Sensitivity to stress is essential in the onset, clinical symptoms, course, and prognosis of major depressive disorder (MDD). Meanwhile, it was unclear how variously classified but connected stress-sensitivity variables affect MDD. We hypothesize that high-level trait- and state-related stress-sensitivity factors may have different cumulative effects on the clinical symptoms and follow-up outcomes of MDD.

To investigate how stress-sensitivity factors added up and affected MDD clinical symptoms and follow-up results.

In this prospective study, 281 MDD patients were enrolled from a tertiary care setting. High-level stress-sensitivity factors were classified as trait anxiety, state anxiety, perceived stress, and neuroticism, with a total score in the top quartile of the research cohort. The cumulative effects of stress-sensitivity factors on cognitive dysfunction, disability and functional impairment, suicide risk, and depressive and anxiety symptoms were examined using an analysis of variance with linear trend analysis. Correlations were investigated further using multiple regression analysis.

Regarding high-level stress-sensitivity factors, 53.40% of patients had at least one at baseline, and 29.61% had two or more. Four high-level stress-sensitivity components had significant cumulative impacts on MDD symptoms at baseline (all P < 0.001). Perceived stress predicted the greatest effect sizes of state-related factors on depressive symptoms (partial η 2 = 0.153; standardized β = 0.195; P < 0.05). The follow-up outcomes were significantly impacted only by the high-level trait-related components, mainly when it came to depressive symptoms and suicide risk, which were predicted by trait anxiety and neuroticism, respectively (partial η 2 = 0.204 and 0.156; standardized β = 0.247 and 0.392; P < 0.05).

To enhance outcomes of MDD and lower the suicide risk, screening for stress-sensitivity factors and considering multifaceted measures, mainly focusing on trait-related ones, should be addressed clinically.

The effective management of depression, anxiety, and other forms of psychological distress depends on individuals' readiness to seek and accept help for their mental suffering. Understanding which personality traits relate to help-seeking can help better tailor mental healthcare to individual needs. However, findings regarding associations of personality traits with help-seeking have been inconsistent.

This systematic review and meta-analysis focused on English-language research studies on the association of personality (encompassing personality disorders, Five Factor -Big Five- dimensions, and other measures of personality) with depression, anxiety, or unspecified psychological distress in adults aged 18 years and older. Procedures followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search strategy included two concepts: personality and help-seeking and was carried out on PubMed, Embase, Web of Science, and PsycINFO. Reference tracking and searches on Google Scholar were additionally performed. Sufficiently homogeneous subsections were analyzed by meta-analysis.

A total of 48 studies described in 47 records reported on the association between personality and help-seeking. Nine assessed personality disorders, 29 Five Factor dimensions, and 13 other personality constructs. Twenty-three studies investigated attitudes towards help-seeking while 25 studies investigated help-seeking behaviors. Of the studies investigating behavior, three used external observations, the rest relied on self-reports/clinician-administered questionnaires. Evidence highlighted a dissociation between attitudes and behavior for schizotypal and borderline personality disorders, and neuroticism, which displayed negative help-seeking attitudes but more help-seeking behavior. By contrast, paranoid, schizoid and obsessive-compulsive personality disorders related to both negative help-seeking attitudes and behavior across studies. Limited evidence linked extraversion to social support seeking and conscientiousness to care seeking behaviors. Meta-analyses on the Five Factor dimensions and help-seeking attitudes supported robust negative associations with neuroticism, as well as positive associations with agreeableness, albeit less reliably. Other personality traits mostly corroborated the above relationships, while also contributing new perspectives, such as help-seeking behavior's negative associations with reality weakness and cynicism, and positive associations with abasement and rigidity.

Future research should investigate help-seeking behavior using external observations and longitudinal designs. Assessing personality in clinical settings can help identify populations at risk of keeping to themselves when mentally distressed.

Major depressive disorder (MDD) is a global health challenge with high prevalence. Further, many diagnosed with MDD are treatment resistant to traditional antidepressants. Repetitive transcranial magnetic stimulation (rTMS) offers promise as an alternative solution, but identifying objective biomarkers for predicting treatment response remains underexplored. Electroencephalographic (EEG) recordings are a cost-effective neuroimaging approach, but traditional EEG analysis methods often do not consider patient-specific variations and fail to capture complex neuronal dynamics. To address this, we propose a data-driven approach combining iterated masking empirical mode decomposition (itEMD) and sparse Bayesian learning (SBL). Our results demonstrated significant prediction of rTMS outcomes using this approach (Protocol 1: r=0.40, p<0.01; Protocol 2: r=0.26, p<0.05). From the decomposition, we obtained three key oscillations: IMF-Alpha, IMF-Beta, and the remaining residue. We also identified key spatial patterns associated with treatment outcomes for two rTMS protocols: for Protocol 1 (10Hz left DLPFC), important areas include the left frontal and parietal regions, while for Protocol 2 (1Hz right DLPFC), the left and frontal, left parietal regions are crucial. Additionally, our exploratory analysis found few significant correlations between oscillation specific predictive features and personality measures. This study highlights the potential of machine learning-driven EEG analysis for personalized MDD treatment prediction, offering a pathway for improved patient outcomes.

Major depressive disorder (MDD) patients' personality traits and illness representations are linked to MDD severity. However, the associations between personality and illness representations in MDD and the mediating role of illness representations between personality and MDD severity have not been investigated. This study aimed to prospectively investigate the aforementioned associations and the possible mediating role of illness representations between personality and MDD severity. One hundred twenty-five patients with a MDD diagnosis, aged 48.18 ± 13.92 (84% females), participated in the study. Personality traits were measured with the Traits Personality Questionnaire at baseline. Illness representations were measured with the Illness Perception Questionnaire-Mental Health about five months later (mean = 5.08 ± 1.14 months). MDD severity was measured about 10 months after the baseline assessment (mean = 9.53 ± 2.36 months) with the Beck Depression Inventory. SPSS 29 and AMOS 27 were used to conduct correlational and parallel mediation analyses. According to the results, Neuroticism was positively and Extraversion was negatively linked to MDD severity. Negative MDD impact representations fully mediated these associations. Neuroticism and Extraversion are linked to future MDD severity through patients' representations of MDD's impact. Restructuring maladaptive representations about MDD's impact can be a promising way to reduce symptom severity in patients with high Neuroticism and low Extraversion levels.

