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Issue 106, Feb 2021
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Comorbid metabolic syndrome and treatment-resistant depression (TRD)

Godin O et al. J ClinPsychiatry.2019. Oct 15;80(6):19m 12755 doi:10.4088/JCP.19m12755.



This French study aimed to estimate the prevalence of metabolic syndrome (MetS) and its components in patients with treatment-resistant depression (TRD) and to determine correlations with sociodemographic, clinical, and treatment-related factors.


205 patients who met DSM-IV criteria for a major depressive episode with moderate-to-severe symptoms (Montgomery-Asberg Depression Rating Scale score (MADRS) ≥ 20), and at least Stage II resistance according to Thase and Rush criteria were enrolled in this study. The study enrolled patients between the years 2012-2018. Data on sociodemographic and clinical characteristics, lifestyle information, and treatment and comorbidities were collected, and a blood sample was drawn. MetS was defined according to the criteria of the International Diabetes Federation.


38% of individuals with TRD met the criteria for MetS. The frequency of MetS was significantly higher in men than in women-only for patients aged 40 years or older (46.3% vs 35.2%). The management for diabetes was good, however, less than one-third of the patients with high blood pressure or dyslipidemia were adequately treated for these conditions. Individuals with abnormal plasma c-reactive protein levels had a 3-fold increased independent risk of having MetS.


The prevalence of MetS is higher in patients with TRD than in those with other psychiatric disorders and is characterized by considerable undertreatment of some components of MetS in this population. Diagnosis and treatment of the components of MetS should be systematically performed to prevent the occurrence of cardiovascular diseases in patients with TRD. These findings highlight the need for integrated care, with more interaction and coordination between psychiatrists and primary care providers.

Clinical Commentary

The prevalence of metabolic syndrome has been an important issue in psychiatry independent of the atypical antipsychotic drugs. This clinical study focused on patients with TRD and evaluated them for metabolic syndrome including evaluating how well the individual components of MetS were addressed for the overall welfare of the patients. It should be noted that this a French cohort. The strengths included the use of objective measures such as the MADRS as well as the Thase and Rush criteria for TRD. MetS was assessed using blood tests including c-reactive protein (CRP). The drawbacks include the lack of a control group. The salient points relevant to the clinician are

  • Over one-third of the TRD patients (38%) met the criteria for Mets. In the non-TRD depressed group, the prevalence of MetS was 7-8.8%. In French cohorts with schizophrenia and bipolar disorder, the Mets prevalence was 24% and 20% respectively based on other studies.
  • In younger patients <40 years sex distribution is equal, however with increasing age MetS was higher in men
  • Overweight individuals had a six times higher risk of having MetS
  • No significant association was found with tobacco use.
  • Abnormal CRP level was associated with metabolic syndrome
  • Surprisingly antidepressants/atypical antipsychotics were not associated with increased risk
  • The study found that diabetes was well managed at 89% whereas hypertension was managed in 29% of patients. Dyslipidemia was only managed in 15% of the patients.

The elevated CRP points to subclinical inflammation which affects both MetS and TRD. CRP is a stable biomarker for systemic inflammation.


In my opinion, when treating patients with TRD we should also simultaneously screen for metabolic syndrome and treat all components efficiently including diabetes, hypertension, dyslipidemia, and obesity. Screening and follow up is key. I tell patients to follow their HbA1c as they would monitor the speedometer of a vehicle while driving to make the point. They should pay attention to nonvisible issues like hypertension and elevated lipids and address them. There may exist a bidirectional link between TRD and Mets facilitated by subclinical inflammation.   

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Insomnia and impaired quality of life in the United States

Olfson M. J Clin Psychiatry. 2018 Sep 11;79 (5):17m12020. doi: 10.4088/JCP.17m12020



This analysis characterizes the individual-level and population-level burden of insomnia in relation to other medical conditions and describes the comorbidity of insomnia with other medical conditions, including the dependence of these comorbidities on pain, life events, and mental disorders.


Information from 34,712 adults in the National Epidemiologic Survey on Alcohol and Related Conditions-III (2012-2013) was analyzed. Quality-adjusted life-years (QALYs) were measured with the SF-6D, a 6-dimensional health state classification derived from the Short-Form-12, version 2.


