Major depressive disorder and insulin resistance in nondiabetic young adults in the United States: the National Health and Nutrition Examination Survey, 1999-2002

The association between insulin resistance and depressive symptoms - A national representative cross-sectional study

OBJECTIVE

Increasing evidence suggests a positive association between insulin resistance (IR) and depression. However, whether sex-or body mass index-specific differences exist remains controversial, and only few studies have analyzed specific symptom domains. Thus, the present study aimed to analyze the association between IR and depressive symptom domains and to clarify the effects of sex and body mass index.

METHODS

The study sample comprised 4007 participants, aged 19-79, from the Korea National Health and Nutrition Examination Study 2020. Participants completed health interviews and examinations, providing data on circulating insulin and glucose levels, the Patient Health Questionnaire-9 (PHQ-9), and related covariates. IR was calculated using the homeostasis model assessment of insulin resistance. Associations between IR and PHQ-9 were analyzed using negative binomial regression with adjustments for the complex survey design.

RESULTS

The association between log-transformed IR and PHQ-9 total scores was statistically significant (incidence rate ratio [IRR] = 1.17, 95% confidence interval [CI] = 1.07-1.29, p = 0.001). Only body mass index specific differences were statistically significant, as the association was only significant in those without obesity (IRR = 1.21, 95% CI = 1.06-1.38, p = 0.005). IR was associated with cognitive/affective (IRR = 1.23, 95% CI = 1.08-1.41, p = 0.002) and somatic (IRR = 1.14, 95% CI = 1.04-1.25, p = 0.005) depressive symptom domains. Sensitivity analyses revealed similar results.

CONCLUSIONS

IR was positively associated with cognitive/affective and somatic depressive symptoms in non-obese individuals.

Potential Biomarkers for Predicting Depression in Diabetes Mellitus

Objective: To identify the potential biomarkers for predicting depression in diabetes mellitus using support vector machine to analyze routine biochemical tests and vital signs between two groups: subjects with both diabetes mellitus and depression, and subjects with diabetes mellitus alone. Methods: Electronic medical records upon admission and biochemical tests and vital signs of 135 patients with both diabetes mellitus and depression and 187 patients with diabetes mellitus alone were identified for this retrospective study. After matching on factors of age and sex, the two groups (n = 72 for each group) were classified by the recursive feature elimination-based support vector machine, of which, the training data, validation data, and testing data were split for ranking the parameters, determine the optimal parameters, and assess classification performance. The biomarkers were identified by 10-fold cross validation. Results: The experimental results identified 8 predictive biomarkers with classification accuracy of 78%. The 8 biomarkers are magnesium, cholesterol, AST/ALT, percentage of monocytes, bilirubin indirect, triglyceride, lactic dehydrogenase, and diastolic blood pressure. Receiver operating characteristic curve analysis was also adopted with area under the curve being 0.72. Conclusions: Some biochemical parameters may be potential biomarkers to predict depression among the subjects with diabetes mellitus.

Factors related to metabolic parameters in medicated patients with major depressive disorder--a naturalistic study

The aim of this study was to examine the metabolic parameters, including body mass index (BMI), homeostasis model assessment-estimated insulin resistance (HOMA-IR), homeostasis model assessment-estimated pancreatic β-cell function (HOMA-β), and lipid plasma level, in medicated patients with major depressive disorder (MDD) and to assess factors related to metabolic parameters in patients with MDD. 121 patients with MDD and 63 controls were recruited. The Hamilton Depression Rating Scale (HDRS), Wisconsin Card Sorting Test (WCST), Continuous Performance Test (CPT), and Finger-Tapping Test (FTT), were administered. BMI, HOMA-IR, and HOMA-β were calculated as modifiable metabolic parameters. The FTT results and BMI in depressed patients were significantly poorer and lower, respectively, than those of the controls. However, no significant differences were noted between MDD patients and controls included metabolic parameters and other neuropsychological tests. Among depressed patients, higher BMI is significantly related with lower education, no tobacco use, and male. The result demonstrated metabolic parameters could be neutral among medicated patients with MDD, particularly in non-elderly Asian individuals. The deficits of psychomotor speed could be more prominent than other cognitive alterations in patient with MDD.

The association between depressive symptoms and insulin resistance, inflammation and adiposity in men and women

INTRODUCTION

Depression has been shown to be associated with elevated leptin levels, low-grade inflammation and insulin resistance. These derangements are often measured in mixed gender cohorts despite the different body compositions and hormonal environments of men and women and gender-specific prevalence and responses to depression.

