Pick Topic
Review Topic
List Experts
Examine Expert
Save Expert
  Site Guide ··   
Depression: HELP
Articles by Albert M. van Hemert
Based on 45 articles published since 2010
(Why 45 articles?)
||||

Between 2010 and 2020, A. van Hemert wrote the following 45 articles about Depression.
 
+ Citations + Abstracts
Pages: 1 · 2
1 Review Huntingtin gene repeat size variations affect risk of lifetime depression. 2017

Gardiner, Sarah L / van Belzen, Martine J / Boogaard, Merel W / van Roon-Mom, Willeke M C / Rozing, Maarten P / van Hemert, Albert M / Smit, Johannes H / Beekman, Aartjan T F / van Grootheest, Gerard / Schoevers, Robert A / Oude Voshaar, Richard C / Roos, Raymund A C / Comijs, Hannie C / Penninx, Brenda W J H / van der Mast, Roos C / Aziz, N Ahmad. ·Departments of Neurology, Leiden University Medical Centre, Leiden, The Netherlands. · Departments of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands. · Departments of Clinical Genetics, and Leiden University Medical Centre, Leiden, The Netherlands. · Department of Public Health, Section of Social Medicine, University of Copenhagen, Copenhagen, Denmark. · Departments of Psychiatry, Leiden University Medical Centre, Leiden, The Netherlands. · Department of Psychiatry, and EMGO Institute for Health and Care Research and Neuroscience Campus Amsterdam, VU University Medical Center/GGZ inGeest, Amsterdam, The Netherlands. · Department of Psychiatry, University Medical Centre Groningen, Groningen, The Netherlands. · Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, Antwerp, Belgium. · Departments of Neurology, Leiden University Medical Centre, Leiden, The Netherlands. N.A.Aziz@lumc.nl. · Department of Neurodegenerative Disease, UCL Huntington's Disease Centre, University College London Institute of Neurology, London, United Kingdom. N.A.Aziz@lumc.nl. ·Transl Psychiatry · Pubmed #29225330.

ABSTRACT: Huntington disease (HD) is a severe neuropsychiatric disorder caused by a cytosine-adenine-guanine (CAG) repeat expansion in the HTT gene. Although HD is frequently complicated by depression, it is still unknown to what extent common HTT CAG repeat size variations in the normal range could affect depression risk in the general population. Using binary logistic regression, we assessed the association between HTT CAG repeat size and depression risk in two well-characterized Dutch cohorts─the Netherlands Study of Depression and Anxiety and the Netherlands Study of Depression in Older Persons─including 2165 depressed and 1058 non-depressed persons. In both cohorts, separately as well as combined, there was a significant non-linear association between the risk of lifetime depression and HTT CAG repeat size in which both relatively short and relatively large alleles were associated with an increased risk of depression (β = -0.292 and β = 0.006 for the linear and the quadratic term, respectively; both P < 0.01 after adjustment for the effects of sex, age, and education level). The odds of lifetime depression were lowest in persons with a HTT CAG repeat size of 21 (odds ratio: 0.71, 95% confidence interval: 0.52 to 0.98) compared to the average odds in the total cohort. In conclusion, lifetime depression risk was higher with both relatively short and relatively large HTT CAG repeat sizes in the normal range. Our study provides important proof-of-principle that repeat polymorphisms can act as hitherto unappreciated but complex genetic modifiers of depression.

2 Review [Emotional scars: impact of childhood trauma on the development of depressive and anxiety disorders later in life]. 2017

Hovens, J G F M / Giltay, E J / van Hemert, A M / Penninx, B W J H. · ·Tijdschr Psychiatr · Pubmed #28593622.

ABSTRACT: BACKGROUND: Childhood trauma and negative life events in childhood are risk factors for the development of anxiety and depressive disorders in adulthood.
AIM: To increase our understanding of the specific associations between trauma and negative life events in childhood and the development and course of anxiety and depressive disorders in adulthood.
METHOD: Our research findings are based on data from the Netherlands Study of Depression and Anxiety (NESDA). In our article we report on two cross-sectional and three prospective studies.
RESULTS: All domains of childhood trauma are risk factors for the development of anxiety and/or depressive disorders in adulthood. Emotional neglect is the main independent predictor of the occurrence and the course of anxiety and depressive disorders. Certain personality characteristics and more unfavorable clinical factors play an important role in mediating the relationship between childhood trauma and the course of anxiety and depressive disorders later in life.
CONCLUSION: Not only does childhood trauma increase an individual's vulnerability to the development of anxiety and depressive disorders, it is also associated with a more serious and more chronic course of these disorders. Our studies have provided new insights into the underlying mechanism that links childhood trauma and anxiety and later anxiety depressive disorders. Consequently, we feel justified in making some recommendations with regards to clinical practice and public health interventions.

3 Article Trait anger and anger attacks in relation to depressive and anxiety disorders. 2019

de Bles, Nienke J / Rius Ottenheim, Nathaly / van Hemert, Albert M / Pütz, Laura E H / van der Does, A J Willem / Penninx, Brenda W J H / Giltay, Erik J. ·Department of Psychiatry, Leiden University Medical Center, PO Box 9600, 2300 Leiden, the Netherlands. Electronic address: N.J.de_Bles@lumc.nl. · Department of Psychiatry, Leiden University Medical Center, PO Box 9600, 2300 Leiden, the Netherlands. · Department of Clinical Psychology, Leiden University, Leiden, the Netherlands. · Department of Psychiatry, Amsterdam Public Health research institute, Amsterdam UMC, Vrije Universiteit, Amsterdam, the Netherlands. ·J Affect Disord · Pubmed #31450135.

ABSTRACT: BACKGROUND: Patients with various psychiatric disorders may suffer from feelings of anger, sometimes leading to maladaptive (e.g., aggressive) behaviors. We examined to what extent depressive and anxiety disorders, relevant clinical correlates, and sociodemographics determined the level of trait anger and the prevalence of recent anger attacks. METHODS: In the Netherlands Study of Depression and Anxiety (NESDA), the Spielberger Trait Anger Subscale and the Anger Attacks Questionnaire were analyzed in patients with depressive (n = 204), anxiety (n = 288), comorbid (n = 222), and remitted disorders (n = 1,107), as well as in healthy controls (n = 470) based on DSM-IV criteria. RESULTS: On average, participants were 46.2 years old (SD = 13.1) and 66.3% were female. Trait anger and anger attacks were most prevalent in the comorbid group (M = 18.5, SD = 5.9, and prevalence 22.1%), followed by anxiety disorder, depressive disorder, remitted disorder, and controls (M = 12.7; SD = 2.9, and prevalence 1.3%). Major depressive disorder, social phobia, panic disorder, and generalized anxiety disorder were most strongly associated to trait anger and anger attacks. LIMITATIONS: Due to a cross-sectional design, it was not possible to provide evidence for temporal or causal relationships between anger and depressive and anxiety disorders. CONCLUSIONS: Trait anger and anger attacks are linked to depressive and anxiety disorders, although the strength of the relationship differed among both anger constructs.

4 Article Sleep, circadian rhythm, and physical activity patterns in depressive and anxiety disorders: A 2-week ambulatory assessment study. 2019

Difrancesco, Sonia / Lamers, Femke / Riese, Harriëtte / Merikangas, Kathleen R / Beekman, Aartjan T F / van Hemert, Albert M / Schoevers, Robert A / Penninx, Brenda W J H. ·Amsterdam UMC, Vrije Universiteit, Psychiatry, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center for Psychopathology and Emotion Regulation, Groningen, The Netherlands. · Genetic Epidemiology Branch, Intramural Research Program, National Institute of Mental Health, Bethesda, Maryland. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. ·Depress Anxiety · Pubmed #31348850.

ABSTRACT: BACKGROUND: Actigraphy may provide a more valid assessment of sleep, circadian rhythm (CR), and physical activity (PA) than self-reported questionnaires, but has not been used widely to study the association with depression/anxiety and their clinical characteristics. METHODS: Fourteen-day actigraphy data of 359 participants with current (n = 93), remitted (n = 176), or no (n = 90) composite international diagnostic interview depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Objective estimates included sleep duration (SD), sleep efficiency, relative amplitude (RA) between day-time and night-time activity, mid sleep on free days (MSF), gross motor activity (GMA), and moderate-to-vigorous PA (MVPA). Self-reported measures included insomnia rating scale, SD, MSF, metabolic equivalent total, and MVPA. RESULTS: Compared to controls, individuals with current depression/anxiety had a significantly different objective, but not self-reported, PA and CR: lower GMA (23.83 vs. 27.4 milli-gravity/day, p = .022), lower MVPA (35.32 vs. 47.64 min/day, p = .023), lower RA (0.82 vs. 0.83, p = .033). In contrast, self-reported, but not objective, sleep differed between people with current depression/anxiety compared to those without current disorders; people with current depression/anxiety reported both shorter and longer SD and more insomnia. More depressive/anxiety symptoms and number of depressive/anxiety diagnoses were associated with larger disturbances of the actigraphy measures. CONCLUSION: Actigraphy provides ecologically valid information on sleep, CR, and PA that enhances data from self-reported questionnaires. As those with more severe or comorbid forms showed the lowest PA and most CR disruptions, the potential for adjunctive behavioral and chronotherapy interventions should be explored, as well as the potential of actigraphy to monitor treatment response to such interventions.

