Advertisement

Personalizing antidepressant choice by sex, body mass index, and symptom profile: An iSPOT-D report

  • Erin Green
    Affiliations
    Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA 94304, USA

    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
    Search for articles by this author
  • Andrea N. Goldstein-Piekarski
    Affiliations
    Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA 94304, USA

    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
    Search for articles by this author
  • Alan F. Schatzberg
    Affiliations
    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
    Search for articles by this author
  • A. John Rush
    Affiliations
    Duke – National University of Singapore, Singapore
    Search for articles by this author
  • Jun Ma
    Affiliations
    Department of Health Policy and Administration, School of Public Health, University of Illinois at Chicago, Chicago, IL 60608, USA
    Search for articles by this author
  • Leanne Williams
    Correspondence
    Corresponding author at: Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA.
    Affiliations
    Department of Veterans Affairs, VA Palo Alto Health Care System, Palo Alto, CA 94304, USA

    Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
    Search for articles by this author
Published:December 08, 2016DOI:https://doi.org/10.1016/j.pmip.2016.12.001

      Abstract

      Antidepressants are efficacious but we do not know which antidepressant is best suited to which person. We investigated the working hypothesis that obesity and sex may together be differential predictors of acute remission of specific symptoms for commonly used antidepressant medications. Data were acquired for 659 outpatients (18–65 years of age) who completed the iSPOT-D practical randomized controlled clinical trial. We measured adiposity by body mass index (BMI). By WHO criteria, 42% of patients were normal weight, 28% overweight and 31%, obese [class I (15%), II (10%) and III (6%)]. Patients were randomly assigned to 8-weeks of treatment with escitalopram, sertraline or venlafaxine extended-release (venlafaxine-XR) and then defined as remitters (17-item Hamilton Rating Scale for Depression score ⩽7) or non-remitters. In logistic regression models, BMI was a differential predictor of remission according to antidepressant type. Morbidly obese patients, compared to those with normal weight, were more likely to remit on venlafaxine-XR in particular. This effect was driven by a reduction specifically in physical symptoms, including sleep disturbance, somatic anxiety and appetite. The number needed to treat to achieve remission with venlafaxine-XR in obese III participants was 6. Higher BMI females but not males were more likely to remit regardless of medication type; this effect was related to a change in cognitive symptoms, including suicidal ideation, guilt, and psychomotor changes. Our findings suggest that considering BMI and sex, and assessing specific symptoms, could help tailor antidepressant choices to improve remission from depression in specialty and primary care settings.

