Commentary: Antidepressants and diabetes risk: why are there discrepant findings from cohort studies based on patient records and those based on serial phenotyping?

Diabetes and mood disorders: shared mechanisms and therapeutic opportunities

OBJECTIVE

The objective of this manuscript is to provide a comprehensive and critical overview of the current evidence on the association between Diabetes mellitus (DM) and mood disorders [i.e., Major depressive disorder (MDD) and bipolar disorder (BD)], and therapeutic opportunities.

METHODS

We searched in MEDLINE (via Ovid) for placebo-controlled clinical trials published in the last 20 years that assessed drug repurposing approaches for the treatment of DM or mood disorders.

RESULTS

We found seven studies that aimed to verify the effects of antidepressants in patients diagnosed with DM, and eight studies that tested the effect of antidiabetic drugs in patients diagnosed with MDD or BD. Most studies published in the last two decades did not report a positive effect of antidepressants on glycemic control in patients with DM. On the other hand, antidiabetic drugs seem to have a positive effect on the treatment of MDD and BD.

CONCLUSIONS

While effect of antidepressants on glycemic control in patients with DM is still controversial, the use of antidiabetic drugs may be a promising strategy for patients with MDD or BD. Prospective studies are still needed.Key pointsMood disorders in patients with DM affect glycemic control, potentially increasing mortality risk.The effect of antidepressants on glycemic control in patients with DM is still controversial. The coexistence of complicated DM and a mood disorders would require a careful, individualised, and comprehensive evaluation.Insulin resistance may increase the risk of depressive symptoms and is associated with worse outcomes in BD.The use antidiabetic drugs may be a promising strategy for patients with MDD or BD. However, prospective trials are needed to prove a potential antidepressant activity of antidiabetic drugs.

Subjective wellbeing as a determinant of glycated hemoglobin in older adults: longitudinal findings from the English Longitudinal Study of Ageing

BACKGROUND

Previous research has shown an association between subjective wellbeing and incident diabetes. Less is known about the role of wellbeing for subclinical disease trajectories as captured via glycated hemoglobin (HbA1c). We aimed to explore the association between subjective wellbeing and future HbA1c levels, and the role of sociodemographic, behavioral and clinical factors in this association.

METHODS

We used data from the English Longitudinal Study of Ageing for this study (N = 2161). Subjective wellbeing (CASP-19) was measured at wave 2 and HbA1c was measured 8 years later at wave 6. Participants were free from diabetes at baseline. We conducted a series of analyses to examine the extent to which the association was accounted for by a range of sociodemographic, behavioral and clinical factors in linear regression models.

RESULTS

Models showed that subjective wellbeing (CASP-19 total score) was inversely associated with HbA1c 8 years later after controlling for depressive symptoms, age, sex, and baseline HbA1c (B = -0.035, 95% CI -0.060 to -0.011, p = 0.005). Inclusion of sociodemographic variables and behavioral factors in models accounted for a large proportion (17.0% and 24.5%, respectively) of the relationship between wellbeing and later HbA1c; clinical risk factors explained a smaller proportion of the relationship (3.4%).

CONCLUSIONS

Poorer subjective wellbeing is associated with greater HbA1c over 8 years of follow-up and this relationship can in part be explained by sociodemographic, behavioral and clinical factors among older adults.

Combination therapy as a potential risk factor for the development of type 2 diabetes in patients with schizophrenia: the GOMAP study

BACKGROUND

Schizophrenia (SCZ) is associated with increased risk of type 2 diabetes (T2D). The potential diabetogenic effect of concomitant application of psychotropic treatment classes in patients with SCZ has not yet been evaluated. The overarching goal of the Genetic Overlap between Metabolic and Psychiatric disease (GOMAP) study is to assess the effect of pharmacological, anthropometric, lifestyle and clinical measurements, helping elucidate the mechanisms underlying the aetiology of T2D.