This systematic review and a meta-analysis synthesised the results from contemporary, randomized and non-randomized controlled studies to assess lasting (one week minimum) changes on cognition/creativity, emotional processing and personality from serotonergic psychedelics. PubMed, Embase and PsycInfo were searched in July 2022. Risk of bias was assessed using Rob 2.0 and ROBINS-I. Ten studies met the eligibility criteria which involved 304 participants. No statistically significant effects were found for the majority outcome measures across the three constructs. A meta-analysis of emotional recognition outcomes found an overall significant effect for faster reaction times in the active treatment groups for disgust (SMD=-0.63, 95% CI=[-1.01 to -0.25], I2 = 65%) and sadness (SMD=-0.45, 95% CI=[-0.85 to -0.06], I2 = 60%). Future research should include larger samples, better control conditions, standardized doses and longer follow-up periods to confirm these preliminary findings.

Suicidal behaviour is one of the main causes of death worldwide, especially among teenagers, and its development is potentially associated with the development of personality. The aim of this systematic review and meta-analysis is to describe the association between the Big Five Personality Traits and suicidal behaviour in adolescents.

Seven databases were systematically searched between June 2022 and July 2022 with no language or year restrictions. We searched for a combination of the following search items (suicid* OR suicidal behaviour OR suicidal ideation OR suicide attempts OR self injury OR self-destructive behaviour OR self-harm OR suicidal risk) AND (personality OR personality traits OR temperament OR neuroticism OR extraversion OR agreeableness OR openness to experience OR conscientiousness) AND (adolescents OR youth OR teenagers OR young adults). Meta-analysis procedures were performed using the R software. A random-effect-model was performed for the models through the incorporation of τ2, based on the DerSimonion Lard method.

Seven studies met all inclusion criteria and were included in this systematic review. Our meta-analysis showed that higher neuroticism are both associated and a risk factor for suicidal behaviour. Higher levels of openness to experience and agreeableness, and lower levels of extraversion and conscientiousness, were linked to suicidal behaviour, especially self-harm.

Due to the heterogeneity of the studies, we were only able to perform meta-analysis regarding neuroticism.

The present study may help professionals to identify adolescents in higher risk for suicidal behaviour, enabling the development of early interventions to prevent suicidality in this population.

Advancements in the treatment of depression are pivotal due to high levels of non-response and relapse. This study evaluated the role of personality pathology in the treatment of depression by testing whether maladaptive personality traits (1) predict changes in depression over treatment or vice versa, (2) change themselves over treatment, (3) change differentially depending on treatment with schema therapy (ST) or cognitive behavioural therapy (CBT), and (4) moderate the effectiveness of these treatments.

We included 193 depressed inpatients (53.4% women, Mage = 42.9, SD = 13.4) participating in an assessor-blind randomized clinical trial and receiving a 7-week course of ST or CBT. The research questions were addressed using multiple indicator latent change score models as well as multigroup structural equation models implemented in EffectLiteR.

Maladaptive traits did not predict changes in depressive symptoms at post-treatment, or vice versa. However, maladaptive trait domains decreased over treatment (standardized Δμ range: -0.38 to -0.89), irrespective of treatment with ST or CBT. Maladaptive traits at baseline did not moderate the effectiveness of these treatments.

Self-reported maladaptive personality traits can change during treatment of depression, but may have limited prognostic or prescriptive value, at least in the context of ST or CBT. These results need to be replicated using follow-up data, larger and more diverse samples, and informant-rated measures of personality pathology.

Personality and psychopathology are highly relevant and easily relatable constructs. The current study investigated the relationships between dependency and self-criticism, sociotropy and autonomy depressive personality traits, and Cloninger's temperament and character personality traits postulated as vulnerability factors for depression, in relation to depressive and general psychopathology symptoms in a clinical sample of 100 patients diagnosed with major depressive disorder. The results showed that self-directedness, a character trait of the temperament and character model, was positively associated with dependency, self-criticism, sociotropy, and autonomy. Applying more in-depth analyses with regression models revealed associations between self-directedness and depressive personality styles dependency and sociotropy, and general psychopathology symptoms was a significant clinical indicator in these relationships. Going beyond the regression models, network analysis showed that self-directedness is associated with self-criticism, sociotropy, autonomy, and general psychopathology symptoms. The relationship between self-directedness and sociotropy, self-criticism and autonomy suggests that these depressive personality traits may be attributable to aspects of self-determination, maturity, responsibility, discipline, and self-acceptance. General psychopathology research informed by literature incorporating personality traits has far-reaching implications for understanding individual differences as well as increasing efforts to contribute to the amelioration of disabling psychological disorders like major depressive disorders.

Personality traits may predict antidepressant discontinuation and response. However, previous studies were rather small, only explored a few personality traits and did not include adverse drug effects nor the interdependency between antidepressant discontinuation patterns and response.

GENDEP included 589 patients with unipolar moderate-severe depression treated with escitalopram or nortriptyline for 12 weeks. Seven personality dimensions were measured using the self-reported 240-item Temperament and Character Inventory-Revised (TCI-R). We applied Cox proportional models to study discontinuation patterns, logistic and linear regression to investigate response and remission after 8 and 12 weeks, and mixed-effects linear models regarding time-varying treatment response and adverse drug reactions.

Low harm avoidance, low cooperativeness, high self-transcendence and high novelty seeking were associated with higher risks for antidepressant discontinuation, independent of depressed mood, adverse drug reactions, drug, sex and age. Regression analyses showed that higher novelty seeking and cooperativeness scores were associated with a greater likelihood of response and remission after 8 and 12 weeks, respectively, but we found no correlations with response in the mixed-effects models. Only high harm avoidance was associated with more self-reported adverse effects.

This study, representing the largest investigation between several personality traits and response to two different antidepressants, suggests that correlations between personality traits and antidepressant treatment response may be confounded by differential rates of discontinuation. Future trials on personality in the treatment of depression need to consider this interdependency and study whether interventions aiming at improving compliance for some personality types may improve response to antidepressants.