      Introduction

      Antidepressants can be efficacious, but which antidepressant is best suited to which person is currently unclear. Simple demographic, vital sign, and symptom information such as sex, height and weight and symptom profiles may be available to prescribing providers, yet there is no consensus as to how these variables may be used to inform antidepressant treatment.
      Obesity in particular, is highly prevalent in individuals with MDD [
      • Luppino F.S.
      • de Wit L.M.
      • Bouvy P.F.
      • Stijnen T.
      • Cuijpers P.
      • Penninx B.W.
      • et al.
      Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies.
      ,
      • McElroy S.L.
      • Kotwal R.
      • Malhotra S.
      • Nelson E.B.
      • Keck P.E.
      • Nemeroff C.B.
      Are mood disorders and obesity related? A review for the mental health professional.
      ]. However, research findings regarding the impact of adiposity (body fat) on the success of antidepressant pharmacotherapy in individuals with MDD are mixed. Some studies suggest that overweight or obese individuals with MDD demonstrate less favorable outcomes [
      • Kloiber S.
      • Ising M.
      • Reppermund S.
      • Horstmann S.
      • Dose T.
      • Majer M.
      • et al.
      Overweight and obesity affect treatment response in major depression.
      ,
      • Lin C.H.
      • Chen C.C.
      • Wong J.
      • McIntyre R.S.
      Both body weight and BMI predicts improvement in symptom and functioning for patients with major depressive disorder.
      ,
      • Oskooilar N.
      • Wilcox C.S.
      • Tong M.L.
      • Grosz D.E.
      Body mass index and response to antidepressants in depressed research subjects.
      ,
      • Papakostas G.I.
      • Petersen T.
      • Iosifescu D.V.
      • Burns A.M.
      • Nierenberg A.A.
      • Alpert J.E.
      • et al.
      Obesity among outpatients with major depressive disorder.
      ,
      • Uher R.
      • Mors O.
      • Hauser J.
      • Rietschel M.
      • Maier W.
      • Kozel D.
      • et al.
      Body weight as a predictor of antidepressant efficacy in the GENDEP project.
      ], while other studies suggest no weight-related differences in response to antidepressant medications [
      • Sagud M.
      • Mihaljevic-Peles A.
      • Uzun S.
      • Cusa B.V.
      • Kozumplik O.
      • Kudlek-Mikulic S.
      • et al.
      The lack of association between components of metabolic syndrome and treatment resistance in depression.
      ,
      • Toups M.S.
      • Myers A.K.
      • Wisniewski S.R.
      • Kurian B.
      • Morris D.W.
      • Rush A.J.
      • et al.
      Relationship between obesity and depression: characteristics and treatment outcomes with antidepressant medication.
      ,
      • Vogelzangs N.
      • Beekman A.T.
      • van Reedt Dortland A.K.
      • Schoevers R.A.
      • Giltay E.J.
      • de Jonge P.
      • et al.
      Inflammatory and metabolic dysregulation and the 2-year course of depressive disorders in antidepressant users.
      ]; for review, see [
      • Woo Y.S.
      • Seo H.J.
      • McIntyre R.S.
      • Bahk W.M.
      Obesity and its potential effects on antidepressant treatment outcomes in patients with depressive disorders: a literature review.
      ].
      Sex differences may be another important factor in predicting outcomes after antidepressant treatment [
      • Baca E.
      • Garcia-Garcia M.
      • Porras-Chavarino A.
      Gender differences in treatment response to sertraline versus imipramine in patients with nonmelancholic depressive disorders.
      ,
      • Khan A.
      • Brodhead A.E.
      • Schwartz K.A.
      • Kolts R.L.
      • Brown W.A.
      Sex differences in antidepressant response in recent antidepressant clinical trials.
      ,
      • Kornstein S.G.
      • Schatzberg A.F.
      • Thase M.E.
      • Yonkers K.A.
      • McCullough J.P.
      • Keitner G.I.
      • et al.
      Gender differences in treatment response to sertraline versus imipramine in chronic depression.
      ,
      • Sagud M.
      • Hotujac L.
      • Mihaljevic-Peles A.
      • Jakovljevic M.
      Gender differences in depression.
      ], although the research on this topic is also somewhat equivocal and does not typically account for differences in adiposity [
      • Hildebrandt M.G.
      • Steyerberg E.W.
      • Stage K.B.
      • Passchier J.
      • Kragh-Soerensen P.
      Are gender differences important for the clinical effects of antidepressants?.
      ,
      • Parker G.
      • Parker K.
      • Austin M.P.
      • Mitchell P.
      • Brotchie H.
      Gender differences in response to differing antidepressant drug classes: two negative studies.
      ,
      • Quitkin F.M.
      • Stewart J.W.
      • McGrath P.J.
      • Taylor B.P.
      • Tisminetzky M.S.
      • Petkova E.
      • et al.
      Are there differences between women’s and men’s antidepressant responses?.
      ,
      • Thiels C.
      • Linden M.
      • Grieger F.
      • Leonard J.
      Gender differences in routine treatment of depressed outpatients with the selective serotonin reuptake inhibitor sertraline.
      ,
      • Wohlfarth T.
      • Storosum J.G.
      • Elferink A.J.
      • van Zwieten B.J.
      • Fouwels A.
      • van den Brink W.
      Response to tricyclic antidepressants: independent of gender?.
      ]. To date, one study suggests that response to a Selective Serotonin Reuptake Inhibitor (SSRI) versus placebo might depend on obesity in females but not in males [
      • Khan A.
      • Schwartz K.A.
      • Kolts R.L.
      • Brown W.A.
      BMI, sex, and antidepressant response.
      ]. Although both non-obese and obese women demonstrated a greater reduction in symptoms to treatment with an SSRI versus placebo, obese men did not benefit more from SSRI treatment. Further, obese females demonstrated approximately double the reduction in symptoms of obese males after antidepressant treatment suggesting that obese women may respond better to SSRIs than obese men.
      Depression is a pervasive disorder with symptoms spanning multiple domains of cognitive (e.g., depressed mood, suicidal thoughts, feelings of guilt) and physical (e.g., sleep disturbance, appetite and weight changes, somatic complaints) function [
      • Woo Y.S.
      • Seo H.J.
      • McIntyre R.S.
      • Bahk W.M.
      Obesity and its potential effects on antidepressant treatment outcomes in patients with depressive disorders: a literature review.
      ]. Thus, it may also be important to consider whether the effects of adiposity and sex differences on antidepressant outcomes may be differentially reflected in specific domains of cognitive and physical symptoms. To date, studies in this area have tended to rely on a combined symptom outcome score, consistent with the typical primary symptom outcome for clinical trials [
      • Khan A.
      • Schwartz K.A.
      • Kolts R.L.
      • Brown W.A.
      BMI, sex, and antidepressant response.
      ,
      • Lin C.H.
      • Chen C.C.
      • Wong J.
      • McIntyre R.S.
      Both body weight and BMI predicts improvement in symptom and functioning for patients with major depressive disorder.
      ,
      • Oskooilar N.
      • Wilcox C.S.
      • Tong M.L.
      • Grosz D.E.
      Body mass index and response to antidepressants in depressed research subjects.
      ,
      • Sagud M.
      • Mihaljevic-Peles A.
      • Uzun S.
      • Cusa B.V.
      • Kozumplik O.
      • Kudlek-Mikulic S.
      • et al.
      The lack of association between components of metabolic syndrome and treatment resistance in depression.
      ,
      • Toups M.S.
      • Myers A.K.
      • Wisniewski S.R.
      • Kurian B.
      • Morris D.W.
      • Rush A.J.
      • et al.
      Relationship between obesity and depression: characteristics and treatment outcomes with antidepressant medication.
      ,
      • Vogelzangs N.
      • Beekman A.T.
      • van Reedt Dortland A.K.
      • Schoevers R.A.
      • Giltay E.J.
      • de Jonge P.
      • et al.
      Inflammatory and metabolic dysregulation and the 2-year course of depressive disorders in antidepressant users.
      ]. However, there is evidence that symptom profiles may in fact vary with factors such as BMI, along with other demographic factors (for review; see Woo et al. [
      • Woo Y.S.
      • Seo H.J.
      • McIntyre R.S.
      • Bahk W.M.
      Obesity and its potential effects on antidepressant treatment outcomes in patients with depressive disorders: a literature review.
      ]). For example, Kloiber and colleagues [
      • Kloiber S.
      • Ising M.
      • Reppermund S.
      • Horstmann S.
      • Dose T.
      • Majer M.
      • et al.
      Overweight and obesity affect treatment response in major depression.
      ] reported differences in pre-treatment neurovegetative symptoms according to BMI, with obese individuals endorsing less insomnia, weight loss, and decreased appetite than nonobese individuals with MDD. Taking this a step further, Uher et al. [
      • Uher R.
      • Mors O.
      • Hauser J.
      • Rietschel M.
      • Maier W.
      • Kozel D.
      • et al.
      Body weight as a predictor of antidepressant efficacy in the GENDEP project.
      ] documented differential changes in neurovegetative (but not cognitive) symptoms of depression according to obesity, sex, and antidepressant type (nortriptyline, escitalopram).
      It has been suggested that different outcomes across treatment studies may be related to several abovementioned factors including differences in sample demographics, types of antidepressants, and categories of depressive symptoms [
      • Woo Y.S.
      • Seo H.J.
      • McIntyre R.S.
      • Bahk W.M.
      Obesity and its potential effects on antidepressant treatment outcomes in patients with depressive disorders: a literature review.
      ]. Our aim was to further investigate the role of these factors, particularly the role of obesity, sex, and type of antidepressant, on acute remission from depression after antidepressant treatment using data from the International Study to Predict Optimized Treatment in Depression (iSPOT-D; [
      • Williams L.M.
      • Rush A.J.
      • Koslow S.H.
      • Wisniewski S.R.
      • Cooper N.J.
      • Nemeroff C.B.
      • et al.
      International Study to Predict Optimized Treatment for Depression (iSPOT-D), a randomized clinical trial: rationale and protocol.
      ]). In many previous studies of overweight and antidepressant outcomes, the medication type has varied across studies or is not controlled for [
      • Kloiber S.
      • Ising M.
      • Reppermund S.
      • Horstmann S.
      • Dose T.
      • Majer M.
      • et al.
      Overweight and obesity affect treatment response in major depression.
      ]; a situation which may have contributed to the variation across findings reported to date. Therefore, we aimed to examine whether the relationship between BMI and remission rates after treatment would depend on medications type. Additionally, we chose to parse out specific symptom clusters (vegetative/physical vs. cognitive) to better understand if adiposity, sex, and antidepressant type are related to a differential reduction of specific symptom types following antidepressant treatment. We tested the following hypotheses:
      • (1)
        Adiposity (assessed by BMI) predicts remission outcomes following antidepressant treatment as a function of type of antidepressant medication. In our predictive analysis we explored the differential contribution of medication type in a priori specified pairwise comparisons (venlafaxine-XR vs. escitalopram, venlafaxine-XR vs. sertaline and sertaline vs. escitalopram).
      • (2)
        The contribution of adiposity to predicting antidepressant remission varies according to sex, and obese women are likely to have comparatively better remission outcomes.
      • (3)
        The mechanisms underlying the role of BMI in predicting remission outcomes, as a function of antidepressant medication type and sex (as tested under hypotheses 1 and 2) are reflected in the differential improvement of specific symptoms (physical or cognitive). This hypothesis draws on evidence suggesting that specific antidepressants (nortriptyline, escitalopram) may preferentially act on specific symptom types (such as vegetative symptoms vs. cognitive symptoms), and this effect varies according to level of body fat [
        • Uher R.
        • Mors O.
        • Hauser J.
        • Rietschel M.
        • Maier W.
        • Kozel D.
        • et al.
        Body weight as a predictor of antidepressant efficacy in the GENDEP project.
        ]. Thus, our working hypothesis was that BMI would have a differential effect on improving symptoms within these specific domains.

