Obesity among outpatients with Major Depressive Disorder

Article · April 2005with18 Reads
DOI: 10.1017/S1461145704004602 · Source: PubMed
Abstract
Studies focusing on the prevalence of obesity in Major Depressive Disorder (MDD), or the impact of excess body fat on the treatment of MDD are lacking. The aim of the present work is to systematically study obesity in MDD outpatients. A total of 369 MDD outpatients enrolled in an 8-wk trial of 20 mg fluoxetine had height and weight measured at baseline. We then examined: (1) the prevalence of being overweight or obese, (2) the relationship between obesity and a number of demographic and clinical variables, and, (3) the relationship between relative body weight and obesity with clinical response. We found that more than 50% of patients were overweight [body mass index (BMI) > or =2 5 kg/m2], while 20% were obese (BMI > or = 30 kg/m2). Obese patients presented with worse somatic well-being scores than non-obese MDD patients, but they did not differ with respect to depression severity, anxiety, somatic complaints, hopelessness or hostility. Greater relative body weight, but not obesity, predicted non-response. In conclusion, greater relative body weight was found to place MDD outpatients at risk for fluoxetine resistance.
Figures
Obesity among outpatients with major
depressive disorder
George I. Papakostas, Timothy Petersen, Dan V. Iosifescu, Alana M. Burns,
Andrew A. Nierenberg, Jonathan E. Alpert, Jerrold F. Rosenbaum and Maurizio Fava
Depression Clinical and Research Program, Massachusetts General Hospital Harvard Medical School, Boston, MA, USA
Abstract
Studies focusing on the prevalence of obesity in major depressive disorder (MDD), or the impact of excess
body fat on the treatment of MDD are lacking. The aim of the present work is to systematically study
obesity in MDD outpatients. A total of 369 MDD outpatients enrolled in an 8-wk trial of 20 mg fluoxetine
had height and weight measured at baseline. We then examined : (1) the prevalence of being overweight or
obese, (2) the relationship between obesity and a number of demographic and clinical variables, and, (3)
the relationship between relative body weight and obesity with clinical response. We found that more
than 50 % of patients were overweight [body mass index (BMI) o25 kg/m
2
], while 20 % were obese (BMI
o30 kg/m
2
). Obese patients presented with worse somatic well-being scores than non-obese MDD
patients, but they did not differ with respect to depression severity, anxiety, somatic complaints, hope-
lessness or hostility. Greater relative body weight, but not obesity, predicted non-response. In conclusion,
greater relative body weight was found to place MDD outpatients at risk for fluoxetine resistance.
Received 24 November 2003 ; Reviewed 31 March 2004; Revised 2 May 2004; Accepted 16 May 2004
Key words : Fluoxetine treatment, major depressive disorder, obesity
Introduction
Obesity is a major public health concern. An esti-
mated half of the current US population is overweight
[National Task Force on the Prevention and Treatment
of Obesity (NTFPTO), 2000], defined as a body mass
index (BMI) of 25 kg/m
2
or greater, while the preva-
lence of obesity in the general population, defined as a
BMI of 30 kg/m
2
or greater, has been estimated at 20%
for men and 25% for women (Flegal et al., 1998). In
addition, the prevalence of obesity has increased
more than 50% from 1960 to 1994 (Flegal et al., 1998).
Although the adverse impact of obesity on medical
illness and all-cause mortality has been well-charac-
terized (Katzmarzyk et al., 2002; NTFPTO, 2000;
Pi-Sunyer, 1993 ; Raman, 2002), less is known about
the relationship between obesity and depression. In
fact, studies specifically reporting on the prevalence
of obesity in major depressive disorder (MDD) or
on the impact of excess body fat on the treatment of
MDD are lacking. Given the increasing prevalence of
obesity in the general population, studies are needed
to better define the role of obesity in MDD, and
specifically on treatment response with standard anti-
depressants such as the selective serotonin reuptake
inhibitors (SSRIs). The purpose of the present study
was to systematically study excess body weight and
obesity in MDD outpatients, with a focus on the
treatment of MDD.