Despite the increase in awareness and support for mental health, college students' mental health is reported to decline every year in many countries. Several interactive technologies for mental health have been proposed and are aiming to make therapeutic service more accessible, but most of them only provide one-way passive contents for their users, such as psycho-education, health monitoring, and clinical assessment. We present a robotic coach that not only delivers interactive positive psychology interventions but also provides other useful skills to build rapport with college students. Results from our on-campus housing deployment feasibility study showed that the robotic intervention showed significant association with increases in students' psychological well-being, mood, and motivation to change. We further found that students' personality traits were associated with the intervention outcomes as well as their working alliance with the robot and their satisfaction with the interventions. Also, students' working alliance with the robot was shown to be associated with their pre-to-post change in motivation for better well-being. Analyses on students' behavioral cues showed that several verbal and nonverbal behaviors were associated with the change in self-reported intervention outcomes. The qualitative analyses on the post-study interview suggest that the robotic coach's companionship made a positive impression on students, but also revealed areas for improvement in the design of the robotic coach. Results from our feasibility study give insight into how learning users' traits and recognizing behavioral cues can help an AI agent provide personalized intervention experiences for better mental health outcomes.

Expectations are a central maintaining mechanism in mental disorders and most psychological treatments aim to directly or indirectly modify clinically relevant expectations. Therefore, it is crucial to examine why patients with mental disorders maintain dysfunctional expectations, even in light of disconfirming evidence, and how expectation-violating situations should be created in treatment settings to optimize treatment outcome and reduce the risk of treatment failures. The different psychological subdisciplines offer various approaches for understanding the underlying mechanisms of expectation development, persistence, and change. Here, we convey recommendations on how to improve psychological treatments by considering these different perspectives. Based on our expectation violation model, we argue that the outcome of expectation violation depends on several characteristics: features of the expectation-violating situation; the dynamics between the magnitude of expectation violation and cognitive immunization processes; dealing with uncertainties during and after expectation change; controlled and automatic attention processes; and the costs of expectation changes. Personality factors further add to predict outcomes and may offer a basis for personalized treatment planning. We conclude with a list of recommendations derived from basic psychology that could contribute to improved treatment outcome and to reduced risks of treatment failures.

Diagnosis of co-occurring personality disorders, particularly the most comorbid cluster B personality disorders in psychiatric patients is clinically important because of their association with the duration, recurrence, and outcome of the comorbid disorders. The study aimed to assess the prevalence of cluster B personality disorders and associated factors among psychiatric outpatients in Jimma Medical Center.

An institution-based cross-sectional study was conducted among 404 patients with mental illnesses at Jimma Medical Center from July 15 to September 14, 2021. A systematic random sampling method was used to recruit the participants. Personality disorder questionnaire four (PDQ-4) was used to assess the prevalence of cluster B personality disorders through a face-to-face interview. Data were entered into Epi Data Version 4.6 and exported to SPSS Version 26 for analysis. Logistic regression analysis was done and variables with a p-value less than 0.05 with a 95% confidence interval in the final fitting model were declared as independent predictors of cluster B personality disorders.

Amongst 401 respondents with response rate of 99.3%, slightly less than one-fourth (23.19%, N = 93) were found to have cluster B personality disorders. Unable to read and write(AOR = 3.28, 95%CI = 1.43-7.51), unemployment(AOR = 2.32, 95%CI = 1.19-4.49), diagnosis of depressive (AOR = 3.72, 95%CI = 1.52-9.10) and bipolar-I disorders (AOR = 2.94, 95%CI = 1.37-6.29), longer duration of illness (AOR = 2.44, 95%CI = 1.33-4.47), multiple relapses (AOR = 2.21, 95%CI = 1.18-4.15)), history of family mental illnesses (AOR = 2.05, 95%CI = 1.17-3.62), recent cannabis use (AOR = 4.38, 95%CI = 1.61-11.95), recent use of alcohol (AOR = 2.86, 95%CI = 1.34-6.10), starting to use substance at earlier age (AOR = 4.42, 95%CI = 1.51 -12.96), and suicidal attempt (AOR = 2.24, 95%CI = 1.01-4.96), were the factors significantly associated with cluster B personality disorders.

The prevalence of cluster B personality disorders was high among mentally ill outpatients and found to be important for mental health professionals working in the outpatient departments to screen for cluster B personality disorders as part of their routine activities, particularly those who have mood disorders, longer duration of illness, multiple relapses, history of family mental illnesses, suicidal attempt and are a current user of alcohol and cannabis.

OBJECTIVES: This study aimed to preliminarily and exploratorily examine the associations between childhood trauma (CT), its subtypes, and personality traits among unaffected first-degree relatives (FDR, children, or siblings) of patients with major depressive disorder (MDD).

The study sample included three subgroups: MDD patients (N = 85), Patients' FDRs (N = 35), and healthy control individuals (HC, N = 89). The Childhood Trauma Questionnaire (CTQ) was used to assess childhood trauma and the Eysenck Personality Questionnaire was used to assess personality traits.

Significant differences were found in a few personality traits (p < 0.05 for extraversion, neuroticism, and psychoticism) among MDD patients, FDR, and HC, and there were no significant differences between HC and FDR. In the FDR group, compared with those without CT, participants with CT scored significantly higher for neuroticism (N) (F = 3.246, p = 0.046). CT was significantly associated with N, psychoticism (P) and Lie (L), and the strongest association was between CT total score and N. Significantly positive correlations were found between N and sexual abuse (SA) (r = 0.344, p = 0.043), emotional neglect (EN) (r = 0.394, p = 0.019), physical neglect (PN) (r = 0.393, p = 0.019), and CTQ total score (r = 0.452, p = 0.006); between P and CTQ total score (r = 0.336, p = 0.049); and significant negative correlations were found between L and EN (r = -0.446, p = 0.007), CTQ total score (r = -0.375, p = 0.027).

In unaffected FDRs, there were significant associations between childhood trauma and a few personality traits, including neuroticism, psychoticism, and lie, and emotional neglect was significantly associated with neuroticism.

Major depression is a heterogeneous disorder. Therefore, careful evaluation and comprehensive assessment are crucial elements for achieving remission. Personality traits influence prognosis and treatment outcomes, but there is not enough evidence on the association between personality traits and sustained remission (SR). Hence, the present study aimed to evaluate the relationship between personality traits and SR among patients with major depression.

