The interplay between polygenic score for tumor necrosis factor-α, brain structural connectivity, and processing speed in major depression.

Reduced processing speed is a core deficit in major depressive disorder (MDD) and has been linked to altered structural brain network connectivity. Ample evidence highlights the involvement of genetic-immunological processes in MDD and specific depressive symptoms. Here, we extended these findings by examining associations between polygenic scores for tumor necrosis factor-α blood levels (TNF-α PGS), structural brain connectivity, and processing speed in a large sample of MDD patients. Processing speed performance of n = 284 acutely depressed, n = 177 partially and n = 198 fully remitted patients, and n = 743 healthy controls (HC) was estimated based on five neuropsychological tests. Network-based statistic was used to identify a brain network associated with processing speed. We employed general linear models to examine the association between TNF-α PGS and processing speed. We investigated whether network connectivity mediates the association between TNF-α PGS and processing speed. We identified a structural network positively associated with processing speed in the whole sample. We observed a significant negative association between TNF-α PGS and processing speed in acutely depressed patients, whereas no association was found in remitted patients and HC. The mediation analysis revealed that brain connectivity partially mediated the association between TNF-α PGS and processing speed in acute MDD. The present study provides evidence that TNF-α PGS is associated with decreased processing speed exclusively in patients with acute depression. This association was partially mediated by structural brain connectivity. Using multimodal data, the current findings advance our understanding of cognitive dysfunction in MDD and highlight the involvement of genetic-immunological processes in its pathomechanisms.

Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis.

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.

Stress during pregnancy and fetal serum BDNF in cord blood at birth.

INTRODUCTION: Adverse environments during pregnancy impact neurodevelopment including cognitive abilities of the developing children. The mediating biological alterations are not fully understood. Maternal stress may impact the neurotrophic regulation of the offspring as early as in utero and at birth. Brain-derived neurotrophic factor (BDNF) is essential for neurodevelopment. Short-term higher levels of BDNF in mice upon stressors associate with lower BDNF later in life, which itself associates with depression in animals and humans. Stress including glucocorticoids may impact BDNF, but there is a lack of data at birth. This study investigated if stress near term associates with fetal BDNF at birth in humans. METHODS: Pregnant women near term who underwent primary cesarean sections (at 38.80±0.64 weeks), were included in this study (n=41). Stress at the end of pregnancy was assessed before the cesarean section by determining maternal depressive symptoms (EDPS), maternal state and trait anxiety (STAI-S and STAI-T), maternal prenatal distress (PDQ), stress over the past month (PSS), prenatal attachment to the offspring (PAI), maternal social support (F-Sozu), maternal early life stress (CTQ), socioeconomic status, and the glucocorticoids cortisol and cortisone (n=40) in amniotic fluid at birth. The association with fetal BDNF was analyzed. Cord blood serum of n=34 newborns at birth was analyzed for BDNF and newborn anthropometrics (weight, length and head circumference per gestational age at birth) were assessed. The association of fetal BDNF with anthropometrics at birth was analyzed. RESULTS: After a BDNF-outlier (>3 SD) was removed, higher fetal BDNF associated significantly with maternal depressive symptoms (r=0.398, p=0.022), with lower socioeconomic status as assessed by the average number of people per room in the household (r=0.526, p=0.002) and with borderline significance with net income per person in the household (r=-0.313, p=0.087) in the bivariate analyses. In multivariable analysis, BDNF stayed positively associated with maternal depressive symptoms (ß=0.404, 95% CI [7.057, 306.041], p=0.041) and lower net income per person in the household (ß=-0.562, 95% CI [-914.511, -60.523], p=0.027) when controlling for maternal age, maternal pre-pregnancy BMI, fetal sex and gestational age. Fetal BDNF did not associate with newborn anthropometrics with the outlier removed in bivariate analyses or in multivariable analyses when controlling for maternal BMI and fetal sex. CONCLUSION: Maternal depressive symptoms and lower socioeconomic status associated with higher fetal BDNF when controlling for confounders. Fetal BDNF did not associate with newborn anthropometrics with the outlier removed. Further studies should investigate how early altered BDNF associate with the development and possibly psychopathology of the offspring.