Methods
A total of 384 outpatients, aged 18–65 yr, who
met criteria for a current major depressive episode
(MDE) according to the Structured Clinical Interview
for DSM-III-R Patient Edition (SCID-P ; Spitzer et al.,
1989), who were medication-free for at least 2 wk,
with a baseline 17-item Hamilton Depression Rating
Scale (HAMD-17; Hamilton, 1960) score of o16 were
enrolled into an 8-wk, fixed-dose, open-label trial of
20 mg fluoxetine conducted at the Massachusetts
General Hospital (MGH) Depression Clinical and
Research Program (DCRP). Patients were recruited
from November 1992 to January 1999 with the use
Address for correspondence : Dr G. I. Papakostas, Massachusetts
General Hosp ital, Department of Psychiatry, Depression Clinical
and Research Program, 15 Parkman Street, WACC 812, Boston,
MA 02114, USA.
Tel. : (617) 726-6697 Fax : (617) 726-7541
E-mail : gpapakostas@partners.org
International Journal of Neuropsychopharmacology (2005), 8, 59–63. Copyright f 2004 CINP
DOI : 10.1017/S1461145704004602
ARTICLE
of radio advertisements, newspaper advertisements
or were referred from colleagues. Institutional Review
Board (IRB)-approved written informed consent was
obtained from all study participants. Patients who
were non- or partial-responders to this open trial were
enrolled in a 4-wk, double-blind, triple-dummy, ran-
domized study comparing high dose fluoxetine with
augmentation of fluoxetine with either desipramine
or lithium. The results of the double-blind study are
reported elsewhere (Fava et al., 2002). The present
study focuses on the first phase of the trial.
Exclusion criteria included pregnant women and
women of childbearing potential who were not using
a medically accepted means of contraception, lactating
women, patients with serious suicidal risk or serious,
unstable medical illness, patients with a history of
seizure disorder, patients with the DSM-III-R diag-
noses of organic mental disorders, substance use dis-
orders, including alcohol, active within the last year,
schizophrenia, delusional disorder, psychotic dis-
orders not elsewhere classified, bipolar disorder, or
antisocial personality disorder, patients with a history
of multiple adverse drug reactions or allergy to the
study drugs, patients with mood-congruent or mood-
incongruent psychotic features, current use of other
psychotropic drugs, patients with clinical or labora-
tory evidence of hypothyroidism, patients whose
depression had failed to respond in the past to a trial
of either higher doses of fluoxetine (60 –80 mg/d), or
to the combination of fluoxetine and desipramine,
or the combination of fluoxetine and lithium, patients
who had failed to respond during the course of their
current MDE to at least one adequate antidepressant
trial, defined as 6 wk or more of treatment with either
>150 mg imipramine (or its tricyclic equivalent) or
>60 mg phenelzine (or its monoamine oxidase in-
hibitor equivalent).
During the screen visit, all enrolled patients signed
an IRB-approved written informed consent form. A
medical and psychiatric history, physical examination,
serum chemistries, haematological measures, electro-
cardiogram (EKG), and urine pregnancy test were
then performed. The 31-item of the Hamilton Rating
Scale for Depression (HAMD-31) was also adminis-
tered during the screen visit. The screen visit was
conducted by experienced psychologists or psy-
chiatrists. In our group, training in the use of instru-
ments such as the HAMD-31 and SCID-P is done by
peer review of videotaped interviews. Our inter-rater
reliability for the use of the SCID-P was recently esti-
mated as k=0.80 (Fava et al., 2000). At the conclusion
of the screen visit, all enrolled patients were asked to
return 1 wk later for the baseline visit.
Visits subsequent to the screen occurred at baseline
and then every other week for a total of 8 wk. The
HAMD-31 was administered during all study visits.