5 Article Testing for response shift in treatment evaluation of change in self-reported psychopathology amongst secondary psychiatric care outpatients. 2019

Carlier, Ingrid V E / van Eeden, Wessel A / de Jong, Kim / Giltay, Erik J / van Noorden, Martijn S / van der Feltz-Cornelis, Christina / Zitman, Frans G / Kelderman, Henk / van Hemert, Albert M. ·Department of Psychiatry, Leiden University Medical Centre, Leiden, The Netherlands. · Clinical Psychology Unit, Institute of Psychology, Leiden University, Leiden, The Netherlands. · Department of Health Sciences, Hull York Medical School, University of York, Heslington, UK. · Department of Methodology and Statistics, Institute of Psychology, Leiden University, Leiden, The Netherlands. ·Int J Methods Psychiatr Res · Pubmed #31206911.

ABSTRACT: OBJECTIVES: If patients change their perspective due to treatment, this may alter the way they conceptualize, prioritize, or calibrate questionnaire items. These psychological changes, also called "response shifts," may pose a threat to the measurement of therapeutic change in patients. Therefore, it is important to test the occurrence of response shift in patients across their treatment. METHODS: This study focused on self-reported psychological distress/psychopathology in a naturalistic sample of 206 psychiatric outpatients. Longitudinal measurement invariance tests were computed across treatment in order to detect response shifts. RESULTS: Compared with before treatment, post-treatment psychopathology scores showed an increase in model fit and factor loading, suggesting that symptoms became more coherently interrelated within their psychopathology domains. Reconceptualization (depression/mood) and reprioritization (somatic and cognitive problems) response shift types were found in several items. We found no recalibration response shift. CONCLUSION: This study provides further evidence that response shift can occur in adult psychiatric patients across their mental health treatment. Future research is needed to determine whether response shift implies an unwanted potential bias in treatment evaluation or a desired cognitive change intended by treatment.

6 Article Neuroticism and chronicity as predictors of 9-year course of individual depressive symptoms. 2019

van Eeden, Wessel A / van Hemert, Albert M / Carlier, Ingrid V E / Penninx, Brenda W / Spinhoven, Philip / Giltay, Erik J. ·Department of Psychiatry, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, the Netherlands. Electronic address: W.A.van_Eeden@lumc.nl. · Department of Psychiatry, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, the Netherlands. · Department of Psychiatry, Amsterdam Public Health Research Institute and Amsterdam Neuroscience, VU University Medical Center, and GGZ inGeest, Amsterdam, the Netherlands. · Department of Psychiatry, Leiden University Medical Center, PO Box 9600, 2300 RC, Leiden, the Netherlands; Institute of Psychology, Leiden University, Leiden, the Netherlands. ·J Affect Disord · Pubmed #31005791.

ABSTRACT: BACKGROUND: 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. METHODS: 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. RESULTS: 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. LIMITATIONS: Neuroticism is partly state dependent and likely affected by depression severity. CONCLUSIONS: Chronicity and neuroticism predict long-term persistence of diverse psychiatric symptoms, in particular low self-esteem and high interpersonal sensitivity.

7 Article Prediction of prolonged treatment course for depressive and anxiety disorders in an outpatient setting: The Leiden routine outcome monitoring study. 2019

Boer, Suzanne / Dekkers, Olaf M / Cessie, Saskia le / Carlier, Ingrid Ve / van Hemert, Albert M. ·Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands; Department of Psychiatry, Leiden University Medical Centre, Leiden, The Netherlands; Department of Medical Decision Making, Leiden University Medical Centre, Leiden, The Netherlands. Electronic address: s.boer@lumc.nl. · Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands. · Department of Clinical Epidemiology, Leiden University Medical Centre, Leiden, The Netherlands; Department of Medical Statistics and Bio-informatics, Leiden University Medical Centre, Leiden, The Netherlands. · Department of Psychiatry, Leiden University Medical Centre, Leiden, The Netherlands. ·J Affect Disord · Pubmed #30658244.

ABSTRACT: OBJECTIVE: The aim of this study was to improve clinical identification of patients with a prolonged treatment course for depressive and anxiety disorders early in treatment. METHOD: We conducted a cohort study in 1.225 adult patients with a depressive or anxiety disorders in psychiatric specialty care setting between 2007 and 2011, with at least two Brief Symptom Inventory (BSI) assessments within 6 months. With logistic regression, we modelled baseline age, gender, ethnicity, education, marital status, housing situation, employment status, psychiatric comorbidity and both baseline and 1st follow-up BSI scores to predict prolonged treatment course (>2 years). Based on the regression coefficients, we present an easy to use risk prediction score. RESULTS: BSI at 1st follow-up proved to be a strong predictor for both depressive and anxiety disorders (OR = 2.17 (CI95% 1.73-2.74); OR = 2.52 (CI95% 1.86-3.23)). The final risk prediction score included BSI 1st follow-up and comorbid axis II disorder for depressive disorder, for anxiety disorders BSI 1st follow-up and age were included. For depressive disorders, for 28% of the patients with the highest scores, the positive predictive value for a prolonged treatment course was60% (sensitivity 0.38, specificity 0.81). For anxiety disorders, for 35% of the patients with the highest scores, the positive predictive value for a prolonged treatment course was 52% (sensitivity 0.55, specificity 0.75). CONCLUSIONS: A high level of symptoms at 2-6 months of follow-up is a strong predictor for prolonged treatment course. This facilitates early identification of patients at risk of a prolonged course of treatment; in a relatively easy way by a self-assessed symptom severity.

8 Article Repetitive negative thinking as a mediator in prospective cross-disorder associations between anxiety and depression disorders and their symptoms. 2019

Spinhoven, Philip / van Hemert, Albert M / Penninx, Brenda W. ·Leiden University, Institute of Psychology, Leiden, the Netherlands; Leiden University Medical Center, Department of Psychiatry, Leiden, the Netherlands. Electronic address: Spinhoven@FSW.LeidenUniv.NL. · Leiden University Medical Center, Department of Psychiatry, Leiden, the Netherlands. · VU University Medical Center, Department of Psychiatry, Amsterdam, the Netherlands. ·J Behav Ther Exp Psychiatry · Pubmed #30551055.

ABSTRACT: BACKGROUND AND OBJECTIVES: Comorbidity among anxiety and depression disorders and their symptoms is high. Rumination and worry have been found to mediate prospective cross-disorder relations between anxiety and depression disorders and their symptoms in adolescents and adults. We examined whether generic repetitive negative thinking (RNT), that is content- and disorder-independent, also mediates prospective cross-disorder associations between anxiety and depressions disorders and their symptoms. METHODS: This was studied using a 5-year prospective cohort study. In a mixed sample of 1859 adults (persons with a prior history of or a current affective disorder and healthy individuals), we assessed DSM-IV affective disorders (Composite Interview Diagnostic Instrument), anxiety (Beck Anxiety Inventory) and depression symptoms (Inventory of Depressive Symptomatology) and RNT (Perseverative Thinking Questionnaire). RESULTS: We found that baseline depression disorders and symptom severity have predictive value for anxiety disorders and symptom severity five years later (and vice versa) and that these associations were significantly mediated by level of RNT as assessed two years after baseline. The significant and rather large mediation effects seemed mainly due to the mental capacity captured by RNT, especially in the prospective relation of anxiety with future depression. LIMITATIONS: The mediation effects were greatly attenuated or even nullified after rigorously controlling for concomitant psychopathology at two years after baseline. CONCLUSIONS: From these results it can be concluded that repetitive negative thinking could be an important transdiagnostic factor, that may constitute a suitable target for treatment.

9 Article Long-term glucocorticoid levels measured in hair in patients with depressive and anxiety disorders. 2019

Gerritsen, Lotte / Staufenbiel, Sabine M / Penninx, Brenda W J H / van Hemert, Albert M / Noppe, Gerard / de Rijke, Yolanda B / van Rossum, Elisabeth F C. ·Department of Clinical Psychology, Utrecht University, Utrecht, the Netherlands. Electronic address: l.gerritsen@uu.nl. · Department of Internal Medicine, Division of Endocrinology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands. · Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands. · Department of Psychiatry, Leiden University Medical Center, Leiden, the Netherlands. · Department of Internal Medicine, Division of Endocrinology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Clinical Chemistry, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands. ·Psychoneuroendocrinology · Pubmed #30472466.