Multimodal Associations of FKBP5 Methylation With Emotion-Regulatory Brain Circuits.

BACKGROUND: Understanding the biological processes that underlie individual differences in emotion regulation and stress responsivity is a key challenge for translational neuroscience. The gene FKBP5 is a core regulator in molecular stress signaling that is implicated in the development of psychiatric disorders. However, it remains unclear how FKBP5 DNA methylation in peripheral blood is related to individual differences in measures of neural structure and function and their relevance to daily-life stress responsivity. METHODS: Here, we characterized multimodal correlates of FKBP5 DNA methylation by combining epigenetic data with neuroimaging and ambulatory assessment in a sample of 395 healthy individuals. RESULTS: First, we showed that FKBP5 demethylation as a psychiatric risk factor was related to an anxiety-associated reduction of gray matter volume in the ventromedial prefrontal cortex, a brain area that is involved in emotion regulation and mental health risk and resilience. This effect of epigenetic upregulation of FKBP5 on neuronal structure is more pronounced where FKBP5 is epigenetically downregulated at baseline. Leveraging 208 functional magnetic resonance imaging scans during a well-established emotion-processing task, we found that FKBP5 DNA methylation in peripheral blood was associated with functional differences in prefrontal-limbic circuits that modulate affective responsivity to daily stressors, which we measured using ecological momentary assessment in daily life. CONCLUSIONS: Overall, we demonstrated how FKBP5 contributes to interindividual differences in neural and real-life affect regulation via structural and functional changes in prefrontal-limbic brain circuits.

Assessing the impact of sex on high-frequency repetitive transcranial magnetic stimulation´s clinical response in schizophrenia - results from a secondary analysis.

BACKGROUND: The evidence for repetitive transcranial magnetic stimulation (rTMS) to treat negative symptoms in schizophrenia (SCZ) is increasing, although variable response rates remain a challenge. Subject´s sex critically influences rTMS´ treatment outcomes. Females with major depressive disorder are more likely to respond to rTMS, while SCZ data is scarce. METHODS: Using data from the 'rTMS for the Treatment of Negative Symptoms in Schizophrenia' (RESIS) trial we assessed the impact of sex on rTMS´ clinical response rate from screening up to 105 days after intervention among SCZ patients. The impact of resting motor threshold (RMT) on response rates was also assessed. RESULTS: 157 patients received either active or sham rTMS treatment. No significant group differences were observed. Linear mixed model showed no effects on response rates (all p > 0.519). Apart from a significant sex*time interaction for the positive subscale of the positive and negative syndrome scale (PANSS) scores (p = 0.032), no other significant effects of sex on continuous PANSS scores were observed. RMT had no effect on response rate. CONCLUSION: In the largest rTMS trial on the treatment of SCZ negative symptoms we did not observe any significant effect of sex on treatment outcomes. Better assessments of sex-related differences could improve treatment individualisation.

Associations of Menstrual Cycle and Progesterone-to-Estradiol Ratio With Alcohol Consumption in Alcohol Use Disorder: A Sex-Separated Multicenter Longitudinal Study.