In addition to the HAMD-31, the self-rated Symptom
Questionnaire (Kellner, 1987) which contains sub-
scales on depression (SQ-D), anxiety (SQ-A), anger/
hostility (SQ-H), somatic symptoms (SQ-SS), and so-
matic well-being (SQ-SWB) along with the self-rated
Beck Hopelessness Scale (BHS ; Beck & Steer, 1988)
were also administered during the baseline visit.
Patients who returned for their baseline visit were
started on a 20 mg, fixed-dose regimen of fluoxetine.
A responder was defined as having a 50 % or greater
reduction in HAMD-17 score from baseline to end-
point. An intent-to-treat (ITT) analysis with the last
observation carried forward was used to define the
severity of depression at end-point, in which the last
recorded HAMD-17 score substituted the end-point
score for patients who prematurely discontinued the
study. BMI was defined as weight (in kg)/height
2
(in m
2
). A total of 369 patients had both height and
weight measured at baseline, allowing for the calcu-
lation of baseline BMI.
Statistical tests
The National Institutes of Health Clinical Guidelines
on the Identification, Evaluation, and Treatment of
Overweight and Obesity in Adults (NIH, 1998) define
overweight as a BMI equal to or greater than 25 kg/m
2
and obesity as a BMI equal to or greater than 30 kg/
m
2
, with healthy weight corresponding to a BMI be-
tween 19 and 25. Defining overweight as a minimum
BMI of 25 kg/m
2
is also consistent with recommend-
ations of the WHO (1998). Appropriate parametric and
non-parametric tests were used to compare differences
in variables between obese and non-obese patients.
With the use of separate logistic regressions we then
tested for the relationship between (1) relative body
weight (BMI as a continuous variable), (2) overweight
status, (3) obesity, or (4) change in weight during
the 8-wk trial and clinical response, controlling for
gender and the severity of depression at baseline
(HAMD-17 total score). We chose to control for gender
because of a recent study showing a gender-based
discrepancy in the relationship between body weight
and MDD (Carpenter et al., 2000).
Results
In total, 369 (96.0%) of the original 384 outpatients
had both height and weight recorded at baseline. The
sample consisted of 199 women (53.9%) and 170 men
60 G. I. Papakostas et al.
(46.1%). The mean age for the entire sample in years
was 39.8¡10.4 yr. In total, 312 (84.5%) out of 369
patients completed the study. Of these, 202 (54.7%)
patients responded to treatment. The mean length
of time in the study for responders was 7.6¡1.2 vs.
6.5¡2.7 for non-responders.
The mean baseline BMI for the entire sample was
26.5¡5.2 kg/m
2
. The distribution of BMI for the entire
sample is presented in Figure 1. Of all 369 patients
with BMI measured at baseline, 190 patients were
overweight (51.4 %). 94 of 199 women were over-
weight (47.2 %) and 96 of 170 men (56.5%). There were
74 patients who were classified as obese (20.0%). Fifty
out of 199 women (25.1%) and 24 out of 170 men
(14.1%) were obese. Demographic and clinical charac-
teristics of obese vs. non-obese MDD patients are
presented in Table 1.
A logistic regression revealed that greater relative
body weight predicted non-response (p=0.049,
x
2
=3.843, coefficient/S.E.=1.960, 95% CI 1.000–1.076).
There was a trend towards statistical significance
for poorer outcome in patients who were overweight
(p=0.067). The presence of obesity did not signifi-
cantly predict outcome (p=0.16). The mean BMI in
responders and non-responders was 25.9¡5.2 kg/m
2
vs. 27.1¡7.0 kg/m
2
. There was no statistically signifi-
cant change in weight during the trial (81.1¡24.7
vs. 81.3¡24.6 kg). Change in weight did not predict
outcome.
Discussion
More than half of the present sample of outpatients
with MDD were overweight, while 20% of patients
were obese. Nearly 25% of women and 14% of men
were found to be obese. These figures reflect the
national average (Flegal et al., 1998 ; NTFPTO, 2000),
with the exception of the somewhat lower prevalence
of obesity among men from the present sample com-
pared to the national average (14% vs. 20%). These
results are also in line with studies looking at the
incidence of obesity in bipolar disorder reported
between 21 % (McElroy et al., 2002) to 35.4% (Fagiolini
et al., 2003).
