1. Ian Persaud
Mentor: Dr. Joshua Chiappelli
MPRC Conte Research Symposium
August 5, 2016
Relationship of Cortisol to Brain
Morphological Abnormalities in
Schizophrenia
2. SZ and Brain Morphology
In a study of 2028 patients and 2540 controls
volume decreases reported in:
Hippocampus
Amygdala
Thalamus
Accumbens
Intracranial Volumes
Volume increases reported in
Pallidum
Lateral ventricles
(Van Erp, 2016)
3. Potential Biomarker?
IN a study of 596 individuals that compared SZ, SAD,
BDP, 1° relatives and healthy controls
Hippocampal volume supported as putative biomarker
for SZ (P = .007 - .02) and SAD (P = .003 - .14)
(Arnold S 2015)
4. Diathesis-Stress Model
Stess -events or experiences that jeopardize
homeostasis (Chrousos & Gold 1992; Sapolsky,
1992)
Onset, exacerbation, and relapse ALL linked to
multiple somatic/environmental stressors
6. Methods
91 Hi-res 3T structural MRI scans
48 healthy control, 43 SZ patients
Controlled for age and sex
Whole blood samples collected
Assays for cytokines, KYNA, and Cortisol
So far, only Cortisol is complete
Manual Hippocampal Volume measurements using Mango
4.0 software
7.
8. Results
No between group hippocampal volume differences
No correlation with cortisol
Significant decrease trend of vol. with age
Trend more prominent in patient group
9. Hippocampal Volume and Age
Overall: (r=-.219, p=.037)
Patients: (r=-.397, p=.008, n=43)
Controls: (r=-.062, p=.67, n=48)
10. Accelerated Aging theory
Patients with SZ have a faster rate of neural aging, related to
decay.
Increased oxidative stress & inflammation
positive feedback mechanisms
Evidence supports
Increased oxidative stress biomarkers (Okusaga O. O. 2014)
Increased inflammatory biomarkers (Kirpatrick B. & Miller B.J.
2013)
11. Allostatic Load Study
“The term ‘allostasis’ refers to how an organism
accommodates to a stressor by adjusting
homeostatic set points to maintain internal stability”
(Nugent et al 2015)
Allostatic Load - 13 biomarkers vs. Cortical thickness
44 Schizophrenia Spectrum Disorder patients, 33
normal controls
Found patients had higher allostatic load, and lower
cortical thickness (p=.008)
16. Plasma Cortisol and CRP
Significant correlation in patients (rho=.429, p=.013,
n=33) but not in controls (rho=-.055,p=.81, n=21)
????????????
17. Moving Forward
Move Forward with KYNA and Cytokine assays to better
explore relationships between these two circuits and
neurodegeneration
Understanding the relationship these neurochemicals have
with Hippocampal volume, and with patient vs control groups
could offer insight to the interaction in the Diathesis-Stress
model
18. Works Cited
Arnold, S. J. M., Ivleva, E. I., Gopal, T. A., Reddy, A. P., Jeon-Slaughter, H., Sacco, C. B., … Tamminga, C. A. (2015).
Hippocampal volume is reduced in schizophrenia and schizoaffective disorder but not in psychotic bipolar i disorder
demonstrated by both manual tracing and automated parcellation (FreeSurfer). Schizophrenia Bulletin, 41(1), 233–249.
http://doi.org/10.1093/schbul/sbu009
Kirkpatrick, B., & Miller, B. J. (2013). Inflammation and schizophrenia. Schizophrenia Bulletin, 39(6), 1174–1179.
http://doi.org/10.1093/schbul/sbt141
Nugent, K. L., Chiappelli, J., Rowland, L. M., & Hong, L. E. (2015). Cumulative stress pathophysiology in schizophrenia
as indexed by allostatic load. Psychoneuroendocrinology, 60, 120–129. http://doi.org/10.1016/j.psyneuen.2015.06.009
Okusaga, O. O. (2014). Accelerated aging in schizophrenia patients: the potential role of oxidative stress. Aging and
Disease, 5(4), 256–62. http://doi.org/10.14336/AD.2014.0500256
van Erp, T. G. M., Hibar, D. P., Rasmussen, J. M., Glahn, D. C., Pearlson, G. D., Andreassen, O. a, … Turner, J. a.
