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 Table of Contents  
Year : 2019  |  Volume : 3  |  Issue : 2  |  Page : 47-54

Inflammatory and vascular correlates of mood change over 8 weeks

1 Department of Psychiatry; Roy J. and Lucille A. Carver College of Medicine, The University of Iowa, Iowa City, Iowa, USA
2 Department of Psychiatry, The University of Iowa, Iowa City, Iowa, USA
3 Department of Psychiatry; Department of Epidemiology, College of Public Health, The University of Iowa, Iowa City, Iowa, USA
4 Department of Health and Human Physiology, The University of Iowa, Iowa City, Iowa, USA
5 Department of Health and Human Physiology; François M. Abboud Cardiovascular Research Center, The University of Iowa, Iowa City, Iowa, USA
6 Department of Psychiatry; Roy J. and Lucille A. Carver College of Medicine; Department of Epidemiology, College of Public Health; Department of Health and Human Physiology; François M. Abboud Cardiovascular Research Center; Department of Internal Medicine; Iowa Neuroscience Institute, Obesity Research and Education Initiative, The University of Iowa, Iowa City, Iowa, USA

Date of Submission08-Aug-2019
Date of Acceptance25-Sep-2019
Date of Web Publication25-Nov-2019

Correspondence Address:
Dr. Jess G Fiedorowicz
200 Hawkins Drive W278GH, Iowa City, Iowa 52242-1057
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/hm.hm_24_19

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Background: Mood disorders have been associated with a variety of cardiovascular disease (CVD) risk factors, including inflammation and large arterial stiffness, particularly while depressed, although longitudinal studies have been limited. Materials and Methods: With measurements at baseline and 8 weeks, the researchers prospectively assessed mood, levels of inflammatory markers (high-sensitivity C-reactive protein and tumor necrosis factor-alpha [TNF-α]), serum lipids, and large arterial stiffness in a cohort of 26 participants with a diagnosis of a mood disorder, enriched for current depression. Depressive symptoms were measured using the Montgomery–Šsberg Depression Rating Scale (MADRS) at baseline and 8 weeks. Associations between depressive symptoms and other measures were assessed using linear mixed models, unadjusted and adjusted for age and body mass index. Results: The mean age of the participants (n = 26) was 41.6 (standard deviation [SD] 12.8) years, and 81% were female. During the study, there was a mean (SD) MADRS score improvement of 9.5 (9.4) from baseline to 8 weeks. Reductions in the primary outcome of tumor necrosis factor-α with improvement in depression fell short of statistical significance (P = 0.076). In secondary analyses, there was a statistically significant association between improved cholesterol ratio (P = 0.038) and triglycerides (P = 0.042) with improvement in depression. There was no statistically significant change in large arterial stiffness during the study. Conclusion: Improved depressive symptoms were associated with improved cholesterol ratios even after adjustment, suggesting a possible mechanism by which acute mood states may influence CVD risk. Future longitudinal studies with extended and intensive follow-up investigating CVD risk related to acute changes and persistence of mood symptoms are warranted.

Keywords: Arterial stiffness, bipolar disorder, cardiovascular disease risk, inflammation, lipids, major depressive disorder, mood disorder, pulse wave velocity

How to cite this article:
Birdsall JW, Schmitz SL, Abosi OJ, DuBose LE, Pierce GL, Fiedorowicz JG. Inflammatory and vascular correlates of mood change over 8 weeks. Heart Mind 2019;3:47-54

How to cite this URL:
Birdsall JW, Schmitz SL, Abosi OJ, DuBose LE, Pierce GL, Fiedorowicz JG. Inflammatory and vascular correlates of mood change over 8 weeks. Heart Mind [serial online] 2019 [cited 2023 May 31];3:47-54. Available from: http://www.heartmindjournal.org/text.asp?2019/3/2/47/271531