Carpenter et al. (2000) were the first to report on
the relationship between body weight and MDD.
In an epidemiological study involving more than
40000 subjects nationwide, the authors reported that
greater relative body weight was associated with
an increased risk for past-year MDD and suicidal
ideation among women while lesser relative body
weight was associated with an increased risk for
past-year MDD, suicidal ideation and suicide at-
tempts among men. Shortly thereafter, Roberts et al.
(2000) found that obesity, defined as a BMI at the
85th percentile or higher, predicted MDD after a 1-yr
follow-up. This finding was soon replicated for
longer follow-up periods (Roberts et al., 2003). While
these reports suggest an increased risk of depression
in obese patients, our study suggest that MDD out-
patients are not more likely to be obese than their
non-depressed counterparts. In addition, while obese
MDD patients presented with worse somatic well-
being scores than non-obese MDD patients, they
did not differ on the basis of depression severity,
100
90
80
70
60
50
40
30
20
10
0
15 20 25 30 35 40 45 50
Body mass index
Count
Figure 1. The distribution of MDD patients according to
body mass index.
Table 1. Demographic and clinical characteristics of obese vs.
non-obese MDD patients
Characteristic
Obese
(n=74)
Non-obese
(n=295) p
Duration MDE (yr) 4.0¡7.5 3.2¡5.5 >0.05
Number MDEs 25.3¡40.7 18.6¡35. 1 >0.05
Age onset (yr) 25.4¡14.2 26.1¡13.2 >0.05
HAMD-17 19.9¡3.4 19.7¡3.4 >0.05
Beck Hopelessness Scale 12.5¡5.2 11.3¡5.0 >0.05
SQ-Depression 17.4¡5.4 16.9¡4.6 >0.05
SQ-Anxiety 15.8¡4.7 15.1¡5.1 >0.05
SQ-Anger/Hostility 12.3¡6.6 11.8¡6.4 >0.05
SQ-Somatic symptoms 11.1¡5.5 9.3¡5.6 >0.05
SQ-Somatic well-being 1.1¡1.5 2.0¡2.1 0.018
Anorexia/current 0 0 >0.05
Anorexia/history 1 8 >0.05
Bulimia/current 1 1 >0.05
Bulimia/history 5 21 >0.05
Cigarettes (per day) 3.0¡8.2 2.9¡8.0 >0.05
SQ, Symptom Questionnaire.
Obesity in MDD 61
or in the severity of a number of depressive symptoms
including anxiety, somatic complaints, hopelessness
or hostility.
However, our study suggests that greater BMI is
associated with an increased risk of non-response
to treatment in MDD. Recently, Fagiolini et al. (2003)
reported a shorter time to recurrence during the
maintenance phase of treatment in obese than non-
obese outpatients with bipolar I disorder. That a di-
chotomous definition of high or normal BMI such
as obesity or being overweight did not significantly
predict treatment response in our trial is in line
with the aforementioned epidemiological study by
Carpenter et al. (2000) that found a link between
greater relative body weight (BMI continuous) and
MDD, but not between obesity (dichotomous) and
MDD. Thus, it may be that a definition of obesity as
a minimum BMI of 30 kg/m
2
may not be best suited
for the purposes of studying any adverse effects of
excess weight on mood or the treatment of depression.
Limitations
One limitation of the present study is the absence
of data on body fat distribution, which is an inde-
pendent predictor of health risk (NIH, 1998). Another
limitation is that of sampling bias. Clinical trials have
a number of inclusion and exclusion criteria and as a
result, patients in clinical trials do not directly reflect
the typical outpatient population. This may be par-
ticularly true in the present study, since we excluded
patients with severe/unstable medical illness. As a
result, given the relationship between excess body fat
and poor health status, many patients excluded on this
basis may have been overweight or obese. An ad-
ditional limitation is the lack of data on the treatment
history of patients enrolled in the study which may
have shed further light on the inter-relationship be-
tween relative body weight and treatment response
in depression. Thus, the degree to which these find-
ings generalize to a more heterogeneous population
of depressed patients including those with severe
severe/unstable medical illness remains to be deter-
mined. The final limitation is the absence of a control
group which would help clarify to what degree the
adverse impact of excessive body weight on outcome
to pharmacotherapy with fluoxetine is mediated
through decreasing drug or placebo response rates.
