Content uploaded by Christopher P Fagundes
Author content
All content in this area was uploaded by Christopher P Fagundes on Mar 22, 2018
Content may be subject to copyright.
Depression, Daily Stressors, and Inflammatory Responses to
High-Fat Meals: When Stress Overrides Healthier Food Choices
Janice K. Kiecolt-Glaser, PhD1,2, Christopher P. Fagundes, PhD3,4, Rebecca Andridge,
PhD5, Juan Peng, MS6, William B. Malarkey, MD1,7, Diane Habash, PhD8, and Martha A.
Belury, PhD1,9
1Institute for Behavioral Medicine Research, The Ohio State University College of Medicine,
Columbus, OH, USA
2Department of Psychiatry and Behavioral Health, The Ohio State University College of Medicine,
Columbus, OH, USA
3Department of Psychology, Rice University, Houston, TX, USA
4Department of Symptoms Research, MD Anderson Cancer Center, Houston, TX, USA
5Division of Biostatistics, College of Public Health, The Ohio State University, Columbus, OH,
USA
6Center for Biostatistics, The Ohio State University, Columbus, OH, USA
7Department of Medicine, The Ohio State University Medical Center, Columbus, OH, USA
8Health and Rehabilitation Sciences, The Ohio State University Medical Center, Columbus, OH,
USA
9Department of Human Sciences, College of Education and Human Ecology, The Ohio State
University, Columbus, OH, USA
Abstract
Depression, stress, and diet can all alter inflammation. This double-blind, randomized crossover
study addressed the impact of daily stressors and a history of major depressive disorder (MDD) on
inflammatory responses to high-fat meals. During two separate 9.5 hour admissions, 58 healthy
women (38 breast cancer survivors and 20 demographically-similar controls), mean age 53.1
years, received either a high saturated fat meal or a high oleic sunflower oil meal. The Daily
Inventory of Stressful Events assessed prior day stressors and the Structured Clinical Interview for
DSM-IV evaluated MDD. As expected, for a woman with no prior day stressors, C-reactive
protein (CRP), serum amyloid A (SAA), intercellular adhesion molecule-1 (sICAM-1), and
vascular cell adhesion molecule-1 (sVCAM-1) were higher following the saturated fat meal than
Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research,
subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms
Correspondence: Janice K. Kiecolt-Glaser, PhD Institute for Behavioral Medicine Research, The Ohio State University College of
Medicine, 460 Medical Center Drive, Columbus, OH 43210 (Janice.Kiecolt-Glaser@osumc.edu), 614-293-3499.
Conflicts of Interest
NIH has funded work by Drs. Kiecolt-Glaser, Malarkey, Fagundes, and Belury. Dr. Andridge and Ms. Peng declare no conflict of
interest.
HHS Public Access
Author manuscript
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Published in final edited form as:
Mol Psychiatry
. 2017 March ; 22(3): 476–482. doi:10.1038/mp.2016.149.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
the high oleic sunflower oil meal after controlling for pre-meal measures, age, trunk fat, and
physical activity. But if a woman had prior day stressors, these meal-related differences
disappeared – because the stressors heightened CRP, SAA, sICAM-1, and sVCAM-1 responses to
the sunflower oil meal, making it look more like the responses to the saturated fat meal. In
addition, women with an MDD history had higher post-meal blood pressure responses than those
without a similar history. These data show how recent stressors and an MDD history can
reverberate through metabolic alterations, promoting inflammatory and atherogenic responses.
Introduction
Adherence to a Mediterranean-type diet can reduce the risk for depression, cardiovascular
disease, type 2 diabetes, and total mortality (1–4). Reduced inflammation may be the
cornerstone for the Mediterranean diet’s benefits (5–8).
The central fat source in the Mediterranean diet, olive oil, appears to be a key anti-
inflammatory dietary component (8, 9). Indeed, a meta-analysis concluded that olive oil
interventions lowered CRP and interleukin 6 (IL)-6 compared to control conditions (9). The
major dietary fatty acids in the North American diet are palmitic acid, a saturated fatty acid
found in meat and dairy products, and the monounsaturated oleic acid, the main fatty acid in
olive oil, and many vegetable oils (10).
Saturated fatty acids trigger proinflammatory signaling pathways (11). For example,
palmitic acid activated toll-like receptor 4 (TLR4), leading to nuclear transcription factor κB
(NF-κB) signaling and increased gene expression of IL-6, IL-8, vascular cell adhesion
molecule-1 (VCAM-1), and intercellular adhesion molecule-1 (ICAM-1) in contrast, the
monounsaturated palmioleate did not have inflammatory sequelae (11). A meal made with
butter, a rich source of saturated fatty acids, activated NF-κB in peripheral blood
mononuclear cells and also increased sICAM-1 concentrations, but a meal with olive oil, a
rich source of oleic acid, did not (12). Palmitate-stimulated monocytes also fuel ICAM-1
expression in endothelial cells via an IL-1 signaling pathway (13).
High saturated fat meals raise adhesion molecule concentrations while monounsaturated fat
meals lower concentrations (14). For example, high palmitate milkshakes boosted sICAM-1
levels while olive oil milkshakes decreased sICAM-1 (14). Similarly, a high-palmitic fatty
acid oil breakfast heightened post-meal sICAM-1 and sVCAM-1, but a refined olive oil
breakfast lowered their concentrations (15). Postprandial sICAM-1 levels were amplified by
a 12-week high saturated fat diet and reduced by a monounsaturated fat diet (16).
These meal-related differences are important because adhesion molecules play a central role
in the development of atherosclerosis and diabetes (17–23). Plasma sICAM-1 reflects a
more generalized inflammatory process, while sVCAM-1 appears to be a better indicator of
plaque burden (19). In healthy people sICAM-1 serves as a more reliable prognostic
indicator of cardiovascular disease than sVCAM-1, but sVCAM-1 better predicts
cardiovascular events among patients with atherosclerotic disease than sICAM-1 (17–19).
