advancing diagnostic biomarkers for posttraumatic...

Co-sponsored by

September 26 – 28, 2013 | Westin Tampa Harbour Island

Advancing Diagnostic Biomarkers for Posttraumatic Stress Disorder (PTSD)

Charles R. Marmar, MD New York University Langone Medical Center New York, NY

Charles R. Marmar, MD

● Dr. Marmar has no disclosures to report.

Disclosures

Learning Objective

Analyze the leading-edge science in the search for biomarkers for post traumatic stress disorder

Biomarkers for PTSD

● PTSD prevalence in Operations Enduring Freedom and Iraqi Freedom (OEF/OIF) is estimated at 20%1; PTSD represents 50% of mental health burden in OEF/OIF2

● Self-reports are unreliable and limit efforts to identify and treat soldiers

●  Identification of objective biomarkers will aid efforts to respond most effectively to the mental health needs of soldiers

1.  Institute of Medicine (IOM). Preface. In: Treatment for Posttraumatic Stress Disorder in Military and Veteran Populations: Initial Assessment. 2012.

2.  Hermes ED, et al. Psychiatr Serv. 2012;63(5):471-476. PMID: 22422018.

Biomarkers for PTSD

● Limitation: No objective way to confirm or rule out diagnosis of PTSD ● Identify biomarkers for: !  Post-deployment medical screening !  Treatment-selection !  Treatment outcome-monitoring !  Disability evaluations !  Informing novel targets for treatment

Marmar C, et al. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Target Biomarkers

● Neurocognitive ● Neurogenetic ● Neuroimaging ● Neuroendocrine ● Metabolic or allostatic load ● Multi-omics

Omics = suffixes that are derived from genome (the whole collection of a person's DNA) Marmar C, et al. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

New York Univ (Marmar)

Mt. Sinai/Bronx VA (Yehuda)

Integrative Systems Biology (Jett/Hammamieh)

& Institute for Systems Biology

(Hood)

Administrative &

Clinical Core

Neuroimaging Core NYU (Sodickson)

UCSF (Weiner)

Neurogenetics Core

University of California San Francisco

(Hamilton/Ressler)

Metabolism & Cell Aging

UCSF (Wolkowitz)

Neuroendocrine &

Clinical Core

Multi-Omics Core

Neuroimaging is acquired for all

participants

Blood procedures are acquired for all

participants

Six Research Cores

Marmar C, et al. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

PTSD-Positive (n = 52)

PTSD-Negative (n = 52)

Race/Ethnicity [Count (%)]

Hispanic 26 (50.0%) 20 (38.5%)

African American 12 (23.1%) 13 (25.0%)

Caucasian 13 (25.0%) 15 (28.8%)

Other 1 (1.9%) 4 (7.7%)

The p values are not significant (p = .46)

Demographic Characteristics

Marmar C, et al. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24. The Posttraumatic Stress Disorder (PTSD) Research Program. New York University Langone Medical Center Website. http://ptsdresearch.nyumc.org.

PTSD-Positive (N = 52)

PTSD-Negative (N = 52)

n (%) n (%) χ2(1) p

Current anxiety 4 (7%) 0 (0%) 4.2 .041

Lifetime anxiety 5 (9.6%) 0 (0%) 5.2 .022

Current major depressive disorder 27 (51.5%) 1 (1.9%) 33.0 <.0001

Lifetime major depressive disorder 44 (84.6%) 12 (23.1%) 39.6 <.0001

Lifetime alcohol abuse dependence 33 (63.5%) 13 (25.0%) 15.6 .001

Lifetime substance abuse / dependence 7 (13.5%) 2 (3.9%) 3.0 .081

Clinical Diagnostic Evaluation DSM-IV (SCID), Matched Sample SCID = Structured Clinical Interview for the DSM-IV Axis I Disorders

Marmar C, et al. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24. The Posttraumatic Stress Disorder (PTSD) Research Program. New York University Langone Medical Center Website. http://ptsdresearch.nyumc.org.

PTSD Positive (N = 51)

PTSD Negative (N = 52)

ANCOVA adjusting for Education

Mean (SD) Mean (SD) F p Estimated IQ (Vocabulary) 99.3 (15.5) 107.9 (14.8) F (1,100) =

4.80 .031

Digit Span 8.62 (2.50) 10.04 (3.37) F (1,100) = 3.57 .062

Letter-Number-Sequencing 9.14 (1.95) 10.12 (4.57) F (1,100) =

1.83 .180

Spatial Addition 9.16(2.82) 10.10 (2.89) F (1,100) = 3.24 .075

Neurocognitive Assessment IQ and Working Memory

Henn-Haase C. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Genetic Studies of PTSD

Steven P. Hamilton, MD, PhD

Neurogenetics Core

● Hypothesis: DNA variants in stress-response genes will be associated with PTSD !  FKBP5 !  COMT !  APOE !  BDNF