Conclusion
While some epidemiological studies suggest an in-
creased risk of MDD in obesity, the prevalence of
obesity in the present sample of outpatients with
MDD does not appear to differ from the general
population. In addition, while obese MDD patients
presented with worse somatic well-being scores than
non-obese MDD patients, they did not differ with
respect to depression severity, anxiety, the number
of somatic complaints, hopelessness or hostility at
baseline than non-obese patients. However, greater
relative body weight was found to place MDD out-
patients at risk for fluoxetine resistance regardless
of the severity of depression at baseline. Studies with
less stringent inclusion/exclusion criteria or focusing
on the medically ill may yield different results.
Acknowledgements
Supported by NIMH grant no. R01-MH-48-483-05
(M.F.), the American College of Neuropsychophar-
macology/GlaxoSmithKline Fellowship in Clinical
Neuropsychopharmacology (G.I.P.), and the Harvard
Medical School/Kaplen Fellowship in Depression
Research (G.I.P.).
Statement of Interest
None.
References
Beck AT, Steer RA (1988). Manual for the Beck Hopelessness
Scale. San Antonio: Psychological Corp.
Carpenter KM, Hasin DS, David AB, Myles FS (2000).
Relationships between obesity and DSM-IV major
depressive disorder, suicide ideation, and suicide attempts :
results from a general population study. American Journal of
Public Health 92, 251–257.
Fagiolini A, Kupfer DJ, Houck PR, Novick DM, Frank E
(2003). Obesity as a correlate of outcome in patients with
bipolar I disorder. American Journal of Psychiatry 160,
112–117.
Fava M, Alpert JE, Nierenberg AA, Russell JM, O’Boyle M,
Camilleri A, Harrison WM (2000). A validation study of a
computerized management system for the diagnosis and
treatment of depression. Report presented at the American
Psychiatric Association Annual Meeting.
Fava M, Alpert J, Nierenberg A, Lagomasino I, Sonawalla S,
Tedlow J, Worthington J, Baer L, Rosenbaum JF (2002).
Double-blind study of high-dose fluoxetine versus lithium
or desipramine augmentation of fluoxetine in partial
responders and nonresponders to fluoxetine. Journal of
Clinical Psychopharmacology 22, 379–387.
Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL (1998).
Overweight and obesity in the United States: prevalence
and trends, 1960–1994. International Journal of Obesity
and Related Metabolic Disorders 22, 39–47.
62 G. I. Papakostas et al.
Hamilton M (1960). A rating scale for depression. Journal
of Neurology Neurosurgery and Psychiatry 23, 56–62.
Katzmarzyk PT, Craig CL, Bouchard C (2002). Adiposity,
adipose tissue distribution and mortality rates in the
Canada Fitness Survey follow-up study. International Journal
of Obesity and Related Metabolic Disorders 26, 1054–1059.
Kellner R (1987). A Symptom Questionnaire. Journal of
Clinical Psychiatry 48, 268–274.
McElroy SL, Frye MA, Suppes T, Dhavale D, Keck Jr. PE,
Leverich GS, Altshuler L, Denicoff KD, Nolen WA,
Kupka R, Grunze H, Walden J, Post RM (2002). Correlates
of overweight and obesity in 644 patients with bipolar
disorder. Journal of Clinical Psychiatry 63, 207–213.
National Task Force on the Prevention and Treatment
of Obesity (NTFPTO) (2000). Overweight, obesity, and
health risk. Archives of Internal Medicine 16, 898–904.
National Institutes of Health (NIH) (1998). Clinical
Guidelines on the Identification, Evaluation, and
Treatment of Overweight and Obesity in Adults: The
Evidence Report. Obesity Research 6 (Suppl. 2), S51–S209.