      Materials and methods

      Overview and study design

      iSPOT-D is a multisite randomized controlled practical trial designed to identify different predictors of outcomes in 1008 participants with nonpsychotic MDD randomly assigned to receive escitalopram, sertraline or venlafaxine extended-release (venlafaxine-XR) for 8 weeks. Randomization to treatment group was performed using Phase-Forward’s™ validated, Web-based Interactive Response Technology, and a blocked procedure across sites (block size of 12). Outcome assessors were masked, but not the treating clinicians nor the participants. Consistent with the practical trial design of iSPOT-D, clinicians adjusted medication dosages according to routine clinical practice. Details of iSPOT-D are described elsewhere [
      • Williams L.M.
      • Rush A.J.
      • Koslow S.H.
      • Wisniewski S.R.
      • Cooper N.J.
      • Nemeroff C.B.
      • et al.
      International Study to Predict Optimized Treatment for Depression (iSPOT-D), a randomized clinical trial: rationale and protocol.
      ]. The study was approved by institutional or ethical review boards at each site, and the protocols were in compliance with International Conference on Harmonization and Good Clinical Practice principles, the U.S. Food and Drug Administration Code of Federal Regulations, and country-specific guidelines.

      Participants

      Participants gave written informed consent. Inclusion criteria were an age from 18 to 65 years (M = 38.9, SD = 12.6); fluency/literacy in English or Dutch; and endorsement of Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV) criteria for single or recurrent nonpsychotic MDD based on the Mini International Neuropsychiatric Interview Plus (MINI-Plus; [
      • Saveanu R.
      • Etkin A.
      • Duchemin A.M.
      • Goldstein-Piekarski A.
      • Gyurak A.
      • Debattista C.
      • et al.
      The international Study to Predict Optimized Treatment in Depression (iSPOT-D): outcomes from the acute phase of antidepressant treatment.
      ,
      • Sheehan D.V.
      • Lecrubier Y.
      • Sheehan K.H.
      • Amorim P.
      • Janavs J.
      • Weiller E.
      • et al.
      The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10.
      ]). Exclusion criteria included suicidal planning, psychiatric comorbidities other than anxiety disorder, contraindications for study treatments or previous treatment failure at the highest recommended dose, current treatment of MDD using study treatments, substance dependence, history of brain injury, sensory impairments that could interfere with study assessments, and pregnancy/breast feeding (see Supplementary Fig. 1).
      The first phase of iSPOT-D enrolled 1008 eligible patients from 17 sites in the United States, Netherlands, Australia, New Zealand and South Africa (see Saveanu et al. [
      • Saveanu R.
      • Etkin A.
      • Duchemin A.M.
      • Goldstein-Piekarski A.
      • Gyurak A.
      • Debattista C.
      • et al.
      The international Study to Predict Optimized Treatment in Depression (iSPOT-D): outcomes from the acute phase of antidepressant treatment.
      ] for the clinical characteristics of these patients). Of these participants, 956 had BMI measurements and 929 had BMIs ⩾ 18.5 kg/m2 (see the CONSORT chart; Supplementary Fig. 2). Of these participants, 659 completed the acute 8-week antidepressant treatment phase of the study. This per-protocol sample of 659 participants was used in this study. Demographic and clinical characteristics for the sample are displayed in Table 1.
      Table 1Demographic, health and clinical characteristics by group.
      CharacteristicTotal SampleMalesFemales
      N (%)659284 (43)375 (57)
      Demographics [Mean (SD)]
       Age (years)38.9 (12.6)39.1 (12.4)38.8 (12.8)
       BMI (kg/m2)28.0 (7.1)27.7 (6.0)28.2 (7.8)
      WHO Classifications [N (%)]
       Normal274 (41.6)107 (37.7)167 (44.5)
       Overweight185 (28.1)105 (37.0)80 (21.3)
       Obese I98 (14.9)38 (13.4)60 (16.0)
       Obese II63 (9.6)22 (7.7)41 (10.9)
       Obese III39 (5.9)12 (4.2)27 (7.2)
      Clinical Characteristics [Mean (SD)]
       Duration of MDD (years)15.2 (12.6)14.7 (12.1)15.7 (12.9)
       Baseline HRSD1721.9 (4.1)21.8 (4.1)21.9 (4.1)
      Treatment [Mean (SD)]
       Dosage at week 8 (mg)
        Escitalopram (N = 213)12.5 (9.6)12.0 (8.7)12.9 (10.4)
        Sertraline (N = 221)60.7 (34.0)56.3 (29.4)63.9 (36.8)
        Venlafaxine-XR (N = 224)76.4 (42.4)81.7 (45.0)72.8 (40.3)
      Abbreviations: BMI = body mass index; WHO = World Health Organization; MDD = major depressive disorder; HRSD17 = 17-item Hamilton Rating Scale for Depression.
      Note: Higher HRSD17 scores are associated with greater depression symptom severity.
      We investigated potential differences between treatment completers and non-completers across several variables using analyses of variance (ANOVAs) with Bonferroni corrections to address multiple statistical tests. There were no differences between treatment completers and non-completers in baseline depression symptom severity based on the 17-item Hamilton Rating Scale for Depression (HRDS17; [
      • Hamilton M.
      A rating scale for depression.
      ]) (F[1, 1006] = 0.75, p = 0.39), and neither sex dropped out at a higher rate than the other (χ2 = 0.72, df = 1, p = 0.40). BMI ranged from 19 to 72 kg/m2 in this sample (completers), or normal weight to obese class III according to the WHO classification, with a mean in the overweight range (28.0 kg/m2; SD: 7.1). The sample consisted of 43% males and 57% females. There were no differences in mean BMI between completers and non-completers (F[1, 954] = 3.93, p = 0.05).
      Issues related to differences in initial symptom severity and other iSPOT-D variables across sites are addressed in detail elsewhere [
      • Saveanu R.
      • Etkin A.
      • Duchemin A.M.
      • Goldstein-Piekarski A.
      • Gyurak A.
      • Debattista C.
      • et al.
      The international Study to Predict Optimized Treatment in Depression (iSPOT-D): outcomes from the acute phase of antidepressant treatment.
      ]. Of note, there were no differences in BMI across different countries (F[4, 654] = 1.78, p > 0.05).

      Study measures

      Height and weight were measured using a stadiometer and digital scale, respectively. BMI was calculated by dividing each participant’s weight in kilograms by their height in meters squared. Depression symptom severity was assessed at baseline (week 0), and again after week 8 of treatment using the HRSD17. Remission, defined categorically as an HRSD17 score ⩽7 after 8 weeks of treatment, was one outcome. We also calculated change in baseline physical symptoms and change in cognitive symptoms (taken from the 21 item HRSD; HRSD21) after antidepressant treatment for outcome variables addressing our third hypothesis. Physical symptoms were defined as the sum of the following HRSD21 items: sleep disturbance, diurnal variation, genital symptoms, hypochondriasis, weight changes, somatic anxiety, somatic gastrointestinal symptoms and general somatic symptoms. The cognitive symptoms were defined as the sum of the following HRSD21 items: suicidal ideation, guilt, psychic anxiety, insight, paranoia, depersonalization/derealization, change in work and activities, depressed mood, psychomotor retardation, and psychomotor agitation. The change in physical or cognitive symptoms were calculated by subtracting the sum post-treatment from the sum at baseline. Administrators of the HRSD17 were blind to treatment condition. Dosage was defined as mg per day for sertraline and venlafaxine-XR. For escitalopram, we multiplied the dosage (mg/day) by a factor of 10 to match the distribution of the other treatment dosages for group analyses.