  Introduction Top

Mood disorders are associated with excess cardiovascular mortality, approximately two-fold greater than expected from general population estimates,[1],[2],[3] and this risk may be greatest in those with more chronic mood symptoms.[4],[5] In an effort to determine how this risk is mediated, prior studies of vascular function in mood disorders have shown a variety of vascular measurements to be impaired relative to controls, especially in older adults with a longer and more persistent course of illness.[6],[7] In a year-long prospective study of 37 participants in medical internship, those who developed depressive symptoms, as measured with the Patient Health Questionnaire-9 every 3 months, also had reduced endothelial function when symptomatic.[8] Similar findings were seen in a cross-sectional study of adolescent girls, presumably without atherosclerosis, but, here, their depressive symptoms were measured using the Beck Depression Inventory.[9] Although these two studies measured depressive symptoms by a different method, endothelial function was measured with the same methodology: using finger plethysmography and subsequent determination of a reactive hyperemia index. Furthermore, it has been shown that the association between large arterial stiffness (measured by carotid–femoral pulse wave velocity [PWV]) and depressive symptoms is strengthened when those with depressive disorders meet the DSM-IV criteria, perhaps suggesting a dose response with severity.[10]

The autonomic nervous system and hypothalamic–pituitary–adrenal (HPA) axis are putative physiological mechanisms that link mood disorders with cardiovascular disease (CVD). Alterations in sympathetic activity[11],[12] or HPA axis[13] can trigger a pro-inflammatory state, and inflammation accelerates atherosclerosis.[14] Taken together, it seems that these may be mechanisms that mediate CVD risk. There have been numerous cross-sectional studies that demonstrated excess pro-inflammatory markers in individuals with mood disorders. One meta-analysis of case–control studies in bipolar disorder found that those with bipolar disorder had higher concentrations of soluble interleukin (IL)-2 receptor, soluble IL-6 receptor, tumor necrosis factor-alpha (TNF-α), soluble TNF receptor type 1, and IL-4.[15] Another meta-analysis of inflammatory markers showed that C-reactive protein (CRP), IL-1, and IL-6 were all significantly associated with depression.[16] A separate meta-analysis showed that levels of TNF-α and IL-6 were significantly elevated in depressed patients when compared to controls.[17] A cross-sectional analysis of the representative Third National Health and Nutrition Examination Survey III data suggests that mood-related inflammation may persist for 1–6 months.[18]

These aforementioned meta-analyses of mood disorders and pro-inflammatory states only included cross-sectional studies, and longitudinal approaches are needed to establish temporal associations between inflammation and mood states. In a prior work, greater inflammation during mood states in those with bipolar I disorder has been observed.[19] Changes in serum lipids related to depressive symptoms have not been observed.[20] With the opportunity to follow a cohort of individuals being treated for diagnosed mood disorders (major depression, bipolar II disorder, and bipolar I disorder) in the midst of a major depressive episode, the researchers sought to evaluate for potential change in the markers of vascular risk. The researchers hypothesized that improvements in depressive symptoms would be correlated with reductions in TNF-α, as well as high-sensitivity CRP (hsCRP) (aim one), but not serum lipids (aim two). The researchers also explored (aim three) whether any changes in depressive symptoms are related to the measures of arterial stiffness, as measured by carotid–femoral PWV.

  Materials and Methods Top


The researchers recruited the study participants from an existing sample of individuals diagnosed with bipolar I disorder, bipolar II disorder, or major depressive disorder – all were recruited from those screened for a separate study of proteomics for mood disorders, funded by Myriad Genetics, Inc. Salt Lake City, Utah, USA. All the participants provided written informed consent in this institutional review board-approved study. During screening, the researchers confirmed diagnoses with the relevant portions of the Structured Clinical Interview for DSM-5 (SCID)[21] and the Mini International Neuropsychiatric Interview (MINI).[22] The researchers enrolled those who met the diagnostic criteria for mood disorder. Given that in the parent study the researchers recruited those with a current depressive episode, the sample was enriched for higher levels of depressive symptoms although this was not a formal inclusion criterion for this study and two participants were not in an episode. All the participants were being treated for their mood disorder by their providers, and there were no psychotropic medications that were prohibitive for inclusion in the study. The inclusion criteria also required participants to be between 18 and 70 years of age. The researchers excluded those at a high risk for suicide, those with severe substance use disorders, those with a diagnosis of borderline personality disorder, those with medical conditions with neurologic sequelae, those with severe chronic pain or with acute unstable medical illness, those on high-potency immune-modulating medications, and pregnant females.