ABSTRACT: BACKGROUND: Depressive and anxiety disorders have been linked to a dysregulated hypothalamus-pituitary-adrenal (HPA)-axis. Hair cortisol levels (HairF) reflect integrated long-term cortisol regulation and are therefore promising endocrine markers of chronic (psychological and physical) stress. Our aim was to assess hair cortisol levels in persons with a depressive and/or anxiety disorder and to compare their levels with that of persons in remission and healthy controls. METHODS: Data from 1166 participants of the Netherlands Study of Depression and Anxiety (NESDA) were used, including 266 participants with a recent (1-month) diagnosis of a depressive and/or anxiety disorder, 655 participants with a diagnosis in remission, and 245 healthy controls. HairF was measured in the proximal three cm of scalp hair, using LC-MS/MS. RESULTS: Compared to the healthy controls no differences on HairF or HairE levels were found for depressive and anxiety disorders alone. However the presence of a comorbid depressive and anxiety disorder was significantly associated with increased HairF levels (β = 0.07; p = .031), as was the severity of depressive symptoms (β = 0.06; p = .029), but no differences were found on HairE nor the HairF:HairE ratio. CONCLUSIONS: Persons with current diagnosis of comorbid depression and anxiety show moderately higher levels of cortisol than patients with only depression or anxiety, or patients in remission and healthy controls, which may be indicative of a chronic state of hyperactivation of the HPA axis.

10 Article Severity, course trajectory, and within-person variability of individual symptoms in patients with major depressive disorder. 2019

van Eeden, W A / van Hemert, A M / Carlier, I V E / Penninx, B W / Giltay, E J. ·Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · Department of Psychiatry, Amsterdam Public Health Research Institute and Amsterdam Neuroscience, VU University Medical Center, GGZ inGeest, Amsterdam, The Netherlands. ·Acta Psychiatr Scand · Pubmed #30447008.

ABSTRACT: BACKGROUND: Depression shows a large heterogeneity of symptoms between and within persons over time. However, most outcome studies have assessed depression as a single underlying latent construct, using the sum score on psychometric scales as an indicator for severity. This study assesses longitudinal symptom-specific trajectories and within-person variability of major depressive disorder over a 9-year period. METHODS: Data were derived from the Netherlands Study of Depression and Anxiety (NESDA). This study included 783 participants with a current major depressive disorder at baseline. The Inventory Depressive Symptomatology-Self-Report (IDS-SR) was used to analyze 28 depressive symptoms at up to six time points during the 9-year follow-up. RESULTS: The highest baseline severity scores were found for the items regarding energy and mood states. The core symptoms depressed mood and anhedonia had the most favorable course, whereas sleeping problems and (psycho-)somatic symptoms were more persistent over 9-year follow-up. Within-person variability was highest for symptoms related to energy and lowest for suicidal ideation. CONCLUSIONS: The severity, course, and within-person variability differed markedly between depressive symptoms. Our findings strengthen the idea that employing a symptom-focused approach in both clinical care and research is of value.

11 Article Comparing factor structures of depressed patients with and without suicidal ideation, a measurement invariance analysis. 2019

van Ballegooijen, Wouter / Eikelenboom, Merijn / Fokkema, Marjolein / Riper, Heleen / van Hemert, Albert M / Kerkhof, Ad J F M / Penninx, Brenda W J H / Smit, Jan H. ·Amsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam, The Netherlands; GGZ inGeest Specialised Mental Health Care, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands; Vrije Universiteit Amsterdam, Section Clinical Psychology, Amsterdam, The Netherlands. Electronic address: w.van.ballegooijen@vu.nl. · Amsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam, The Netherlands; GGZ inGeest Specialised Mental Health Care, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands. · Leiden University, Department of Methods & Statistics, Leiden, Netherlands. · Amsterdam UMC, Vrije Universiteit, Department of Psychiatry, Amsterdam, The Netherlands; GGZ inGeest Specialised Mental Health Care, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands; Vrije Universiteit Amsterdam, Section Clinical Psychology, Amsterdam, The Netherlands. · Leiden University Medical Centre, Department of Psychiatry, Leiden, Netherlands. · Vrije Universiteit Amsterdam, Section Clinical Psychology, Amsterdam, The Netherlands. ·J Affect Disord · Pubmed #30396056.

ABSTRACT: BACKGROUND: Suicidality could be associated with specific combinations of biological, social and psychological factors. Therefore, depressive episodes with suicidal ideation could be different from depressive episodes without suicidal ideation in terms of latent variable structures. METHODS: In this study we compared latent variable structures between suicidal and non-suicidal depressed patients using confirmatory factor analysis (CFA), following a measurement invariance test procedure. Patients (N = 919) suffering from major depressive disorder were selected from the Netherlands Study of Depression and Anxiety (NESDA) and split into a group that showed no symptoms of suicidal ideation (non-SI; N = 691) and a suicidal ideation (SI) group that had one or more symptoms of suicidal ideation (N = 228). Depression and anxiety symptoms were measured using the short form of the Mood and Anxiety Symptoms Questionnaire (MASQ-D30). RESULTS: CFA implied a difference in latent variable structures between the non-SI sample (CFI 0.957; RMSEA 0.041) and the SI sample (CFI 0.900; RMSEA 0.056). Subsequent multiple-group CFA showed violations of measurement invariance. The General distress and Anhedonic depression subscales were best indicated by hopelessness and lack of optimism in the SI sample and by dissatisfaction and not feeling lively in the non-SI sample. Overall, the SI sample had higher scores and lower inter-item correlations on the Anhedonic depression items. LIMITATIONS: We have included very mild cases of suicidal ideation in our SI sample. CONCLUSIONS: On a latent variable level, depression with suicidal ideation differs from depression without suicidal ideation. Results encourage further research into the symptom structure of depression among suicidal patients.

12 Article Comparative responsiveness of generic versus disorder-specific instruments for depression: An assessment in three longitudinal datasets. 2019

de Beurs, Edwin / Vissers, Ellen / Schoevers, Robert / Carlier, Ingrid V E / van Hemert, Albert M / Meesters, Ybe. ·Faculty of Clinical Psychology, Leiden University, Leiden, The Netherlands. · Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. ·Depress Anxiety · Pubmed #30188602.

ABSTRACT: BACKGROUND: Routine outcome monitoring (ROM) may enhance individual treatment and is also advocated as a means to compare the outcome of different treatment programs or providers. There is debate on the optimal instruments to be used for these separate tasks. METHODS: Three sets with longitudinal data from ROM were analyzed with correlational analysis and repeated measures ANOVAs, allowing for a head-to-head comparison of measures regarding their sensitivity to detect change. The responsiveness of three disorder-specific instruments, the Beck Depression Inventory, the Inventory of Depressive Symptoms, and the Mood and Anxiety Symptoms Questionnaire, was compared to three generic instruments, the Symptom Checklist (SCL-90), the Outcome Questionnaire (OQ-45), and the Brief Symptom Inventory, respectively. RESULTS: In two of the three datasets, disorder-specific measures were more responsive compared to the total score on generic instruments. Subscale scores for depression embedded within generic instruments are second best and almost match disorder-specific scales in responsiveness. No evidence of a desynchronous response on outcome measures was found. LIMITATIONS: The present study compares measures head-to-had, and responsiveness is not assessed against an external criterion, such as clinical recovery. DISCUSSION: Disorder-specific measures yield the most precise assessment for individual treatment and are recommended for clinical use. Generic measures may allow for comparisons across diagnostic groups and their embedded subscales approach the responsiveness of disorder-specific measures.

13 Article Predicting the naturalistic course of depression from a wide range of clinical, psychological, and biological data: a machine learning approach. 2018

Dinga, Richard / Marquand, Andre F / Veltman, Dick J / Beekman, Aartjan T F / Schoevers, Robert A / van Hemert, Albert M / Penninx, Brenda W J H / Schmaal, Lianne. ·Department of Psychiatry and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands. · Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands. · Department of Neuroimaging, Institute of Psychiatry, King's College London, London, United Kingdom. · University Medical Center Groningen, Department of Psychiatry, Research School of Behavioural and Cognitive Neurosciences (BCN), University of Groningen, Groningen, The Netherlands. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · Department of Psychiatry and Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands. lianne.schmaal@unimelb.edu.au. · Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, VIC, Australia. lianne.schmaal@unimelb.edu.au. · Centre for Youth Mental Health, The University of Melbourne, Melbourne, VIC, Australia. lianne.schmaal@unimelb.edu.au. ·Transl Psychiatry · Pubmed #30397196.