Furthermore, adhesion molecules and inflammation are associated with an increased risk of
Kiecolt-Glaser et al. Page 2
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
hypertension (24, 25), and monounsaturated fat interventions have reduced blood pressure
(26, 27).
Elevated sICAM-1 levels also predict type II diabetes (20–23). For example, data from the
Nurses’ Health Study showed that sICAM-1 independently predicted incident diabetes (21).
In a large population-based prospective, sICAM-1 levels were higher among those
participants who developed diabetes than in those who did not (20).
In addition to these dietary fat influences, depression and stressors can also boost NF-κB
signaling, thus augmenting inflammation and increasing adhesion molecule concentrations
(1, 28–30). For example, sICAM-1 levels were higher among all 18 physicians following an
academic oral presentation compared to their own values two hours earlier, as well as their
data from parallel assessments obtained on a control day (31). Comparisons of 22 patients
who developed posttraumatic stress disorder (PTSD) following a myocardial infarction (MI)
and 22 who did not develop post-MI PTSD showed that those with PTSD had higher
concentrations of sICAM-1 and sVCAM-1 at rest, as well as following a trauma-specific
interview than their PTSD-free counterparts (32). Among patients who had experienced a
recent acute coronary syndrome, sICAM-1 levels were higher among those with major
depression than those who did not meet criteria (33). Young adults with major depression
had higher levels of sICAM-1 than nondepressed controls (34), and heightened sICAM-1
concentrations have also been found in healthy adults with elevated depressive symptoms
(35–38).
People with a history of depression experience more major and minor stressors than those
without a similar history, and past depression can also boost emotional reactivity to stressors
(39, 40). Thus a mood disorder history could act synergistically with stress through multiple
pathways.
Indeed, other data from this same sample of healthy breast cancer survivors and controls
demonstrated that women with a history of depression who had also experienced more prior
day stressors had a higher peak postprandial triglyceride response than other participants
(41). Similarly, in our subsequent study with married couples that included the same high-fat
meals, men and women who had a mood disorder history and who also displayed more
hostile behaviors during the laboratory marital conflict discussions had lower post-meal
resting energy expenditure, higher insulin, and higher peak triglyceride responses than other
participants (42).
Accordingly, this secondary analysis assessed the impact of prior day stressors and past
depression on metabolic responses to two different high-fat meals (41). We expected that our
high saturated fat meal would increase inflammatory markers and adhesion molecules, but
not our high oleic sunflower oil meal (14–16). We also hypothesized that both prior day
stressors and an MDD history would be associated with higher post-meal concentrations of
inflammatory markers and adhesion molecules.
Kiecolt-Glaser et al. Page 3
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
METHODS AND MATERIALS
Design and Overview
This double-blind, randomized crossover study assessed metabolic responses following
high-fat meals. Women received one high saturated fat meal and one high oleic sunflower oil
meal during two separate 9.5 hour Clinical Research Center (CRC) visits spaced 1–4 weeks
apart. The Ohio State institutional review board approved this study, and each participant
provided informed consent.
After fasting for 12 hours, a catheter was inserted in the arm on admission. Women had 20
minutes to eat the meal. Blood samples were obtained before and 2, 4, and 7 hours after the
meal. Body composition was assessed by dual x-ray absorptiometry (DXA) (43).
Participants
The parent study was designed to assess whether a high-fat diet in combination with a
depression history increased fatigue in post-treatment cancer survivors and benign controls,
and thus the 58 healthy women included 38 breast cancer survivors and 20 benign controls
(women who had an initial abnormal mammogram) were recruited from a large
observational study (41). Exclusions included a history of any other prior cancer, chronic
obstructive pulmonary disease, symptomatic ischemic heart disease, alcohol/drug abuse, and
immune-related conditions such as diabetes, autoimmune disease, and major inflammatory
diseases. Medication exclusions included blood lipid medications, angiotensin type I
receptor blockers, and medications with major immunological or endocrinological
consequences, e.g., steroids. We invited 91 women from the large observational study who
met these criteria to participate; of those, 3 had exclusionary health problems not previously
identified, 18 declined to participate, and 14 did not respond to our recruitment letter.
Demographic and laboratory data did not differ between groups with the exception of higher
sICAM-1 in survivors compared to controls (Table 1). Survivors averaged 27.03 months
(SD=17.45) since diagnosis and 19.87 months (SD=6.47) since treatment completion. Only
one participant failed to return for her second visit.
Standardized Pre-Study Meals
Participants were instructed to avoid alcohol use the day before study visits, and any
strenuous physical activity two days previously (44). They were also asked not to take
aspirin, vitamins, antioxidants, or other dietary supplements for the 7 days before each
admission.
On the day before each of the two study visits participants received three standardized meals
from the CRC’s metabolic kitchen to reduce the variability associated with recent intake.
Equations from the Dietary Reference Intakes calculated the total kcal requirements for each
participant based on age, height, weight, and physical activity (45). Macronutrient targets (as
percent of total energy) for these meals were 54.9 ± 2.68% carbohydrate, 27.6 ±2.13% fat,
and 17.6 ± 0.95% protein. The fat content was 9.10 ± 1.20 % saturated fats, 9.43 ± 1.55%
monounsaturated fats, and 7.26 ± 1.25% polyunsaturated fats. Participants ate their last meal
Kiecolt-Glaser et al. Page 4
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
no later than 7:30 pm the night before admission; the dinner was light and low in fat (44).
Compliance was good: women consumed 91.83 ± 8.41% of these meals.