Mood assessments

There was a baseline assessment and 8-week follow-up assessment. Weights were measured without shoes, in light clothing, using a scale that measures to the nearest 0.25 kg. Standing heights were measured without shoes, to the nearest 0.1 cm, using a free-standing stadiometer. These weights and heights were utilized for the computation of body mass index (BMI). A medical history and structured psychiatric history (MINI + SCID portions) were obtained during the first visit, with medication use recorded at both visits, including a list of medications taken in the last 12 months. The participants filled out the MacArthur Scale of Subjective Social Status and Beck's Anxiety Inventory during the first visit.

During both visits, the participants were assessed with the Young Mania Rating Scale[23] and the Montgomery–Šsberg Depressive Rating Scale (MADRS)[24] for clinician assessment of manic and depressive symptoms, respectively. The participants also filled out the Major Depressive Inventory (MDI)[25],[26] to self-assess depressive symptoms.

Inflammatory markers and lipid panel

Venous blood was obtained during each visit to measure hsCRP (turbidimetric method) and TNF-α. Plasma TNF-α was measured by a high-sensitivity 4-h solid phase enzyme-linked immunosorbent assay (R and D Systems, Inc. Minneapolis, Minnesota, USA) in duplicate using a sandwich enzyme immunoassay technique. These data were used to investigate the primary aim of the study to assess change in inflammatory markers with mood. Nonfasting measures of total cholesterol, high-density lipoprotein-cholesterol (HDL-c), plasma triglycerides, and glucose were obtained. Low-density lipoprotein-cholesterol (LDL-c) was calculated from these values as long as triglycerides did not exceed 400 mg/dL. Cholesterol ratio was calculated by dividing total cholesterol by HDL-c. According to the longitudinal analysis of the Framingham Offspring Cohort (n = 3014), this cholesterol ratio is predictive of insulin resistance (measured by the Homeostasis Model Assessment of Insulin Resistance) with an area under the curve of 0.71.[27] Total cholesterol and HDL-c vary little with respect to fasting status, so in order to make follow-up less burdensome yet still provide quality measurements of insulin resistance, the participants did not fast.[28] The lipid panel data were used to investigate the secondary aim of the study, i.e., the relationship between changes in mood and serum lipids.

Carotid–femoral pulse wave velocity

Carotid–femoral PWV is an independent predictor of coronary heart disease and stroke in healthy controls[29] and an independent predictor of mortality in the general population,[30] hypertensive patients,[31] older community,[32] hospitalized[33] individuals, and patients with end-stage renal disease.[34] A standard deviation (SD) increase in carotid–femoral PWV has also been associated with a 48% increase in first-onset CVD event risk, as evidenced in one community-based observational study of middle-aged and older participants (n = 2232).[35] Carotid–femoral, carotid–brachial, and carotid–radial PWV are measured noninvasively by recording carotid, femoral, brachial, and radial artery pressure waveforms sequentially with an applanation tonometer (noninvasive Hemodynamics Workstation, Cardiovascular Engineering, Inc. Norwood, Massachusetts, USA). Pressure waveforms are gated to the electrocardiography R wave in order to calculate the transit time (t) between the foot of the carotid and the respective peripheral (femoral, brachial, and radial) waveforms. The carotid–femoral transit distance (CFTD) is estimated between the two anatomical sites as the difference between the suprasternal notch (SSN) to carotid (SSN-C) and femoral (SSN-F) sites. Thus, the CFTD is calculated as CFTD = SSN-F − SSN-C and PWV is calculated as CFTD/t. This approach accounts for parallel transmission of the pulse wave up to the brachiocephalic and carotid arteries, and simultaneously along the aortic arch using the SSN as a fiducial point where parallel transmission begins (i.e., bifurcation site of aortic arch and brachiocephalic artery).