      Statistical analysis

      Per-protocol statistical analyses were performed using the SPSS statistical software package (IBM SPSS Statistics, Version 21). Prior to running the primary analyses, we identified potential confounds including pre-treatment symptom severity, age, number of comorbid cardiovascular conditions, and dosage. When one or more of these variables was associated with remission status or BMI, we included them in the regression model as covariates. For primary analyses, we used hierarchical and linear logistic regression analyses.
      To test Hypothesis 1, the interaction between BMI and treatment arm, we used a priori planned comparisons between BMI and antidepressants modeled using dummy coded variables. More specifically, although we tested the full interaction across the three treatment arms, our specific aim was to examine pairwise differences in the relationship between BMI and remission across the antidepressants. To address our second hypothesis, we ran another hierarchical logistic regression to investigate whether sex moderates the relationship between BMI and prediction of remission. Finally, to address Hypothesis 3 and to determine whether the BMI by treatment arm and/or BMI by sex interactions are driven by a reduction in specific symptom types, we ran linear regressions using the same stepwise predictors as for Hypothesis 1 and 2, but using either change in HRSD17 cognitive and physical/vegetative symptoms as the outcome variable.
      For logistic regressions, we used the Wald Statistic (W) to determine the significance of the contribution of each predictor and the chi-square test to determine the overall interaction effect. Odds ratios are reported for each main effect and simple interaction. In order to comment on the clinical utility of our results, we also calculated the number needed to treat (NNT) at different levels of BMI based on WHO classifications and odds ratios generated from the predicted probabilities of remission. For linear regressions, t-tests were conducted to determine the significance of beta (β) values relating to the contribution of each predictor and the F test to determine the overall interaction effects.

      Results

      Baseline differences in physical or cognitive symptoms

      One way Analyses of Variance (ANOVAs) revealed no mean differences in cognitive symptoms (F(1, 656) = 0.26, p = 0.61), or physical/vegetative symptoms (F(1, 655) = 1.32, p = 0.25) between males and females. See Table 1 for group means and standard deviations. Bivariate correlations revealed no statistically significant association between BMI and physical/vegetative symptoms, (r = −0.07, p = 0.084), although individuals with larger BMIs had a trend towards having less physical symptoms. However, individuals with larger BMIs had fewer cognitive symptoms (r = −0.15, p < 0.001). Individuals with larger BMI at baseline had less severe overall symptom severity at baseline (HRSD17; r = −0.11, p = 0.005).

      Predictors of remission

      We found significant and modest inverse associations between remission and both age (r = −0.11, p = 0.003) and baseline HRSD17 depressive symptom severity (r = −0.20, p < 0.001). BMI was positively related to dose of antidepressant medications (r = 0.10, p = 0.009) and number of comorbid cardiovascular conditions (r = 0.18, p < 0.001). Thus age, symptom severity, dosage and the number of comorbid cardiovascular conditions were included as covariates in our primary regression analyses. We note that the relationship between BMI and dosage did not significantly differ between types of antidepressant treatment (all p > 0.05).

      BMI by treatment interaction

      The overall model for BMI and treatment type predicting remission was significant (χ2 = 50.14, df = 10, p < 0.001, Nagelkerke R2 = 0.10; Table 2). Our a priori specified interactions between BMI and treatment type showed that BMI was a differential predictor of remission for the comparison of venlafaxine-XR and escitalopram, but not for the other pairwise treatment comparisons (Table 2). More specifically, every unit increase of BMI was associated with 6% greater odds of remission for venlafaxine-XR (95% CI 1.01–1.11), but BMI did not significantly predict remission for escitalopram (95% CI 0.96 to 1.04) or sertraline (95% CI 0.99–1.08) (Table 2).
      Table 2BMI by treatment interaction and BMI by sex interaction.
      Model PredictorsΔχ2BSEWaldOR (95% CL)p
      Level 1
       Age−0.020.018.160.98 (0.97–0.99)0.004
      HRSD17−0.100.0222.690.91 (0.870.94)<0.001
       Dosage−0.0020.0011.601.00 (1.00–1.00)0.206
       Comorbid Cardiovascular Conditions−0.160.230.470.85 (0.54–1.34)0.491
      BMI0.030.016.041.03 (1.011.06)0.014
       Sex−0.140.170.760.87 (0.63–1.20)0.380
       Venlafaxine vs. escitalopram0.390.213.451.48 (0.98–2.24)0.063
       Sertraline vs escitalopram0.190.220.771.21 (0.79–1.86)0.381
       Sertraline vs. venlafaxine-XR−0.200.201.000.82 (0.55–1.21)0.317
      Level 2: BMI by Treatment
       BMI × Treatment (overall interaction)4.380.112
      BMI×(venlafaxine-XR vs. escitalopram)0.060.034.031.06 (1.0011.12)0.045
       BMI × (sertraline vs. escitalopram)0.040.032.091.04 (0.99–1.10)0.148
       BMI × (sertraline vs. venlafaxine-XR)−0.020.030.370.98 (0.93–1.04)0.272
      Level 2: BMI by Sex
      Sex×Treatment5.630.060.035.501.06 (1.011.12)0.019
      Bold value indicates a significant effect at p < 0.5.
      To graphically depict this interaction, we calculated probabilities of remission at meaningful levels of BMI (per WHO classifications) and fitted them with regression lines (Fig. 1). Specifically, we calculated predicted probabilities of remission at the midpoint of the normal range (21.5 kg/m2), overweight (27.5 kg/m2), obese class I (32.5 kg/m2), obese class II (37.5 kg/m2) and at two points within the obese class III (45 kg/m2 and 55 kg/m2).
      Figure thumbnail gr1
      Fig. 1Predicted probabilities of remission for each treatment at different levels of Body Mass Index (BMI). Probabilities were calculated at the midpoint of the normal range (21.7 kg/m2), overweight (27.5 kg/m2), obese class I (32.5 kg/m2), obese class II (37.5 kg/m2) and at two points within the range of obese class III (42.5 kg/m2 and 50 kg/m2). Of note, the relationship between BMI and prediction of remission was only significant for venlafaxine-XR. However, predicted probabilities are shown for each treatment arm here.

      BMI by sex interaction

      The overall model for BMI and sex predicting remission was also significant (χ2 = 51.38, df = 9, p < 0.001, Nagelkerke R2 = 0.10; Table 2). As hypothesized, there was a significant BMI by sex interaction (W = 5.50, p = 0.019, interaction odds ratio = 1.06 [95% CI 1.01–1.12]) in predicting remission from depression. BMI was not associated with remission in males, but in females every unit increase of BMI was associated with a 5% greater odds of remission (Table 2). Females with a higher BMI were more likely to achieve remission than those with a smaller BMI, regardless of type of antidepressant treatment. Again, to graphically depict this interaction, we calculated the predicted probabilities of remission at the aforementioned BMI levels and plotted them for males and females separately (Fig. 2).
      Figure thumbnail gr2
      Fig. 2Predicted probabilities of remission for males and females collapsed across treatment at differing levels of Body Mass Index (BMI).

      Independent effects of BMI and sex

      Sex was not independently predictive of remission from depression (p = 0.38). However, we observed a main effect for BMI such that higher BMI was associated with a higher rate of remission (W = 6.04, p = 0.01, odds ratio = 1.03, [95% CI 1.01 to 1.06]). For every unit increase of BMI, the odds of remission increased by 3%. This main effect for BMI is qualified by the above interactions with both treatment arm and sex.