Research Meals
Both research meals included eggs, turkey sausage, biscuits, and gravy for a total of 930
kcals, with 60 grams fat, 59 grams carbohydrate, and 36 grams protein (percent of total kcals
= 60, 25, 15, respectively). However, the saturated:unsaturated fatty acid ratio varied
between the meals; the high saturated fat meal contained 16.84 g palmitic and 13.5 g oleic
(ratio=1.93), compared to 8.64 g palmitic and 31.21 g oleic for the high oleic sunflower oil
meal (ratio=0.67).
Assays
Serum CRP, serum amyloid A (SAA), sICAM-1 and sVCAM-1 were measured in duplicate
with the Vascular Injury Panel 2 Multispot Kit on an MSD Imager 2400 (both Meso Scale
Discovery, Rockville, MD), following kit instructions. Both samples for each subject were
analyzed within the same plate, and all plates were from the same kit/lot. The intra-assay
coefficient of variation (CV) and inter-assay CV for each analyte were: CRP 6.28% and
7.36%, SAA 4.90% and 3.09%, sICAM-1 4.19% and 6.92%, and sVCAM-1 2.14% and
5.16%.
Blood Pressure
Blood pressure was assessed using the Critikon Dinamap 1846 SX (GE, Tampa, FL) every 2
minutes for 20 minutes at baseline, and then every 2 minutes for 10 minutes immediately
following the meal. Subsequently, 2 readings were taken 2 minutes apart every hour for the
remainder of the visit.
Interview Data
The mood disorder modules of the Structured Clinical Interview for DSM-IV (SCID)
provided data on lifetime prevalence of major depressive disorder (MDD) (46). SCID data
showed that 29% (n=17) had met MDD criteria. The average time since diagnosis was 8.32
years (SD=10.94).
The Daily Inventory of Stressful Events (DISE) assessed the number of daily stressors
within the last 24 hours (47). The transcribed interview responses were rated in a consensus
meeting using the DISE’s extensive electronic “dictionary” which specifies codable events
(47). In our sample 31 women reported at least one recent stressor at one visit, 21 at both
visits, and 6 women reported no stressors.
Questionnaires
Following CRC admission participants completed several questionnaires. The Center for
Epidemiological Studies Depression Scale (CES-D) assessed depressive symptomatology in
the last week (48). The Community Healthy Activities Model Program for Seniors
questionnaire (CHAMPS) assessed the weekly frequency and duration of various physical
activities (49, 50). These measures have well-established reliability and validity (48–50).
Kiecolt-Glaser et al. Page 5
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Statistical methods
The primary analyses used linear mixed models, since these models allow explicit modeling
of the within-subject correlations due to repeated study visits and repeated measurements
during each visit.
Demographics and other pre-meal characteristics were compared across groups (cancer,
control) using two-sample t-tests and chi-square tests for data collected at only one visit
(e.g., age) and linear mixed models with a random subject effect for data collected at both
visits (e.g., body mass index). Four primary outcome measures (CRP, SAA, sICAM-1, and
sVCAM-1) were right-skewed and were natural-log transformed to better approximate
normality of residuals. Linear mixed effects models were used to model post-meal outcome
values, with the premeal (fasting) outcome measurement included as a covariate. All models
included the three-way interaction of group (cancer, control) by meal type by time point and
all lower-order terms to properly account for the design of the parent study. However, there
were no significant effects of group (p > 0.2 for all tests) and thus reported results are
averaged over group.
Of primary interest was the impact of prior day stressors and MDD history on post-meal
responses. Initial models contained interactions of these predictors with time post-meal
(categorical) and with meal type; nonsignificant interactions were removed for final models.
All models further controlled on additional covariates to guard against confounding,
including age, trunk fat, physical activity (caloric expenditure per week), and study visit
(first vs. second). Additional models also controlled for menopausal status, but results were
unchanged, thus final models did not include this factor. To capture the within-subject
correlations within and across visits, all models included a pair of correlated subject-specific
random meal effects, which allowed the magnitude of within-subject correlation for the two
meal types to differ. The Kenward-Roger adjustment to the degrees of freedom was used to
control type I error (51). All analyses were conducted in SAS version 9.3 (Cary, North
Carolina).
Results
There were no associations between fasting levels of CRP, SAA, sICAM-1, or sVCAM-1
and either prior day stressors (p > 0.2 for all tests) or MDD history (p > 0.15 for all tests),
after controlling for visit, age, trunk fat, and physical activity. Trunk fat was significantly
positively associated with fasting levels of CRP (p<0.0001), SAA (p = 0.004), and
sVCAM-1 (p = 0.05), and marginally associated with fasting sICAM-1 (p = 0.09). Each 1 kg
increase in trunk fat was associated with a 12.7% increase in the geometric mean of CRP, a
5.0% increase in the geometric mean of SAA, a 1.0% increase in the geometric mean of
sICAM-1, and a 1.2% increase in the geometric mean of sVCAM-1. Physical activity was
marginally negatively associated with fasting SAA (p = 0.09), with a 100 kcal increase in
caloric expenditure associated with a 1.3% decrease in the geometric mean of SAA. Both
fasting sICAM-1 and fasting CRP were elevated at the first study visit compared to the
second, with a 9.5% higher geometric mean (p<0.0001) for sICAM-1 and a 21% higher
geometric mean for CRP (p = 0.06). Age and cancer status were not significantly associated
with fasting levels of any outcome (p > 0.1 for all tests).