Pi-Sunyer FX (1993). Medical hazards of obesity. Annals of
Internal Medicine 119, 655–660.
Raman RP (2002). Obesity and health risks. Journal of the
American College of Nutrition 21, S134–S139.
Roberts RE, Deleger S, Strawbridge WJ, Kaplan GA (2003).
Prospective association between obesity and depression :
evidence from the Almeida county study. International
Journal of Obesity and Related Metabolic Disorders 27,
514–521.
Roberts RE, Kaplan GA, Shema SJ, Strawbridge WJ (2000).
Are the obese at greater risk for depression? American
Journal of Epidemiology 152, 163–170.
Spitzer RL, Williams JBW, Gibbon M, First M (1989).
Structured Clinical Interview for DSM-III-R Patient Edition
(SCID-P). New York : New York State Psychiatric Institute,
Biometrics Research Department.
WHO (1998). Obesity : preventing and managing the global
epidemic. In : Report of a World Health Organization
Consultation on Obesity, Geneva, 3–5 June 1997. Geneva,
Switzerland: World Health Organization, pp. 1–276.
Obesity in MDD 63
    • 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 venlafaxineXR regardless of sex, is somewhat contrary to what several studies have reported[7,9,12,13,22,23]. Of note, several studies have also reported no relationship between BMI and treatment outcome[18,22,24].
    [Show abstract] [Hide abstract] 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.
    Full-text · Article · Dec 2017 · Neuroscience & Biobehavioral Reviews
    • In addition, the reference lists in the selected articles were searched manually to identify additional references.Table 1 presents a summary of studies that evaluated the relationship between body weight and the response to antidepressants. In 2005, Papakostas et al. [10] investigated 369 adult outpatients with major depressive disorder (MDD) and a 17-item Hamilton Depression Rating Scale (HAMD) score of ě16 at baseline. The subjects were administered open-label, fixed-dose 20 mg fluoxetine for 8 weeks, and those showing a partial or no response to fluoxetine treatment were enrolled in a 4-week, double-blind, randomized study comparing high-dose fluoxetine with augmentation of fluoxetine with desipramine or lithium.
    [Show abstract] [Hide abstract] ABSTRACT: Accumulating evidence regarding clinical, neurobiological, genetic, and environmental factors suggests a bidirectional link between obesity and depressive disorders. Although a few studies have investigated the link between obesity/excess body weight and the response to antidepressants in depressive disorders, the effect of weight on treatment response remains poorly understood. In this review, we summarized recent data regarding the relationship between the response to antidepressants and obesity/excess body weight in clinical studies of patients with depressive disorders. Although several studies indicated an association between obesity/excess body weight and poor antidepressant responses, it is difficult to draw definitive conclusions due to the variability of subject composition and methodological differences among studies. Especially, differences in sex, age and menopausal status, depressive symptom subtypes, and antidepressants administered may have caused inconsistencies in the results among studies. The relationship between obesity/excess body weight and antidepressant responses should be investigated further in high-powered studies addressing the differential effects on subject characteristics and treatment. Moreover, future research should focus on the roles of mediating factors, such as inflammatory markers and neurocognitive performance, which may alter the antidepressant treatment outcome in patients with comorbid obesity and depressive disorder.
    Full-text · Article · Jan 2016
    • However, our results pointed out that chronic escitalopram administration had no major effect on HFD-induced metabolic impairments. As previously mentioned , our results did not allow us to definitively exclude the possibility that obesity played an important role in the phenotype of HFD-fed mice, and this is further supported by the fact that depressed obese patients or rodents show little or no therapeutic benefit with different classes of antidepressant drugs (Kloiber et al., 2007), including tricyclics (Uher et al., 2009) and SSRIs (Guo and Lu, 2014) such as fluoxetine (Lin et al., 2014; Papakostas et al., 2005). However, although a higher body mass index and obesity can predict poor response to antidepressant drugs, a recent study challenged this hypothesis for escitalopram (Uher et al., 2009).