OBJECTIVE: Alcohol use disorder (AUD) constitutes a critical public health issue and has sex-specific characteristics. Initial evidence suggests that progesterone and estradiol might reduce or increase alcohol intake, respectively. However, there is a need for a better understanding of how the menstrual cycle in females and the ratio of progesterone to estradiol in females and males influence alcohol use patterns in individuals with AUD. METHODS: In this sex-separated multicenter longitudinal study, the authors analyzed 12-month data on real-life alcohol use (from 21,460 smartphone entries), menstrual cycle, and serum progesterone-to-estradiol ratios (from 667 blood samples at four individual study visits) in 74 naturally cycling females and 278 males with AUD between 2020 and 2022, using generalized and general linear mixed modeling. RESULTS: Menstrual cycle phases were significantly associated with binge drinking and progesterone-to-estradiol ratio. During the late luteal phase, females showed a lower predicted binge drinking probability of 13% and a higher predicted marginal mean of progesterone-to-estradiol ratio of 95 compared with during the menstrual, follicular, and ovulatory phases (binge drinking probability and odds ratios vs. late luteal phase, respectively: 17%, odds ratio=1.340, 95% CI=1.031, 1.742; 19%, odds ratio=1.523, 95% CI=1.190, 1.949; and 20%, odds ratio=1.683, 95% CI=1.285, 2.206; difference in progesterone-to-estradiol ratios, respectively: -61, 95% CI=-105.492, -16.095; -78, 95% CI=-119.322, -37.039; and -71, 95% CI=-114.568, -27.534). In males, a higher progesterone-to-estradiol ratio was related to lower probabilities of binge drinking and of any alcohol use, with a 10-unit increase in the hormone ratio resulting in odds ratios of 0.918 (95% CI=0.843, 0.999) and 0.914 (95% CI=0.845, 0.988), respectively. CONCLUSIONS: These ecologically valid findings suggest that high progesterone-to-estradiol ratios can have a protective effect against problematic alcohol use in females and males with AUD, highlighting the progesterone-to-estradiol ratio as a promising treatment target. Moreover, the results indicate that females with AUD may benefit from menstrual cycle phase-tailored treatments.

A Systematic Evaluation of Machine Learning-Based Biomarkers for Major Depressive Disorder.

Importance: Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified. Objective: To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD. Design, Setting, and Participants: This study used data from the Marburg-Münster Affective Disorders Cohort Study, a case-control clinical neuroimaging study. Patients with acute or lifetime MDD and healthy controls aged 18 to 65 years were recruited from primary care and the general population in Münster and Marburg, Germany, from September 11, 2014, to September 26, 2018. The Münster Neuroimaging Cohort (MNC) was used as an independent partial replication sample. Data were analyzed from April 2022 to June 2023. Exposure: Patients with MDD and healthy controls. Main Outcome and Measure: Diagnostic classification accuracy was quantified on an individual level using an extensive ML-based multivariate approach across a comprehensive range of neuroimaging modalities, including structural and functional magnetic resonance imaging and diffusion tensor imaging as well as a polygenic risk score for depression. Results: Of 1801 included participants, 1162 (64.5%) were female, and the mean (SD) age was 36.1 (13.1) years. There were a total of 856 patients with MDD (47.5%) and 945 healthy controls (52.5%). The MNC replication sample included 1198 individuals (362 with MDD [30.1%] and 836 healthy controls [69.9%]). Training and testing a total of 4 million ML models, mean (SD) accuracies for diagnostic classification ranged between 48.1% (3.6%) and 62.0% (4.8%). Integrating neuroimaging modalities and stratifying individuals based on age, sex, treatment, or remission status does not enhance model performance. Findings were replicated within study sites and also observed in structural magnetic resonance imaging within MNC. Under simulated conditions of perfect reliability, performance did not significantly improve. Analyzing model errors suggests that symptom severity could be a potential focus for identifying MDD subgroups. Conclusion and Relevance: Despite the improved predictive capability of multivariate compared with univariate neuroimaging markers, no informative individual-level MDD biomarker-even under extensive ML optimization in a large sample of diagnosed patients-could be identified.

Biological aging markers in blood and brain tissue indicate age acceleration in alcohol use disorder.