METHODS

A cross-sectional analysis was carried out on a cohort of 639 participants from the ADDITION-Leicester dataset to assess differences in markers of diabetes risk, cardiovascular risk and inflammation in depressed and non-depressed individuals. Depressive symptoms were determined using the WHO (Five) well-being index. Multivariate linear and logistic regression analyses were adjusted for age, sex, ethnicity, body mass index, smoking, social deprivation and activity levels for continuous and binary variables respectively. Further analysis included stratifying the data by gender as well as assessing the interaction between depression and gender by including an interaction term in the model.

RESULTS

Women with depressive symptoms had a 5.3% larger waist circumference (p = 0.003), 28.7% higher HOMA IR levels (p = 0.026), 6.6% higher log-leptin levels (p = 0.01) and 22.37% higher TNF-α levels (p = 0.015) compared with women without. Conversely, depressive symptoms in men were associated with 7.8% lower body fat % (p = 0.015) but 48.7% higher CRP levels (p = 0.031) compared to men without. However, interaction analysis failed to show a significant difference between men and women.

CONCLUSIONS

Depressive symptoms are associated with metabolic derangements. Whilst women tended to show elevations in biomarkers related to an increased risk of type 2 diabetes (HOMA IR, leptin and TNF-α), men showed a marked increase in the cardiovascular disease risk biomarker CRP. However, perhaps due to the cohort size, interaction analysis did not show a significant gender difference.

Relationship between major depression and insulin resistance: does it vary by gender or race/ethnicity among young adults aged 20-39 years?

BACKGROUND

To examine the relationship between major depression and insulin resistance by gender and race/ethnicity among young adults without diabetes mellitus.

METHODS

Secondary analyses of cross-sectional data from the National Health and Nutrition Examination Survey 1999-2008 were performed (n = 2265). Major depression was measured by the Composite International Diagnostic Interview and the Patient Health Questionnaire 9. Insulin resistance was measured by the homeostasis model assessment of insulin resistance. Multivariate logistic regression analyses adjusted for risk factors of insulin resistance were conducted.

RESULTS

There was a significant negative association between major depression and insulin resistance among men. For women, no significant association was found. There was no significant interaction between race/ethnicity and major depression on insulin resistance (Wald χ(2) = 4.2927, P = 0.2315). Body mass index (BMI) and waist circumference (WC) were significantly associated with insulin resistance among both men (odds ratio [OR] 1.255, 95% confidence interval [CI] 1.195-1.318 for BMI; OR 1.095, 95% CI 1.076-1.115 for WC) and women (OR 1.220, 95% CI 1.182-1.260 for BMI; OR 1.084, 95% CI 1.064-1.105 for WC).

CONCLUSIONS

There are gender differences in the relationship between major depression and insulin resistance among adults aged 20-39 years. No evidence was found to support the role of race/ethnicity in this relationship. Health care professionals should be aware of risk factors for insulin resistance and develop interventions to help prevent the progression of insulin resistance to type 2 diabetes mellitus.

Associations Among Depression, Obesity, and Metabolic Syndrome in Young Adult Females

Depression may be a risk factor for obesity or metabolic syndrome. The aims of this study were to determine the relationships among depression, obesity, and metabolic syndrome in young adult females as well as the role of depression in the components of metabolic syndrome. A cross-sectional study was conducted on 323 young adult females. Demographic characteristics, anthropometric measurements, and laboratory values were collected. The criteria of the Bureau of Health Promotion, Department of Health, Taiwan, were used to define metabolic syndrome. Depression was measured using the Center for Epidemiologic Studies Depression scale. The prevalence of depression in the sample was 17%, that of overweight and obesity was 17%, and that of metabolic syndrome was 6.8%. Depression showed significant associations with high body mass index (BMI), increased waist circumference and blood pressure (BP), and overweight and obesity (β = 0.15, odds ratio [OR] = 1.17, 95% confidence interval [CI] = [1.11, 1.23], p < .001). No associations were observed between depression and metabolic syndrome (β = −0.01, OR = 0.99, 95% CI = [0.92, 1.06], p = .69) or any of its individual components after adjustment for BMI and demographic variables. The findings show that depression was associated with increasing odds of overweight and obesity in young adult females and may also have increased the physiological risk associated with metabolic syndrome. Early detection of depression and obesity as part of metabolic syndrome is important in the health management of young adult females for decreasing the risks of cardiovascular disease and diabetes.

A systematic review and meta-analysis of the association between depression and insulin resistance

OBJECTIVE

Depression is associated with the onset of type 2 diabetes. A systematic review and meta-analysis of observational studies, controlled trials, and unpublished data was conducted to examine the association between depression and insulin resistance (IR).