In the last 12 months, 27.3% of adults reported insomnia. The US annual loss of QALYs associated with insomnia was significantly larger than that associated with any of the other 18 medical conditions assessed, including arthritis, depression, and hypertension. After control for demographic factors, all conditions examined from obesity to mania were associated with an increased risk of insomnia. Further controlling for pain, stressful life events, and mental disorders decreased the odds of the co-occurrence of insomnia with these conditions. The decrease in insomnia comorbidity associated with pain was greatest for fibromyalgia (31.8%) and arthritis (20.1%); the decrease in insomnia comorbidity associated with life events was greatest for mania (13.4%) and drug use disorders (11.2%); the decrease in insomnia comorbidity associated with mental disorders was greatest for peptic ulcer disease (11.2%) and liver diseases (11.1%).


Insomnia is prevalent and associated with a substantial population-level burden in self-assessed health. The co-occurrence of insomnia with common medical conditions is differentially related to pain and to a lesser extent to stressful life events and mental disorders.

Clinical Commentary

This large study revealed that approximately one-fourth of US adults have sleeping issues within the past 12 months. The more important point is three fourth of these individuals thought that their sleep disturbance was not recognized by a health care professional. The limitations of this study include measuring medical conditions based on self-report rather than independent medical evaluations resulting in surveillance bias. Insomnia was assessed by a single item that captured a wide range of sleep disturbances. Dissatisfaction with sleep does not necessarily meet the criteria for insomnia. The survey was cross-sectional. 

  • Several medical conditions had a risk of insomnia: fibromyalgia, peptic ulcer disease, cardiac symptoms, and mood and anxiety disorders.
  • Insomnia comorbidity had a stronger linkage to pain than to stressful life events or mental disorders.
  • Insomnia significantly affects the quality of life of US adults particularly those with medical issues.
  • Increased risk of insomnia is associated with female sex, older adult, lower socioeconomic status as assessed by education and employment
  • Insomnia results in cognitive deficits in attention, concentration, or memory which impacts daily functioning.


Insomnia affects the quality of life in a big way. In my professional opinion, it is important to ask about the quality of sleep-in detail to have a thorough assessment as insomnia is a key part of psychiatric as well as medical ailments. This comorbid condition is like a ring of fire surrounding physical and mental disorders. We should in mental health particularly think about obstructive sleep apnea due to its high prevalence in association with psychiatric disorders and co-occurring obesity. Treatment of insomnia includes appropriate management of co-occurring medical conditions.

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Social media use and its implications for depression and anxiety

Shensa A et al. Am J Health Behav 2018; 42 (2):116-128. doi: 10.5993/AJHB.42.2.11.



Social media is used with varying quantity, emotional, and behavioral attachment that may affect anxiety and depression. This study aimed to identify distinct patterns of social media use (SMU) and to assess associations between those patterns and depression and anxiety symptoms.


A nationally representative sample of 1730 US adults ages 19 to 32 years completed an online survey in 2014. Cluster analysis was used to identify patterns of SMU. Depression and anxiety were measured using respective 4-item Patient-Reported Outcome Measurement Information System (PROMIS) scales. Statistical analysis was conducted to assess the associations of SMU with depression and anxiety symptoms.  This study assessed 11 common social media platforms which included Facebook, Twitter, Google+, YouTube, LinkedIn, Instagram, Pinterest, Tumblr, Vine, Snapchat, and Reddit.


 Cluster analysis yielded a 5-cluster solution. Participants were characterized as "Wired," "Connected," "Diffuse Dabblers," "Concentrated Dabblers," and "Unplugged." Membership in 2 clusters - "Wired" and "Connected" – significantly increased the odds of elevated depression and anxiety symptoms.


SMU pattern characterization of a large population suggests 2 patterns are associated with risk for depression and anxiety. Developing educational interventions that address use patterns rather than single aspects of SMU (e.g., quantity) would likely be useful.

Clinical Commentary

Sharing of information using computer-mediated technology is now common practice. Research has suggested increased SMU may lead to negative online experiences, fewer in-person social interactions, and decreased ability to sustain attention. This large study has suggested increased depression and anxiety. SMU has been known to cause addiction to use neglecting “real-life responsibilities and relationships".  There is also contrarian literature suggesting no increased association of depression associated with time spent on Facebook. The belief may be that SMU provides social capital and increased life satisfaction which may be protective.