METHODS

The GOMAP case-control study (Genetic Overlap between Metabolic and Psychiatric disease) includes hospitalized patients with SCZ, some of whom have T2D. We enrolled 1653 patients with SCZ; 611 with T2D and 1042 patients without T2D. This is the first study of SCZ and T2D comorbidity at this scale in the Greek population. We retrieved detailed information on first- and second-generation antipsychotics (FGA, SGA), antidepressants and mood stabilizers, applied as monotherapy, 2-drug combination, or as 3- or more drug combination. We assessed the effects of psychotropic medication, body mass index, duration of schizophrenia, number of hospitalizations and physical activity on risk of T2D. Using logistic regression, we calculated crude and adjusted odds ratios (OR) to identify associations between demographic factors and the psychiatric medications.

RESULTS

Patients with SCZ on a combination of at least three different classes of psychiatric drugs had a higher risk of T2D [OR 1.81 (95% CI 1.22-2.69); p = 0.003] compared to FGA alone therapy, after adjustment for age, BMI, sex, duration of SCZ and number of hospitalizations. We did not find evidence for an association of SGA use or the combination of drugs belonging to two different classes of psychiatric medications with increased risk of T2D [1.27 (0.84-1.93), p = 0.259 and 0.98 (0.71-1.35), p = 0.885, respectively] compared to FGA use.

CONCLUSIONS

We find an increased risk of T2D in patients with SCZ who take a combination of at least three different psychotropic medication classes compared to patients whose medication consists only of one or two classes of drugs.

The risk of new-onset diabetes in antidepressant users - A systematic review and meta-analysis

Background

Antidepressant Drugs (ADs) are among the most commonly prescribed medications in developed countries. The available epidemiological evidence suggests an association between AD use and higher risk of developing type 2 diabetes mellitus. However, some methodological issues make the interpretation of these results difficult. Moreover, very recent studies provided conflicting results. Given the high prevalence of both diabetes and AD use in many countries, clarifying whether this association is causal is of extreme relevance for the public health. The aim of the present study is to provide an up-to-date evaluation of the evidence in support of a causal role of ADs in inducing diabetes.

Methods and findings

A systematic literature search was conducted to identify relevant studies in MEDLINE (PubMed), PsycINFO, and International Pharmaceutical Abstracts (IPA) through 31^st December 2016. Only studies assessing the incidence of new-onset diabetes in subjects treated with ADs were included. Results were pooled using a random-effects meta-analysis. Moreover, we extensively reviewed the role of the different sources of bias that have been proposed to explain the association between AD and diabetes. Twenty studies met the inclusion criteria. In the meta-analysis, the association between AD use and diabetes was still evident after the inclusion of the recent negative studies [pooled relative risk = 1.27, 95% confidence interval (CI), 1.19–1.35; p<0.001]. None of the biases proposed by previous authors seemed able to fully explain the observed association.

Conclusions

This updated meta-analysis confirms the association between AD use and incident diabetes. It still remains a matter of debate whether single ADs exert a different effect on the risk of diabetes. Given the possible heterogeneity, we suggest that a classification of ADs according to their pharmacological profiles could be useful in better elucidating the nature of this association.

Use of antidepressant medications not associated with A1C among individuals with diabetes in NHANES sample

INTRODUCTION

Studies on the relationships between antidepressant medications and A1C, a measure of glucose levels over the past three months, have resulted in mixed findings. Most available research examined subclass effects. The current study aims to measure the association between individual antidepressant medications and A1C in a large nationally-representative dataset.

METHODS

The sample of this study consists of 45,786 individuals who participated in the National Health and Nutrition Examination Survey between 1999 and 2012. We examined the relationships between 18 antidepressant medications and continuous A1C in crude and adjusted linear models stratified by diabetes status (ever or never diagnosed). Adjusted models included demographic covariates (age, gender, race/ethnicity, and education), smoking status, and physical activity.

RESULTS

No significant associations were found for most antidepressants. However, those who used selegiline (n=11), all of whom were in the no diabetes stratum, were found to have a higher A1C compared with individuals who do not use antidepressants.

DISCUSSION

The study agrees with a number of earlier findings. Most antidepressant medications do not appear to be associated with A1C levels among individuals with or without diabetes. Limitations include small numbers for some exposure categories and cross-sectional data. Strengths include use of a nationally-representative dataset and large total sample size.