(2016). Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the
ENIGMA consortium. Molecular Psychiatry, (October 2014), 1–7. http://doi.org/10.1038/mp.2015.63
Walker, E. F., & Diforio, D. (1997). Schizophrenia: A Neural Diathesis-Stress Model. Psychological Review, 104(4), 667–
685. http://doi.org/10.1037/0033-295X.104.4.667
19. Acknowledgements
Dr. Ana Pocivavsek
My mentor, Dr. Chiappelli
Dr. Elliot Hong
Neuroimaging staff, all of the Conte Staff
THANK YOU ALL!
Editor's Notes
Examples:
Prenatal stress increases disease risk
Stress full events precede disease onset
Patients have greater affective reactivity to experimental stress exposure after illness onset
Stressful life event precipitate the worsening of psychosis
Psychological and physiological stress reactivity are associated with psychotic episodes, quality of life, and symptom severity
HYPOTHESIS: environmental exposure to stress throughout the lifespan and especially at certain critical timepoints in development can contribute and drive SZ
There is a complex framework that controls the biological stress response. Dysfunction in any area of this framework could contribute significantly to the set of symptoms that is grouped together as SZ. Top Down Control of the response byFRONTAL AREAS to the HPA axis. Here we see release of cortisol.
Cortisol
is a biomarker for stress, and can be measured in saliva, serum, and in urine.
Release typically enhances glutamatergic activity
concentration has a modulating effect on cytokine levels, is ANTI-INFLAMMATORY
Cytokines
Cortisol also modulates immune response via cytokines.
Increased Cytokines sensitize FRONTAL areas
KYNA
High cytokine levels push the KYNurenine pathway to increase concentration of KYNA, metabolites of KYNA and this pathway interact with the frontal limbic circuit. Varying the concentrations of these metabolites could contribute to dysfunction in the circuit at its highest point of glutamate release.
Cytokines assays will include: IL-6, Il-10, interferon –gamma in a single molecule array assay, higher sensitivity than ELISA.
Controls for age and sex
Pt characteristics: wide age range, most on medication, many chronics
No correlation found to antipsychs in the current measures
In the whole sample, hippocampal volume decreases as an individual ages. More prominent in patients, vs. controls. Support for the Accelerated aging theory.
Aging – a decline in intrinsic physiological function which is age dependent or age progressive and leads to an increase in age specific mortality rate (aka reduction in survival rate)
Reduced cortical thickness and hippocampal volume are testament to this neural degradation. However, the chemical mechanisms are still not well understood.
INTRODUCE
Since our data with cortisol did not make any conlusive findings, we also reviewed data previously available from another study that had many overlapping participants with the current study.
Allostatic Load – When we encounter stressors, our body woks to accommodate and change homeostatic conditions to best accommodate the stressor in the environment. This puts a “tax” on the system, and uses up resources.
Allostatic load is measured in overall and metabolism, as a combo of 13 biomarkers including cardiovascular, neuroendocrine, immune, and metabolic measurements.
Whole Sample, containing both groups. From allostatic load study. Urinary cortisol is more accurate b/c cortisol release over extended time period (study design) plasma cortisol is a snapshot and influenced by several factors, while uriniary cortisol is done overnight so less confounds
Suggests potential differences b/w plasma and urinary cortisol: confounds w/ plasma
The plasma analysis was not standardized for time (circadian effects), and the participants did not fast before specimen collection
Cortical thickness refers to the grey matter layer. In SZ, it is noted that even in first episode cases there are significant reductions in thickness of this grey matter layer in the cerebral cortex
Cortical Thickness Decreases as serum cortisol levels increase
Higher levels of stress biomarker, paired with higher levels of brain neurodegeneration.
Interpretation: higher levels of stress contribute to the grey matter decay associated with SZ. Supports role of stress in the diathesis stress model as a driving factor for progression of neural degeneration
However, CRP was not correlated with hippocampal volume.
In the study, one of the most strongly correlated was CRP – an indices that is related to immune inflammation
Found in SZ spectrum patients, as well as normal controls
CRP is indicative of higher cytokine levels, as induced by high stress. In this case, it is another biomarker that shows increase, like plasma cortisol that could contribute to the cortical degradation.
Relationship here is specific to patients important because in returning to this diagram, it shows some unexpected dysregulation
Typically, cortisol is anti inflammatory, so they would NOT have a postiive relationship. It is more expected there is an inegative relationship here, with decreasing crp as cortisol increases
But we found the opposite.
THIS SHOWS THERE IS SOME DYSREGULATION OCCURING on this leg here
Results are pending for the KYNA and Cytokine assays, as these samples have been sent out to other labs for analysis