    [Show abstract] [Hide abstract] ABSTRACT: Background and purpose: The link between type 2 diabetes mellitus (T2DM) and depression is bidirectional. However, the possibility that metabolic disorders may elicit anxiogenic/depressive-like symptoms or alter the efficacy of antidepressant drugs remains poorly documented. This study explored the influence of T2DM on emotionality and proposed a therapeutic strategy that might be used in depressed diabetic patients. Experimental approach: Mice were fed a high-fat diet (HFD) and subjected to a full comprehensive metabolic and behavioral analysis to establish correlations between metabolic and psychiatric disorders. In vivo intra-hippocampal microdialysis was also applied to propose a mechanism underpinning the phenotype of mice fed a HFD. Finally, we tested whether the chronic administration of the selective serotonin reuptake inhibitor escitalopram or HFD withdrawal could reverse HFD-induced metabolic and behavioural anomalies. Key results: Our data show that increased body weight, hyperglycaemia and impaired glucose tolerance in response to a HFD are correlated with anxiogenic/depressive-like symptoms. Moreover, this phenotype was associated with decreased hippocampal extracellular serotonin levels which may result from increased sensitivity of the dorsal raphe 5-HT1A autoreceptor. Interestingly, we found that the beneficial effect of prolonged administration of escitalopram was completely blunted in HFD-fed mice. On the contrary, HFD withdrawal completely reversed metabolic impairments and positively impacted anxious symptoms, although some behavioural anomalies persisted. Conclusions and implications: Our data provide clear-cut evidence that both pathologies are finely correlated and associated with impaired hippocampal serotonergic neurotransmission. Further experiments are warranted to define the most adequate strategy for the treatment of such comorbidity.
    Article · Oct 2015
    • This is consistent with findings that early trauma is also associated with increased risk of general obesity and elevated IAAT in adult life (Thomas et al., 2008). Both cross-sectional (Papakostas et al., 2005; Simon et al., 2001) and longitudinal (Rotella and Mannucci, 2013) studies have shown increased risk for obesity in depressed patients. What has received considerably less attention, however, is the association between obesity and systemic inflammation in depressed patients.
    [Show abstract] [Hide abstract] ABSTRACT: Many people with major depressive disorder (MDD) show evidence of systemic inflammation, including elevations in inflammatory factors, but the cause is unclear. The purpose of this analysis was to determine if obesity might contribute to the pro-inflammatory state in MDD patients. Blood was obtained from 135 MDD patients and 50 controls. Serum was extracted and assayed for interleukin (IL) -1β, IL-2, IL-5, IL-6, IL-8, IL-10, IL-12p70, IL-17, interferon-γ (IFNγ), tumor necrosis factor α (TNFα), C-reactive protein (CRP), leptin, and adiponectin using single- or multi-plex human immunoassay kits. The primary analysis contrasted IL-6, TNFα, and CRP between MDD and control groups with body mass index (BMI) as a covariate. The other analytes were compared in an exploratory fashion. IL-6 (but not TNFα or CRP) showed significant differences between MDD and controls even after covarying for BMI. Obese controls and obese MDD groups were significantly higher in IL-6 than both lean groups, but the two obese groups did not differ from each other. In the exploratory analyses, the IL-2 level showed robust and significant differences between MDD and controls even after covarying for BMI. Both lean and obese MDD were higher than lean and obese controls. Adiponectin levels were also lower in the MDD sample than controls. Prior findings of higher IL-6, and CRP in MDD patients may be explained, at least in part, based on obesity. High IL-2, however, was associated with depression and not obesity. The results have significant implications for the understanding of pathophysiology and, potentially treatment of MDD.