BACKGROUND: Alcohol use disorder (AUD) is associated with increased mortality and morbidity risk. A reason for this could be accelerated biological aging, which is strongly influenced by disease processes such as inflammation. As recent studies of AUD show changes in DNA methylation and gene expression in neuroinflammation-related pathways in the brain, biological aging represents a potentially important construct for understanding the adverse effects of substance use disorders. Epigenetic clocks have shown accelerated aging in blood samples from individuals with AUD. However, no systematic evaluation of biological age measures in AUD across different tissues and brain regions has been undertaken. METHODS: As markers of biological aging (BioAge markers), we assessed Levine's and Horvath's epigenetic clocks, DNA methylation telomere length (DNAmTL), telomere length (TL), and mitochondrial DNA copy number (mtDNAcn) in postmortem brain samples from Brodmann Area 9 (BA9), caudate nucleus, and ventral striatum (N = 63-94), and in whole blood samples (N = 179) of individuals with and without AUD. To evaluate the association between AUD status and BioAge markers, we performed linear regression analyses while adjusting for covariates. RESULTS: The majority of BioAge markers were significantly associated with chronological age in all samples. Levine's epigenetic clock and DNAmTL were indicative of accelerated biological aging in AUD in BA9 and whole blood samples, while Horvath's showed the opposite effect in BA9. No significant association of AUD with TL and mtDNAcn was detected. Measured TL and DNAmTL showed only small correlations in blood and none in brain. CONCLUSIONS: The present study is the first to simultaneously investigate epigenetic clocks, telomere length, and mtDNAcn in postmortem brain and whole blood samples in individuals with AUD. We found evidence for accelerated biological aging in AUD in blood and brain, as measured by Levine's epigenetic clock, and DNAmTL. Additional studies of different tissues from the same individuals are needed to draw valid conclusions about the congruence of biological aging in blood and brain.

Speech Features as Predictors of Momentary Depression Severity in Patients With Depressive Disorder Undergoing Sleep Deprivation Therapy: Ambulatory Assessment Pilot Study.

BACKGROUND: The use of mobile devices to continuously monitor objectively extracted parameters of depressive symptomatology is seen as an important step in the understanding and prevention of upcoming depressive episodes. Speech features such as pitch variability, speech pauses, and speech rate are promising indicators, but empirical evidence is limited, given the variability of study designs. OBJECTIVE: Previous research studies have found different speech patterns when comparing single speech recordings between patients and healthy controls, but only a few studies have used repeated assessments to compare depressive and nondepressive episodes within the same patient. To our knowledge, no study has used a series of measurements within patients with depression (eg, intensive longitudinal data) to model the dynamic ebb and flow of subjectively reported depression and concomitant speech samples. However, such data are indispensable for detecting and ultimately preventing upcoming episodes. METHODS: In this study, we captured voice samples and momentary affect ratings over the course of 3 weeks in a sample of patients (N=30) with an acute depressive episode receiving stationary care. Patients underwent sleep deprivation therapy, a chronotherapeutic intervention that can rapidly improve depression symptomatology. We hypothesized that within-person variability in depressive and affective momentary states would be reflected in the following 3 speech features: pitch variability, speech pauses, and speech rate. We parametrized them using the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS) from open-source Speech and Music Interpretation by Large-Space Extraction (openSMILE; audEERING GmbH) and extracted them from a transcript. We analyzed the speech features along with self-reported momentary affect ratings, using multilevel linear regression analysis. We analyzed an average of 32 (SD 19.83) assessments per patient. RESULTS: Analyses revealed that pitch variability, speech pauses, and speech rate were associated with depression severity, positive affect, valence, and energetic arousal; furthermore, speech pauses and speech rate were associated with negative affect, and speech pauses were additionally associated with calmness. Specifically, pitch variability was negatively associated with improved momentary states (ie, lower pitch variability was linked to lower depression severity as well as higher positive affect, valence, and energetic arousal). Speech pauses were negatively associated with improved momentary states, whereas speech rate was positively associated with improved momentary states. CONCLUSIONS: Pitch variability, speech pauses, and speech rate are promising features for the development of clinical prediction technologies to improve patient care as well as timely diagnosis and monitoring of treatment response. Our research is a step forward on the path to developing an automated depression monitoring system, facilitating individually tailored treatments and increased patient empowerment.

Childhood Trauma and Somatic and Mental Illness in Adulthood.