      Predicted probability of remission and number needed to treat (NNT)

      To further describe the results, we created a flow chart detailing the predicted probabilities of remission (based on the full model containing the sex by BMI and treatment by BMI interactions) for every possible combination of sex, obesity classification (using the World Health Organization classifications), and medication (Fig. 3).
      Figure thumbnail gr3
      Fig. 3Flow chart demonstrating the predicted probability for every combination of sex, obesity classification calculated at the midpoint of the normal range (21.7 kg/m2), overweight (27.5 kg/m2), obese class I (32.5 kg/m2), obese class II (37.5 kg/m2) and obese class III (42.5 kg/m2). Predicted probabilities lower than 40% are highlighted in red and probabilities greater than 70% are highlighted in green.
      Abbreviations: NM = normal; OW = overweight; OB = obese; ESC = escitalopram; SER = sertraline; VEN = venlafaxine-XR.
      To assess clinical utility for predicting remission, we calculated NNT for venlafaxine-XR (associated with highest predicted probability of remission for males and at the highest obesity levels). NNT was computed based on the overall 45% remission rate for the entire sample,[
      • Saveanu R.
      • Etkin A.
      • Duchemin A.M.
      • Goldstein-Piekarski A.
      • Gyurak A.
      • Debattista C.
      • et al.
      The international Study to Predict Optimized Treatment in Depression (iSPOT-D): outcomes from the acute phase of antidepressant treatment.
      ] odds ratios, and predicted probabilities of remission at differing levels of BMI. Individuals with a BMI ⩾ 40 were more likely to remit on venlafaxine-XR than on the other antidepressants regardless of sex, with an NNT of 6. Thus, for this morbidly obese group, knowing BMI for six participants yields one additional remitter. In the other WHO BMI categories, there was no advantage for knowing BMI level (NNT ⩾ 12). For females specifically, meeting the criteria for WHO class III obesity or class II obesity was associated with a greater likelihood of remission regardless of treatment type, with an NNT of 3 and 6, respectively. Thus, only 3 females with a BMI ⩾ 40 kg/m2 or 6 females with a BMI between 35 and 39.9 kg/m2 may need to be treated in order to yield one additional remitter.

      Prediction of cognitive and physical symptom reduction

      BMI by treatment interaction

      The results from the linear regressions are displayed in Table 3, Table 4. The overall model for BMI and treatment type predicting change in physical symptoms was significant (F (10, 622) = 9.28, p < 0.001, R2 = 0.11; Table 4). The overall BMI by treatment arm interaction was significant (F (2, 622) = 4.46, p = 0.012, R2 = 0.012). Specifically, for every unit increase in BMI, venlafaxine was associated with a 0.15 larger decrease in HRDS physical symptoms than escitalopram (b = 0.15, p = 0.003). There were no other significant interactions between BMI and other antidepressants. The BMI by treatment type interaction was not significantly associated with a change in cognitive symptoms, (F (2, 623) = 0.68, p = 0.509, R2 = 0.002; Table 3).
      Table 3BMI × Treatment Interaction and BMI × Sex Interaction on Change in Cognitive Symptoms of suicidal ideation, guilt, psychic anxiety, insight, paranoia, depersonalization/derealization, impact on work and activities, depressed mood, psychomotor retardation, and psychomotor agitation.
      Model PredictorsΔR2BSEtBeta (95% CL)p
      Level 1
      Age0.050.013.450.140.001
      HRSD17−0.240.04−5.89−0.23<0.001
       Dosage0.0040.0031.370.060.172
       Comorbid Cardiovascular Conditions−0.510.47−1.09−0.050.278
       BMI0.010.030.430.0170.668
       Sex0.060.340.190.0070.853
       Venlafaxine-XR vs. escitalopram0.210.440.470.020.637
       Sertraline vs escitalopram0.250.450.540.030.590
       Sertraline vs venlafaxine-XR0.040.420.960.0040.924
      Level 2: BMI by Treatment
       BMI × Treatment (overall interaction)0.0020.509
       BMI × (venlafaxine-XR vs. escitalopram)NS
       BMI × (sertraline vs. escitalopram)NS
       BMI × (sertraline vs. venlafaxine-XR)NS
      Level 2: BMI by Sex
      Sex×BMI0.010−0.130.05−2.56−0.1770.01
      Bold value indicates a significant effect at p < 0.5.
      Table 4BMI × Treatment Interaction and BMI × Sex Interaction on Change in Physical Symptoms of sleep disturbance, diurnal variation, genital symptoms, hypochondriasis, weight changes, somatic anxiety, somatic gastrointestinal symptoms and general somatic symptoms.
      Model PredictorsΔR2BSEtBeta (95% CL)p
      Level 1
       Age0.020.011.870.070.062
      HRSD17−0.300.04−8.32−0.32<0.001
       Dosage0.0040.0021.830.080.068
       Comorbid Cardiovascular Conditions−0.450.41−1.11−0.040.269
       BMI−0.040.02−1.680.070.093
       Sex−0.200.30−0.67−0.030.506
      Venlafaxine-XR vs. escitalopram0.790.382.090.100.037
       Sertraline vs escitalopram0.200.400.520.030.605
       Venlafaxine-XR vs sertraline0.590.361.620.070.105
      Level 2: BMI by Treatment
      BMI×Treatment (overall interaction)0.0120.012
      BMI×(venlafaxine-XR vs. escitalopram)−0.150.05−2.97−0.150.003
       BMI × (sertraline vs. escitalopram)−0.080.05−1.65−0.090.099
       BMI × (venlafaxine-XR vs. sertraline)−0.070.05−1.36−0.070.174
      Level 2: BMI by Sex
       Sex × BMI0.003−0.060.05−1.34−0.0910.180
      Bold value indicates a significant effect at p < 0.5.

      BMI by sex interaction

      The BMI by sex interaction was not significant in predicting change in physical/vegetative symptoms (F (1, 623) = 1.804, p = 0.180, ΔR2 = 0.003; Table 4). However, the sex by BMI interaction was significant for predicting change in cognitive symptoms after antidepressant treatment (F (1, 624) = 6.544, p = 0.011, ΔR2 = 0.010; Table 3). Specifically, for every unit increase in BMI, females demonstrated a 0.13 greater decrease in cognitive symptoms than males (b = −0.133, p = 0.011).

      Independent effects of BMI and sex on change in specific symptom types

      BMI was not significantly associated with a differential decrease in either cognitive (b = 0.01, p = 0.67), or physical/vegetative symptoms (b = −0.04, p = 0.37). Similarly, sex was not significantly associated with a differential decrease in either cognitive (b = 0.06, p = 0.85), or physical/vegetative symptoms (b = −0.20, p = 0.51).

      Discussion

      To our knowledge, this is the first report to suggest that pre-treatment BMI predicts a greater probability of acute remission following venlafaxine-XR antidepressant treatment, particularly for the physical symptoms of depression (e.g., sleep, appetite, somatic symptoms), while BMI predicts greater probability of remission for females relative to males across antidepressants, particularly with respect to cognitive symptoms (e.g., depressed mood, guilt, suicidal ideation).