Kiecolt-Glaser et al. Page 6
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
When modeling the postprandial responses, controlling for pre-meal levels, there were
significant two-way interactions of prior day stressors by meal type in the models for CRP
(p = 0.04), sICAM-1 (p = 0.02), and sVCAM-1 (p = 0.05), and a borderline interaction for
SAA (p = 0.09). Thus the effect of stressors on post-meal inflammation depended on the
meal type, and differences between the meals depended on a woman’s number of prior day
stressors. A larger number of stressors was associated with higher levels of postprandial
CRP, SAA, sICAM-1, and sVCAM-1 after the high oleic sunflower oil meal but not after the
high saturated fat meal (Figure 1, Table 2). After the high oleic sunflower oil meal, each
additional prior day stressor was associated with a 2.9% increase in the geometric mean of
CRP, a 2.3% increase in the geometric mean of SAA, a 1.7% increase in the geometric mean
of sICAM-1, and a 2.1% increase in the geometric mean of sVCAM-1. In contrast, after the
high saturated fat meal there was no significant effect of stressors (Table 2). As shown in
Figure 1, for a woman with no prior day stressors, post-meal inflammation was higher
following the high saturated fat meal than the high oleic sunflower oil meal. But having prior
day stressors shifted the response to the high oleic sunflower oil meal such that it looked like
the response to the high saturated fat meal. There were no significant effects of MDD history
on these outcomes (p > 0.07 for all tests).
There were no associations between pre-meal levels of SBP or DBP, and prior day stressors
(p > 0.15 for all tests) or MDD history (p > 0.15 for all tests), after controlling for visit, age,
trunk fat, and physical activity. Subjects with MDD history had marginally higher SBP (p =
0.06) and DBP (p = 0.10).
There were no significant effects of prior day stressors or meal type on the blood pressure
outcomes (p > 0.25 for all tests). There was a significant main effect of MDD history on
postprandial DBP (p = 0.05), even after controlling for pre-meal levels. In the post-meal
period, DBP was higher for subjects with a history of MDD compared to those without
(Figure 2). There was also a significant interaction between MDD history and time on
postprandial SBP (p = 0.02) despite controlling for pre-meal levels. Subjects with a history
of MDD had elevated SBP at most time points, particularly at around 3 hours and 6–7 hours
post-meal (Figure 2).
Discussion
This study is the first to demonstrate that stressors can heighten inflammatory responses to
high oleic sunflower oil meals. Importantly, the stress- and depression-related metabolic
responses to the two meals revealed adverse effects that were not evident when fasting. As
expected, CRP, sICAM-1, and sVCAM-1 were higher following the saturated fat meal than
the high oleic sunflower oil meal. However, a higher number of prior day stressors was
associated with higher postprandial CRP, SAA, sICAM-1, and sVCAM-1 after the high oleic
sunflower oil meal, but not after the high saturated fat meal. Putting it another way, for a
woman with no prior day stressors, outcomes were higher after the saturated fat meal than
after the sunflower oil meal. But if a woman had prior day stressors, the differences
disappeared – because the stressors heightened responses to the sunflower oil meal, making
it look more like the responses to the saturated fat meal.
Kiecolt-Glaser et al. Page 7
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
The endothelial activation that was reflected by the heightened post-meal sICAM-1 and
sVCAM-1 concentrations may also mirror a more chronic inflammatory responsiveness
associated with atherosclerosis of brain arteries, a process that could itself promote
depression (33, 52). Among adults with moderate to severe traumatic brain injury, higher
levels of sICAM-1, sVCAM-1, and soluble Fas in cerebrospinal fluid had a 3.92-fold
increase in the odds for developing posttraumatic depression at 6 months (53); indeed,
having any one of these markers above the 75th percentile had a predictive value of 85.7%
for posttraumatic depression at six months (53). Similarly, among patients treated with
interferon-α for melanoma, sICAM-1 levels were correlated with the development of
depressive symptoms during treatment (54). Postmortem studies of depressed older adults
revealed elevated ICAM-1 expression in the dorsolateral prefrontal cortex compared to
nondepressed controls (55, 56). ICAM-1 is thought to play a key role in blood-brain barrier
(BBB) permeability, and enhanced levels of depressive symptoms may reflect greater BBB
porousness (54). The fact that a Mediterranean diet offers some protection against the
development of both depressive symptoms and depressive disorders (4, 57, 58) may be
related to its anti-inflammatory actions (8, 9).
Women with an MDD history had higher post-meal blood pressure responses than those
without a similar history, with no differences evident in the fasted state; MDD history was
not related to the inflammatory responses. A meta-analysis of prospective cohort studies
concluded that depression increases the risk of hypertension, an important risk factor for
cardiovascular disease (59). Other research from this sample has demonstrated that women
with an MDD history who had also experienced more prior day stressors had a higher peak
postprandial triglyceride response than other participants (41). Larger post-meal triglyceride
responses are reliably associated with enhanced cardiovascular risk and the progression of
atherosclerosis (60–62). Depression has well-established effects on cardiovascular morbidity
and mortality, and these two different meal-related changes highlight previously
unrecognized depression-sensitive mechanistic pathways (63, 64).
Strengths of our study included control of both the composition and energy content of each
woman’s diet on the day prior to admission as well as during admission. The only difference
between the two challenge meals was the fat source. Both meals included 930 kcal and 60 g
fat, values that are quite comparable to common fast food choices. For example, a Burger
King Double Whopper with cheese has 990 kcal and 64 g fat, while a Big Mac cheeseburger
and medium French fries contain 930 kcals and 58 g fat.
It is unclear why, with the addition of a stressor to the high saturated fat meal, there were no
further increase in levels of CRP, sICAM-1 and sVCAM-1, while stress-related changes
were observed in response to the high oleic sunflower oil meal. Speculatively, inflammatory
markers may have already reached their ceiling level in response to the high saturated fat
condition, a reasonable possibility because our participants did not have overt signs of
cardiac disease or other diseases associated with chronically elevated inflammation.
Our two meals, regardless of their fat source, were high in energy and fat, and they included
refined flour and little fiber. We do not know whether a relatively healthier meal (e.g.,
energy balanced, lower in total fat, higher in polyunsaturated oils and containing more
Kiecolt-Glaser et al. Page 8
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
protein and fiber with fewer simple carbohydrates) would attenuate the adverse postprandial
inflammatory and metabolic changes, one limitation. Nonetheless, our study meals reflected
typical everyday dietary choices because they were designed to mimic common fast food
meals.