BACKGROUND: Childhood trauma is associated with somatic and mental illness in adulthood. The strength of the association varies as a function of age, sex, and type of trauma. Pertinent studies to date have mainly focused on individual diseases. In this study, we investigate the association between childhood trauma and a multiplicity of somatic and mental illnesses in adulthood. METHODS: Data from 156 807 NAKO Health Study participants were analyzed by means of logistic regressions, with adjustment for age, sex, years of education, and study site. The Childhood Trauma Screener differentiated between no/minor (n = 115 891) and moderate/severe childhood trauma (n = 40 916). The outcome variables were medical diagnoses of five somatic and two mental health conditions as stated in the clinical history. RESULTS: Persons with childhood trauma were more likely to bear a diagnosis of all of the studied conditions: cancer (odds ratio [OR] = 1.10; 95% confidence interval: [1.05; 1.15]), myocardial infarction (OR = 1.13 [1.03; 1.24]), diabetes (OR = 1.16, [1.10; 1.23]), stroke (OR = 1.35 [1.23; 1.48]), chronic obstructive pulmonary disease (OR = 1.45 [1.38; 1.52]), depression (OR = 2.36 [2.29; 2.43]), and anxiety disorders (OR = 2.08 [2.00; 2.17]). All of these associations were stronger in younger persons, regardless of the nature of childhood trauma. Differences between the sexes were observed only for some of these associations. CONCLUSION: Childhood trauma was associated with a higher probability of developing mental as well as somatic illness in adulthood. As childhood trauma is an element of individual history that the victim has little to no control over, and because the illnesses that can arise in adulthood in association with it are a heavy burden on the affected persons and on society, there is a need for research on these associations and for the development of preventive measures.

Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials.

BACKGROUND: Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment. AIMS: To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants. METHOD: Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses. RESULTS: Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, ßpooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, ßpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I2= 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (ßpooled = 0.16) and the IMD index (ßpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission. CONCLUSIONS: Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

Evidence for a shared genetic contribution to loneliness and borderline personality disorder.

Loneliness, influenced by genetic and environmental factors such as childhood maltreatment, is one aspect of interpersonal dysfunction in Borderline Personality Disorder (BPD). Numerous studies link loneliness and BPD and twin studies indicate a genetic contribution to this association. The aim of our study was to investigate whether genetic predisposition for loneliness and BPD risk overlap and whether genetic risk for loneliness contributes to higher loneliness reported by BPD patients, using genome-wide genotype data. We assessed the genetic correlation of genome-wide association studies (GWAS) of loneliness and BPD using linkage disequilibrium score regression and tested whether a polygenic score for loneliness (loneliness-PGS) was associated with case-control status in two independent genotyped samples of BPD patients and healthy controls (HC; Witt2017-sample: 998 BPD, 1545 HC; KFO-sample: 187 BPD, 261 HC). In the KFO-sample, we examined associations of loneliness-PGS with reported loneliness, and whether the loneliness-PGS influenced the association between childhood maltreatment and loneliness. We found a genetic correlation between the GWAS of loneliness and BPD in the Witt2017-sample (rg = 0.23, p = 0.015), a positive association of loneliness-PGS with BPD case-control status (Witt2017-sample: NkR² = 2.3%, p = 2.7*10-12; KFO-sample: NkR² = 6.6%, p = 4.4*10-6), and a positive association between loneliness-PGS and loneliness across patient and control groups in the KFO-sample (ß = 0.186, p = 0.002). The loneliness-PGS did not moderate the association between childhood maltreatment and loneliness in BPD. Our study is the first to use genome-wide genotype data to show that the genetic factors underlying variation in loneliness in the general population and the risk for BPD overlap. The loneliness-PGS was associated with reported loneliness. Further research is needed to investigate which genetic mechanisms and pathways are involved in this association and whether a genetic predisposition for loneliness contributes to BPD risk.

Impulsivity, decision-making, and risk behavior in bipolar disorder and major depression from bipolar multiplex families.