Statistical analysis

R 3.5.2 (R Core Team, Vienna, Austria) and package “lme4” were used to conduct data analysis.[36],[37] To assess the relationship between the MADRS score and the outcome variables (TNF-α, hsCRP, serum lipids, and PWV), the researchers used a linear mixed model with a random intercept. A linear mixed model allows for baseline MADRS score responses to vary between individuals, account for repeated observations (baseline and week 8), and adjust for other variables, while still determining whether a shared relationship with the outcome variables exists. The researchers initially performed unadjusted analyses and subsequently adjusted for age and BMI. A sensitivity analysis of the relationship between self-reported MDI scores and the outcome variables was also done to compare with clinician-administered MADRS analysis. An apriori statistical analysis plan was done and the level of statistical significance was set to be P < 0.05 for the primary outcome (TNF-α). As a cross-sectional analysis, a univariate Spearman's rank correlation of baseline and week 8 MADRS scores with the outcome variables (TNF-α, hsCRP, PWV, serum lipids, and vitals) was done.

  Results Top

The mean age of the participants (n = 26) was 41.6 (standard deviation [SD] 12.8) years, and 81% were female. Ten participants (38%) had bipolar I disorder, nine (35%) had bipolar II disorder, and seven (27%) had major depressive disorder. Half of the participants were employed and had a mean (SD) of 15.3 (2.5) years of education. The racial distribution of the participants was 88% White and 8% Black, with 4% of the participants reporting a Hispanic ethnicity. With regard to significant past medical history, one (4%) participant had a heart attack, three (12%) had heart disease, four (15%) had diabetes, and six (23%) had hypertension. Additional sociodemographic information is summarized in [Table 1],[38],[39] and baseline clinical characteristics are summarized in [Table 2]. Additional clinical characteristics of the sample are summarized in [Supplemental Table 1][Additional file 1].
Table 1: Baseline sociodemographic characteristics (n=26)

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Table 2: Baseline clinical characteristics (n=26)

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During the 8-week study period, there was a mean (SD) decrease of 9.5 (9.4) in MADRS scores for those with baseline and follow-up assessments, as anticipated with participants being treated for depression by their providers. This improvement was also reflected in the self-reported MDI that the participants filled out. The mean and SDs of all variables in the study, at the two time points, are shown in [Table 3]. Only two participants reached remission (MADRS <10) at the end of the study. There were no participants in the study that started a new selective serotonin reuptake inhibitor (SSRI) or serotonin-norepinephrine reuptake inhibitor, whereas 14 participants were on this class of medication throughout the study period and four participants changed their dose: three increased and one decreased. Ten participants had dose changes in nonpsychotropic medications between baseline and 8 weeks, and four participants started new nonpsychotropic medications during the study.
Table 3: Values of key variables at baseline and follow-up

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When modeling MADRS on TNF-α levels over an 8-week period, the researchers found reductions in TNF-α corresponding to improvements in MADRS that fell short of statistical significance (P = 0.076). There were no statistically significant associations between MADRS scores and change in the secondary inflammatory marker, hsCRP, as shown in [Table 4]. No statistically significant associations were reflected between self-reported MDI and TNF-α or hsCRP.
Table 4: Linear mixed model: Effects of total Montgomery-Åsberg Depression Rating Scale score on outcomes