The inclusion of healthy breast cancer survivors could have affected our results, another
limitation. However, we found no reliable post-meal differences between cancer survivors
and controls in these analyses, or in other metabolic data from this study (41). We selected
our healthy survivors using the same inclusion/exclusion criteria as our controls; had we
used a larger and more representative sample of cancer survivors we might have seen group
differences related to cancer treatment. Additionally, depressive symptoms did not differ
between cancer survivors and controls, and the relatively low levels of depressive symptoms
limited our ability to see depression-related effects.
These data are important because heightened inflammation characterizes a number of
disorders and systemic diseases including cardiovascular disease, diabetes, metabolic
syndrome, rheumatoid arthritis, asthma, multiple sclerosis, chronic pain, and psoriasis; each
of these also features an elevated risk for depression (65, 66). Our data show how recent
stressors and a depression history can reverberate through these metabolic alterations to fuel
inflammation, which can, in turn, promote depression.
Acknowledgments
The study was supported in part by NIH grants CA154054, CA172296, UL1TRR025755, and CA016058. The
sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of
the data; and preparation, review, or approval of the manuscript. We are grateful to Michael Di Gregorio, M.A., for
his role as a key organizer and experimenter, and to Bryon Laskowski for laboratory analyses.
References
1. Kiecolt-Glaser JK, Derry HM, Fagundes CP. Inflammation: Depression fans the flames and feasts
on the heat. Am J Psychiatry. 2015; 172(11):1075–91. [PubMed: 26357876]
2. Salas-Salvado J, Garcia-Arellano A, Estruch R, Marquez-Sandoval F, Corella D, Fiol M, et al.
Components of the mediterranean-type food pattern and serum inflammatory markers among
patients at high risk for cardiovascular disease. Eur J Clin Nutr. 2008; 62(5):651–9. [PubMed:
17440519]
3. Martinez-Gonzalez MA, Dominguez LJ, Delgado-Rodriguez M. Olive oil consumption and risk of
CHD and/or stroke: A meta-analysis of case-control, cohort and intervention studies. Br J Nutr.
2014; 112(2):248–59. [PubMed: 24775425]
4. Psaltopoulou T, Sergentanis TN, Panagiotakos DB, Sergentanis IN, Kosti R, Scarmeas N.
Mediterranean diet, stroke, cognitive impairment, and depression: A meta-analysis. Ann Neurol.
2013; 74(4):580–91. [PubMed: 23720230]
5. Esposito K, Marfella R, Ciotola M, Di Palo C, Giugliano F, Giugliano G, et al. Effect of a
Mediterranean-style diet on endothelial dysfunction and markers of vascular inflammation in the
metabolic syndrome: A randomized trial. JAMA. 2004; 292(12):1440–6. [PubMed: 15383514]
6. Dai J, Miller AH, Bremner JD, Goldberg J, Jones L, Shallenberger L, et al. Adherence to the
Mediterranean diet is inversely associated with circulating interleukin-6 among middle-aged men: A
twin study. Circulation. 2008; 117(2):169–75. [PubMed: 18086924]
7. Milaneschi Y, Bandinelli S, Penninx BW, Vogelzangs N, Corsi AM, Lauretani F, et al. Depressive
symptoms and inflammation increase in a prospective study of older adults: A protective effect of a
healthy (Mediterranean-style) diet. Mol Psychiatry. 2011; 16(6):589–90. [PubMed: 21042319]
Kiecolt-Glaser et al. Page 9
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
8. Schwingshackl L, Hoffmann G. Mediterranean dietary pattern, inflammation and endothelial
function: A systematic review and meta-analysis of intervention trials. Nutrition Metabolism and
Cardiovascular Diseases. 2014; 24(9):929–39.
9. Schwingshackl L, Christoph M, Hoffmann G. Effects of olive oil on markers of inflammation and
endothelial function-a systematic review and meta-analysis. Nutrients. 2015; 7(9):7651–75.
[PubMed: 26378571]
10. Borsheim E, Kien CL, Pearl WM. Differential effects of dietary intake of palmitic acid and oleic
acid on oxygen consumption during and after exercise. Metabolism. 2006; 55(9):1215–21.
[PubMed: 16919541]
11. Pillon NJ, Azizi PM, Li YE, Liu J, Wang C, Chan KL, et al. Palmitate-induced inflammatory
pathways in human adipose microvascular endothelial cells promote monocyte adhesion and
impair insulin transcytosis. Am J Physiol Endocrinol Metab. 2015; 309(1):E35–44. [PubMed:
25944880]
12. Bellido C, Lopez-Miranda J, Blanco-Colio LM, Perez-Martinez P, Muriana FJ, Martin-Ventura JL,
et al. Butter and walnuts, but not olive oil, elicit postprandial activation of nuclear transcription
factor kappab in peripheral blood mononuclear cells from healthy men. Am J Clin Nutr. 2004;
80(6):1487–91. [PubMed: 15585759]
13. Shikama Y, Aki N, Hata A, Nishimura M, Oyadomari S, Funaki M. Palmitate-stimulated
monocytes induce adhesion molecule expression in endothelial cells via IL-1 signaling pathway. J
Cell Physiol. 2015; 230(3):732–42. [PubMed: 25201247]
14. Peairs AD, Rankin JW, Lee YW. Effects of acute ingestion of different fats on oxidative stress and
inflammation in overweight and obese adults. Nutr J. 2011; 10:122. [PubMed: 22059644]
15. Pacheco YM, Lopez S, Bermudez B, Abia R, Villar J, Muriana FJ. A meal rich in oleic acid
beneficially modulates postprandial sICAM-1 and sVCAM-1 in normotensive and hypertensive
hypertriglyceridemic subjects. J Nutr Biochem. 2008; 19(3):200–5. [PubMed: 17651961]