ABSTRACT: Many variables have been linked to different course trajectories of depression. These findings, however, are based on group comparisons with unknown translational value. This study evaluated the prognostic value of a wide range of clinical, psychological, and biological characteristics for predicting the course of depression and aimed to identify the best set of predictors. Eight hundred four unipolar depressed patients (major depressive disorder or dysthymia) patients were assessed on a set involving 81 demographic, clinical, psychological, and biological measures and were clinically followed-up for 2 years. Subjects were grouped according to (i) the presence of a depression diagnosis at 2-year follow-up (yes n = 397, no n = 407), and (ii) three disease course trajectory groups (rapid remission, n = 356, gradual improvement n = 273, and chronic n = 175) identified by a latent class growth analysis. A penalized logistic regression, followed by tight control over type I error, was used to predict depression course and to evaluate the prognostic value of individual variables. Based on the inventory of depressive symptomatology (IDS), we could predict a rapid remission course of depression with an AUROC of 0.69 and 62% accuracy, and the presence of an MDD diagnosis at follow-up with an AUROC of 0.66 and 66% accuracy. Other clinical, psychological, or biological variables did not significantly improve the prediction. Among the large set of variables considered, only the IDS provided predictive value for course prediction on an individual level, although this analysis represents only one possible methodological approach. However, accuracy of course prediction was moderate at best and further improvement is required for these findings to be clinically useful.

14 Article [Complete recovery from depression is the exception rather than the rule: prognosis of depression beyond diagnostic boundaries]. 2018

Verhoeven, Josine E / Verduijn, Judith / Schoevers, Robert A / van Hemert, Albert M / Beekman, Aartjan T F / Penninx, Brenda W J H. ·VUmc, afd. Psychiatrie/GGZ inGeest, Amsterdam. · Contact: J.E. Verhoeven (j.verhoeven@ggzingeest.nl). · UMCG-Rijksuniversiteit Groningen, afd. Psychiatrie. · LUMC, afd. Psychiatrie, Leiden. ·Ned Tijdschr Geneeskd · Pubmed #30306757.

ABSTRACT: OBJECTIVE: To investigate whether the course of depression changes when (a) follow-up duration is longer and (b) in addition to depression other mood and anxiety disorders are considered as outcome measures. DESIGN: Longitudinal observational cohort study. METHOD: We selected patients from the Netherlands Study of Depression and Anxiety (NESDA) who had active depression at baseline (n=903) and for whom data from the 2, 4 and/or 6 year measurements were available. Using DSM-IV diagnoses and data from the 'Life chart interview', we divided participants in one of the following four course categories: (1) recovered (no diagnosis at 2-year measurement or later), (2) recurring without chronic episodes, (3) recurring with chronic episodes or (4) consistent chronic depression since baseline. We looked at the distribution of patients over the course categories from a short, diagnostically narrow perspective (over 2 years, only looking at depression) to a long, diagnostically broad perspective (over 6 years, looking at depression, dysthymia, hypomania, mania and anxiety). RESULTS: In the short, diagnostically narrow perspective, 58% of participants had recovered and 21% met the criteria for a chronic episode. In the long, diagnostically broad perspective however, only 17% had recovered while 55% had chronic episodes. CONCLUSION: Monitoring patients with depression over a longer period and with broader outcome measures (depression and related psychiatric disorders belonging to the mood disorder spectrum) shows that the course of depression is unfavourable and chronic for the majority. Conceptualising depression as a defined episodic disorder underestimates the severity of the prognosis for many patients and, as a consequence, the type of care indicated.

15 Article Repetitive negative thinking as a predictor of depression and anxiety: A longitudinal cohort study. 2018

Spinhoven, Philip / van Hemert, Albert M / Penninx, Brenda W. ·Leiden University, Institute of Psychology, Leiden, The Netherlands; Leiden University Medical Center, Department of Psychiatry, Leiden, The Netherlands. Electronic address: Spinhoven@FSW.LeidenUniv.NL. · Leiden University Medical Center, Department of Psychiatry, Leiden, The Netherlands. · Leiden University Medical Center, Department of Psychiatry, Leiden, The Netherlands; VU University Medical Center, Department of Psychiatry Amsterdam, The Netherlands. ·J Affect Disord · Pubmed #30138805.

ABSTRACT: BACKGROUND: Repetitive Negative Thinking (RNT) is assumed to be a transdiagnostic proximal risk factor in depression and anxiety. We examined the prospective relations of disorder-dependent as well as disorder-independent measures of RNT with depression and anxiety outcomes. METHODS: In a prospective cohort study, 1972 adults completed a 3-year follow-up period (attrition = 12.6%). DSM-IV diagnoses were assessed with the CIDI, symptom severity with the IDS and BAI, and RNT with measures for perseverative thinking (PTQ), rumination (LEIDS-R) and worry (PWQ). RESULTS: The common dimension of our RNT measurements (according to Confirmatory Factor Analysis) was significantly associated with comorbidity among depressive and among anxiety disorders, severity of depressive and anxiety symptoms, as well as persistence and relapse of depressive and anxiety disorders. Additionally, a specific factor for rumination predicted comorbidity of depressive disorders, comorbidity of anxiety disorders and relapse of depressive disorder, while a specific factor for worry predicted comorbidity of anxiety disorders and relapse of anxiety disorders, although to a lesser extent than general RNT. LIMITATIONS: The present study relied solely on self-report measures of RNT and controlling for baseline demographic and clinical variables greatly attenuated the predictive value of RNT. DISCUSSION: Disorder-independent RNT may be a similar underlying process present across depressive and anxiety disorders. It seems more important than the representation of this process in disorder-specific cognitive content such as rumination in depression and worry in anxiety. RNT as a pathological trait deserves more attention in clinical diagnosis and the transdiagnostic treatment of comorbid depression and anxiety in particular.

16 Article Factors Related To Depression and Post-Traumatic Stress Disorder in Shelter-Based Abused Women. 2018

Jonker, Irene E / Lako, Danielle A M / Beijersbergen, Mariëlle D / Sijbrandij, Marit / van Hemert, Albert M / Wolf, Judith R L M. ·1 Radboud University Nijmegen Medical Center, The Netherlands. · 2 VU University Amsterdam, The Netherlands. · 3 Leiden University Medical Center, The Netherlands. ·Violence Against Women · Pubmed #30124130.

ABSTRACT: In this study, linear mixed-effects regression analyses were used to examine whether sociodemographic variables, abuse-related variables, and well-being variables were associated with symptoms of depression and post-traumatic stress disorder (PTSD) in abused women residing in shelters. Results pointed out that symptoms of depression severity were positively associated with migration background and the experience of physical abuse and negatively associated with self-esteem and social support. PTSD symptoms were positively associated with the experience of sexual abuse and negatively associated with self-esteem. Within women's shelters, staff could be sensitive to improving the social integration of women, especially those with a non-Dutch background, and strengthening the women's social networks and their self-esteem.

17 Article Clinical and sociodemographic associations with treatment selection in major depression. 2018

Rodenburg-Vandenbussche, S / Carlier, I V E / van Vliet, I M / van Hemert, A M / Stiggelbout, A M / Zitman, F G. ·Department of Psychiatry, Leiden University Medical Centre, Leiden, the Netherlands. Electronic address: S.Rodenburg-Vandenbussche@LUMC.nl. · Department of Psychiatry, Leiden University Medical Centre, Leiden, the Netherlands. · Department of Medical Decision Making, Leiden University Medical Centre, Leiden, the Netherlands. ·Gen Hosp Psychiatry · Pubmed #30048764.

ABSTRACT: OBJECTIVE: To investigate treatment selection in a naturalistic sample of MDD outpatients and the factors influencing treatment selection in specialized psychiatric care. METHOD: Multinomial Logistic Regression analysis investigated associations between treatment selection and patients' sociodemographic and clinical characteristics, using retrospective chart review data and Routine Outcome Monitoring (ROM) data of MDD outpatients. RESULTS: Of the patients included for analyses (N = 263), 34% received psychotherapy, 32% received an antidepressant (AD) and 35% received a combination. Men were more likely than women to receive AD with reference to psychotherapy (OR CONCLUSION: AD prescriptions in primary care, severity and gender influenced treatment selection for depressive disorders in secondary psychiatric care. Other factors such as the accessibility of treatment and patient preferences may have played a role in treatment selection in this setting and need further investigation.

18 Article Elevated salivary alpha-amylase levels at awakening in patients with depression. 2018

Bauduin, S E E C / van Noorden, M S / van der Werff, S J A / de Leeuw, M / van Hemert, A M / van der Wee, N J A / Giltay, E J. ·Department of Psychiatry, Leiden University Medical Center (LUMC), The Netherlands. Electronic address: S.E.E.C.Bauduin@lumc.nl. · Department of Psychiatry, Leiden University Medical Center (LUMC), The Netherlands. · Department of Psychiatry, Leiden University Medical Center (LUMC), The Netherlands; Psychiatric Outpatient Clinic, GGZ Rivierduinen, The Netherlands. ·Psychoneuroendocrinology · Pubmed #30005283.