      Obesity is associated with reductions in the physical symptoms for venlafaxine-XR in particular

      In our sample, greater adiposity was predictive of better rates of remission for patients treated with venlafaxine-XR in particular. Further, our data suggest that higher remission rates for individuals with larger BMIs are actually driven by changes in the physical symptoms specifically. In other words, in individuals with larger BMIs, venlafaxine-XR appears to reduce depressive symptomatology related to the more physical symptoms of sleep, appetite/weight changes, and somatic symptoms (fatigue, headache, muscle aches). Interestingly, we also report an association between larger BMI and lower symptom severity ratings at baseline, particularly for the symptoms that are more cognitive in nature. Lower baseline symptom severity in individuals with larger BMIs is consistent with one previous report [
      • Kloiber S.
      • Ising M.
      • Reppermund S.
      • Horstmann S.
      • Dose T.
      • Majer M.
      • et al.
      Overweight and obesity affect treatment response in major depression.
      ], although BMI groups in other cohorts have not differed on baseline symptom severity [
      • Toups M.S.
      • Myers A.K.
      • Wisniewski S.R.
      • Kurian B.
      • Morris D.W.
      • Rush A.J.
      • et al.
      Relationship between obesity and depression: characteristics and treatment outcomes with antidepressant medication.
      ,
      • Uher R.
      • Mors O.
      • Hauser J.
      • Rietschel M.
      • Maier W.
      • Kozel D.
      • et al.
      Body weight as a predictor of antidepressant efficacy in the GENDEP project.
      ].
      The mechanisms associated with this finding are currently unclear. However, should adiposity prolong the absorption of antidepressants, it is possible this effect is pronounced for venlafaxine-XR because it is already in a sustained release formulation. It is also possible that adiposity is most relevant to the distinct pharmacological action of venlafaxine-XR, involving norepinephrine. However, this is all speculation and the question of how differing pharmacological properties of venlafaxine-XR relative to SSRIs may interact with varying levels of body fat to impact depressive symptom reduction warrants independent investigation.

      Obesity is associated with reductions in the cognitive symptoms for females

      We also demonstrate a BMI by sex interaction on prediction of remission after controlling for the effects of dosage and other covariates. Specifically, as BMI increases, females, but not males, show a higher likelihood of remitting regardless of medication. Better outcomes after antidepressant treatment in females compared to males has been previously documented without taking levels of adiposity into account (a finding we did not replicate) [
      • Baca E.
      • Garcia-Garcia M.
      • Porras-Chavarino A.
      Gender differences in treatment response to sertraline versus imipramine in patients with nonmelancholic depressive disorders.
      ,
      • Khan A.
      • Brodhead A.E.
      • Schwartz K.A.
      • Kolts R.L.
      • Brown W.A.
      Sex differences in antidepressant response in recent antidepressant clinical trials.
      ,
      • Kornstein S.G.
      • Schatzberg A.F.
      • Thase M.E.
      • Yonkers K.A.
      • McCullough J.P.
      • Keitner G.I.
      • et al.
      Gender differences in treatment response to sertraline versus imipramine in chronic depression.
      ,
      • Sagud M.
      • Hotujac L.
      • Mihaljevic-Peles A.
      • Jakovljevic M.
      Gender differences in depression.
      ]. However, our findings are consistent with Khan and colleagues [
      • Khan A.
      • Schwartz K.A.
      • Kolts R.L.
      • Brown W.A.
      BMI, sex, and antidepressant response.
      ] who suggest that sex may moderate the relationship between obesity and remission after antidepressant treatment and reported greater symptom reduction in obese females relative to obese males following SSRI antidepressant treatment.
      It is not entirely clear why obese women would demonstrate better outcomes than obese men in response to antidepressants. Interestingly, higher remission rates in the high BMI females relative to high BMI males were driven by a differential reduction in the cognitive symptoms of depression specifically. In other words, depressive symptoms related to suicidal thoughts, guilt, anxiety, insight, paranoia, and depressed mood were addressed in females to a greater degree than in males after antidepressant treatment.
      Currently, there is no consistent agreement in the literature on the exact relationship between obesity and remission from depression. However, the notion that patients with higher BMIs may have better outcomes after antidepressant treatment, a finding that we demonstrate for females regardless of medication and venlafaxine-XR regardless of sex, is somewhat contrary to what several studies have reported [
      • Kloiber S.
      • Ising M.
      • Reppermund S.
      • Horstmann S.
      • Dose T.
      • Majer M.
      • et al.
      Overweight and obesity affect treatment response in major depression.
      ,
      • Lin C.H.
      • Chen C.C.
      • Wong J.
      • McIntyre R.S.
      Both body weight and BMI predicts improvement in symptom and functioning for patients with major depressive disorder.
      ,
      • Oskooilar N.
      • Wilcox C.S.
      • Tong M.L.
      • Grosz D.E.
      Body mass index and response to antidepressants in depressed research subjects.
      ,
      • Papakostas G.I.
      • Petersen T.
      • Iosifescu D.V.
      • Burns A.M.
      • Nierenberg A.A.
      • Alpert J.E.
      • et al.
      Obesity among outpatients with major depressive disorder.
      ,
      • Toups M.S.
      • Myers A.K.
      • Wisniewski S.R.
      • Kurian B.
      • Morris D.W.
      • Rush A.J.
      • et al.
      Relationship between obesity and depression: characteristics and treatment outcomes with antidepressant medication.
      ,
      • Uher R.
      • Mors O.
      • Hauser J.
      • Rietschel M.
      • Maier W.
      • Kozel D.
      • et al.
      Body weight as a predictor of antidepressant efficacy in the GENDEP project.
      ]. Of note, several studies have also reported no relationship between BMI and treatment outcome [
      • Sagud M.
      • Mihaljevic-Peles A.
      • Uzun S.
      • Cusa B.V.
      • Kozumplik O.
      • Kudlek-Mikulic S.
      • et al.
      The lack of association between components of metabolic syndrome and treatment resistance in depression.
      ,
      • Toups M.S.
      • Myers A.K.
      • Wisniewski S.R.
      • Kurian B.
      • Morris D.W.
      • Rush A.J.
      • et al.
      Relationship between obesity and depression: characteristics and treatment outcomes with antidepressant medication.
      ,
      • Vogelzangs N.
      • Beekman A.T.
      • van Reedt Dortland A.K.
      • Schoevers R.A.
      • Giltay E.J.
      • de Jonge P.
      • et al.
      Inflammatory and metabolic dysregulation and the 2-year course of depressive disorders in antidepressant users.
      ]. In the COMED trial for example, BMI was not related to antidepressant effects without consideration of sex or symptom characteristics [
      • Toups M.S.
      • Myers A.K.
      • Wisniewski S.R.
      • Kurian B.
      • Morris D.W.
      • Rush A.J.
      • et al.
      Relationship between obesity and depression: characteristics and treatment outcomes with antidepressant medication.
      ]. One cross-sectional study investigating associations between metabolic syndrome components and depression treatment resistance also failed to report an association between higher BMI and treatment response [
      • Sagud M.
      • Mihaljevic-Peles A.
      • Uzun S.
      • Cusa B.V.
      • Kozumplik O.
      • Kudlek-Mikulic S.
      • et al.
      The lack of association between components of metabolic syndrome and treatment resistance in depression.
      ]. In this study, logistic regression analyses were adjusted for sex. However, treatment success was defined as a minimum of 50% reduction in HDRS scores; changes in specific symptom types (physical vs. cognitive) were not investigated.
      It has been suggested that differences across studies in sample composition (e.g., age and sex of the patients), antidepressants administered, types of depressive symptoms, or other comorbid medical conditions with associated implications (inflammation) may account for discrepant findings [
      • Woo Y.S.
      • Seo H.J.
      • McIntyre R.S.
      • Bahk W.M.
      Obesity and its potential effects on antidepressant treatment outcomes in patients with depressive disorders: a literature review.
      ], especially considering that many studies may lack the power necessary to incorporate all factors into predictive models. Even in the current study, we do not report a robust association between BMI alone predicting better outcomes. BMI was independently associated with remission, but not with decreases in specific symptoms.