The 12-month prospective study evaluated 77 patients diagnosed with major depressive disorder. All patients underwent a comprehensive assessment, including the Temperament and Personality Questionnaire (T&P) at baseline, and depression severity was measured at baseline as well as six and 12 months. SR was defined as remission (the GRID-Hamilton Depression Rating Scale [GRID-HAMD₁₇] score ≦ 7) at both the 6- and 12-month follow-up. We compared eight T&P construct scores at baseline between the SR and non-SR groups. Multivariable logistic regression analyses were performed to determine the T&P personality traits related to SR.

Patients who achieved SR had a lower T&P personal reserve and lower T&P rejection sensitivity. Further, lower scores on the T&P personal reserve trait were independently associated with higher rates of SR among patients with major depression. Patients who achieved SR had a shorter duration of the current depressive episode and milder severity of depression at baseline.

A lower level of personal reserve predicted a higher probability of SR in the treatment of depression. Extended observations in naturalistic follow-up settings with larger sample sizes are required to better understand the personality traits affecting SR in patients with depression.

Selective serotonin reuptake inhibitors (SSRIs) are often the first-line treatment option for depressive symptoms, however their efficacy varies across patients. Identifying predictors of response to SSRIs could facilitate personalised treatment of depression and improve treatment outcomes. The aim of this study was to develop a data-driven formulation of demographic, personality, and symptom-level factors associated with subjective response to SSRI treatment.

Participants were recruited online and data were collected retrospectively through an extensive digital mental health questionnaire. Extreme gradient boosting classification with nested cross-validation was used to identify factors distinguishing between individuals with low (n=37) and high (n=111) perceived benefit from SSRI treatment.

The algorithm demonstrated a good predictive performance (test AUC=.88±.07). Positive affectivity was the strongest predictor of response to SSRIs and a major confounder of the remaining associations. After controlling for positive affectivity, as well as current wellbeing, severity of current depressive symptoms, and multicollinearity, only low positive affectivity, chronic pain, sleep problems, and unemployment remained significantly associated with diminished subjective response to SSRIs.

This was an exploratory analysis of data collected at a single time point, for a study which had a different primary aim. Therefore, the results may not reflect causal relationships, and require validation in future prospective studies. Furthermore, the data were self-reported by internet users, which could affect integrity of the dataset and limit generalisability of the results.

Our findings suggest that demographic, personality, and symptom data may offer a potential cost-effective and efficient framework for SSRI treatment outcome prediction.

Antidepressant efficacy in people with major depressive disorder (MDD) remains modest, yet identifying treatment predictive neurobiological markers may improve outcomes. While disruptions in functional connectivity within and between large-scale brain networks predict poorer treatment outcome, it is unclear whether higher trait neuroticism - which has been associated with generally poorer outcome - contributes to these disruptions and to antidepressant-specific treatment outcomes. Here, we used whole-brain functional connectivity analysis to identify a neural connectomic signature of neuroticism and tested whether this signature predicted antidepressant treatment outcome.

Participants were 229 adults with MDD and 68 healthy controls who underwent functional MRI and were assessed on clinical features at baseline. MDD participants were then randomized to one of three commonly prescribed antidepressants and after 8 weeks completed a second functional MRI and were reassessed for depressive symptom remission/response. Baseline intrinsic functional connectivity between each pair of 436 brain regions were analysed using network-based statistics to identify connectomic features associated with neuroticism. Features were then assessed on their ability to predict treatment outcome and whether they changed after 8 weeks of treatment.

Higher baseline neuroticism was associated with greater connectivity within and between the salience, executive control, and somatomotor brain networks. Greater connectivity across these networks predicted poorer treatment outcome that was not mediated by baseline neuroticism, and connectivity strength decreased after antidepressant treatment.

Our findings demonstrate that neuroticism is associated with organization of intrinsic neural networks that predict treatment outcome, elucidating its biological underpinnings and opportunity for better treatment personalization.

Taking a developmental perspective, guided by core principles of developmental science and developmental psychopathology, is necessary to move the fields of personality science and psychopathology forward. Personality and psychopathology can be delineated using hierarchical models of individual differences, as evidenced by decades of converging evidence across community and psychiatric samples, countries and cultures, and ages and developmental periods. A large body of empirical research likewise documents associations between personality and various forms of psychopathology. Cross-sectional investigations of personality-psychopathology links in samples of adults now yield diminishing returns. Prospective, longitudinal investigations that assess personality, psychopathology, and their co-development across the life span are needed to determine their temporal ordering, capture dynamic associations over time and development, and elucidate causal origins and underlying mechanisms. We lay out a developmental framework that integrates across the developmental, personality, and psychopathology literatures in order to further understanding and guide future investigations of the nature of personality-psychopathology links.

One of the biggest threats to modern societies is the increasing prevalence of mood disorders. Cognitive deficits associated with depressive and bipolar disorders are a major driver of functional impairment and the ensuing disability of the suffering individuals. Growing evidence has indicated strong inter-individual differences in the vulnerability to development and effectivity of treatment of these psychiatric conditions, linking various levels of reinforcement sensitivity with specific mood conditions. In this study, we took a unique opportunity to investigate how trait sensitivity to reinforcement determines the reactivity of rats to acute antidepressant treatment. For this, using a preclinical version of the probabilistic reversal-learning (PRL) paradigm, we identified 4 phenotypes of sensitivity to negative and positive feedback in rats, which could represent various types of potential vulnerability to affective disorders. Subsequently, using the light/dark box (LDB) and progressive ratio schedule of reinforcement (PRSR) tests, we evaluated inter-phenotypic differences in the effects of acute treatment with 3 different antidepressant drugs (escitalopram, mirtazapine and clomipramine, each in 3 doses) on anxiety and appetitive motivation of experimental animals. We report statistically significant differences between the investigated phenotypes of reinforcement sensitivity in the effects of acute escitalopram treatment on anxiety in the LDB test. We also report phenotype-independent effects of mirtazapine on motivation and anxiety and a lack of effect of clomipramine. These results demonstrate for the first time that trait sensitivity to reinforcement could have important implications for the effectiveness of treatment in affective disorders.