ABSTRACT: BACKGROUND: Specific Major Depressive Disorder (MDD) biomarkers could help improve our understanding of MDD pathophysiology and aid in the refinement of current MDD criteria. While salivary cortisol (SC) can differentiate between healthy controls and patients with psychiatric disorders, salivary alpha amylase (sAA), may be a putative candidate biomarker for MDD specifically. METHODS: In a naturalistic cohort of consecutive out-patients and healthy controls, sAA and SC were determined in 833 participants (97 MDD patients, 142 patients with other mood, anxiety, and/or somatoform (MAS-) disorders, and 594 healthy controls). Samples were collected at 7 different time points (at awakening, after 30, 45, and 60 min, at 10:00 p.m., at 11:00 p.m., and at awakening on day 2). RESULTS: The mean age of the sample was 43.8 years (SD = 12.9; 63.9% female). Concerning sAA, MDD patients had higher sAA levels upon awakening on two consecutive days (p = 0.04, p = 0.01 respectively), as well as a higher area under the curve with respect to the increase (AUCi; p = 0.04) in comparison to both controls and the other MAS-disorders group. Regarding SC, mean levels of evening SC were elevated in MDD patients (p = 0.049) in comparison to both controls and the other MAS-disorders group. SC values on day 2 after ingestion of dexamethasone were elevated in both MDD patients and the other MAS-disorders group (p = 0.04, p = 0.047 respectively). CONCLUSIONS: sAA at awakening and not cortisol differentiates MDD from other psychiatric disorders in outpatients. This suggests that sAA may be a valuable candidate biomarker specifically for MDD.

19 Article Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. 2018

Wray, Naomi R / Ripke, Stephan / Mattheisen, Manuel / Trzaskowski, Maciej / Byrne, Enda M / Abdellaoui, Abdel / Adams, Mark J / Agerbo, Esben / Air, Tracy M / Andlauer, Till M F / Bacanu, Silviu-Alin / Bækvad-Hansen, Marie / Beekman, Aartjan F T / Bigdeli, Tim B / Binder, Elisabeth B / Blackwood, Douglas R H / Bryois, Julien / Buttenschøn, Henriette N / Bybjerg-Grauholm, Jonas / Cai, Na / Castelao, Enrique / Christensen, Jane Hvarregaard / Clarke, Toni-Kim / Coleman, Jonathan I R / Colodro-Conde, Lucía / Couvy-Duchesne, Baptiste / Craddock, Nick / Crawford, Gregory E / Crowley, Cheynna A / Dashti, Hassan S / Davies, Gail / Deary, Ian J / Degenhardt, Franziska / Derks, Eske M / Direk, Nese / Dolan, Conor V / Dunn, Erin C / Eley, Thalia C / Eriksson, Nicholas / Escott-Price, Valentina / Kiadeh, Farnush Hassan Farhadi / Finucane, Hilary K / Forstner, Andreas J / Frank, Josef / Gaspar, Héléna A / Gill, Michael / Giusti-Rodríguez, Paola / Goes, Fernando S / Gordon, Scott D / Grove, Jakob / Hall, Lynsey S / Hannon, Eilis / Hansen, Christine Søholm / Hansen, Thomas F / Herms, Stefan / Hickie, Ian B / Hoffmann, Per / Homuth, Georg / Horn, Carsten / Hottenga, Jouke-Jan / Hougaard, David M / Hu, Ming / Hyde, Craig L / Ising, Marcus / Jansen, Rick / Jin, Fulai / Jorgenson, Eric / Knowles, James A / Kohane, Isaac S / Kraft, Julia / Kretzschmar, Warren W / Krogh, Jesper / Kutalik, Zoltán / Lane, Jacqueline M / Li, Yihan / Li, Yun / Lind, Penelope A / Liu, Xiaoxiao / Lu, Leina / MacIntyre, Donald J / MacKinnon, Dean F / Maier, Robert M / Maier, Wolfgang / Marchini, Jonathan / Mbarek, Hamdi / McGrath, Patrick / McGuffin, Peter / Medland, Sarah E / Mehta, Divya / Middeldorp, Christel M / Mihailov, Evelin / Milaneschi, Yuri / Milani, Lili / Mill, Jonathan / Mondimore, Francis M / Montgomery, Grant W / Mostafavi, Sara / Mullins, Niamh / Nauck, Matthias / Ng, Bernard / Nivard, Michel G / Nyholt, Dale R / O'Reilly, Paul F / Oskarsson, Hogni / Owen, Michael J / Painter, Jodie N / Pedersen, Carsten Bøcker / Pedersen, Marianne Giørtz / Peterson, Roseann E / Pettersson, Erik / Peyrot, Wouter J / Pistis, Giorgio / Posthuma, Danielle / Purcell, Shaun M / Quiroz, Jorge A / Qvist, Per / Rice, John P / Riley, Brien P / Rivera, Margarita / Saeed Mirza, Saira / Saxena, Richa / Schoevers, Robert / Schulte, Eva C / Shen, Ling / Shi, Jianxin / Shyn, Stanley I / Sigurdsson, Engilbert / Sinnamon, Grant B C / Smit, Johannes H / Smith, Daniel J / Stefansson, Hreinn / Steinberg, Stacy / Stockmeier, Craig A / Streit, Fabian / Strohmaier, Jana / Tansey, Katherine E / Teismann, Henning / Teumer, Alexander / Thompson, Wesley / Thomson, Pippa A / Thorgeirsson, Thorgeir E / Tian, Chao / Traylor, Matthew / Treutlein, Jens / Trubetskoy, Vassily / Uitterlinden, André G / Umbricht, Daniel / Van der Auwera, Sandra / van Hemert, Albert M / Viktorin, Alexander / Visscher, Peter M / Wang, Yunpeng / Webb, Bradley T / Weinsheimer, Shantel Marie / Wellmann, Jürgen / Willemsen, Gonneke / Witt, Stephanie H / Wu, Yang / Xi, Hualin S / Yang, Jian / Zhang, Futao / Anonymous12721124 / Anonymous12731124 / Arolt, Volker / Baune, Bernhard T / Berger, Klaus / Boomsma, Dorret I / Cichon, Sven / Dannlowski, Udo / de Geus, E C J / DePaulo, J Raymond / Domenici, Enrico / Domschke, Katharina / Esko, Tõnu / Grabe, Hans J / Hamilton, Steven P / Hayward, Caroline / Heath, Andrew C / Hinds, David A / Kendler, Kenneth S / Kloiber, Stefan / Lewis, Glyn / Li, Qingqin S / Lucae, Susanne / Madden, Pamela F A / Magnusson, Patrik K / Martin, Nicholas G / McIntosh, Andrew M / Metspalu, Andres / Mors, Ole / Mortensen, Preben Bo / Müller-Myhsok, Bertram / Nordentoft, Merete / Nöthen, Markus M / O'Donovan, Michael C / Paciga, Sara A / Pedersen, Nancy L / Penninx, Brenda W J H / Perlis, Roy H / Porteous, David J / Potash, James B / Preisig, Martin / Rietschel, Marcella / Schaefer, Catherine / Schulze, Thomas G / Smoller, Jordan W / Stefansson, Kari / Tiemeier, Henning / Uher, Rudolf / Völzke, Henry / Weissman, Myrna M / Werge, Thomas / Winslow, Ashley R / Lewis, Cathryn M / Levinson, Douglas F / Breen, Gerome / Børglum, Anders D / Sullivan, Patrick F / Anonymous12741124. ·Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia. naomi.wray@uq.edu.au. · Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia. naomi.wray@uq.edu.au. · Medical and Population Genetics, Broad Institute, Cambridge, MA, USA. · Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. · Department of Psychiatry and Psychotherapy, Universitätsmedizin Berlin Campus Charité Mitte, Berlin, Germany. · Department of Biomedicine, Aarhus University, Aarhus, Denmark. · iSEQ, Centre for Integrative Sequencing, Aarhus University, Aarhus, Denmark. · iPSYCH, Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark. · Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden. · Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia. · Department of Biological Psychology and EMGO+ Institute for Health and Care Research, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. · Division of Psychiatry, University of Edinburgh, Edinburgh, UK. · Centre for Integrated Register-Based Research, Aarhus University, Aarhus, Denmark. · National Centre for Register-Based Research, Aarhus University, Aarhus, Denmark. · Discipline of Psychiatry, University of Adelaide, Adelaide, South Australia, Australia. · Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany. · Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. · Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA. · Center for Neonatal Screening, Department for Congenital Disorders, Statens Serum Institut, Copenhagen, Denmark. · Department of Psychiatry, Vrije Universiteit Medical Center and GGZ inGeest, Amsterdam, The Netherlands. · Virginia Institute for Psychiatric and Behavior Genetics, Richmond, VA, USA. · Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA. · Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. · Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark. · Statistical Genomics and Systems Genetics, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK. · Human Genetics, Wellcome Trust Sanger Institute, Cambridge, UK. · Department of Psychiatry, University Hospital of Lausanne, Prilly, Switzerland. · MRC Social Genetic and Developmental Psychiatry Centre, King's College London, London, UK. · Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia. · Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia. · Centre for Advanced Imaging, University of Queensland, Brisbane, Queensland, Australia. · Psychological Medicine, Cardiff University, Cardiff, UK. · Center for Genomic and Computational Biology, Duke University, Durham, NC, USA. · Department of Pediatrics, Division of Medical Genetics, Duke University, Durham, NC, USA. · Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. · Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. · Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK. · Institute of Human Genetics, University of Bonn, Bonn, Germany. · Life & Brain Center, Department of Genomics, University of Bonn, Bonn, Germany. · Psychiatry, Dokuz Eylul University School of Medicine, Izmir, Turkey. · Epidemiology, Erasmus MC, Rotterdam, The