16. Perez-Martinez P, Moreno-Conde M, Cruz-Teno C, Ruano J, Fuentes F, Delgado-Lista J, et al.
Dietary fat differentially influences regulatory endothelial function during the postprandial state in
patients with metabolic syndrome: From the LIPGENE study. Atherosclerosis. 2010; 209(2):533–
8. [PubMed: 19818442]
17. Silvestro A, Brevetti G, Schiano V, Scopacasa F, Chiariello M. Adhesion molecules and
cardiovascular risk in peripheral arterial disease - soluble vascular cell adhesion molecule-i
improves risk stratification. Thromb Haemost. 2005; 93(3):559–63. [PubMed: 15735810]
18. Ridker PM, Hennekens CH, Roitman-Johnson B, Stampfer MJ, Allen J. Plasma concentration of
soluble intercellular adhesion molecule 1 and risks of future myocardial infarction in apparently
healthy men. Lancet. 1998; 351(9096):88–92. [PubMed: 9439492]
19. Blankenberg S, Barbaux S, Tiret L. Adhesion molecules and atherosclerosis. Atherosclerosis.
2003; 170(2):191–203. [PubMed: 14612198]
20. Hoogeveen RC, Ballantyne CM, Bang H, Heiss G, Duncan BB, Folsom AR, et al. Circulating
oxidised low-density lipoprotein and intercellular adhesion molecule-1 and risk of type 2 diabetes
mellitus: The Atherosclerosis Risk in Communities study. Diabetologia. 2007; 50(1):36–42.
[PubMed: 17136392]
21. Meigs JB, Hu FB, Rifai N, Manson JE. Biomarkers of endothelial dysfunction and risk of type 2
diabetes mellitus. JAMA. 2004; 291(16):1978–86. [PubMed: 15113816]
22. Song Y, Manson JE, Tinker L, Rifai N, Cook NR, Hu FB, et al. Circulating levels of endothelial
adhesion molecules and risk of diabetes in an ethnically diverse cohort of women. Diabetes. 2007;
56(7):1898–904. [PubMed: 17389327]
23. Thorand B, Baumert J, Chambless L, Meisinger C, Kolb H, Doring A, et al. Elevated markers of
endothelial dysfunction predict type 2 diabetes mellitus in middle-aged men and women from the
general population. Arterioscler Thromb Vasc Biol. 2006; 26(2):398–405. [PubMed: 16322530]
24. Chae CU, Lee RT, Rifai N, Ridker PM. Blood pressure and inflammation in apparently healthy
men. Hypertension. 2001; 38(3):399–403. [PubMed: 11566912]
25. Rohde LE, Hennekens CH, Ridker PM. Cross-sectional study of soluble intercellular adhesion
molecule-1 and cardiovascular risk factors in apparently healthy men. Arterioscler Thromb Vasc
Biol. 1999; 19(7):1595–9. [PubMed: 10397675]
Kiecolt-Glaser et al. Page 10
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
26. Schwingshackl L, Hoffmann G. Monounsaturated fatty acids and risk of cardiovascular disease:
Synopsis of the evidence available from systematic reviews and meta-analyses. Nutrients. 2012;
4(12):1989–2007. [PubMed: 23363996]
27. Hohmann CD, Cramer H, Michalsen A, Kessler C, Steckhan N, Choi K, et al. Effects of high
phenolic olive oil on cardiovascular risk factors: A systematic review and meta-analysis.
Phytomedicine. 2015; 22(6):631–40. [PubMed: 26055128]
28. Kiecolt-Glaser JK. Stress, food, and inflammation: Psychoneuroimmunology and nutrition at the
cutting edge. Psychosom Med. 2010; 72:365–9. [PubMed: 20410248]
29. Pace TWW, Mletzko TC, Alagbe O, Musselman DL, Nemeroff CB, Miller AH, et al. Increased
stress-induced inflammatory responses in male patients with major depression and increased early
life stress. Am J Psychiatry. 2006; 163(9):1630–2. [PubMed: 16946190]
30. Bierhaus A, Wolf J, Andrassy M, Rohleder N, Humpert PM, Petrov D, et al. A mechanism for
converting psychosocial stress into mononuclear cell activation. Proc Natl Acad Sci U S A. 2003;
100(4):1920–5. [PubMed: 12578963]
31. Heinz A, Hermann D, Smolka M, Rieks M, Gräf K-J, Pöhlau D, et al. Effects of acute
psychological stress on adhesion molecules, interleukins and sex hormones: Implications for
coronary heart disease. Psychopharmacology (Berl). 2003; 165(2):111–7. [PubMed: 12417965]
32. von Kanel R, Abbas CC, Begre S, Saner H, Gander ML, Schmid JP. Posttraumatic stress disorder
and soluble cellular adhesion molecules at rest and in response to a trauma-specific interview in
patients after myocardial infarction. Psychiatry Res. 2010; 179(3):312–7. [PubMed: 20488551]
33. Lesperance F, Frasure-Smith N, Theroux P, Irwin M. The association between major depression
and levels of soluble intercellular adhesion molecule 1, interleukin-6, and C-reactive protein in
patients with recent acute coronary syndromes. Am J Psychiatry. 2004; 161:271–7. [PubMed:
14754776]
34. Rajagopalan S, Brook R, Rubenfire M, Pitt E, Young E, Pitt B. Abnormal brachial artery flow-
mediated vasodilation in young adults with major depression. Am J Cardiol. 2001; 88(2):196–8.
A7. [PubMed: 11448425]
35. Empana JP, Sykes DH, Luc G, Juhan-Vague I, Arveiler D, Ferrieres J, et al. Contributions of
depressive mood and circulating inflammatory markers to coronary heart disease in healthy
European men - the Prospective Epidemiological Study of Myocardial Infarction (PRIME).