Using a factor mixture model (FMM) approach, this study examined if SAD could be subtyped by distinct risk profiles, and whether these subtypes predicted different manifestations of the disorder. We derived risk profiles from neurotic temperament (NT), positive temperament (PT), and autonomic arousability (AA), which are hypothesized to be important in the maintenance of anxiety disorders such as SAD. In our sample of 758 SAD outpatients, a two-class FMM solution fit the data best. Class 1 was characterized by very low PT whereas PT in Class 2 was substantially higher. The two classes differed to a lesser extent on NT, but were virtually equivalent on AA. Class 1 had significantly more males, individuals with depressive disorders, generalized SAD, and higher SAD severity. Class 2 had more individuals with performance subtype SAD. These findings provide initial support for distinct risk profiles within SAD that may be predictive of its clinical expression.

Personality functioning is predictive of drug misuse and relapse, yet little is known about the role of personality in engagement with the treatment process. This study aimed to estimate the extent to which broad- and facet-level characteristic adaptations contribute to or hinder treatment engagement, while controlling for psychosocial indicators.

Multi-site cross-sectional survey.

In-patient treatment units covering 80% of residential treatment entries in Greece.

A total of 338 service users, 287 (84.9%) male, 51 (15.1%) female, average age 33.4 years.

Expressions of personality functioning (characteristic adaptations) were assessed using the Severity Indices of Personality Problems (SIPP-118). Treatment engagement was measured using the Client Evaluation of Self and Treatment, in-patient version (CEST).

Dysfunctional levels of relational capacities predicted counselling rapport [β = 1.50, 95% confidence interval (CI) = 0.326-2.69, P = 0.013], treatment participation (β = 2.09, 95% CI = 1.15-3.11, P < 0.001) and treatment satisfaction (β = 1.65, 95% CI = 0.735-2.57, P < 0.001). Counselling rapport was also predicted by dysfunctional levels in self-control (β = 1.78, 95% CI = 0.899-2.67, P < 0.001), self-reflective functioning at the facet-level (β = 2.24, 95% CI = 1.01-3.46, P < 0.001) and aggression regulation (β = 1.43, 95% CI = 0.438-2.42, P = 0.005). Dysfunctional levels on social concordance (β = -1.90, 95% CI = -2.87 to -0.941, P = 0.001), emotional regulation (β = 1.90, 95% CI = 0.87-2.92, P < 0.001) and intimacy (β = 2.04, 95% CI = 1.31-3.05, P < 0.001) were significant predictors of treatment participation. Treatment readiness and desire for help predicted treatment engagement.

In people attending substance use treatment services, maladaptive interpersonal patterns and relational intimacy, emotional dysregulation and impulse control may be associated with low levels of counselling rapport and treatment participation. Low frustration tolerance and aggressive impulses also appeared to predict low participation.

There is a lack of prospective studies that test pre-specified hypotheses on the role of personality traits in outpatient psychotherapy. A total of 47 patients with a broad range of psychopathological syndromes were enrolled in a prospective 6-month observational study conducted in Zurich, Switzerland. We found evidence for remarkably high differential stability in all Big Five personality traits during the first 6 months of psychotherapy. Mean-level stability was very high in agreeableness and conscientiousness, while modest changes were observed in neuroticism, extraversion and openness. Baseline scores in neuroticism and conscientiousness at the beginning of therapy predicted modest change in self-reported severity of psychopathology over 6 months, but no effect was found in association with therapist-rated functional deficits. We conclude that personality trait levels may change slightly over the course of 6 months of psychotherapy and that both neuroticism and conscientiousness may have weak associations with the self-perceived improvement in psychopathology.

Psychotic disorders have varied clinical presentations, diagnostic stability is poor and other mental disorders often co-occur with the conditions. To improve the clinical and pathophysiological utility of classification systems for psychosis, it is necessary to consider how symptoms may reflect dimensions of psychopathology that extend beyond the boundaries of traditional diagnostic classifications. We examined personality deviation as a means for explaining symptom variation across individuals with serious mental illness. Participants (N = 312) with psychosis, first-degree biological relatives and healthy controls underwent comprehensive clinical evaluations that included symptom ratings and Diagnostic Statistical Manual consensus diagnoses. They completed the Personality Inventory for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (PID-5), which provides multidimensional assessment of personality disturbances and characterizes psychosis-relevant phenomena, and the Schizotypal Personality Questionnaire (SPQ), a widely accepted measure of schizotypal traits. PID-5 was comparable with SPQ in differentiating between participants with and without psychosis. Greater psychotic symptomatology and higher scores on the SPQ Cognitive-perceptual dimension were associated with higher scores on PID-5 Psychoticism. Facet-level traits showed diverse associations with existing clinical syndromes, suggesting they have utility for quantifying separable symptom dimensions that cut across existing disorders. Yet the patient groups were similar across four of the five PID-5 personality trait domains, indicating shared patterns of personality expression that challenge existing categorical delineations. © 2019 John Wiley & Sons, Ltd.

Few studies focused on the relationship between psychological measures, major depressive disorder (MDD) and repetitive transcranial magnetic stimulation (rTMS) response. This study investigated several psychological measures as potential predictors for rTMS treatment response. Additionally, this study employed two approaches to evaluate the robustness of our findings by implementing immediate replication and full-sample exploration with strict p-thresholding.

This study is an open-label, multi-site study with a total of 196 MDD patients. The sample was subdivided in a Discovery (60% of total sample, n = 119) and Replication sample (40% of total sample, n = 77). Patients were treated with right low frequency (1 Hz) or left high frequency (10 Hz) rTMS at the dorsolateral prefrontal cortex. Clinical variables [Beck Depression Inventory (BDI), Neuroticism, Extraversion, Openness Five-Factor Inventory, and Depression, Anxiety, and Stress Scale, and BDI subscales] were obtained at baseline, post-treatment, and at follow-up. Predictors were analyzed in terms of statistical association, robustness (independent replication), as well as for their clinical relevance [positive predictive value (PPV) and negative predictive value (NPV)].

Univariate analyses revealed that non-responders had higher baseline anhedonia scores. Anhedonia scores at baseline correlated negatively with total BDI percentage change over time. This finding was replicated. However, anhedonia scores showed to be marginally predictive of rTMS response, and neither PPV nor NPV reached the levels of clinical relevance.