Netherlands. · Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA. · Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA. · Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Massachusetts General Hospital, Boston, MA, USA. · Research, 23andMe, Inc., Mountain View, CA, USA. · Neuroscience and Mental Health, Cardiff University, Cardiff, UK. · Bioinformatics, University of British Columbia, Vancouver, British Columbia, Canada. · Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. · Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA, USA. · Department of Psychiatry (UPK), University of Basel, Basel, Switzerland. · Human Genomics Research Group, Department of Biomedicine, University of Basel, Basel, Switzerland. · Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany. · Department of Psychiatry, Trinity College Dublin, Dublin, Ireland. · Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. · Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA. · Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia. · Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark. · Institute of Genetic Medicine, Newcastle University, Newcastle-upon-Tyne, UK. · University of Exeter Medical School, Exeter, UK. · Danish Headache Centre, Department of Neurology, Rigshospitalet, Glostrup, Denmark. · Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Capital Region of Denmark, Copenhagen, Denmark. · iPSYCH, Lundbeck Foundation Initiative for Psychiatric Research, Copenhagen, Denmark. · Brain and Mind Centre, University of Sydney, Sydney, New South Wales, Australia. · Interfaculty Institute for Genetics and Functional Genomics, Department of Functional Genomics, University Medicine and Ernst Moritz Arndt University Greifswald, Greifswald, Germany. · Roche Pharmaceutical Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche, Ltd, Basel, Switzerland. · Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA. · Statistics, Pfizer Global Research and Development, Groton, CT, USA. · Max Planck Institute of Psychiatry, Munich, Germany. · Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA. · Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, USA. · Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA. · Psychiatry and Behavioral Sciences, University of Southern California, Los Angeles, CA, USA. · Informatics Program, Boston Children's Hospital, Boston, MA, USA. · Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. · Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. · Department of Endocrinology at Herlev University Hospital, University of Copenhagen, Copenhagen, Denmark. · Swiss Institute of Bioinformatics, Lausanne, Switzerland. · Institute of Social and Preventive Medicine (IUMSP), University Hospital of Lausanne, Lausanne, Switzerland. · Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA. · Mental Health, NHS 24, Glasgow, UK. · Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK. · Department of Psychiatry and Psychotherapy, University of Bonn, Bonn, Germany. · Statistics, University of Oxford, Oxford, UK. · Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, USA. · School of Psychology and Counseling, Queensland University of Technology, Brisbane, Queensland, Australia. · Child and Youth Mental Health Service, Children's Health Queensland Hospital and Health Service, South Brisbane, Queensland, Australia. · Child Health Research Centre, University of Queensland, Brisbane, Queensland, Australia. · Estonian Genome Center, University of Tartu, Tartu, Estonia. · Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada. · Statistics, University of British Columbia, Vancouver, British Columbia, Canada. · DZHK (German Centre for Cardiovascular Research), partner site Greifswald, University Medicine, University Medicine Greifswald, Greifswald, Germany. · Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany. · Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland, Australia. · Humus, Reykjavik, Iceland. · MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK. · Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA. · Complex Trait Genetics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. · Clinical Genetics, Vrije Universiteit Medical Center, Amsterdam, The Netherlands. · Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA. · Solid Biosciences, Boston, MA, USA. · Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, MO, USA. · Department of Biochemistry and Molecular Biology II, Institute of Neurosciences, Center for Biomedical Research, University of Granada, Granada, Spain. · Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. · Department of Psychiatry and Psychotherapy, Medical Center of the University of Munich, Campus Innenstadt, Munich, Germany. · Institute of Psychiatric Phenomics and Genomics (IPPG), Medical Center of the University of Munich, Campus Innenstadt, Munich, Germany. · Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. · Behavioral Health Services, Kaiser Permanente Washington, Seattle, WA, USA. · Faculty of Medicine, Department of Psychiatry, University of Iceland, Reykjavik, Iceland. · School of Medicine and Dentistry, James Cook University, Townsville, Queensland, Australia. · Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK. · deCODE Genetics/Amgen, Inc., Reykjavik, Iceland. · Psychiatry and Human Behavior, University of Mississippi Medical Center, Jackson, MS, USA. · College of Biomedical and Life Sciences, Cardiff University, Cardiff, UK. · Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany. · Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. · KG Jebsen Centre for Psychosis Research, Norway Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway. · Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA. · Medical Genetics Section, CGEM, IGMM, University of Edinburgh, Edinburgh, UK. · Clinical Neurosciences, University of Cambridge, Cambridge, UK. · Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. · Roche Pharmaceutical Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases Discovery and Translational Medicine Area, Roche Innovation Center Basel, F. Hoffmann-La Roche, Ltd, Basel, Switzerland. · Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA. · Computational Sciences Center of Emphasis, Pfizer Global Research and Development, Cambridge, MA, USA. · Department of Psychiatry, University of Münster, Munster, Germany. · Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Juelich, Germany. · Institute of Medical Genetics and Pathology, University Hospital Basel, University of Basel, Basel, Switzerland. · Amsterdam Public Health Institute, Vrije Universiteit Medical Center, Amsterdam, The Netherlands. · Centre for Integrative Biology, Università degli Studi di Trento, Trento, Italy. · Department of Psychiatry and Psychotherapy, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany. · Psychiatry, Kaiser Permanente Northern California, San Francisco, CA, USA. · MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK. · Centre for Addiction and Mental Health, Toronto, Ontario, Canada. · Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada. · Division of Psychiatry, University College London, London, UK. · Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, NJ, USA. · Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia. · Psychosis Research Unit, Aarhus University Hospital, Risskov, Aarhus, Denmark. · Institute of Translational Medicine, University of Liverpool, Liverpool, UK. · Mental Health Center Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark. · Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Groton, CT, USA. · Psychiatry, Harvard Medical School, Boston, MA, USA. · Psychiatry, University of Iowa, Iowa City, IA, USA. · Human Genetics Branch, NIMH Division of Intramural Research Programs, Bethesda, MD, USA. · Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany. · Faculty of Medicine, University of Iceland, Reykjavik, Iceland. · Child and Adolescent Psychiatry, Erasmus MC, Rotterdam, The Netherlands. · Psychiatry, Erasmus MC, Rotterdam, The Netherlands. · Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada. · Division of Epidemiology, New York State Psychiatric Institute, New York, NY, USA. · Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark. · Human Genetics and Computational Biomedicine, Pfizer Global Research and Development, Cambridge, MA, USA. · Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. · Department of Medical and Molecular Genetics, King's College London, London, UK. · Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA. · NIHR BRC for Mental Health, King's College London, London, UK. · Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. pfsulliv@med.unc.edu. · Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. pfsulliv@med.unc.edu. · Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. pfsulliv@med.unc.edu. ·Nat Genet · Pubmed #29700475.