Circulation. 2005; 111(18):2299–305. [PubMed: 15867179]
36. Tchalla AE, Wellenius GA, Sorond FA, Travison TG, Dantoine T, Lipsitz LA. Elevated circulating
vascular cell adhesion molecule-1 (sVCAM-1) is associated with concurrent depressive symptoms
and cerebral white matter hyperintensities in older adults. BMC Geriatrics. 2015:15. [PubMed:
25888051]
37. Dimopoulos N, Piperi C, Salonicioti A, Mitsonis C, Liappas L, Lea RW, et al. Elevation of plasma
concentration of adhesion molecules in late-life depression. Int J Geriatr Psychiatry. 2006; 21(10):
965–71. [PubMed: 16927406]
38. van Sloten TT, Schram MT, Adriaanse MC, Dekker JM, Nijpels G, Teerlink T, et al. Endothelial
dysfunction is associated with a greater depressive symptom score in a general elderly population:
The Hoorn study. Psychol Med. 2014; 44(7):1403–16. [PubMed: 23942242]
39. Hammen C. Generation of stress in the course of unipolar depression. J Abnorm Psychol. 1991;
100:555–61. [PubMed: 1757669]
40. Husky M, Mazure C, Maciejewski P, Swendsen J. Past depression and gender interact to influence
emotional reactivity to daily life stress. Cognit Ther Res. 2009; 33(3):264–71.
41. Kiecolt-Glaser JK, Habash DL, Fagundes CP, Andridge R, Peng J, Malarkey WB, et al. Daily
stressors, past depression, and metabolic responses to high-fat meals: A novel path to obesity. Biol
Psychiatry. 2015; 77(7):653–60. [PubMed: 25034950]
42. Kiecolt-Glaser JK, Jaremka L, Andridge R, Peng J, Habash D, Fagundes CP, et al. Marital discord,
past depression, and metabolic responses to high-fat meals: Interpersonal pathways to obesity.
Psychoneuroendocrinology. 2015; 52:239–50. [PubMed: 25506778]
43. Kennedy AP, Shea JL, Sun G. Comparison of the classification of obesity by BMI vs. Dual-energy
x-ray absorptiometry in the Newfoundland population. Obesity. 2009; 17(11):2094–9. [PubMed:
19360011]
Kiecolt-Glaser et al. Page 11
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
44. Lairon D, Lopez-Miranda J, Williams C. Methodology for studying postprandial lipid metabolism.
Eur J Clin Nutr. 2007; 61(10):1145–61. [PubMed: 17457341]
45. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and
amino acids. Washington, DC: National Academy Press; 2002.
46. First, M., Gibbon, M., Spitzer, R., Williams, J. User’s guide for the Structured Clinical Interview
for DSM-IV Axis I disorders—research version. New York, NY: Biometrics Research Department,
New York State Psychiatric Institute; 1996.
47. Almeida DM, Kessler RC. Everyday stressors and gender differences in daily distress. J Pers Soc
Psychol. 1998; 75:670–80. [PubMed: 9781406]
48. Radloff LS. The CES-D scale: A self-report depression scale for research in the general population.
Appl Psych Meas. 1977; 1:385–401.
49. Stewart AL, Mills KM, King AC, Haskell WL, Gillis D, Ritter PL. Champs physical activity
questionnaire for older adults: Outcomes for interventions. Med Sci Sports Exerc. 2001; 33:1126–
41. [PubMed: 11445760]
50. Harada ND, Chiu V, Stewart AL. An evaluation of three self-report physical activity instruments
for older adults. Med Sci Sports Exerc. 2001; 33:962–70. [PubMed: 11404662]
51. Kenward MG, Roger JH. Small sample inference for fixed effects from restricted maximum
likelihood. Biometrics. 1997; 53(3):983–97. [PubMed: 9333350]
52. Alexopoulos GS, Morimoto SS. The inflammation hypothesis in geriatric depression. Int J Geriatr
Psychiatry. 2011; 26(11):1109–18. [PubMed: 21370276]
53. Juengst SB, Kumar RG, Failla MD, Goyal A, Wagner AK. Acute inflammatory biomarker profiles
predict depression risk following moderate to severe traumatic brain injury. J Head Trauma
Rehabil. 2015; 30(3):207–18. [PubMed: 24590155]
54. Schaefer M, Horn M, Schmidt F, Schmid-Wendtner MH, Volkenandt M, Ackenheil M, et al.
Correlation between sICAM-1 and depressive symptoms during adjuvant treatment of melanoma
with interferon-alpha. Brain Behav Immun. 2004; 18(6):555–62. [PubMed: 15331126]
55. Thomas AJ, Ferrier IN, Kalaria RN, Davis S, O’Brien JT. Cell adhesion molecule expression in the
dorsolateral prefrontal cortex and anterior cingulite cortex in major depression in the elderly. Br J
Psychiatry. 2002; 181:129–34. [PubMed: 12151283]
56. Thomas AJ, Ferrier IN, Kalaria RN, Woodward SA, Ballard C. Elevation in late-life depression of
intercellular adhesion molecule-1 expression in the dorsolateral prefrontal cortex. Am J Psychiatry.
2000; 157(10):1682–4. [PubMed: 11007725]
57. Sanchez-Villegas A, Delgado-Rodriguez M, Alonso A, Schlatter J, Lahortiga F, Majem LS, et al.
Association of the Mediterranean dietary pattern with the incidence of depression: The
Seguimiento Universidad de Navarra/University of Navarra Follow-up (SUN) cohort. Arch Gen
Psychiatry. 2009; 66(10):1090–8. [PubMed: 19805699]
58. Rienks J, Dobson AJ, Mishra GD. Mediterranean dietary pattern and prevalence and incidence of
depressive symptoms in mid-aged women: Results from a large community-based prospective
study. Eur J Clin Nutr. 2013; 67(1):75–82. [PubMed: 23212131]
59. Meng L, Chen D, Yang Y, Zheng Y, Hui R. Depression increases the risk of hypertension
incidence: A meta-analysis of prospective cohort studies. J Hypertens. 2012; 30(5):842–51.