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Contrary to expectations, the secondary analysis showed statistically significant associations between lower cholesterol ratio (P = 0.038) and lower triglycerides (P = 0.042) with reductions in MADRS. The statistically significant relationship for cholesterol ratio remained the same (P = 0.034) after adjusting for age and BMI, whereas triglycerides no longer crossed the threshold of statistical significance (P = 0.063). There were no statistically significant associations between MADRS scores over time and any of the other metabolic measurements, including cholesterol, HDL-c, LDL-c, and glucose. These results are shown in [Table 4]. A similar relationship appears when running an unadjusted sensitivity analysis comparing self-reported MDI with serum lipids, except that the researchers no longer see statistical significance for triglycerides (P = 0.269) or cholesterol ratio (P = 0.066). A sensitivity analysis of the effect that psychotropic medications might have on these results was also conducted, with separate models adding indicator variables for all psych meds, antidepressants, antipsychotics, and mood stabilizers. This did not substantially alter results or change the statistical significance when also adjusting for age and BMI.

In the exploratory analysis of carotid–femoral PWV using linear mixed models, there were no statistically significant associations between carotid–femoral PWV and MADRS scores over 8 weeks (P = 0.892). When looking at Spearman's rank correlations of baseline and week eight MADRS scores and our outcomes of interest, statistical significance for a positive correlation in baseline TNF-α (P = 0.011) was shown. These results are summarized in [Table 5].
Table 5: Spearman's rank correlation of Montgomery-Åsberg Depression Rating Scale

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  Discussion Top

In this small prospective 8-week study of individuals with rigorously diagnosed mood disorders, the researchers observed a reduction in the primary outcome (TNF-α) and improvement in depressive symptoms (MADRS) in the expected direction that fell short of statistical significance. The researchers did not expect associations between serum lipids and mood over time, based on a previous work done by Persons et al., 2017.[20] Interestingly, the largest observed effects involved reductions in cholesterol ratio and triglycerides with improvement of depressive symptoms. Persons et al. did not explore cholesterol ratio in their analysis, so this may be a finding that warrants further investigation. Other surrogate measures for insulin resistance have been used to show a significant cross-sectional association between insulin resistance and depression, as detailed in a systematic review and meta-analysis by Kan et al., 2013.[40]

Total cholesterol/HDL-c ratio has been linked to greater risk of CVD[41] and highly correlated with insulin resistance.[42] Furthermore, insulin resistance is associated with risk factors for coronary artery disease, such as increased triglyceride concentration.[43] In the current study, the association between cholesterol ratio and depression is strengthened by the persistence of this statistically significant relationship after adjusting for change in BMI. The pattern observed could be related to an increase in insulin resistance among those in a depressive episode, thereby increasing CVD risk with more frequent or chronic depressive episodes. This association does not appear to be confounded by BMI. The study did not measure insulin levels, and glucose levels alone would not be sensitive enough to detect changes in insulin resistance. Insulin resistance that improves with depressive symptom resolution, as measured by the clinician-administered Hamilton Rating Scale for Depression (HRSD), has been shown previously in a prospective study of twenty nondiabetic patients.[44] In the aforementioned study, every HRSD point improvement would see an average increase in 2.34 insulin sensitivity index, a measurement from the intravenous glucose tolerance test. The twenty depressed patients had oral and intravenous glucose tolerance tests when symptomatic at baseline and a mean (SD) of 82 (28) days later following treatment with tricyclic antidepressants, and then were compared with age-, sex-, and BMI-matched healthy controls (n = 13) who had one measurement with the intravenous glucose tolerance test. The authors opted not to use SSRIs because of possible weight reduction, as has been observed in short-term studies of SSRIs, or improvement in insulin sensitivity. A systematic review published years later by different authors describes this finding that serotonergic antidepressants are associated with increased insulin sensitivity.[45] Perhaps, aggressively treating depression with serotonergic medication leads to a better cardiometabolic profile in patients, rather than owing the relationship to depressive symptom resolution.