ABSTRACT: Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

20 Article Reconsidering the prognosis of major depressive disorder across diagnostic boundaries: full recovery is the exception rather than the rule. 2017

Verduijn, Judith / Verhoeven, Josine E / Milaneschi, Yuri / Schoevers, Robert A / van Hemert, Albert M / Beekman, Aartjan T F / Penninx, Brenda W J H. ·Department of Psychiatry, Amsterdam Public Health Research Institute, VU University Medical Center, PO Box 74077, 1070 BB, Amsterdam, The Netherlands. · Department of Psychiatry, Amsterdam Public Health Research Institute, VU University Medical Center, PO Box 74077, 1070 BB, Amsterdam, The Netherlands. j.verhoeven@ggzingeest.nl. · Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. ·BMC Med · Pubmed #29228943.

ABSTRACT: BACKGROUND: Major depressive disorder (MDD) is often handled as an episodic and isolated disorder, resulting in an optimistic view about its prognosis. Herein, we test the idea that the prognosis of MDD changes if we vary the perspective in terms of (1) a longer time frame and (2) a broader diagnostic conceptualisation including dysthymia, (hypo)mania and anxiety disorders as relevant outcomes. METHODS: Patients with current MDD at baseline (n = 903) and available 2-, 4-, and/or 6-year follow-up assessments were selected from the Netherlands Study of Depression and Anxiety, a psychiatric cohort study. Combining psychiatric DSM-IV-based diagnoses and life-chart data, patient course trajectories were classified as (1) recovered (no diagnoses at 2-year follow-up or thereafter), (2) recurrent without chronic episodes, (3) recurrent with chronic episodes or (4) consistently chronic since baseline. A chronic episode was defined as having a current diagnosis at the follow-up assessment and consistent symptoms over 2 years. Proportions of course trajectories were provided moving from a short, narrow perspective (2-year follow-up, considering only MDD diagnosis) to a long, broad perspective (6-year follow-up, including MDD, dysthymia, (hypo)mania and anxiety diagnoses). RESULTS: With the short, narrow perspective, the recovery rate was 58% and 21% had a chronic episode. However, in the long, broad perspective the recovery rate was reduced to 17%, while 55% of the patients experienced chronic episodes. CONCLUSIONS: Results from a long and rigorous follow-up in a large cohort suggests that most MDD patients have an unfavourable prognosis. Longer follow-up and broader diagnostic conceptualisation show that the majority of patients have a disabling and chronic disorder. Conceptualising and handling MDD as a narrowly defined and episodic disorder may underestimate the prognosis of the majority of depressed patients and, consequently, the type of care that is appropriate.

21 Article The role of anxious distress in immune dysregulation in patients with major depressive disorder. 2017

Gaspersz, Roxanne / Lamers, Femke / Wittenberg, Gayle / Beekman, Aartjan T F / van Hemert, Albert M / Schoevers, Robert A / Penninx, Brenda W J H. ·Department of Psychiatry, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands. r.gaspersz@ggzingeest.nl. · Department of Psychiatry, Amsterdam Public Health Research Institute, VU University Medical Center, Amsterdam, The Netherlands. · Janssen Research & Development, LLC, Titusville, NJ, USA. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. ·Transl Psychiatry · Pubmed #29217840.

ABSTRACT: Although depression with anxious distress appears to be a clinically relevant subtype of major depressive disorder (MDD), whether it involves specific pathophysiology remains unclear. Inflammation has been implicated, but not comprehensively studied. We examined within a large MDD sample whether anxious distress and related anxiety features are associated with differential basal inflammation and innate cytokine production capacity. Data are from 1078 MDD patients from the Netherlands Study of Depression and Anxiety. In addition to the DSM-5 anxious distress specifier, we studied various dimensional anxiety scales (e.g. Inventory of Depressive Symptomatology anxiety arousal subscale [IDS-AA], Beck Anxiety Inventory [BAI], Mood and Anxiety Symptoms Questionnaire Anxious Arousal scale [MASQ-AA]). The specifier was constructed using five self-report items from the IDS and BAI. Basal inflammatory markers included C-reactive protein (CRP), interleukin (IL)-6 and tumor necrosis factor (TNF)-α. Innate production capacity was assessed by 13 lipopolysaccharide (LPS)-stimulated inflammatory markers. Basal and LPS-stimulated inflammation index scores were created. Basal inflammation was not associated with anxious distress (prevalence = 54.3%) in MDD patients, except for a modest positive association for BAI score. However, anxious distress was associated with higher LPS-stimulated levels (interferon-γ, IL-6, monocyte chemotactic protein (MCP)-1, macrophage inflammatory protein (MIP)-1α, matrix metalloproteinase (MMP)-2, TNF-α, LPS-stimulated index). Other anxiety indicators (anxious distress specifier score, BAI, MASQ-AA) were also associated with increased innate production capacity. Within a large MDD sample, the anxious distress specifier was associated with increased innate cytokine production capacity but not with basal inflammation. Results from dimensional anxiety indicators largely confirm these results. These findings provide new insight into the pathophysiology of anxious depression.

22 Article Large normal-range TBP and ATXN7 CAG repeat lengths are associated with increased lifetime risk of depression. 2017

Gardiner, S L / van Belzen, M J / Boogaard, M W / van Roon-Mom, W M C / Rozing, M P / van Hemert, A M / Smit, J H / Beekman, A T F / van Grootheest, G / Schoevers, R A / Oude Voshaar, R C / Comijs, H C / Penninx, B W J H / van der Mast, R C / Roos, R A C / Aziz, N A. ·Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands. · Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands. · Department of Clinical Genetics, Leiden University Medical Centre, Leiden, The Netherlands. · Centre for Healthy Ageing/Department of Public Health, Section of Social Medicine, University of Copenhagen, Copenhagen, Denmark. · Department of Psychiatry, Leiden University Medical Centre, Leiden, The Netherlands. · Department of Psychiatry, Amsterdam Public Health Research Institute and Neuroscience Campus Amsterdam, VU University Medical Centre/GGZ inGeest, Amsterdam, The Netherlands. · Department of Psychiatry, University of Groningen, University Medical Centre Groningen, Research School Cognitive Behavioural Neuroscience, Groningen, The Netherlands. · Department of Psychiatry, Collaborative Antwerp Psychiatric Research Institute (CAPRI), University of Antwerp, Antwerp, Belgium. ·Transl Psychiatry · Pubmed #28585930.

ABSTRACT: Depression is one of the most prevalent and debilitating psychiatric disorders worldwide. Recently, we showed that both relatively short and relatively long cytosine-adenine-guanine (CAG) repeats in the huntingtin gene (HTT) are associated with an increased risk of lifetime depression. However, to what extent the variations in CAG repeat length in the other eight polyglutamine disease-associated genes (PDAGs) are associated with depression is still unknown. We determined the CAG repeat sizes of ATXN1, ATXN2, ATXN3, CACNA1A, ATXN7, TBP, ATN1 and AR in two well-characterized Dutch cohorts-the Netherlands Study of Depression and Anxiety and the Netherlands Study of Depression in Older Persons-including 2165 depressed and 1058 non-depressed individuals-aged 18-93 years. The association between PDAG CAG repeat size and the risk for depression was assessed via binary logistic regression. We found that the odds ratio (OR) for lifetime depression was significantly higher for individuals with >10, compared with subjects with ≤10, CAG repeats in both ATXN7 alleles (OR=1.90, confidence interval (CI) 1.26-2.85). For TBP we found a similar association: A CAG repeat length exceeding the median in both alleles was associated with an increased risk for lifetime depression (OR=1.33, CI 1.00-1.76). In conclusion, we observed that carriers of either ATXN7 or TBP alleles with relatively large CAG repeat sizes in both alleles had a substantially increased risk of lifetime depression. Our findings provide critical evidence for the notion that repeat polymorphisms can act as complex genetic modifiers of depression.