Hamilton S. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Neurogenetics Core

●  Genotype 107 SNPs in FKBP5, COMT, APOE, and BDNF using genome-wide dataset from Illumina OmniExpress

●  51 controls and 51 cases, all male ●  Logistic regression with dichotomous PTSD +/- outcome, without

covariates ●  Analyses with permutation to determine empirical significance, with

significance threshold: p = .013

SNP = single nucleotide polymorphism. Hamilton S. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

•  APOE: 16 SNPs over 27kb (also APOE4 status)

•  BDNF: 25 SNPs over 92kb (including val66met)

•  COMT: 46 SNPs over 37kb, (including val158met)

•  FKBP5: 20 SNPs over 145kb

Neurogenetics Core

SNP = single nucleotide polymorphism. Hamilton S. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Gene Total SNPs p value APOE 16 .75 BDNF 25 .009 COMT 46 .67 FKBP5 20 .88

4 tests, threshold p = .013, 10K permutations; set-based analysis with all SNPs, p = 1, r2 = 1, n = 102 subjects.

Neurogenetics Core

Gene SNP MAF PTSD MAF Control OR p

BDNF rs11030119 0.17 0.35 0.37 .002

BDNF rs7124442 0.27 0.48 0.41 .002

BDNF rs962369 0.15 0.29 0.41 .01

BDNF rs7934165 0.40 0.58 0.49 .01

BDNF rs925946 0.20 0.34 0.47 .02

BDNF rs10767658 0.20 0.34 0.47 .02

BDNF rs11819808 0.15 0.05 3.35 .02

107 tests, threshold p =.0005, n = 102

SNP = single nucleotide polymorphism; MAF = minor allele frequency; OR = odds ratio. Hamilton S. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Neurogenetics Core

GWAS = genome-wide association study; GSEA = gene set enrichment analysis; FDR = false discovery rate. Hamilton S. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

GWAS analysis–GSEA Amine receptor activity: p=.001, FDR = 0.05,

24 of 33 genes with p ≤ .05 HRH2, HTR1B, HTR5A, ADRA1B, HTR2A,

HTR4, DRD1, ADRA1D, HRH1, HTR1E, ADRA1A, CHRM2, CHRM5, CHRM3,

ADRA2B, HTR1F, ADRB1, DRD2, ADRB2, HTR1D, HTR7, DRD3, HTR1A, ADRA2C

Neurogenetics Core

GWAS analysis–GSEA Six pathways with FDR ≤ 0.05

Cytokine receptor binding

Rhodopsin-like receptor activity

Nucleotide kinase activity

Neurotransmitter receptor activity

Double-stranded DNA binding

Amine receptor activity

GWAS = genome-wide association study; GSEA = gene set enrichment analysis; FDR = false discovery rate. Hamilton S. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Structural Imaging Core Systems Biology Studies of PTSD: Brain Structural Abnormalities

Susanne Mueller, MD Peter Ng, BS Michael Weiner, MD

Hypotheses to Be Tested

1.  PTSD is associated with hippocampal volume loss due to volume loss in CA1 and/or CA3/dentate that leads to an overall hippocampal volume loss1-3

2.  PTSD is associated with volume loss in amygdala, nucleus accumbens, and thalamus; and thinning of the anterior cingulate, and the medial frontal, orbitofrontal, dorso-lateral frontal and insular cortices3-5

3.  Analysis: The PTSD-related structural abnormalities are associated with a reorganization favoring an enhanced interaction in limbic (hippocampus/amygdala) and mesial frontal structures (cingulate, superior frontal) as evidenced by an increased nodal degree and nodal between-ness centrality3-5

CA = Cornu Ammonis 1. Neylan TC, et al. Biol Psychiatry. 2010;68(5):494-496. PMID: 20598672 . 2. Wang Z, et al. Arch Gen Psychiatry. 2010;67(3):296-303. PMID: 20194830. 3. Karl A, et al. Neurosci Behav Review. 2006;30(7): 1004-1031. PMID: 16730374. 4. Kuhn S, et al. J Affect Dis. 2011;134(1-3):315-319. PMID: 21705088. 5. Lyoo IK, et al. Arch Gen Psychiatry. 2011;68(7): 701-713. PMID: 21727254.

Freesurfer 5.1 Automated volumetry and regional cortical thickness

CA3&DG

ERC

SUB CA1

CA1-2 transition

T2 high resolution hippocampal image and

manual parcellation scheme

Methods I: Image Processing

Raz N, et al. Cereb Cortex. 2005;15(11):1676-1689. PMID: 15703252.