Finally, the exploratory analysis of changes in arterial stiffness (PWV) with improvements in depressive symptoms did not show statistical significance. The short duration of follow-up may not be long enough to see significant changes in arterial stiffness. In a recent prospective study of participants with type 2 diabetes mellitus with dyslipidemia being treated with diet and low-dose atorvastatin, a 7.5% reduction in carotid–femoral PWV was observed at 12 weeks from baseline with statistical significance (P< 0.001).[46] The previously mentioned Fiedorowicz et al.'s study on endothelial dysfunction during medical internship investigated changes in reactive hyperemia index at baseline and 1 year later, another indication that changes in vascular function need to be studied over a longer period of time.[8] The sample was not aggressively treated, with only two participants achieving remission (MADRS <10) and followed up for only 8 weeks.[47]

Nonetheless, the study sample's depressive symptoms did improve over the course of the study; hence, the researchers could appropriately address the question of whether immediate depressive symptom improvement is associated with improved measures of cardiovascular risk, presuming that the effects were observable within 8 weeks and did not require remission of symptoms to resolve. MADRS and MDI scores both improved, but unlike MADRS, the MDI analyses did not show statistically significant associations with any of the dependent variables. MADRS was more sensitive to changes in the sample. This difference could be due to interviewer (MADRS)- or self (MDI)-reporting ratings, or how each scoring system is weighted. There are two measurements related to mood in MADRS, as opposed to just one item in MDI. MADRS is also framed in the context of the previous week, rather than the previous 2 weeks in the MDI – perhaps, the more precise time frame of MADRS better captures mood symptoms, and their changes, particularly in such a short-term study. It is worth noting that MADRS measures sleep and appetite in a unidirectional fashion: a higher score results from less sleep and appetite, which would not capture those with atypical depression. Interestingly, in a cross-sectional study of 153 adolescents comparing self- versus interviewer-ratings of the negative impact acute and chronic stressors have on the individual, the interviewer assessments are stronger predictors of adolescent low-grade inflammation than adolescents' own evaluation of the impact of the very same stressful life events.[48]

The small sample size is a key limitation in the study, leaving the study powered to detect only moderate-to-large effects. As most participants were female, it is worth noting that these findings cannot be generalizable to males and should warrant further research in this area – a larger sample size could better study the distribution of male and female participants that reflects the population. With the primary outcome being negative, the secondary findings should be considered hypothesis generating and require replication, ideally in a larger sample and including better assessments of insulin resistance. The duration of the study is also a limitation in evaluating lasting relationships between cardiovascular health and mood disorders, as these are both chronic health conditions. Observations of arterial stiffness changes due to depressive symptoms and the proposed subsequent inflammation may take longer than 8 weeks. Infrequent remission of the sample size is another limitation and would bias results to the null hypothesis. Strengths of the study include its prospective design with a population whose symptoms improved with treatment, an apriori statistical analysis plan to decrease the risk of type I error, and a well-characterized cohort.

  Conclusion Top

The cohort had improved CVD risk factors with improvement of their depressive symptoms. Long-term prospective studies are lacking in the study of how acute changes in mood may negatively affect cardiovascular health and hence, larger samples that are treated to remission should be explored for a longer term. The results highlight the potential acute role of lipid changes that perhaps reflect the underlying insulin resistance. With marginally significant findings in this small sample, the researchers can neither confirm nor rule out inflammation as another potentially relevant mediator. Longitudinal study in mood disorders with their episodic nature holds some promise for identifying the most relevant mechanisms for this public health disparity in which those with mood disorders face nearly twice the expected risk of CVD and mortality.


The authors thank Janie E. Myers for her assistance in the recruitment of patients, Lauren J. Points for running the inflammatory marker assays, Martin Rosenfeld for literature review, and Amy K. Stroud for conducting pulse wave velocity measurements.

Financial support and sponsorship

This study was financially supported by the National Institutes of Health (P01HL014388) and the Department of Psychiatry at the University of Iowa.

Conflicts of interest

There are no conflicts of interest.

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  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]

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