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Table 1.  Demographic and Clinical Characteristics by Depression Group and Insulin Resistance Status by QUICKIa
Demographic and Clinical Characteristics by Depression Group and Insulin Resistance Status by QUICKIa
Table 2.  Linear Regression Models of the Association Between Depression Characteristics and Measures of Insulin Resistance: Depression Severity and Depression Chronicity Among Participants With Current MDDa
Linear Regression Models of the Association Between Depression Characteristics and Measures of Insulin Resistance: Depression Severity and Depression Chronicity Among Participants With Current MDDa
1.
Wilcox  G.  Insulin and insulin resistance.   Clin Biochem Rev. 2005;26(2):19-39. doi:10.1016/S0025-7125(03)00128-7Google Scholar
2.
Reaven  G.  The metabolic syndrome or the insulin resistance syndrome? different names, different concepts, and different goals.   Endocrinol Metab Clin North Am. 2004;33(2):283-303. doi:10.1016/j.ecl.2004.03.002PubMedGoogle ScholarCrossref
3.
Watson  K, Nasca  C, Aasly  L, McEwen  B, Rasgon  N.  Insulin resistance, an unmasked culprit in depressive disorders: promises for interventions.   Neuropharmacology. 2018;136(Pt B):327-334. doi:10.1016/j.neuropharm.2017.11.038PubMedGoogle ScholarCrossref
4.
Penninx  BWJH, Beekman  ATF, Smit  JH,  et al; NESDA Research Consortium.  The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods.   Int J Methods Psychiatr Res. 2008;17(3):121-140. doi:10.1002/mpr.256PubMedGoogle ScholarCrossref
5.
Katz  A, Nambi  SS, Mather  K,  et al.  Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.   J Clin Endocrinol Metab. 2000;85(7):2402-2410. doi:10.1210/jcem.85.7.6661PubMedGoogle ScholarCrossref
6.
Trivedi  MH, Rush  AJ, Ibrahim  HM,  et al.  The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation.   Psychol Med. 2004;34(1):73-82. doi:10.1017/S0033291703001107PubMedGoogle ScholarCrossref
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    Research Letter
    December 2, 2020

    Association of Insulin Resistance With Depression Severity and Remission Status: Defining a Metabolic Endophenotype of Depression

    Author Affiliations
    • 1Department of Epidemiology and Population Health, Stanford School of Medicine, Stanford, California
    • 2Department of Psychiatry and Behavioral Sciences, Stanford School of Medicine, Stanford, California
    • 3Department of Neurology and Neurological Sciences, Stanford University, Stanford, California
    • 4Department of Psychiatry and Amsterdam Public Health Research Institute, Amsterdam, the Netherlands
    JAMA Psychiatry. 2021;78(4):439-441. doi:10.1001/jamapsychiatry.2020.3669

    Insulin resistance (IR) is a physiological state characterized by the attenuated response of peripheral receptors to insulin.1 It is a known risk factor for somatic and brain-based disorders, including cardiovascular disease, Alzheimer disease, and major depressive disorder (MDD).1,2 Several plausible mechanisms tie IR to MDD.3 Insulin resistance leads to diminished insulin-mediated glucose disposal, compensatory hyperinsulinemia, and type 2 diabetes.1,2 However, there is little evaluation of how IR is associated with specific features of major depression. Characterization of these associations represents a critical step at better phenotyping, a prelude to longitudinal studies, and a more targeted approach to the treatment of MDD. We investigated whether IR was positively associated with the presence of major depression, the severity of major depression, and the chronicity of major depression using the Netherlands Study of Depression and Anxiety (NESDA).

    Methods

    The NESDA is a longitudinal Dutch study of adults that describes the course and consequences of depressive and anxiety disorders.4 We studied 1269 participants with proteomic data in 3 diagnostic groups: current MDD, remitted MDD, and those with no history of the disorder (control individuals). Non-Dutch speakers and those with a history of other psychiatric disorders were excluded. The NESDA protocol was approved by the Vrije University Medical Center ethical committee, and all participants provided written informed consent.

    We used 2 well-validated surrogate biomarkers of IR, the quantitative insulin sensitivity check index (QUICKI) and the triglyceride to high-density lipoprotein (HDL) ratio, with the aim of understanding whether using different surrogate IR measures has consistent associations with MDD. Those in the bottom QUICKI quartile were categorized as insulin resistant and all others as insulin sensitive, as is standard in studies of IR.5 The triglyceride-HDL ratio is an index based on fasting blood sample measurements and used a sex-specific cutpoint for IR.

    Trained research staff assessed depression diagnostic status via the Composite International Diagnostic Interview, version 2.1.6 The Inventory of Depressive Symptomatology assessed depression severity. Depression chronicity over the preceding 4 years was measured using the life chart interview.

    The association between depression group and IR status was evaluated using multivariable-adjusted multinomial logistic regression. We used adjusted linear regression to investigate the association between IR and depression characteristics among current and remitted cases. A supplementary analysis adjusted models of MDD characteristics for antidepressant use. All models were adjusted for age, sex, education, partner status, smoking, and alcohol use.