OBJECTIVES: Bipolar disorder (BD) and major depressive disorder (MDD) are characterized by specific alterations of mood. In both disorders, alterations in cognitive domains such as impulsivity, decision-making, and risk-taking have been reported. Identification of similarities and differences of these domains in BD and MDD could give further insight into their etiology. The present study assessed impulsivity, decision-making, and risk-taking behavior in BD and MDD patients from bipolar multiplex families. METHODS: Eighty-two participants (BD type I, n = 25; MDD, n = 26; healthy relatives (HR), n = 17; and healthy controls (HC), n = 14) underwent diagnostic interviews and selected tests of a cognitive battery assessing neurocognitive performance across multiple subdomains including impulsivity (response inhibition and delay aversion), decision-making, and risk behavior. Generalized estimating equations (GEEs) were used to analyze whether the groups differed in the respective cognitive domains. RESULTS: Participants with BD and MDD showed higher impulsivity levels compared to HC; this difference was more pronounced in BD participants. BD participants also showed lower inhibitory control than MDD participants. Overall, suboptimal decision-making was associated with both mood disorders (BD and MDD). In risk-taking behavior, no significant impairment was found in any group. LIMITATIONS: As sample size was limited, it is possible that differences between BD and MDD may have escaped detection due to lack of statistical power. CONCLUSIONS: Our findings show that alterations of cognitive domains-while present in both disorders-are differently associated with BD and MDD. This underscores the importance of assessing such domains in addition to mere diagnosis of mood disorders.

Association of polygenic scores for depression and neuroticism with perceived stress in daily life during a long-lasting stress period.

Genetic factors contribute significantly to interindividual differences in the susceptibility to stress-related disorders. As stress can also be conceptualized as environmental exposure, controlled gene-environment interaction (GxE) studies with an in-depth phenotyping may help to unravel mechanisms underlying the interplay between genetic factors and stress. In a prospective-longitudinal quasi-experimental study, we investigated whether polygenic scores (PGS) for depression (DEP-PGS) and neuroticism (NEU-PGS), respectively, were associated with responses to chronic stress in daily life. We examined law students (n = 432) over 13 months. Participants in the stress group experienced a long-lasting stress phase, namely the preparation for the first state examination for law students. The control group consisted of law students without particular stress exposure. In the present manuscript, we analyzed perceived stress levels assessed at high frequency and in an ecologically valid manner by ambulatory assessments as well as depression symptoms and two parameters of the cortisol awakening response. The latter was only assessed in a subsample (n = 196). No associations between the DEP-PGS and stress-related variables were found. However, for the NEU-PGS we found a significant GxE effect. Only in individuals experiencing academic stress a higher PGS for neuroticism predicted stronger increases of perceived stress levels until the exam. At baseline, a higher NEU-PGS was associated with higher perceived stress levels in both groups. Despite the small sample size, we provide preliminary evidence that the genetic disposition for neuroticism is associated with stress level increases in daily life during a long-lasting stress period.

Lack of guidelines and translational knowledge is hindering the implementation of psychiatric genetic counseling and testing within Europe - A multi-professional survey study.

Genetic research has identified a large number of genetic variants, both rare and common, underlying neurodevelopmental disorders (NDD) and major psychiatric disorders. Currently, these findings are being translated into clinical practice. However, there is a lack of knowledge and guidelines for psychiatric genetic testing (PsychGT) and genetic counseling (PsychGC). The European Union-funded COST action EnGagE (CA17130) network was started to investigate the current implementation status of PsychGT and PsychGC across 35 participating European countries. Here, we present the results of a pan-European online survey in which we gathered the opinions, knowledge, and practices of a self-selected sample of professionals involved/interested in the field. We received answers from 181 respondents. The three main occupational categories were genetic counselor (21.0%), clinical geneticist (24.9%), and researcher (25.4%). Of all 181 respondents, 106 provide GC for any psychiatric disorder or NDD, corresponding to 58.6% of the whole group ranging from 43.2% in Central Eastern Europe to 66.1% in Western Europe. Overall, 65.2% of the respondents reported that genetic testing is offered to individuals with NDD, and 26.5% indicated the same for individuals with major psychiatric disorders. Only 22.1% of the respondents indicated that they have guidelines for PsychGT. Pharmacogenetic testing actionable for psychiatric disorders was offered by 15%. Interestingly, when genetic tests are fully covered by national health insurance, more genetic testing is provided for individuals with NDD but not those with major psychiatric disorders. Our qualitative analyses of responses highlight the lack of guidelines and knowledge on utilizing and using genetic tests and education and training as the major obstacles to implementation. Indeed, the existence of psychiatric genetic training courses was confirmed by only 11.6% of respondents. The question on the relevance of up-to-date education and training in psychiatric genetics on everyday related practice was highly relevant. We provide evidence that PsychGC and PsychGT are already in use across European countries, but there is a lack of guidelines and education. Harmonization of practice and development of guidelines for genetic counseling, testing, and training professionals would improve equality and access to quality care for individuals with psychiatric disorders within Europe.

