Context: Stress is suggested to lead to metabolic dysregulations as clustered in the metabolic syndrome, but the underlying biological mechanisms are not yet well understood.Objective: We examined the relationship between two main str systems, the autonomic nervous system and the hypothalamic-pituitary-adrenal (HPA) axis, with the metabolic syndrome and its components.Design: The design was baseline data (yr 2004–2007) of a prospective cohort: the Netherlands Study of Depression and Anxiety (NESDA).Setting: The study comprised general community, primary care, and specialized mental health care.Participants: This study included 1883 participants aged 18–65 yr.Main Outcome Measures: Autonomic nervous system measures included heart rate, respiratory sinus arrhythmia (RSA; high RSA reflecting high parasympathetic activity), and preejection period (PEP; high PEP reflecting low sympathetic activity). HPA axis measures included the cortisol awakening response, evening cortisol, and a 0.5 mg dexamethasone suppression test as measured in saliva. Metabolic syndrome was based on the updated Adult Treatment Panel III criteria and included high waist circumference, serum triglycerides, blood pressure, serum glucose, and low high-density lipoprotein cholesterol.Results: RSA and PEP were both independently negatively associated with the presence of the metabolic syndrome, the number of metabolic dysregulations as well as all individual components except high-density lipoprotein cholesterol (all P < 0.02). Heart rate was positively related to the metabolic syndrome, the number of metabolic dysregulations, and all individual components (all P < 0.001). HPA axis measures were not related to metabolic syndrome or its components.Conclusion: Our findings suggest that increased sympathetic and decreased parasympathetic nervous system activity is associated with metabolic syndrome, whereas HPA axis activity is not.

Background
Dyslipidemia and obesity have been observed in persons with severe anxiety or depression, and in tricyclic antidepressant (TCA) users. This likely contributes to the higher risk of cardiovascular disease (CVD) in anxiety and depressive disorders. We aimed to elucidate whether biological stress systems or lifestyle factors underlie these associations. If so, they may be useful targets for CVD prevention and intervention.
Methods
Within 2850 Netherlands Study of Depression and Anxiety (NESDA) participants, we evaluated the explaining impact of biological stress systems (i.e., the hypothalamic–pituitary–adrenal [HPA] axis, autonomic nervous system [ANS] and inflammation) and lifestyle factors (i.e., tobacco and alcohol use, and physical activity) on adverse associations of anxiety and depression severity and TCA use with high and low-density lipoprotein cholesterol, triglycerides, body mass index and waist circumference. Through linear regression analyses, percentual change (%Δ) in β was determined and considered significant when %Δ>10.
Results
The inflammatory marker C-reactive protein had the most consistent impact (explaining 14–53% of the associations of anxiety and depression severity and TCA use with lipid and obesity levels), followed by tobacco use (explaining 34–43% of the associations with lipids). The ANS mediated all associations with TCA use (explaining 32–61%). The HPA axis measures did not explain any of the associations.
Conclusions
Increased dyslipidemia and (abdominal) obesity risk in patients with more severe anxiety disorders and depression may be partly explained by chronic low-grade inflammation and smoking. TCAs may increase metabolic risk through enhanced sympathetic and decreased parasympathetic ANS activity. That the HPA axis had no impact in our sample may reflect the possibility that the HPA axis only plays a role in acute stress situations rather than under basal conditions.

Background
Childhood trauma (CT) is a risk factor for depressive and anxiety disorders. Although dysregulated biological stress systems may underlie the enduring effect of CT, the relation between CT and separate and cumulative activity of the major stress systems, namely, the hypothalamic-pituitary-adrenal (HPA)-axis, the immune-inflammatory system, and the autonomic nervous system (ANS), remains inconclusive.
Methods
In the Netherlands Study of Depression and Anxiety (NESDA, n = 2778), we determined whether self-reported CT (as assessed by the Childhood Trauma Interview) was associated with separate and cumulative markers of the HPA-axis (cortisol awakening response, evening cortisol, dexamethasone suppression test cortisol), the immune-inflammatory system (C-reactive protein, interleukin-6, tumor necrosis factor-α), and the ANS (heart rate, respiratory sinus arrhythmia, pre-ejection period) in adulthood.
Results
Almost all individuals with CT (n = 1330) had either current or remitted depressive and/or anxiety disorder (88.6%). Total-sample analyses showed little evidence for CT being significantly associated with the separate or cumulative stress systems’ activity in adulthood. These findings were true for individuals with and without depressive and/or anxiety disorders. To maximize contrast, individuals with severe CT were compared to healthy controls without CT. This yielded slight, but significantly higher levels of cortisol awakening response (AUCg, β = .088, p =  .007; AUCi, β = .084, p =  .010), cumulative HPA-axis markers (β = .115, p =  .001), C-reactive protein (β = .055, p = .032), interleukin-6 (β = .053, p =  .038), cumulative inflammation (β = .060, p =  .020), and cumulative markers across all systems (β = .125, p =  .0003) for those with severe CT, partially explained by higher rates of smoking, body mass index, and chronic diseases.
Conclusion
While our findings do not provide conclusive evidence on CT directly dysregulating stress systems, individuals with severe CT showed slight indications of dysregulations, partially explained by an unhealthy lifestyle and poorer health.

Background: Given the strong relationship between depression and anxiety, there is an urge to investigate their shared and specific long-term course determinants. The current study aimed to identify and compare the main determinants of the 9-year trajectories of combined and pure depression and anxiety symptom severity. Methods: Respondents with a 6-month depression and/or anxiety diagnosis (n=1,701) provided baseline data on 152 sociodemographic, clinical and biological variables. Depression and anxiety symptom severity assessed at baseline, 2-, 4-, 6- and 9-year follow-up, were used to identify data-driven course-trajectory subgroups for general psychological distress, pure depression, and pure anxiety severity scores. For each outcome (class-probability), a Superlearner (SL) algorithm identified an optimally weighted (minimum mean squared error) combination of machine-learning prediction algorithms. For each outcome, the top determinants in the SL were identified by determining variable-importance and correlations between each SL-predicted and observed outcome (ρpred) were calculated. Results: Low to high prediction correlations (ρpred: 0.41-0.91, median=0.73) were found. In the SL, important determinants of psychological distress were age, young age of onset, respiratory rate, participation disability, somatic disease, low income, minor depressive disorder and mastery score. For course of pure depression and anxiety symptom severity, similar determinants were found. Specific determinants of pure depression included several types of healthcare-use, and of pure-anxiety course included somatic arousal and psychological distress. Limitations: Limited sample size for machine learning. Conclusions: The determinants of depression- and anxiety-severity course are mostly shared. Domain-specific exceptions are healthcare use for depression and somatic arousal and distress for anxiety-severity course.