    Article · Oct 2015
    • Although, the mechanism of how inflammation affects the onset, course or treatment of mood disorders is still controversial, an emerging trend indicates that increased pro-inflammatory cytokine production in obesity is also associated with a poor antidepressant treatment response (Eller et al., 2008; O'Brien et al., 2007; Yoshimura et al., 2009). For example, higher body weight, but not obesity, is associated with a poorer response to antidepressant fluoxetine (Papakostas et al., 2005). Likewise, a higher body mass index (BMI) and obesity predicted poorer response to other antidepressant, nortriptyline, although it had no influence on the response to escitalopram (Uher et al., 2009 ).
    [Show abstract] [Hide abstract] ABSTRACT: Global levels of obesity are reaching epidemic proportions, leading to a dramatic increase in incidence of secondary diseases and the significant economic burden associated with their treatment. These comorbidities include diabetes, cardiovascular disease, and some psychopathologies, which have been linked to a low-grade inflammatory state. Obese individuals exhibit an increase in circulating inflammatory mediators implicated as the underlying cause of these comorbidities. A number of these molecules are also manufactured and released by white adipose tissue (WAT), in direct proportion to tissue mass and are collectively known as adipokines. In the current review we focused on the role of two of the better-studied members of this family namely, leptin and adiponectin, with particular emphasis on their role in neuro-immune interactions, neuroinflammation and subsequent brain diseases. Copyright © 2014. Published by Elsevier Ltd.
    Article · Jan 2015
    • Notwithstanding the accumulating body of evidence linking obesity and mood disorders, there are important methodological limitations that should be considered. A significant number of studies failed to find an association between these two conditions or could not support the idea that this association incurred in differences in phenomenology, trajectory or treatment response (Papakostas et al., 2005; Dave et al., 2011; Chang and Yen, 2012; Dong et al., 2013; Goldstein et al., 2013; Toups et al., 2013). Inconsistencies in the results have also been frequent in studies evaluating metabolic processes and mood disorders.
    [Show abstract] [Hide abstract] ABSTRACT: Obesity and mood disorders are highly prevalent and co-morbid. Epidemiological studies have highlighted the public health relevance of this association, insofar as both conditions and its co-occurrence are associated with a staggering illness-associated burden. Accumulating evidence indicates that obesity and mood disorders are intrinsically linked and share a series of clinical, neurobiological, genetic and environmental factors. The relationship of these conditions has been described as convergent and bidirectional; and some authors have attempted to describe a specific subtype of mood disorders characterized by a higher incidence of obesity and metabolic problems. However, the nature of this association remains poorly understood. There are significant inconsistencies in the studies evaluating metabolic and mood disorders; and, as a result, several questions persist about the validity and the generalizability of the findings. An important limitation in this area of research is the noteworthy phenotypic and pathophysiological heterogeneity of metabolic and mood disorders. Although clinically useful, categorical classifications in both conditions have limited heuristic value and its use hinders a more comprehensive understanding of the association between metabolic and mood disorders. A recent trend in psychiatry is to move toward a domain specific approach, wherein psychopathology constructs are agnostic to DSM-defined diagnostic categories and, instead, there is an effort to categorize domains based on pathogenic substrates, as proposed by the National Institute of Mental Health (NIMH) Research Domain Criteria Project (RDoC). Moreover, the substrates subserving psychopathology seems to be unspecific and extend into other medical illnesses that share in common brain consequences, which includes metabolic disorders. Overall, accumulating evidence indicates that there is a consistent association of multiple abnormalities in neuropsychological constructs, as well as correspondent brain abnormalities, with broad-based metabolic dysfunction, suggesting, therefore, that the existence of a "metabolic-mood syndrome" is possible. Nonetheless, empirical evidence is necessary to support and develop this concept. Future research should focus on dimensional constructs and employ integrative, multidisciplinary and multimodal approaches. Copyright © 2015. Published by Elsevier Ltd.
    Article · Jan 2015
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Omega-3 Fatty Acids for Major Depressive Disorder With High Inflammation: A Personalized Approach
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October 1986 · American Journal of Psychiatry · Impact Factor: 12.30
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    February 1964 · Acta Psychiatrica Scandinavica · Impact Factor: 5.61
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        July 2015 · Psychiatric Quarterly · Impact Factor: 1.26
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