Limitations included modified scales without extensive validation, self-reported questionnaires, not assessing user's reactions to social media. The data were collected in 2014 and patterns of use have changed now. The results of this study can still guide us. This study did not assess What’s App a popular internationally used platform with like-minded people forming groups related to work, scientific interests, social activities such as golf, biking, etc. This platform has become very popular for alumni groups such as high school, college, and sports.

This study used five variables resulting in clusters: time, frequency, multiple platform use, problematic social media use, and social media intensity to identify patterns. It also used the PROMIS depression scale which has been correlated with PHQ-9 and the PROMIS anxiety scale has been correlated with the GAD-7 anxiety scale. Hence symptom assessment was done on-line with the mental health field. The completion rate was 96.3%. The connected and wired clusters were associated with increased depression and anxiety.

Wired Cluster: high time, frequency, multiple platform use, SMI, and high PSMU. Strongly associated with depression and anxiety.

Connected cluster: high time, frequency, multiple platform use, and social media intensity (SMI) but none reported high Problematic Social Media Use (PSMU).  Associated with depression and anxiety but to a lesser degree than wired

Unplugged: no high levels of any of the five clustering variables. No significant depression or anxiety associated

Concentrated Dabblers: no high multiple platform use, or PMSU, but had high time, frequency, and SMI. No significant depression or anxiety is associated.

Diffuse Dabblers: reported high multiple platform use, none had PSMU, some had high time-frequency and SMI.

The unplugged, concentrated, and diffuse dabbler groups were not associated with anxiety and depression which supports the notion that moderate SMU may not be associated with mental health risks to some individuals.


When taking a history today we should dig a little deeper to inquire about Problematic social media use (PSM U) in addition to high frequency, time, and multiple platform use. It is important to note that we should consider the daily involvement of SMU in a person's life and the resulting neglect of responsibilities and relationships. Look for addictive patterns of social media use. 

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Depression and ADHD-Related Risk for Substance Use in Adolescence and Early Adulthood

Howard AL. et al.  J Abnorm Psychol. Dec; 47(12) 2019; 1903-1916. doi:10.1007/s10802-019-00573-y.

PMID 31273568


Childhood attention-deficit/hyperactivity disorder (ADHD) is prospectively linked to a substance use disorder. Depression emerging in adolescence is an understudied risk factor that may explain some of this risk. This study investigated the mediating and moderating roles of adolescent depression in explaining this association.


This study used longitudinal data from the prospective 16-year follow-up of the Multimodal Treatment Study of ADHD (MTA).  547 children diagnosed with DSM-IV ADHD Combined Type, and 258 age- and sex-matched comparison children were included in this study. The self-report Substance Use Questionnaire (SUQ) was used along with Childhood Depression Inventory (CDI). The ADHD assessment was done using the Conners' Adult ADHD Rating Scale (CAARS). Depression was assessed using the Diagnostic Interview Schedule (DIS) to meet the DSM-IV criteria.


In adolescence, depressive symptoms did not exacerbate the effects of childhood ADHD on any substance use. For both groups, time-varying and average depressive symptoms were associated with more frequent use of all substances. Prospectively, we found no evidence of depression mediation to adult substance use. However, adolescent depression moderated the association between childhood ADHD and adult marijuana use. Although adults without ADHD histories used marijuana more frequently if they had elevated depressive symptoms in adolescence, marijuana use by adults with ADHD histories was independent of their adolescent depression. In adulthood, depression diagnoses and ADHD persistence continued to operate as independent, additive correlates of substance use risk.


These findings suggest a circumscribed role for depression in substance use risk that adds to but does not alter or explain, ADHD-related risk.

Clinical Commentary

There is no single explanatory model that has emerged to account for the co-occurrence of ADHD and depression, however, depression is a plausible mediator between childhood ADHD and substance abuse.  This study examined in multiple ways the role that depressive symptoms may play in ADHD related-risk for both adolescent and young adult substance abuse. Limitations include the measurement of depressive symptoms using self-reports.