This study suggests that non-responders to rTMS treatment have higher baseline anhedonia scores. However, anhedonia was only marginally predictive of rTMS response. Since all other psychological measures did not show predictive value, it is concluded that psychological measures cannot be used as clinically relevant predictors to rTMS response in MDD.

Internet-based cognitive behavioral therapy (ICBT) for bulimic eating disorders has demonstrated clinical utility and cost efficiency, but is associated with low patient preference, low credibility, sizeable dropout and only moderate symptom reduction. To improve outcome it is imperative to learn more about who might benefit from internet-based interventions. To do this, the current study investigated the Five Factor Model of personality as predictor of outcome in patients with full or sub-threshold bulimia nervosa (n = 109). Patients in a randomized controlled trial of ICBT were assessed prior to and at the end of treatment. Patients showed significant symptom reduction over time (Cohen's d = 1.0, p < .001). Remission as well as overall symptom reduction was positively predicted by Openness to Experience and Conscientiousness. Binge eating cessation specifically, was positively predicted by Extraversion. The study supports the use of personality assessment for patient selection and outcome optimization in internet-based treatment of bulimic eating disorders.

Generalized anxiety disorder (GAD) is a prevalent and chronic mental disorder that elicits widespread functional impairment. Given the high degree of non-response/partial response among patients with GAD to available pharmacological treatments, there is a strong need for novel approaches that can optimize outcomes, and lead to medications that are safer and more effective. Although investigations have identified interesting targets predicting treatment response through pharmacogenetics (PGx), pharmaco-epigenetics, and neuroimaging methods, these studies are often solitary, not replicated, and carry several limitations. This review provides an overview of the current status of GAD genetics and PGx and presents potential strategies to improve treatment response by combining better phenotyping with PGx and improved analytical methods. These strategies carry the dual benefit of delivering data on biomarkers of treatment response as well as pointing to disease mechanisms through the biology of the markers associated with response. Overall, these efforts can serve to identify clinical, genetic, and epigenetic factors that can be incorporated into a pharmaco(epi)genetic test that may ultimately improve treatment response and reduce the socioeconomic burden of GAD.

Substantial heterogeneity exists in both the severity of symptoms experienced as part of the sickness response to naturally-occurring infections, and the time taken for individuals to recover from these symptoms. Although contributing immunological and genetic factors have been previously been explored, less is known about the role of individual psychological and psychosocial factors, which may modulate the host immune response, or contribute independently, to symptom severity and duration.

Longitudinally-collected data from 484 Caucasian participants (mean age: 33.5 years; 51% women) experiencing a naturally-occurring acute infective illness enrolled in the prospective Dubbo Infection Outcome Study (DIOS) were analysed. At intake and subsequent follow-up assessments, self-report questionnaires were used to ascertain individual psychological and psychosocial characteristics and symptom information. Principal component analysis was applied to symptom data to derive endophenotype severity scores representing discrete symptom domains (fatigue, mood, pain, neurocognitive difficulties) and an overall index of severity. The contribution of individual psychological (trait neuroticism, locus of control, and illness behaviours) and psychosocial factors (relative socioeconomic advantage) to endophenotype severity at baseline were examined using multivariable linear regression models; interval-censored flexible parametric proportional hazards survival models were used to explore time to recovery (defined using within-sample negative threshold values).

After controlling for time since symptom onset, greater levels of trait neuroticism consistently predicted greater symptom severity across all symptom domains (all p's < 0.015). Similarly, greater relative socioeconomic disadvantage was significantly associated with greater severity across all endophenotypes (p's < 0.025) except neurocognitive disturbance. Locus of control and illness behaviours contributed differentially across endophenotypes. Reduced likelihood of recovery was significantly predicted by greater initial symptom severity for all endophenotypes (all p's < 0.001), as well as higher levels of trait neuroticism.

Individual psychological and psychosocial factors contribute to the initial severity and to the prolonged course of symptoms after naturally-occurring infective illnesses. These factors may play an independent role, represent a bias in symptom reporting, or reflect increased stress responsivity and a heightened inflammatory response. Objective metrics for severity and recovery are required to further elucidate their roles.

Two core features of depression include depressed mood (heightened distress) and anhedonia (reduced pleasure). Despite their centrality to depression, studies have not examined their contribution to treatment outcomes in a randomized clinical trial providing mainstream treatments like antidepressant medications (ADM) and cognitive therapy (CT). We used baseline distress and anhedonia derived from a factor analysis of the Mood and Anxiety Symptom Questionnaire to predict remission and recovery in 433 individuals with recurrent/chronic major depressive disorder. Patients were provided with only ADM or both ADM and CT. Overall, higher baseline distress and anhedonia predicted longer times to remission within one year and recovery within three years. When controlling for treatment condition, distress improved prediction of outcomes over and above anhedonia, while anhedonia did not improve prediction of outcomes over and above distress. Interactions with treatment condition demonstrated that individuals with higher distress and anhedonia benefited from receiving CT in addition to ADM, whereas there was no added benefit of CT for individuals with lower distress and anhedonia. Assessing distress and anhedonia prior to treatment may help select patients who will benefit most from CT in addition to ADM. For the treatments and outcome measures tested, utilizing distress to guide treatment planning may yield the greatest benefit. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT00057577.

Serotonin reuptake inhibitors (SRIs) are the first-line pharmacotherapy for body dysmorphic disorder (BDD), a common and severe disorder. However, predictors and correlates of treatment response are not well understood. A closer examination of baseline personality dimensions and disorders and of changes in personality during SRI treatment is needed to advance knowledge of this clinically important issue.

We conducted a secondary analysis of data from a pharmacotherapy relapse prevention trial of the SRI escitalopram in adults with BDD to examine personality dimensions and traits, as well as whether these variables predict and correlate with treatment response. A total of 65 participants with BDD completed the Revised NEO Personality Inventory (NEO PI-R) before starting open-label treatment with escitalopram and 42 participants completed the NEO PI-R after treatment.

At baseline, participants with BDD displayed higher levels of neuroticism and lower levels of extraversion than a normed reference group. Higher baseline neuroticism was a significant predictor of nonresponse to escitalopram treatment, even when baseline depression severity was controlled for. Changes in neuroticism were not associated with treatment response.