RESEARCH DESIGN AND METHODS

Medline, EMBASE, and PsycINFO were searched for studies published up to September 2011. Two independent reviewers assessed the eligibility of each report based on predefined inclusion criteria (study design and measure of depression and IR, excluding prevalent cases of diabetes). Individual effect sizes were standardized, and a meta-analysis was performed to calculate a pooled effect size using random effects. Subgroup analyses and meta-regression were conducted to explore any potential source of heterogeneity between studies.

RESULTS

Of 967 abstracts reviewed, 21 studies met the inclusion criteria of which 18 studies had appropriate data for the meta-analysis (n = 25,847). The pooled effect size (95% CI) was 0.19 (0.11-0.27) with marked heterogeneity (I(2) = 82.2%) using the random-effects model. Heterogeneity between studies was not explained by age or sex, but could be partly explained by the methods of depression and IR assessments.

CONCLUSIONS

A small but significant cross-sectional association was observed between depression and IR, despite heterogeneity between studies. The pathophysiology mechanisms and direction of this association need further study using a purposively designed prospective or intervention study in samples at high risk for diabetes.

A neural circuitry linking insulin resistance to depressed mood

OBJECTIVE

Insulin resistance (IR) confers risk for Type 2 diabetes and is associated with depressed mood. Neurons within the ventral striatum (VS) are sensitive to insulin levels and show altered function in the context of both IR and depression. Hence, VS may represent a critical component of a neural circuitry linking IR to depressed mood.

METHODS

Ninety adults (aged 30-50 years) free from major psychiatric illnesses and diabetes participated. Fasting blood was sampled, and participants completed a set of questionnaires (including the Beck Depression Inventory-II). Participants also underwent resting-state functional magnetic resonance imaging of the brain. Seed-based connectivity analyses, centered on VS, were conducted to examine how resting-state interregional connectivity patterns covaried with IR and depressed mood.

RESULTS

Higher levels of IR covaried with increased connective strength between the left VS and two regions: the insula and the anterior midcingulate cortex (aMCC). Moreover, aMCC-VS connectivity predicted depressed mood (b = 0.93, standard error = 0.36, F(change)(1,81) = 6.54, p = .01). Finally, aMCC-VS connectivity was shown by Monte Carlo analysis to mediate the relationship between IR and depressed mood (a*b indirect effect = 0.16, confidence interval = 0.005-0.39, p = .03).

CONCLUSIONS

IR relates to changes in the functional connectivity between VS and aMCC. These changes in interregional communication partly account for the coupling of IR to depressed mood in otherwise healthy adults. These findings are relevant for understanding bidirectional associations between diabetes risk and depressed mood.

A review of the association between depression and insulin resistance: pitfalls of secondary analyses or a promising new approach to prevention of type 2 diabetes?

We review the validity of the evidence for an association between depression and the risk of insulin resistance (IR). We describe the potentially plausible biological and behavioral mechanisms that explain how depression increases the risk of IR and consequent overt diabetes. We have identified gaps in the literature to guide future research. Evidence for bidirectional associations between depression and IR is inconsistent. Results showing positive associations between depression and IR are derived from cross-sectional studies, whereas negative findings are typically reported in cohort studies. On the other hand, tentative trial evidence suggests that the effective treatment of depression can improve IR, and that lifestyle programs improve IR and reduce depressive symptoms. These emerging themes could lead to potential new multidisciplinary approaches to preventing diabetes.

Functional biomarkers of depression: diagnosis, treatment, and pathophysiology

Major depressive disorder (MDD) is a heterogeneous illness for which there are currently no effective methods to objectively assess severity, endophenotypes, or response to treatment. Increasing evidence suggests that circulating levels of peripheral/serum growth factors and cytokines are altered in patients with MDD, and that antidepressant treatments reverse or normalize these effects. Furthermore, there is a large body of literature demonstrating that MDD is associated with changes in endocrine and metabolic factors. Here we provide a brief overview of the evidence that peripheral growth factors, pro-inflammatory cytokines, endocrine factors, and metabolic markers contribute to the pathophysiology of MDD and antidepressant response. Recent preclinical studies demonstrating that peripheral growth factors and cytokines influence brain function and behavior are also discussed along with their implications for diagnosing and treating patients with MDD. Together, these studies highlight the need to develop a biomarker panel for depression that aims to profile diverse peripheral factors that together provide a biological signature of MDD subtypes as well as treatment response.