Differential associations of specific depressive and anxiety disorders with somatic symptoms

AbstractObjectivePrevious studies have shown that depressive and anxiety disorders are strongly related to somatic symptoms, but much is unclear about the specificity of this association. This study examines the associations of specific depressive and anxiety disorders with somatic symptoms, and whether these associations are independent of comorbid depressive and anxiety disorders.MethodsCross-sectional data were derived from The Netherlands Study of Depression and Anxiety (NESDA). A total of 2008 persons (mean age: 41.6years, 64.9% women) were included, consisting of 1367 patients with a past-month DSM-diagnosis (established with the Composite International Diagnostic Interview [CIDI]) of depressive disorder (major depressive disorder, dysthymic disorder) and/or anxiety disorder (generalized anxiety disorder, social phobia, panic disorder, agoraphobia), and 641 controls. Somatic symptoms were assessed with the somatization scale of the Four-Dimensional Symptom Questionnaire (4DSQ), and included cardiopulmonary, musculoskeletal, gastrointestinal, and general symptoms. Analyses were adjusted for covariates such as chronic somatic diseases, sociodemographics, and lifestyle factors.ResultsAll clusters of somatic symptoms were more prevalent in patients with depressive and/or anxiety disorders than in controls (all p<.001). Multivariable logistic regression analyses showed that all types of depressive and anxiety disorders were independently related to somatic symptoms, except for dysthymic disorder. Major depressive disorder showed the strongest associations. Associations remained similar after adjustment for covariates.ConclusionThis study demonstrated that depressive and anxiety disorders show strong and partly differential associations with somatic symptoms. Future research should investigate whether an adequate consideration and treatment of somatic symptoms in depressed and/or anxious patients improve treatment outcomes

The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders

Although current classification systems have greatly contributed to the reliability of psychiatric diagnoses, they ignore the unique role of individual symptoms and, consequently, potentially important information is lost. The network approach, in contrast, assumes that psychopathology results from the causal interplay between psychiatric symptoms and focuses specifically on these symptoms and their complex associations. By using a sophisticated network analysis technique, this study constructed an empirically based network structure of 120 psychiatric symptoms of twelve major DSM-IV diagnoses using cross-sectional data of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, second wave; N = 34,653). The resulting network demonstrated that symptoms within the same diagnosis showed differential associations and indicated that the strategy of summing symptoms, as in current classification systems, leads to loss of information. In addition, some symptoms showed strong connections with symptoms of other diagnoses, and these specific symptom pairs, which both concerned overlapping and non-overlapping symptoms, may help to explain the comorbidity across diagnoses. Taken together, our findings indicated that psychopathology is very complex and can be more adequately captured by sophisticated network models than current classification systems. The network approach is, therefore, promising in improving our understanding of psychopathology and moving our field forward

Mental disorders as networks of problems:A review of recent insights

Purpose: The network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years. Methods: This paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three main themes: comorbidity, prediction, and clinical intervention. Results: Pertaining to comorbidity, the network approach provides a powerful new framework to explain why certain disorders may co-occur more often than others. For prediction, studies have consistently found that symptom networks of people with mental disorders show different characteristics than that of healthy individuals, and preliminary evidence suggests that networks of healthy people show early warning signals before shifting into disordered states. For intervention, centrality—a metric that measures how connected and clinically relevant a symptom is in a network—is the most commonly studied topic, and numerous studies have suggested that targeting the most central symptoms may offer novel therapeutic strategies. Conclusions: We sketch future directions for the network approach pertaining to both clinical and methodological research, and conclude that network analysis has yielded important insights and may provide an important inroad towards personalized medicine by investigating the network structures of individual patients

NET-RMDs study: networks of fatigue and pain in rheumatic and musculoskeletal diseases - protocol for an international cross-sectional study

Introduction Fatigue and pain are the main symptoms of rheumatic and musculoskeletal diseases (RMDs). Healthcare professionals have a primary role in helping patients to manage both these symptoms, which are part of a complex network of co-occurring factors including sleep problems, psychological distress, social support, body weight, diet, inactive lifestyle and disease activity. The patterns of relationships (networks) between these factors and these symptoms, fatigue and pain, are largely unknown. The current proposal aims to reveal them using network estimation techniques. We will also consider differences in networks for subgroups of people with (1) different RMDs and (2) different clusters (profiles) of biopsychosocial factors. Methods and analysis Adults with at least one RMD will be recruited to this online cross-sectional observational project. To provide a complete overview, a large sample size from different countries will be included. A brief online survey, using 0–10 numeric rating scales will measure, for the past month, levels of fatigue and pain as well as scores on seven biopsychosocial factors. These factors were derived from literature and identified by interviews with patients, health professionals and rheumatologists. Using this input, the steering committee of the project decided the factors to be measured giving priority to those that can be modified in self-management support in community health centres worldwide. Network estimation techniques are used to detect the complex patterns of relationships between these biopsychosocial factors, fatigue and pain; and how these differ for subgroups of people with different RMDs and profiles. Ethics and dissemination Ethical approval of national Institutional Review Boards was obtained. The online survey includes an information letter and informed consent form. The findings will be disseminated via conferences and publications in peer-reviewed scientific journals, while public media channels will be used to inform people with RMDs and other interested parties

