with available data from both 18 months and 5 years follow-ups. Results Dimensional course characteristics from the first 18 months prospectively predicted outcomes over the following 3.5 years. The proportion of time depressed, the severity of depressive symptoms and the proportion of time manic predicted more time ill. The proportion of time manic, the severity of manic symptoms and depression-to-mania switching predicted a greater likelihood of hospital admissions. All predictions remained significant after controlling for age, sex and bipolar I v. II disorder. Conclusions Differential associations with long-term outcomes suggest that course characteristics may facilitate care planning with greater predictive validity than established types of bipolar disorders. A clinical course dominated by depressive symptoms predicts a greater proportion of time ill. A clinical course characterized by manic episodes predicts hospital admissions.

Multimodal Deep Learning for Mental Disorders Prediction from Audio Speech Samples.

Abstract: Key features of mental illnesses are reflected in speech. Our research focuses on designing a multimodal deep learning structure that automatically extracts salient features from recorded speech samples for predicting various mental disorders including depression, bipolar, and schizophrenia. We adopt a variety of pre-trained models to extract embeddings from both audio and text segments. We use several state-of-the-art embedding techniques including BERT, FastText, and Doc2VecC for the text representation learning and WaveNet and VGG-ish models for audio encoding. We also leverage huge auxiliary emotion-labeled text and audio corpora to train emotion-specific embeddings and use transfer learning in order to address the problem of insufficient annotated multimodal data available. All these embeddings are then combined into a joint representation in a multimodal fusion layer and finally a recurrent neural network is used to predict the mental disorder. Our results show that mental disorders can be predicted with acceptable accuracy through multimodal analysis of clinical interviews.

Like father like daughter: sex-specific parent-of-origin effects in the transmission of liability for psychotic symptoms to offspring.

Abstract: Children of parents with major mood and psychotic disorders are at increased risk of psychopathology, including psychotic symptoms It has been suggested that the risk of psychosis may be more often transmitted from parent to opposite-sex offspring (eg, from father to daughter) than to same-sex offspring (eg, from father to son) To test whether sex-specific transmission extends to early manifestations of psychosis, we examined sex-specific contributions to psychotic symptoms among offspring of mothers and fathers with depression, bipolar disorder and schizophrenia We assessed psychotic symptoms in 309 offspring (160 daughters and 149 sons) aged 8-24 years (mean=131, sd=43), of whom 113 had a mother with schizophrenia, bipolar disorder or major depression and 43 had a father with schizophrenia, bipolar disorder or major depression In semi-structured interviews, 130 (42%) offspring had definite psychotic symptoms established and confirmed by psychiatrists on one or more assessments We tested the effects of mental illness in parents on same-sex and opposite-sex offspring psychotic symptoms in mixed-effect logistic regression models Psychotic symptoms were more prevalent among daughters of affected fathers and sons of affected mothers than among offspring of the same sex as their affected parent Mental illness in the opposite-sex parent increased the odds of psychotic symptoms (odds ratio (OR)=265, 95% confidence interval (CI) 143-491, P=0002), but mental illness in the same-sex parent did not have a significant effect on psychotic symptoms in offspring (OR=113, 95% CI 061-207, P=0697) The opposite-sex-specific parent-of-origin effects may suggest X chromosome-linked genetic transmission or inherited chromosomal modifications in the etiology of psychotic symptoms

Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Abstract: Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk.Environmental influences during prenatal development may have implications for health and disease later in life. Here, Czamara et al. assess DNA methylation in cord blood from new-born under various models including environmental and genetic effects individually and their additive or interaction effects.

Review of use of the Trials within Cohorts (TwiCs) design approach

Abstract: Introduction: Trials within Cohorts (TwiCs) is an innovative approach to the design and conduct of multiple randomised controlled trials (RCTs) (Relton et al, 2010). This approach utilises an obser ...

Clinical course predicts long-term outcomes in bipolar disorder

Abstract: Background The long-term outcomes of bipolar disorder range from lasting remission to chronic course or frequent recurrences requiring admissions. The distinction between bipolar I and II disorders has limited utility in outcome prediction. It is unclear to what extent the clinical course of bipolar disorder predicts long-term outcomes. Methods A representative sample of 191 individuals diagnosed with bipolar I or II disorder was recruited and followed for up to 5 years using a life-chart method. We previously described the clinical course over the first 18 months with dimensional course characteristics and latent classes. Now we test if these course characteristics predict long-term outcomes, including time ill (time with any mood symptoms) and hospital admissions over a second non-overlapping follow-up period in 111 individuals with available data from both 18 months and 5 years follow-ups. Results Dimensional course characteristics from the first 18 months prospectively predicted outcomes over the following 3.5 years. The proportion of time depressed, the severity of depressive symptoms and the proportion of time manic predicted more time ill. The proportion of time manic, the severity of manic symptoms and depression-to-mania switching predicted a greater likelihood of hospital admissions. All predictions remained significant after controlling for age, sex and bipolar I v. II disorder. Conclusions Differential associations with long-term outcomes suggest that course characteristics may facilitate care planning with greater predictive validity than established types of bipolar disorders. A clinical course dominated by depressive symptoms predicts a greater proportion of time ill. A clinical course characterized by manic episodes predicts hospital admissions.

A polygenic predictor of treatment-resistant depression using whole exome sequencing and genome-wide genotyping

Abstract: Treatment-resistant depression (TRD) occurs in ∼30% of patients with major depressive disorder (MDD) but the genetics of TRD was previously poorly investigated. Whole exome sequencing and genome-wide genotyping were performed in 1320 MDD patients. Response to the first pharmacological treatment was compared to non-response to one treatment and non-response to two or more treatments (TRD). Differences in the risk of carrying damaging variants were tested. A score expressing the burden of variants in genes and pathways was calculated weighting each variant for its functional (Eigen) score and frequency, considering rare variants only and rare + common variants. Gene- and pathway-based scores were used to develop predictive models of TRD and non-response using gradient boosting in 70% of the sample (training) which were tested in the remaining 30% (testing), evaluating also the addition of clinical predictors. Independent replication was tested in STAR*D and GENDEP using exome array-based data. After quality control 1209 subjects were included. TRD and non-responders did not show higher risk to carry damaging variants compared to responders. Genes/pathways associated with TRD included those modulating cell survival and proliferation, neurodegeneration and immune response. Significant prediction of TRD vs. response was observed in the testing sample which was improved by the addition of clinical factors. Some models were replicated, with a weaker prediction, in STAR*D and GENDEP when considering also clinical factors and in the extremes of the genetic score distribution. These results suggested relevant biological mechanisms implicated in TRD and a new methodological approach to the prediction of TRD.