Psychological, endocrine and polygenic predictors of emotional well-being during the COVID-19 pandemic in a longitudinal birth cohort.

The COVID-19 pandemic severely affected the lives of families and the well-being of both parents and their children. Various factors, including prenatal stress, dysregulated stress response systems, and genetics may have influenced how the stress caused by the pandemic impacted the well-being of different family members. The present work investigated if emotional well-being during the COVID-19 pandemic could be predicted by developmental stress-related and genetic factors. Emotional well-being of 7-10 year-old children (n = 263) and mothers (n = 241) (participants in a longitudinal German birth cohort (POSEIDON)) was assessed during the COVID-19 pandemic using the CRISIS questionnaire at two time periods (July 2020-October 2020; November 2020-February 2021). Associations of the children's and mothers' well-being with maternal perceived stress, of the children's well-being with their salivary and morning urine cortisol at 45 months, and polygenic risk scores (PRSs) for depression, schizophrenia, loneliness were investigated. Lower emotional well-being was observed in both children and mothers during compared to before the pandemic, with the children's but not the mothers' emotional well-being improving over the course of the pandemic. A positive association between the child and maternal emotional well-being was found. Prenatally assessed maternal perceived stress was associated with a lower well-being in children, but not in mothers. Cortisol measures and PRSs were not significantly associated with the children's emotional well-being. The present study confirms that emotional well-being of children and mothers are linked, and were negatively affected by the COVID-19 pandemic, with differences in development over time.

Meta-analysis of CYP2C19 and CYP2D6 metabolic activity on antidepressant response from 13 clinical studies using genotype imputation.

Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. The association of CYP2C19 and CYP2D6 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR=1.46, 95% CI [1.03, 2.06], p=0.033, heterogeneity I2=0%, subgroup difference p=0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19 and CYP2D6, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. CYP2D6 structural variants cannot be imputed from genotype data, limiting inference of pharmacogenetic effects. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.

Genetic structure of major depression symptoms across clinical and community cohorts.

Diagnostic criteria for major depressive disorder allow for heterogeneous symptom profiles but genetic analysis of major depressive symptoms has the potential to identify clinical and aetiological subtypes. There are several challenges to integrating symptom data from genetically-informative cohorts, such as sample size differences between clinical and community cohorts and various patterns of missing data. We conducted genome-wide association studies of major depressive symptoms in three clinical cohorts that were enriched for affected participants (Psychiatric Genomics Consortium, Australian Genetics of Depression Study, Generation Scotland) and three community cohorts (Avon Longitudinal Study of Parents and Children, Estonian Biobank, and UK Biobank). We fit a series of confirmatory factor models with factors that accounted for how symptom data was sampled and then compared alternative models with different symptom factors. The best fitting model had a distinct factor for Appetite/Weight symptoms and an additional measurement factor that accounted for missing data patterns in the community cohorts (use of Depression and Anhedonia as gating symptoms). The results show the importance of assessing the directionality of symptoms (such as hypersomnia versus insomnia) and of accounting for study and measurement design when meta-analysing genetic association data.

Rapid Detection of Lithium Concentrations in Oral Fluid.