23 Article Genetic effects influencing risk for major depressive disorder in China and Europe. 2017

Bigdeli, T B / Ripke, S / Peterson, R E / Trzaskowski, M / Bacanu, S-A / Abdellaoui, A / Andlauer, T F M / Beekman, A T F / Berger, K / Blackwood, D H R / Boomsma, D I / Breen, G / Buttenschøn, H N / Byrne, E M / Cichon, S / Clarke, T-K / Couvy-Duchesne, B / Craddock, N / de Geus, E J C / Degenhardt, F / Dunn, E C / Edwards, A C / Fanous, A H / Forstner, A J / Frank, J / Gill, M / Gordon, S D / Grabe, H J / Hamilton, S P / Hardiman, O / Hayward, C / Heath, A C / Henders, A K / Herms, S / Hickie, I B / Hoffmann, P / Homuth, G / Hottenga, J-J / Ising, M / Jansen, R / Kloiber, S / Knowles, J A / Lang, M / Li, Q S / Lucae, S / MacIntyre, D J / Madden, P A F / Martin, N G / McGrath, P J / McGuffin, P / McIntosh, A M / Medland, S E / Mehta, D / Middeldorp, C M / Milaneschi, Y / Montgomery, G W / Mors, O / Müller-Myhsok, B / Nauck, M / Nyholt, D R / Nöthen, M M / Owen, M J / Penninx, B W J H / Pergadia, M L / Perlis, R H / Peyrot, W J / Porteous, D J / Potash, J B / Rice, J P / Rietschel, M / Riley, B P / Rivera, M / Schoevers, R / Schulze, T G / Shi, J / Shyn, S I / Smit, J H / Smoller, J W / Streit, F / Strohmaier, J / Teumer, A / Treutlein, J / Van der Auwera, S / van Grootheest, G / van Hemert, A M / Völzke, H / Webb, B T / Weissman, M M / Wellmann, J / Willemsen, G / Witt, S H / Levinson, D F / Lewis, C M / Wray, N R / Flint, J / Sullivan, P F / Kendler, K S. ·Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA. · Department of Psychiatry, Charite Universitatsmedizin Berlin Campus Benjamin Franklin, Berlin, Germany. · Medical and Population Genetics, Broad Institute, Cambridge, MA, USA. · Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. · Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia. · Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia. · Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands. · Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany. · Munich Cluster for Systems Neurology (SyNergy), Munich, Germany. · Department of Psychiatry, VU University Medical Center and GGZ inGeest, Amsterdam, The Netherlands. · Institute of Epidemiology and Social Medicine, University of Muenster, Münster, Germany. · Division of Psychiatry, University of Edinburgh, Edinburgh, UK. · King's College London, NIHR BRC for Mental Health, London, UK. · King's College London, MRC Social Genetic and Developmental Psychiatry Centre, London, UK. · Department of Clinical Medicine, Translational Neuropsychiatry Unit, Aarhus University, Aarhus, Denmark. · Department of Biomedicine, University of Basel, Basel, Switzerland. · Division of Medical Genetics, University of Basel, Basel, Switzerland. · Institute of Neuroscience and Medicine (INM-1), Research Center Juelich, Jülich, Germany. · Institute of Human Genetics, University of Bonn, Bonn, Germany. · Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. · Centre for Advanced Imaging, University of Queensland, Brisbane, QLD, Australia. · Department of Psychological Medicine, Cardiff University, Cardiff, UK. · EMGO+ Institute, VU University Medical Center, Amsterdam, The Netherlands. · Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany. · Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA. · Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA. · Psychiatric and Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. · Department of Psychiatry and Behavioral Sciences, State University of New York Downstate Medical Center, Brooklyn, NY, USA. · Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany. · Department of Psychiatry, Trinity College Dublin, Dublin, Ireland. · Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany. · Department of Psychiatry, Kaiser-Permanente Northern California, San Fransisco, CA, USA. · Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland. · Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK. · Department of Psychiatry, Washington University in Saint Louis School of Medicine, St Louis, MO, USA. · Division of Medical Genetics, Department of Biomedicine, University of Basel, Basel, Switzerland. · Brain and Mind Research Institute, University of Sydney, Sydney, NSW, Australia. · Human Genomics Research Group, Department of Biomedicine, University of Basel, Basel, Switzerland. · Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst Moritz Arndt University Greifswald, Greifswald, Germany. · Max Planck Institute of Psychiatry, Munich, Germany. · Department of Psychiatry and The Behavioral Sciences, University of Southern California, Los Angeles, CA, USA. · Neuroscience Therapeutic Area, Janssen Research and Development, LLC, Titusville, NJ, USA. · School of Psychology, University of Queensland, Brisbane, QLD, Australia. · Department of Psychiatry, New York State Psychiatric Institute, Columbia University College of Physicians and Surgeons, New York, NY, USA. · Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK. · Institute for Molecular Biology, University of Queensland, Brisbane, QLD, Australia. · Psychosis Research Unit, Aarhus University Hospital, Risskov, Denmark. · Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK. · Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany. · Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia. · MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK. · Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA. · Department of Psychiatry, Harvard Medical School, Boston, MA, USA. · Medical Genetics Section, CGEM, IGMM, University of Edinburgh, Edinburgh, UK. · Department of Psychiatry, University of Iowa, Iowa, IA, USA. · Department of Psychiatry, Washington University in Saint Louis, St Louis, MO, USA. · Department of Human and Molecular Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA. · Department of Biochemistry and Molecular Biology II, Institute of Neurosciences, Center for Biomedical Research, University of Granada, Granada, Spain. · Department of Psychiatry, University of Groningen, University of Medical Center Groningen, Groningen, The Netherlands. · Institute of Psychiatric Phenomics and Genomics, Medical Center of the University of Munich, Campus Innenstadt, Munich, Germany. · Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, The Netherlands. · Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA. · Human Genetics Branch, NIMH Division of Intramural Research Programs, Bethesda, MD, USA. · Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA. · Division of Psychiatry, Group Health, Seattle, WA, USA. · Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · Division of Epidemiology, New York State Psychiatric Institute, New York, NY, USA. · Department of Psychiatry, Columbia University College of Physicians and Surgeons, New York, NY, USA. · Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA. · King's College London, Department of Medical and Molecular Genetics, London, UK. · Merton College, University of Oxford, Oxford, UK. · Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK. · Medical Epidemiology and Biostatistics, Karolinska Institutet, Solna, Sweden. · Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. · Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. ·Transl Psychiatry · Pubmed #28350396.

ABSTRACT: Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30-40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log

24 Article Anxious distress predicts subsequent treatment outcome and side effects in depressed patients starting antidepressant treatment. 2017

Gaspersz, Roxanne / Lamers, Femke / Kent, Justine M / Beekman, Aartjan T F / Smit, Johannes H / van Hemert, Albert M / Schoevers, Robert A / Penninx, Brenda W J H. ·Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands. Electronic address: r.gaspersz@ggzingeest.nl. · Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands. · Janssen Research & Development, LLC, Titusville, NJ, USA. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · University of Groningen, University Medical Center Groningen, Department of Psychiatry, Groningen, The Netherlands. · Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands; Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands; University of Groningen, University Medical Center Groningen, Department of Psychiatry, Groningen, The Netherlands. ·J Psychiatr Res · Pubmed #27693981.

ABSTRACT: Evidence has shown that the DSM-5 anxious distress specifier captures a clinically valid construct that predicts a worse clinical course. Although of importance for treatment planning and monitoring, however, the specifier's ability to predict treatment outcome is unknown. This is the first study to examine the ability of the DSM-5 anxious distress specifier to predict treatment response and side effects in depressed patients who recently initiated antidepressant treatment. Patients were from the Netherlands Study of Depression and Anxiety, an ongoing longitudinal cohort study. Baseline, 1-year and 2-year follow-up data were used from 149 patients (18-65 years) with current Major Depressive Disorder (MDD) who recently started adequately dosed antidepressant medication. Five self-report items were used to construct the DSM-5 anxious distress specifier. Treatment outcomes were depression severity after 1 year and 2 years, remission of MDD after 2 years and antidepressant side effects during treatment. For comparison, analyses were repeated for comorbid DSM-IV-based anxiety disorders as a predictor. In depressed patients who received antidepressant treatment, the anxious distress specifier (prevalence = 59.1%) significantly predicted higher severity (1 year: B = 1.94, P = 0.001; 2 years: B = 1.63, P = 0.001), lower remission rates (OR = 0.44, P = 0.0496) and greater frequency of side effects (≥4 vs. 0: OR = 2.74, P = 0.061). In contrast, the presence of comorbid anxiety disorders did not predict these treatment outcomes. The anxious distress specifier significantly predicts poorer treatment outcomes as shown by higher depression severity, lower remission rates, and greater frequency of antidepressant side effects in patients with MDD on adequate antidepressant treatment. Therefore, this simple 5-item specifier is of potential great clinical usefulness for treatment planning and monitoring in depressed patients.

25 Article Longitudinal Predictive Validity of the DSM-5 Anxious Distress Specifier for Clinical Outcomes in a Large Cohort of Patients With Major Depressive Disorder. 2017

Gaspersz, Roxanne / Lamers, Femke / Kent, Justine M / Beekman, Aartjan T F / Smit, Johannes H / van Hemert, Albert M / Schoevers, Robert A / Penninx, Brenda W J H. ·Department of Psychiatry, VU University Medical Center, Postbus 74077, 1070 BB Amsterdam, The Netherlands. r.gaspersz@ggzingeest.nl. · Department of Psychiatry, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, The Netherlands. · Janssen Research & Development, LLC, Titusville, New Jersey, USA. · Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands. · Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands. ·J Clin Psychiatry · Pubmed #27035515.

ABSTRACT: OBJECTIVE: While the new DSM-5 anxious distress specifier is of great clinical importance, no evidence exists for its longitudinal predictive validity for clinical outcomes in patients with major depressive disorder (MDD). We examined the longitudinal validity of this specifier and validated it against DSM-IV-based comorbid anxiety disorder diagnoses. METHODS: Data are from 1,080 patients with current MDD at baseline (September 2004 to February 2007), of which 911 participated in the 2-year follow-up (September 2006 to April 2009). Patients are from the Netherlands Study of Depression and Anxiety, which is an ongoing longitudinal cohort study, and were sampled from the community, primary care, and outpatient specialized care settings. The specifier was constructed in the existing sample by 5 matching self-report items. Predictive outcomes were 2-year chronicity, time to remission of MDD, and functional disability. Discriminant performance and convergent validity of the specifier were also assessed. RESULTS: The specifier was present in 54.2% of the sample. The specifier significantly outperformed anxiety disorders in predicting chronicity (OR = 1.96, P < .001, vs OR = 1.11, P = .49), time to remission of MDD (HR = 0.75, P = .002, vs HR = 0.94, P = .55), and functional disability (B = 10.03, P < .001, vs B = 2.53, P = .07). The specifier significantly discriminated in clinical characteristics, had convergent validity for anxiety characteristics, and poorly overlapped with DSM-IV-based anxiety disorder diagnoses (Cohen κ = .09). CONCLUSIONS: The short anxious distress specifier outperforms DSM-IV-based anxiety disorder diagnoses as a longitudinal predictor for clinical outcomes in patients with MDD.

Next