      Limitations

      Several limitations of the study warrant discussion. First, it should be noted that this is a secondary analysis of a large practical trial designed to allow dosing similar to what might be seen in real world clinics, and to identify specific predictors antidepressant response. Second, individuals who had previously failed treatment at the highest recommended dose were excluded from the study, meaning that some potentially treatment resistant patients might have been excluded, such that true remission rates in the population might be overestimated. Third, we used BMI because it is easily calculated and readily available to most medical providers. Waist circumference or waist-to-hip ratio may better estimate adiposity; however, these alternative measures are infrequently obtained in routine clinical practice.
      Although individuals with larger BMIs were prescribed higher dosages of antidepressants, the relationship between BMI and final dosage did not differ by treatment arm, and dosage was controlled for in the regression models. In the iSPOT-D trial, providers made dose adjustments based on their usual clinical practice, thus increasing the generalizability of our results. However, future studies of depression and obesity using controlled designs in which dosage is titrated according to treatment algorithms would complement the current study.
      Finally, we only analyzed the data for individuals who completed the study. Non-completers had somewhat smaller BMIs on average, although both were in the “overweight” range. Participants with larger BMIs were less likely to leave the study prior to completion. Thus, differential attrition rates may contribute to the findings, but this is unlikely because it cannot account for the association between increasing BMI and remission.

      Implications for practice

      Approximately 60% of patients with depression are treated in primary care settings, [
      • Young A.S.
      • Klap R.
      • Sherbourne C.D.
      • Wells K.B.
      The quality of care for depressive and anxiety disorders in the United States.
      ] and treated almost twice as frequently with medications than psychotherapy [
      • Robinson W.D.
      • Geske J.A.
      • Prest L.A.
      • Barnacle R.
      Depression treatment in primary care.
      ]. It is estimated that less than 40% of these patients achieve remission with first-line pharmacotherapy [
      • Gaynes B.N.
      • Warden D.
      • Trivedi M.H.
      • Wisniewski S.R.
      • Fava M.
      • Rush A.J.
      What did STAR∗D teach us? Results from a large-scale, practical, clinical trial for patients with depression.
      ]. Although prescribing physicians have access to information about patient sex, height and weight, and the empirical evidence suggests that these factors independently may be important predictors of differential treatment outcomes, there is currently no clear consensus to guide antidepressant medication tailoring based on adiposity and sex.
      Although replication of these findings are warranted, the results of this study could be easily translatable to practice to guide antidepressant selection for prescribing providers who are working with patients with large BMIs and differential symptom profiles. Simple demographic and vital sign information such as sex, height and weight and symptom subtypes (cognitive vs. physical/vegetative) may be obtainable in primary care clinics where most patients with MDD are seen and treated with antidepressant medications [
      • Robinson W.D.
      • Geske J.A.
      • Prest L.A.
      • Barnacle R.
      Depression treatment in primary care.
      ,
      • Young A.S.
      • Klap R.
      • Sherbourne C.D.
      • Wells K.B.
      The quality of care for depressive and anxiety disorders in the United States.
      ]. This information takes a very limited amount of time to obtain relative to other indicators of depression treatment response (e.g., genetics, psychiatric or medical comorbidities, etc.).
      The current results are also consistent with current initiatives designed to enhance precision medicine in psychiatry and use of this information in primary care and specialty settings may be an easy and efficient way to predict and maximize antidepressant treatment effectiveness for some individuals. Based on these data, for an individual with MDD and a BMI of 40 kg/m2, NNT is only 6 for venlafaxine-XR regardless of sex, and 3 for females regardless of medication. Further, venlafaxine-XR may be particularly useful for obese individuals with primarily physical complaints. Therefore, venlafaxine-XR may be associated with a greater likelihood of impacting physical symptoms in both male and female patients who meet the criteria for obesity class II or III, and females who meet the criteria for obesity class II or III may have favorable outcomes after treatment with escitalopram, sertraline or venlafaxine-XR in targeting cognitive symptoms of depression.

      Summary

      Overall, individuals with comorbid obesity and MDD benefit more from venlafaxine-XR than from escitalopram due to a reduction in physical symptoms. The association between greater adiposity and the likelihood of remission was greatest for females regardless of treatment. Pretreatment information about sex, height, weight, and presenting symptoms may inform medication selection in depressed outpatients.

      Funding and disclosure

      iSPOT-D is supported by Brain Resource, Ltd. Brain Resource was involved in the design of the study, managed the central coordination of the study, and provided the executive structure for a publication committee to manage the preparation of manuscripts. Brain Resource was not involved in the acquisition, analysis, interpretation of the data, or preparation of the manuscript. This work is also supported by the award UH2HL132368 from common fund through the NIH office of the director, which is administered by the National Heart, Lung and Blood Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. EG was supported by the Mental Illness Research, Education, and Clinical Center. This study’s researchers are independent of the funder.
      AFS has served as a consultant to Bay City Capital, BrainCells, CeNeRx, Cervel, Depomed, Eli Lilly, Forum, Genentech, Gilead, Jazz, Lundbeck/Takeda, McKinsey, Merck, MSI, Neuronetics, Novadel, One Carbon, PharmaNeuroBoost, Sunovion, Synosia, and Xhale; he has received honoraria from Merck; he has equity in Amnestix, BrainCells, CeNeRx, Corcept (co-founder), Delpor, Forest, Merck, Neurocrine, Novadel, Pfizer, PharmaNeuroBoost, Somaxon, Synosis, Titan, and Xhale; and he receives royalties from Stanford University for patents on mifepristone use and the pharmacogenetics of antidepressant response. AJR has received consulting fees from Brain Resource Ltd, Duke-NUS, Eli Lilly, Emmes Corp, Lundbeck A/S, Medavante Inc, National Institute of Drug Abuse, Santium Inc., Stanford University, Takeda USA, University of Colorado, University of Texas Southwestern Med Cntr.; speaking fees from the University of California at San Diego, Hershey Penn State Medical Center, New York State Psychiatric Institute, and the American Society for Clinical Psychopharmacology; royalties from Guilford Publications and the University of Texas Southwestern Medical Center; a travel grant from CINP and research support from Duke-National University of Singapore.
      LMW received fees as a consultant for Brain Resource Ltd. and was a stockholder in Brain Resource Ltd. prior to 2013. In 2015 she served as a consultant with Humana.
      AG-P and JM report no conflicts of interest.

      Acknowledgements

      LMW was the Academic PI for iSPOT-D from 2008-2013. LMW, EG, and AGP conducted and are responsible for the data analysis. LMW had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Dr. Claire V.A. Day was the Global Trial Coordinator for iSPOT-D. We gratefully acknowledge the contributions of the investigators at each site. We gratefully acknowledge the editorial support of Jon Kilner, MS, MA (Pittsburgh, PA, USA).