BACKGROUND: Lithium medication is considered to be the first-line treatment for bipolar disorder as a monotherapy, and for treatment-resistant depression with lithium augmentation. However, because of potential toxicity, lithium levels must be monitored frequently. Recent studies have demonstrated a significant correlation between lithium levels measured in serum and those detected in oral fluid, suggesting that oral fluid analysis may represent an easy, noninvasive means to monitor lithium levels. The aim of this study was to evaluate the analytical performance of rapid assays for lithium measurements in oral fluid. METHODS: Levels of lithium in oral fluid from psychiatric patients (n = 108 in total) taking lithium medications were quantified using 2 rapid techniques: an automated clinical chemistry analyzer and a novel, commercially available colorimetric lithium assay. These results were compared with those obtained using inductively coupled plasma optical emission spectrometry (ICP-OES). RESULTS: The mean and median oral fluid lithium levels in this cohort were 1.43-1.61 mM and 1.32-1.52 mM, respectively, depending on the method, with the overall range, across all methods, being 0.213-4.42 mM. Linear regression analysis showed excellent agreement between the oral fluid values measured using ICP-OES and the colorimetric method (r 2 value = 0.926; P < 0.0001; slope = 1.084 ± 0.038). Similarly, excellent agreement was observed between ICP-OES and the automated method (r 2 = 0.872; P < 0.0001; slope = 1.019 ± 0.057). CONCLUSIONS: These results demonstrate that lithium levels in oral fluid can be rapidly and reliably quantified using colorimetric approaches. These findings may facilitate the development of point-of-care lithium monitoring systems for use in oral fluid.

DNA methylation in cocaine use disorder-An epigenome-wide approach in the human prefrontal cortex.

Background: Cocaine use disorder (CUD) is characterized by a loss of control over cocaine intake and is associated with structural, functional, and molecular alterations in the human brain. At the molecular level, epigenetic alterations are hypothesized to contribute to the higher-level functional and structural brain changes observed in CUD. Most evidence of cocaine-associated epigenetic changes comes from animal studies while only a few studies have been performed using human tissue. Methods: We investigated epigenome-wide DNA methylation (DNAm) signatures of CUD in human post-mortem brain tissue of Brodmann area 9 (BA9). A total of N = 42 BA9 brain samples were obtained from N = 21 individuals with CUD and N = 21 individuals without a CUD diagnosis. We performed an epigenome-wide association study (EWAS) and analyzed CUD-associated differentially methylated regions (DMRs). To assess the functional role of CUD-associated differential methylation, we performed Gene Ontology (GO) enrichment analyses and characterized co-methylation networks using a weighted correlation network analysis. We further investigated epigenetic age in CUD using epigenetic clocks for the assessment of biological age. Results: While no cytosine-phosphate-guanine (CpG) site was associated with CUD at epigenome-wide significance in BA9, we detected a total of 20 CUD-associated DMRs. After annotation of DMRs to genes, we identified Neuropeptide FF Receptor 2 (NPFFR2) and Kalirin RhoGEF Kinase (KALRN) for which a previous role in the behavioral response to cocaine in rodents is known. Three of the four identified CUD-associated co-methylation modules were functionally related to neurotransmission and neuroplasticity. Protein-protein interaction (PPI) networks derived from module hub genes revealed several addiction-related genes as highly connected nodes such as Calcium Voltage-Gated Channel Subunit Alpha1 C (CACNA1C), Nuclear Receptor Subfamily 3 Group C Member 1 (NR3C1), and Jun Proto-Oncogene, AP-1 Transcription Factor Subunit (JUN). In BA9, we observed a trend toward epigenetic age acceleration (EAA) in individuals with CUD remaining stable even after adjustment for covariates. Conclusion: Results from our study highlight that CUD is associated with epigenome-wide differences in DNAm levels in BA9 particularly related to synaptic signaling and neuroplasticity. This supports findings from previous studies that report on the strong impact of cocaine on neurocircuits in the human prefrontal cortex (PFC). Further studies are needed to follow up on the role of epigenetic alterations in CUD focusing on the integration of epigenetic signatures with transcriptomic and proteomic data.