  • Increased depressive symptoms in adolescence were associated with increased substance abuse in both the ADHD and the Local Normative Comparison Group (LNCG). Depression adds to but does not modify the ADHD-related risk of substance abuse in adolescence.
  • Young adults with ADHD history were at increased for regular marijuana use regardless of the severity of depressive symptoms in adolescence. Maladaptive coping may contribute to increased marijuana use in those with ADHD. Adults report feelings of calm and better focus.
  • Adolescent ADHD symptoms were associated with increased adult use of all substances except alcohol. This has also been found in adolescents with externalizing problems.
  • Importantly depression was not found to contribute in a significant way in the ADHD population compared with the LNCG group.
  • Adult depression diagnosis was associated with nicotine dependence at age 25 whereas ADHD symptoms persistence was associated with marijuana and other SUD.
  • This 16-year longitudinal study of children with and without ADHD found no evidence that depressive symptoms mediated ADHD-related substance use risk.


In my opinion, inadequately or undetected ADHD can increase the risk of substance abuse in the population unrelated to depression, and hence ADHD should be detected and adequately treated. Screen all patients with ADHD with surprise urine drug screens for 1) substance abuse 2) to ensure they are taking their stimulant medication.

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Depression in young men and women with ADHD

Babinski DE et al.  J Clin Psychiatry 2020 Sep 22;81;(6) 378 (6):19m13130.doi:10.4088/JCP.19m13130

PMID 29414272.


This study examined the effects of ADHD and sex on the prevalence of depression, suicidal ideation, and suicide attempts in a sample of young adult men and women (aged 18-25 years) with and without attention-deficit/hyperactivity disorder (ADHD).


This study used commercial claims data. Young adults with ADHD (162,263 women and 225,705 men) having at least 2 claims with the International Classification of Diseases, Ninth Revision (ICD-9), code for ADHD and sex- and an age-matched group of young adults without an ICD-9 code for ADHD (162,263 women and 225,705 men) were identified. The prevalence of ICD-9 depression and suicidal behavior along with the use and cost of related treatment were compared between young adults with and without ADHD using 2014 claims data.


Compared to young adults without ADHD, young adults with ADHD were more frequently identified with depression, suicidal ideation, and suicide attempts. Depression and suicidal ideation were identified more frequently among women with ADHD compared to all other groups. Young adults with ADHD were statistically significantly more frequently engaged in outpatient and inpatient mental health care compared to young adults without ADHD. Furthermore, the overall costs of outpatient and inpatient care were statistically significantly greater among young adults with ADHD compared to young adults without ADHD.


These findings highlight the substantial burden of depression and suicidal behavior among young adults with ADHD, particularly women. There is a need for more research focused on mitigating risk for depression and suicidal behavior among both men and women with ADHD.

Clinical Commentary

This study found that depression and suicidal ideation had a greater prevalence in those with ADHD than those without, particularly women. This finding is interesting as ADHD was often missed in women as they were less likely to have hyperactivity. Limitations include a case-control study of 2014 claims data. Besides, ICD-9 codes were used.

  • Depression is an important comorbid condition with ADHD and inadequate treatment of the comorbid condition will prevent full recovery.
  • It should also be noted that depression in young adulthood is likely to persist across the life span.
  • Impaired concentration is an important overlapping symptom in depression and ADHD. The clinician should be aware of the overlapping nature of this symptom to provide for more efficient treatment.
  • The heightened vulnerability of women was brought to light by this study concerning ADHD and depression.
  • Patients with ADHD and depression had greater utilization of services compared to those without ADHD.

In Summary

In my professional opinion, depression is comorbid with ADHD and we should screen ADHD patients for a mood disorder which includes major depression and bipolar disorder. Even though bipolar disorder was not studied in this research we need to ascertain if the depressive symptoms are due to a cyclical mood disorder such as bipolar disorder or major depression. This is important as the treatments for both kinds of mood disorders vary. In the case of bipolar disorder, the mood disorder is first treated followed by ADHD.

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Sanjay Gupta, MD
Clinical Professor of Psychiatry, SUNY Buffalo

GME Research Review is a monthly newsletter edited by Sanjay Gupta, MD, Clinical Professor of Psychiatry, SUNY Buffalo. Dr. Gupta selects, summarizes, and provides a clinical commentary on the latest published research in psychiatry. 

We are always carefully evaluating which research papers to discuss in GME Research Review. Have come across a research paper published in the last 6 months that you thought is clinically relevant? Do you want me to analyze it for you and for the benefit of others? Please email Dr. Gupta the citation at [email protected]

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