    Results

    The IR participants (defined by QUICKI) were older, less educated, and had higher body mass index than those who were insulin sensitive (Table 1). Insulin resistance was associated with current MDD compared with control individuals (odds ratio [OR], 1.51; 95% CI, 1.08-2.12), but not with remitted MDD (OR, 1.14; 95% CI, 0.79-1.64).

    Among participants with current MDD, both measures of IR were positively associated with depression severity (Table 2). Depression chronicity was associated with triglyceride-HDL ratio but not the QUICKI (Table 2). Among participants with remitted MDD, neither depression severity nor chronicity was associated with IR (not shown). There were no substantial changes in model outcomes after adjustment for antidepressant use.

    Discussion

    We report an association between IR and current MDD but not with remitted MDD, suggesting that IR is a state, rather than trait, biomarker of depression. Among specific biomarkers of IR, triglyceride-HDL ratio was positively associated with depression severity and chronicity (again, among participants with current MDD only), whereas IR measured by QUICKI was associated with depression severity. Taken together, these biomarkers of metabolic dysfunction represent simple, clinically accessible methods of identification of IR among currently depressed patients. One limitation of this analysis was the cross-sectional design. Longitudinal analyses need to extend these findings and examine temporality and are the subject of our current investigations.

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    Article Information

    Corresponding Authors: Natalie Rasgon, MD, PhD, Stanford Center for Neuroscience in Women’s Health, 401 Quarry Rd, MC 5723, Palo Alto, CA 94304 (nrasgon@stanford.edu); Kathleen T. Watson, PhD, 259 Campus Dr, Redwood Building, Stanford, CA 94305 (ktwatson@stanford.edu).

    Accepted for Publication: September 22, 2020.

    Published Online: December 2, 2020. doi:10.1001/jamapsychiatry.2020.3669

    Author Contributions: Dr Watson had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Watson, Henderson, Rasgon, Penninx.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Watson, Nutkiewicz.

    Critical revision of the manuscript for important intellectual content: Watson, Simard, Henderson, Lamers, Rasgon, Penninx.

    Statistical analysis: Watson.

    Obtained funding: Rasgon, Penninx.

    Administrative, technical, or material support: Nutkiewicz, Penninx.

    Supervision: Simard, Lamers, Rasgon, Penninx.

    Conflict of Interest Disclosures: Dr Lamers reported grants from ZonMw during the conduct of the study. Dr Penninx reported grants from Boehringer Ingelheim and Jansen Research outside the submitted work. No other disclosures were reported.

    Funding/Support: The infrastructure for the Netherlands Study of Depression and Anxiety study is funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-MW, grant number 10-000-1002) and is supported by participating universities and mental health care organizations (VU University Medical Center, GGZ inGeest, Arkin, Leiden University Medical Center, GGZ Rivierduinen, University Medical Center Groningen, Lentis, GGZ Friesland, GGZ Drenthe, IQ Healthcare, Netherlands Institute for Health Services Research, and the Netherlands Institute of Mental Health and Addiction [Trimbos]). Dr Henderson was supported by National Institutes of Health grant P50-AG047366.

    Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    References
    1.
    Wilcox  G.  Insulin and insulin resistance.   Clin Biochem Rev. 2005;26(2):19-39. doi:10.1016/S0025-7125(03)00128-7Google Scholar
    2.
    Reaven  G.  The metabolic syndrome or the insulin resistance syndrome? different names, different concepts, and different goals.   Endocrinol Metab Clin North Am. 2004;33(2):283-303. doi:10.1016/j.ecl.2004.03.002PubMedGoogle ScholarCrossref
    3.
    Watson  K, Nasca  C, Aasly  L, McEwen  B, Rasgon  N.  Insulin resistance, an unmasked culprit in depressive disorders: promises for interventions.   Neuropharmacology. 2018;136(Pt B):327-334. doi:10.1016/j.neuropharm.2017.11.038PubMedGoogle ScholarCrossref
    4.
    Penninx  BWJH, Beekman  ATF, Smit  JH,  et al; NESDA Research Consortium.  The Netherlands Study of Depression and Anxiety (NESDA): rationale, objectives and methods.   Int J Methods Psychiatr Res. 2008;17(3):121-140. doi:10.1002/mpr.256PubMedGoogle ScholarCrossref
    5.
    Katz  A, Nambi  SS, Mather  K,  et al.  Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.   J Clin Endocrinol Metab. 2000;85(7):2402-2410. doi:10.1210/jcem.85.7.6661PubMedGoogle ScholarCrossref
    6.
    Trivedi  MH, Rush  AJ, Ibrahim  HM,  et al.  The Inventory of Depressive Symptomatology, Clinician Rating (IDS-C) and Self-Report (IDS-SR), and the Quick Inventory of Depressive Symptomatology, Clinician Rating (QIDS-C) and Self-Report (QIDS-SR) in public sector patients with mood disorders: a psychometric evaluation.   Psychol Med. 2004;34(1):73-82. doi:10.1017/S0033291703001107PubMedGoogle ScholarCrossref
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