Our findings underscore the relationship between BDD and neuroticism, and they suggest a link between neuroticism and SRI treatment response.

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.

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.

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.

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.

The large between-person differences in symptomatology suggest that major depressive disorder (MDD) is a heterogeneous psychiatric disorder. However, symptom-specific prospective studies are scarce. We hypothesized that chronicity (i.e., being depressed for 24 months during a patient's preceding 48 months at baseline) and neuroticism at baseline would predict adverse course trajectories over 9 years of follow up with differential magnitudes for individual depressive symptoms.

In total, 560 patients with a current MDD were included from the Netherlands Study of Depression and Anxiety (NESDA-cohort). We used a multivariate linear mixed model with repeated measures, with a history of chronicity and neuroticism separately as main independent variables and with Inventory of Depressive Symptomatology self-report (IDS-SR) item scores as outcome variables. For each individual symptom, the model was adjusted for age, gender, and baseline depression severity.

Patients were on average 42.7 (SD = 12.1) years old and 64.7% were women. Patients with chronic depression or high levels of neuroticism showed similar absolute rates of decline over time compared to their counterparts. However, because symptoms had higher starting points for mood, cognitive, and somatic/vegetative symptoms (in that order), symptom severity remained higher over time. Chronicity and neuroticism were especially linked to persistent low self-esteem and high interpersonal sensitivity.

Neuroticism is partly state dependent and likely affected by depression severity.

Chronicity and neuroticism predict long-term persistence of diverse psychiatric symptoms, in particular low self-esteem and high interpersonal sensitivity.

Chronic Major Depressive Disorder (CMDD) is a common, disabling illness that is often complicated by high reactivity to social stress. To further elucidate the nature of this reactivity, the current study evaluated whether the personality dimensions of neuroticism and extraversion influenced cortisol responses to a social challenge in CMDD patients vs. controls.

Fifty participants with CMDD and 58 healthy controls completed the Trier Social Stress Test (TSST) using a standard protocol. Neuroticism and extraversion were measured using the Revised NEO Personality Inventory. Hierarchical linear regressions assessed associations between independent variables neuroticism and extraversion and dependent variable cortisol area-under-the-curve increase (AUCi) in response to the TSST in the two study groups.

The extraversion-by-group interaction was a significant predictor of cortisol AUCi, while no significant findings related to neuroticism were found. Simple slopes analysis revealed a significant negative association between extraversion and AUCi in the CMDD group, but not in healthy controls. Post-hoc analysis of the raw cortisol data over time found that CMDD participants with higher extraversion scores had significantly higher pre-challenge cortisol levels than did other study participants, however this did not explain or confound the AUCi results.

In participants with CMDD but not in controls, higher levels of extraversion were associated with higher pre-challenge cortisol levels and decreased cortisol reactivity during the TSST, however these two findings were statistically independent. These findings underline the importance of considering personality factors when studying stress biology in CMDD patients. Extraversion may prove to be an important intermediate target for both research and clinical work in this complex, heterogenous and often treatment-resistant population.

High frequency repetitive transcranial magnetic stimulation (HF-rTMS) delivered to the left dorsolateral prefrontal cortex (DLPFC) is an effective treatment option for treatment resistant depression. However, the underlying mechanisms of a full session of HF-rTMS in healthy volunteers have not yet been described. Here we investigated, with a personalized selection of DLPFC stimulation sites, the effects driven by HF-rTMS in healthy volunteers (n = 23) over the default mode network (DMN) in multiple time windows. After a complete 10 Hz rTMS (3000 pulses) session, we observe a decrease of functional connectivity between the DMN and the subgenual Anterior Cingulate Cortex (sgACC), as well as the ventral striatum (vStr). A negative correlation between the magnitude of this decrease in the right sgACC and the harm avoidance domain measure from the Temperament and Character Inventory was observed. Moreover, we identify that coupling strength of right vStr with the DMN post-stimulation was proportional to a decrease in self-reports of negative mood from the Positive and Negative Affect Schedule. This shows HF-rTMS attenuates perception of negative mood in healthy recipients in agreement with the expected effects in patients. Our study, by using a personalized selection of DLPFC stimulation sites, contributes understanding the effects of a full session of rTMS approved for clinical use in depression over related brain regions in healthy volunteers.

Major depressive disorder (MDD) is one of the most well-known psychiatric disorders, which can be destructive for its damage to people's normal cognitive, emotional and social functions. Personality refers to the unique and stable character of thinking and behavior style of an individual, which has long been thought as a key influence factor for MDD. Although some knowledge about the common neural basic between MDD and personality traits has been acquired, there are few studies exploring dynamic neural mechanism behind them, which changes brain connectivity pattern rapidly to adapt to the environment over time.

In this study, the emerging dynamic functional network connectivity (DFNC) method was used in resting-state fMRI data to find the differences between healthy group (N = 107) and MDD group (N = 109) in state-based dynamic measures, and the correlations between these measures and personality traits (extraversion and neuroticism in Eysenck Personality Questionnaire, EPQ) were explored.

The results showed that MDD was significantly less than the health control group in dwell time and fraction time of state 4, which was positively correlated with extraversion score and negatively correlated with neuroticism score. Further exploration on state 4 showed that it had low modularity, hyper-connectedness of sensory-related regions and DMN, and weak connections between cortex and subcortical areas, which suggested that the absence of this state in MDD might represent a decrease in activity and positive emotions.

We found the dynamic functional connectivity mechanism underlying MDD, confirmed our hypothesis that there existed the interacted relationship between trait, disease and the brain's dynamic characteristic, and suggested some reference for treatment of depression.

The aim of this retrospective cohort study was to examine if interpreter-mediated psychotherapy with trauma-affected refugees affects treatment outcome. The clinical sample consisted of 825 patients who, as part of treatment, were offered 16 sessions of cognitive behavioural therapy. The cohort was allocated to two subsamples based on whether interpreters were used in psychotherapy or not and the treatment outcome for the two subsamples was compared. The primary outcome measure was severity of PTSD-symptoms (Harvard Trauma Questionnaire (HTQ)) and secondary outcome measures were depression and anxiety symptoms (Hopkins Symptom Checklist-25 (HSCL-25), Hamilton Depression and Anxiety rating scales (HAM-D, HAM-A)), somatisation (somatisation items of SCL-90 (SI-SCL-90)), quality of life (WHO-5-Well-being Index (WHO-5)) and functioning (Sheehan Disability Scale (SDS), Global Assessment of Functioning (GAF-F, GAF-S)). Compared to no use of interpreter, the use of interpreter in psychotherapy was associated with less improvement during treatment on the primary outcome measure HTQ and the secondary outcome measures HSCL-25, SI-SCL-90, SDS, WHO-5, HAM-A, but not on GAF-S, GAF-F and HAM-D. Based on the primary outcome measure HTQ and the majority of the secondary ratings the subsample in interpreter-mediated psychotherapy had less improvement in their mental health status compared to the subsample without interpreter.