[PubMed: 22343537]
60. Pollin TI, Damcott CM, Shen HQ, Ott SH, Shelton J, Horenstein RB, et al. A null mutation in
human apoc3 confers a favorable plasma lipid profile and apparent cardioprotection. Science.
2008; 322(5908):1702–5. [PubMed: 19074352]
61. Boquist S, Ruotolo G, Tang R, Bjorkegren J, Bond MG, de Faire U, et al. Alimentary lipemia,
postprandial triglyceride-rich lipoproteins, and common carotid intima-media thickness in healthy,
middle-aged men. Circulation. 1999; 100(7):723–8. [PubMed: 10449694]
62. Teno S, Uto Y, Nagashima H, Endoh Y, Iwamoto Y, Omori Y, et al. Association of postprandial
hypertriglyceridemia and carotid intima/media thickness in patients with type 2 diabetes. Diabetes
Care. 2000; 23(9):1401–6. [PubMed: 10977041]
63. Carney RM, Freedland KE. Depression in patients with coronary heart disease. Am J Med. 2008;
121(11 Suppl 2):S20–7.
Kiecolt-Glaser et al. Page 12
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
64. Nemeroff CB, Goldschmidt-Clermont PJ. Heartache and heartbreak-the link between depression
and cardiovascular disease. Nature Reviews Cardiology. 2012; 9(9):526–39. [PubMed: 22733213]
65. Shelton RC, Miller AH. Eating ourselves to death (and despair): The contribution of adiposity and
inflammation to depression. Prog Neurobiol. 2010; 91(4):275–99. [PubMed: 20417247]
66. Slavich GM, Irwin MR. From stress to inflammation and major depressive disorder: A social signal
transduction theory of depression. Psychol Bull. 2014; 140(3):774–815. [PubMed: 24417575]
Kiecolt-Glaser et al. Page 13
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Figure 1.
Mean post-meal sICAM-1, sVCAM-1, SAA, and CRP as a function of the number of prior
day stressors and meal type. Results are estimates from linear mixed effects models
controlling for pre-meal values, cancer status, visit, age, trunk fat, physical activity, and
depression history. Bars are +/− 1 standard error.
Kiecolt-Glaser et al. Page 14
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Figure 2.
Post-meal trajectories of mean SBP and DBP as a function of major depression history.
Results are estimates from linear mixed effects models controlling for pre-meal values,
cancer status, visit, age, trunk fat, physical activity, and prior day stressors. Bars are +/− 1
standard error.
Kiecolt-Glaser et al. Page 15
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Kiecolt-Glaser et al. Page 16
Table 1
Subject Characteristics
Control Subjects (n=20) Breast Cancer Survivors (n=38) P-value
Age, years 55.0 (10.2) 52.1 (7.3) 0.23
Body Mass Index, kg/m2 26.7 (4.1) 28.8 (5.3) 0.13
Waist, cm 91.2 (10.3) 96.6 (12.8) 0.11
Trunk fat, g (DXA) 13994.2 (5218.7) 16983.8 (5758.6) 0.06
Lean body mass, g (DXA) 40559.1 (3839.9) 42541.1 (5239.7) 0.14
Caloric expenditure per week, moderate intensity exercise 1331 (1285) 1066 (1196) 0.44
Systolic blood pressure, mmHg 124.0 (18.5) 124.9 (20.1) 0.89
Diastolic blood pressure, mmHg 72.6 (7.9) 75.5 (8.6) 0.21
Pulse pressure, mmHg 51.4 (15.0) 49.5 (14.7) 0.60
Fasting sICAM-1 290.7 (86.9) 326.7 (78.4) 0.04
Fasting sVCAM-1 423.5 (137.0) 416.4 (114.2) 0.95
Fasting CRP 2.9 (5.3) 2.6 (2.9) 0.72
Fasting SAA 6892.4 (10338.1) 6018.3 (5208.3) 0.74
Post-menopausal 13 (65%) 32 (84%) 0.10
CES-D score 8.23 (5.70) 11.01 (7.54) 0.15
Number of prior day stressors 1.2 (1.1) 1.1 (1.2) 0.56
History of major depression 3 (15%) 14 (37%) 0.08
Data shown are mean (SD) or N (%). Body Mass Index, blood pressure, CES-D, and number of stressors were measured at both study visits; data
shown are aggregated across the two measurements per subject.
CES-D, Center for Epidemiological Studies Depression Scale; DXA, dual x-ray absorptiometry
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.
Author Manuscript Author Manuscript Author Manuscript Author Manuscript
Kiecolt-Glaser et al. Page 17
Table 2
Estimated changes in post-meal sICAM-1, sVCAM-1, CRP, and SAA for each additional prior day stressor, for each meal type. Estimates from linear
mixed models controlling for cancer status, visit, age, trunk fat, physical activity, and depression history.
High oleic sunflower oil High saturated fat oil
Estimate 95% CI P-value Estimate 95% CI P-value
sICAM-1 1.7% (0.2%,3.1%) 0.02 −0.7% (−2.1%,0.8%) 0.34
sVCAM-1 2.1% (0.6%,3.6%) 0.007 0.1% (−1.5%,1.6%) 0.93
CRP 2.9% (0.6%,5.3%) 0.02 −0.5% (−2.9%,2.0%) 0.68
SAA 2.3% (0.1%,4.5%) 0.04 −0.5% (−3.0%,2.0%) 0.69
Mol Psychiatry
. Author manuscript; available in PMC 2017 July 13.