      Appendix A. Supplementary data

      References

        • Baca E.
        • Garcia-Garcia M.
        • Porras-Chavarino A.
        Gender differences in treatment response to sertraline versus imipramine in patients with nonmelancholic depressive disorders.
        Prog Neuropsychopharmacol Biol Psychiatry. 2004; 28: 57-65
        • Gaynes B.N.
        • Warden D.
        • Trivedi M.H.
        • Wisniewski S.R.
        • Fava M.
        • Rush A.J.
        What did STAR∗D teach us? Results from a large-scale, practical, clinical trial for patients with depression.
        Psychiatr Serv. 2009; 60: 1439-1445
        • Hamilton M.
        A rating scale for depression.
        J Neurol Neurosurg Psychiatry. 1960; 23: 56-62
        • Hildebrandt M.G.
        • Steyerberg E.W.
        • Stage K.B.
        • Passchier J.
        • Kragh-Soerensen P.
        Are gender differences important for the clinical effects of antidepressants?.
        Am J Psychiatry. 2003; 160: 1643-1650
        • Khan A.
        • Brodhead A.E.
        • Schwartz K.A.
        • Kolts R.L.
        • Brown W.A.
        Sex differences in antidepressant response in recent antidepressant clinical trials.
        J Clin Psychopharmacol. 2005; 25: 318-324
        • Khan A.
        • Schwartz K.A.
        • Kolts R.L.
        • Brown W.A.
        BMI, sex, and antidepressant response.
        J Affect Disord. 2007; 99: 101-106
        • Kloiber S.
        • Ising M.
        • Reppermund S.
        • Horstmann S.
        • Dose T.
        • Majer M.
        • et al.
        Overweight and obesity affect treatment response in major depression.
        Biol Psychiatry. 2007; 62: 321-326
        • Kornstein S.G.
        • Schatzberg A.F.
        • Thase M.E.
        • Yonkers K.A.
        • McCullough J.P.
        • Keitner G.I.
        • et al.
        Gender differences in treatment response to sertraline versus imipramine in chronic depression.
        Am J Psychiatry. 2000; 157: 1445-1452
        • Lin C.H.
        • Chen C.C.
        • Wong J.
        • McIntyre R.S.
        Both body weight and BMI predicts improvement in symptom and functioning for patients with major depressive disorder.
        J Affect Disord. 2014; 161: 123-126
        • Luppino F.S.
        • de Wit L.M.
        • Bouvy P.F.
        • Stijnen T.
        • Cuijpers P.
        • Penninx B.W.
        • et al.
        Overweight, obesity, and depression: a systematic review and meta-analysis of longitudinal studies.
        Arch Gen Psychiatry. 2010; 67: 220-229
        • McElroy S.L.
        • Kotwal R.
        • Malhotra S.
        • Nelson E.B.
        • Keck P.E.
        • Nemeroff C.B.
        Are mood disorders and obesity related? A review for the mental health professional.
        J Clin Psychiatry. 2004; 65 (quiz 730): 634-651
        • Oskooilar N.
        • Wilcox C.S.
        • Tong M.L.
        • Grosz D.E.
        Body mass index and response to antidepressants in depressed research subjects.
        J Clin Psychiatry. 2009; 70: 1609-1610
        • Papakostas G.I.
        • Petersen T.
        • Iosifescu D.V.
        • Burns A.M.
        • Nierenberg A.A.
        • Alpert J.E.
        • et al.
        Obesity among outpatients with major depressive disorder.
        Int J Neuropsychopharmacol. 2005; 8: 59-63
        • Parker G.
        • Parker K.
        • Austin M.P.
        • Mitchell P.
        • Brotchie H.
        Gender differences in response to differing antidepressant drug classes: two negative studies.
        Psychol Med. 2003; 33: 1473-1477
        • Quitkin F.M.
        • Stewart J.W.
        • McGrath P.J.
        • Taylor B.P.
        • Tisminetzky M.S.
        • Petkova E.
        • et al.
        Are there differences between women’s and men’s antidepressant responses?.
        Am J Psychiatry. 2002; 159: 1848-1854
        • Robinson W.D.
        • Geske J.A.
        • Prest L.A.
        • Barnacle R.
        Depression treatment in primary care.
        J Am Board Fam Pract. 2005; 18: 79-86
        • Sagud M.
        • Hotujac L.
        • Mihaljevic-Peles A.
        • Jakovljevic M.
        Gender differences in depression.
        Coll Antropol. 2002; 26: 149-157
        • Sagud M.
        • Mihaljevic-Peles A.
        • Uzun S.
        • Cusa B.V.
        • Kozumplik O.
        • Kudlek-Mikulic S.
        • et al.
        The lack of association between components of metabolic syndrome and treatment resistance in depression.
        Psychopharmacology. 2013; 230: 15-21
        • Saveanu R.
        • Etkin A.
        • Duchemin A.M.
        • Goldstein-Piekarski A.
        • Gyurak A.
        • Debattista C.
        • et al.
        The international Study to Predict Optimized Treatment in Depression (iSPOT-D): outcomes from the acute phase of antidepressant treatment.
        J Psychiatr Res. 2015; 61: 1-12
        • Sheehan D.V.
        • Lecrubier Y.
        • Sheehan K.H.
        • Amorim P.
        • Janavs J.
        • Weiller E.
        • et al.
        The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10.
        J Clin Psychiatry. 1998; 59 (quiz 34–57): 22-33
        • Thiels C.
        • Linden M.
        • Grieger F.
        • Leonard J.
        Gender differences in routine treatment of depressed outpatients with the selective serotonin reuptake inhibitor sertraline.
        Int Clin Psychopharmacol. 2005; 20: 1-7
        • Toups M.S.
        • Myers A.K.
        • Wisniewski S.R.
        • Kurian B.
        • Morris D.W.
        • Rush A.J.
        • et al.
        Relationship between obesity and depression: characteristics and treatment outcomes with antidepressant medication.
        Psychosom Med. 2013; 75: 863-872
        • Uher R.
        • Mors O.
        • Hauser J.
        • Rietschel M.
        • Maier W.
        • Kozel D.
        • et al.
        Body weight as a predictor of antidepressant efficacy in the GENDEP project.
        J Affect Disord. 2009; 118: 147-154
        • Vogelzangs N.
        • Beekman A.T.
        • van Reedt Dortland A.K.
        • Schoevers R.A.
        • Giltay E.J.
        • de Jonge P.
        • et al.
        Inflammatory and metabolic dysregulation and the 2-year course of depressive disorders in antidepressant users.
        Neuropsychopharmacology. 2014; 39: 1624-1634
        • Williams L.M.
        • Rush A.J.
        • Koslow S.H.
        • Wisniewski S.R.
        • Cooper N.J.
        • Nemeroff C.B.
        • et al.
        International Study to Predict Optimized Treatment for Depression (iSPOT-D), a randomized clinical trial: rationale and protocol.
        Trials. 2011; 12: 4
        • Wohlfarth T.
        • Storosum J.G.
        • Elferink A.J.
        • van Zwieten B.J.
        • Fouwels A.
        • van den Brink W.
        Response to tricyclic antidepressants: independent of gender?.
        Am J Psychiatry. 2004; 161: 370-372
        • Woo Y.S.
        • Seo H.J.
        • McIntyre R.S.
        • Bahk W.M.
        Obesity and its potential effects on antidepressant treatment outcomes in patients with depressive disorders: a literature review.
        Int J Mol Sci. 2016; 17
        • Young A.S.
        • Klap R.
        • Sherbourne C.D.
        • Wells K.B.
        The quality of care for depressive and anxiety disorders in the United States.
        Arch Gen Psychiatry. 2001; 58: 55-61