Internet-based cognitive behavioral therapy (iCBT), provided with guidance, has been shown to outperform wait-list control conditions and appears to perform on par with face-to-face psychotherapy. However, dropout remains an important problem. Dropout rates for iCBT programs for depression have ranged from 0% to 75%, with a mean of 32%. Drawing from a recent study in which 117 people participated in iCBT with support, we examined participant characteristics, participants' use of iCBT skills, and their experience of technical difficulties with iCBT as predictors of dropout risk. Educational level, extraversion, and participant skill use predicted lower risk of dropout; technical difficulties and openness predicted higher dropout risk. We encourage future research on predictors of dropout in the hope that greater understanding of dropout risk will inform efforts to promote program engagement and retention.

Personality is an important contributor to an individual's mental health and is consistently linked to the two most prevalent mental health conditions among older adults: dementia and depression. This review summarizes the current findings on personality and its association with cognitive decline and depression, as well as treatment outcomes and possible intervention strategies.

Literature searches were conducted in Web of Science, PubMed, and PsycINFO. Search terms included 'personality traits,' 'depression,' 'treatment,' and 'older adults.'

Cognitive decline and depressive disorders are both associated with a common personality profile: high neuroticism, and low conscientiousness, extraversion, openness, and agreeableness. Across studies, the most consistent predictor of late-life depression, its course, and treatment outcomes is higher neuroticism.

Personality traits are associated with cognitive decline, as well as the diagnosis and course of late-life depression in older adults. However, formal personality assessment is not typically incorporated in clients' treatment plans, even though personality traits may influence treatment efficacy and outcomes.

Formal assessment of personality traits may be beneficial in terms of treatment adherence and outcomes for older adults. Tailored interventions that specifically target the client's strengths are likely to be well received by both clients and clinicians.

Selective serotonin re-uptake inhibitors (SSRI) have proven to be effective in treatment of depression. Still, treatment efficacy varies significantly from patient to patient and about 40% of patients do not respond to initial treatment. Personality traits have been considered one source of variability in treatment outcome.

Current study aimed at identifying specific personality traits that could be predictive of treatment response and/or the dynamics of symptom change in depressive patients.

In a sample of 132 outpatients with major depressive disorder (MDD) treated with an SSRI-group antidepressant escitalopram, the Swedish universities Scales of Personality (SSP) were used in order to find predictive personality traits. For the assessment of the severity of depressive symptoms and the improvement rates, the Hamilton Depression Scale (HAM-D) and Montgomery-Åsberg Depression Rating Scale (MADRS) were used.

Escitalopram-treated MDD patients with higher social desirability achieved more rapid decrease in symptom severity. None of the studied traits predicted the end result of the treatment.

The findings suggest that specific personality traits may predict the trajectory of symptom change rather than the overall improvement rate.

Optimal patient care in psychiatry necessitates attention to the treatment relationship and to the patient's experience as an individual. The growth of patient-centered medicine has led to an increased appreciation of the importance of the biopsychosocial formulation, the personhood of both the patient and the physician, the autonomy and authority of the patient, and the therapeutic alliance. Patient-centered medicine, developed by the seminal psychoanalytic theorist Michael Balint, has its roots in psychodynamic concepts. A psychodynamic approach to psychopharmacology improves psychiatric prescribing, and guides the psychiatrist in providing brief, limited psychotherapy, similar to that which the Balints recommended in primary care practice.

Despite its demonstrated empirical superiority over the DSM-5 Section 2 categorical model of personality disorders for organizing the features of personality pathology, limitations remain with regard to the translation of the DSM-5 Section 3 alternative model of personality disorders (AMPD) to clinical practice. The goal of this paper is to outline a general and preliminary framework for approaching treatment from the perspective of the AMPD. Specific techniques are discussed for the assessment and treatment of both Criterion A personality dysfunction and Criterion B maladaptive traits. A concise and step-by-step model is presented for clinical decision making with the AMPD, in the hopes of offering clinicians a framework for treating personality pathology and promoting further research on the clinical utility of the AMPD. Copyright © 2018 John Wiley & Sons, Ltd.

Studies reported a strong genetic correlation between the Big Five personality traits and major depressive disorder (MDD). Moreover, personality traits are thought to be associated with response to antidepressants treatment that might partly be mediated by genetic factors. In this study, we examined whether polygenic scores (PGSs) derived from the Big Five personality traits predict treatment response and remission in patients with MDD who were prescribed selective serotonin reuptake inhibitors (SSRIs). In addition, we performed meta-analyses of genome-wide association studies (GWASs) on these traits to identify genetic variants underpinning the cross-trait polygenic association. The PGS analysis was performed using data from two cohorts: the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS, n = 529) and the International SSRI Pharmacogenomics Consortium (ISPC, n = 865). The cross-trait GWAS meta-analyses were conducted by combining GWAS summary statistics on SSRIs treatment outcome and on the personality traits. The results showed that the PGS for openness and neuroticism were associated with SSRIs treatment outcomes at p < 0.05 across P_T thresholds in both cohorts. A significant association was also found between the PGS for conscientiousness and SSRIs treatment response in the PGRN-AMPS sample. In the cross-trait GWAS meta-analyses, we identified eight loci associated with (a) SSRIs response and conscientiousness near YEATS4 gene and (b) SSRI remission and neuroticism eight loci near PRAG1, MSRA, XKR6, ELAVL2, PLXNC1, PLEKHM1, and BRUNOL4 genes. An assessment of a polygenic load for personality traits may assist in conjunction with clinical data to predict whether MDD patients might respond favorably to SSRIs.