Alcohol use disorders and the course of depressive and anxiety disorders

BACKGROUND: Inconsistent findings have been reported on the role of comorbid alcohol use disorders as risk factors for a persistent course of depressive and anxiety disorders. AIMS: To determine whether the course of depressive and/or anxiety disorders is conditional on the type (abuse or dependence) or severity of comorbid alcohol use disorders. METHOD: In a large sample of participants with current depression and/or anxiety (n = 1369) we examined whether the presence and severity of DSM-IV alcohol abuse or alcohol dependence predicted the 2-year course of depressive and/or anxiety disorders. RESULTS: The persistence of depressive and/or anxiety disorders at the 2-year follow-up was significantly higher in those with remitted or current alcohol dependence (persistence 62% and 67% respectively), but not in those with remitted or current alcohol abuse (persistence 51% and 46% respectively), compared with no lifetime alcohol use disorder (persistence 53%). Severe (meeting six or seven diagnostic criteria) but not moderate (meeting three to five criteria) current dependence was a significant predictor as 95% of those in the former group still had a depressive and/or anxiety disorder at follow-up. This association remained significant after adjustment for severity of depression and anxiety, psychosocial factors and treatment factors. CONCLUSIONS: Alcohol dependence, especially severe current dependence, is a risk factor for an unfavourable course of depressive and/or anxiety disorders, whereas alcohol abuse is not

Applying polygenic risk scores to postpartum depression

The etiology of major depressive disorder (MDD) is likely to be heterogeneous, but postpartum depression (PPD) is hypothesized to represent a more homogenous subset of MDD. We use genome-wide SNP data to explore this hypothesis

Disturbances in Hypothalamic-Pituitary-Adrenal Axis and Immunological Activity Differentiating between Unipolar and Bipolar Depressive Episodes

Differentiating bipolar depression (BD) from unipolar depression (UD) is difficult in clinical practice and, consequently, accurate recognition of BD can take as long as nine years. Research has therefore focused on the discriminatory capacities of biomarkers, such as markers of the hypothalamic-pituitary-adrenal (HPA) axis or immunological activity. However, no previous study included assessments of both systems, which is problematic as they may influence each other. Therefore, this study aimed to explore whether cortisol indicators and inflammatory markers were a) independently associated with and/or b) showed effect modification in relation to a lifetime (hypo)manic episode in a large sample of depressed patients.Data were derived from the Netherlands Study of Depression and Anxiety and comprised 764 patients with a DSM-IV depressive disorder at baseline, of which 124 (16.2%) had a lifetime (hypo)manic episode at the 2-year assessment, or a more recent episode at the 4-year or 6-year assessment. Baseline cortisol awakening response, evening cortisol and diurnal cortisol slope were considered as cortisol indicators, while baseline C-reactive Protein (CRP), Interleukin-6 (IL-6), and Tumor Necrosis Factor Alpha (TNF-α) were included as inflammatory markers.In depressed men and women, none of the cortisol indicators and inflammatory markers were (independently) associated with a (hypo)manic episode. However, effect modification was found of diurnal cortisol slope and CRP in relation to a (hypo)manic episode. Further analyses showed that depressed men with high levels of diurnal cortisol slope and CRP had an increased odds (OR=10.99, p=.001) of having a (hypo)manic episode. No significant differences were found in women.Our findings suggest that the combination of high diurnal cortisol slope and high CRP may differentiate between UD and BD. This stresses the importance of considering HPA-axis and immunological activity simultaneously, but more research is needed to unravel their interrelatedness

Zooming In and Zooming Out:A Network Perspective on the Comorbidity of Depression and Anxiety

Several statistical techniques are available to shed light on the structure of psychopathology, and each is valuable in its own way. It is, however, important to realize that the results of these techniques are substantially influenced by the structure of the studied instrument. Network analyses are no exception and do not perform miracles. However, they are unique in embracing the diversity of psychopathology, as the approach is both specific, by zooming in on individual symptoms, and transdiagnostic, by zooming out on the broad spectrum of psychopathology. Therefore, I genuinely believe that it will move our field forward

The complex clinical response to selective serotonin reuptake inhibitors in depression: a network perspective

The clinical response to selective serotonin reuptake inhibitors (SSRIs) in depression takes weeks to be fully developed and is still not entirely understood. This study aimed to determine the direct and indirect effects of SSRIs relative to a placebo control condition on clinical symptoms of depression. We included data of 8262 adult patients with major depression participating in 28 industry-sponsored US Food and Drug Administration (FDA) registered trials on the efficacy of SSRIs. Clinical symptoms of depression were assessed by the 17 separate items of the Hamilton Depression Rating Scale (HDRS) after 1, 2, 3, 4 and 6 weeks of treatment. Network estimation techniques showed that SSRIs had quick and strong direct effects on the two affective symptoms, i.e., depressed mood and psychic anxiety; direct effects on other symptoms were weak or absent. Substantial indirect effects were found for all four cognitive symptoms, which showed larger reductions in the SSRI condition but mainly in patients reporting larger reductions in depressed mood. Smaller indirect effects were found for two arousal/somatic symptoms via the direct effect on psychic anxiety. Both direct and indirect effects on sleep problems and most arousal/somatic symptoms were weak or absent. In conclusion, our study revealed that SSRIs primarily caused reductions in affective symptoms, which were related to reductions in mainly cognitive symptoms and some specific arousal/somatic symptoms. The results can contribute to disclosing the mechanisms of action of SSRIs, and has the potential to facilitate early detection of responders and non-responders in clinical practice