Image Processing: Methods II

●  Image Analysis: Volumes were corrected for differences of head size using the following formula: adjusted volume = raw volume − b × (ICV − mean ICV)

●  Measurements of both volume sides were combined to test for group differences with multiple regression analyses correcting for nuisance variables age and ethnicity

●  Graph-analysis was done with the GAT toolbox (nnl.stanford.edu/tools/GAT) using the Freesurfer labels as nodes and the the adjacency matrices of both groups had thresholds set at the minimal density (0.2908) and compared to 100 random networks with similar properties

B = is the slope of regression of an ROI volume on ICV ICV = intracranial vault GAT = graph-theoretical analysis Raz N, et al. Cereb Cortex. 2005;15(11):1676-1689. PMID: 15703252.

ERC Sub CA1 CA1-2 trans CA3&DG

PTSD negative

PTSD positive

Results Volumetry: Subfields


Volu

mes

Cor

rect

ed fo

r IC

V

PTSD negative

PTSD positive

Hippocampus Amygdala Thalamus Ncl. Accumbens

Results Volumetry: Prefrontal-Limbic-Insular System I


Volu

mes

Cor

rect

ed fo

r IC

V (m

m3 )

Results Thickness: Prefrontal-Limbic-Insular System II

Raz N, et al. Cereb Cortex. 2005;15(11):1676-1689. PMID: 15703252. *p < .05

Resting State fMRI Studies of PTSD

X Yan, AD Brown, M Lazar, C Henn-Haase, TC Neylan, A Shalev, OM Wolkowitz, R Yehuda, DK Sodickson, MW Weiner, CR Marmar

Mechanisms in Fear Response

Davidson JR, et al. J Neuropsychiatry Clin Neurosci. 2004;16(2):135-147. PMID: 15260364.

Resting State fMRI Studies in PTSD

● Are the findings specific to the mental states involved in the tasks or can they be generalized to other mental states? ● Besides the regional

“activation” (responsivity), how about the connectivity between different brain regions?

Yan X, et al. J Neurosci Methods. 2011;199(1):108-118. PMID: 21565220.

Methods

● Resting state fMRI, 6.6 minute, eyes open, TR-2s, voxel size-3.123x3.5mm

● Analysis & hypothesis ! Amplitudes of Low Frequency Fluctuation (ALFF) !  Increased ALFF in amygdala and/or insula ! Decreased ALFF in PCC/precuneus

! Functional connectivity (FC) ! Decreased aymgdala/insula frontal FCs ! Decreased default mode network FCs

TR = temporal resolution; PCC = posterior cingulate cortex Yan X, et al. J Neurosci Methods. 2011;199(1):108-118. PMID: 21565220.

Summary

● Consistent activity patterns across brain states ! Increased activity in the amygdala & insula ! Decreased activity in the percuneus

● Functional connectivity (FC) ! Decreased FCs within DWN ! Decreased amygdala-frontal FC

DMN = default mode network. Yan X, et al. J Neurosci Methods. 2011;199(1):108-118. PMID: 21565220.

Endocrine Core: Glucocorticoid-Related Biomarkers

Rachel Yehuda, PhD Janine D. Flory, PhD Linda M. Bierer, MD Amy Lehrner, PhD Erin Koch, BA Nikos Daskalakis, MD, PhD Frank Desarnaud, PhD Iouri Makotkine, PhD Owen Wolkowitz, MD Charles Marmar, MD

24-Hour Urinary Cortisol

Yehuda R, et al. Front Psychiatry. 2013;4:118.

Group: ns BMI: F(1,95) = 3.926, p = .051

Group: F(1,95) = 2.969, p = .088 Race/Ethnicity: ns BMI: F(1,95) = 3.301, p = .073

0

10

20

30

40

50

60

70

80

Urin

ary

Cor

tisol

PTSD+ PTSD-

0

10

20

30

40

50

60

70

80

90

Hispanic Black White

Urin

ary

Cor

tisol

PTSD+ PTSD-

24-Hour Urinary Cortisol (cont’d.) ●  Not a good diagnostic biomarker ●  Correlated with:

!  Early trauma (physical abuse) r = -.207, n = 96, p = .043 !  Perceived stress r = -.209, n = 96 p = .042 !  IC50-DEX r = .234, n = 96, p = .023 !  Body weight: r = .218, n = 96, p = .033

●  Urinary cortisol correlated with other health measures such as HDL cholesterol, glucose, C-reactive protein

●  Urinary cortisol and 8:00am plasma cortisol NOT related (r = -.047, n = 96, ns)

IC50-Dex = decamethasone Yehuda R, et al. Front Psychiatry. 2013;4:118.

Cortisol Suppression of the DST

DST = dexamethasone suppression test; Dex = dexamethasone Yehuda R, et al. Front Psychiatry. 2013;4:118.

0

5

10

15

20

25

Dec

line

in c

ortis

ol D

ay1-

Day

2

PTSD+ PTSD-

0

4

8

12

16

20

Hispanic Black White

Dec

line

in c

ortis

ol D

ay1-

Day

2

PTSD+ PTSD-

Group: F(1,96) = 6.084; p = .015 BMI: ns DEX: ns

Group: F(1,96) = 7.796; p = .006 Race/Ethnicity: ns Interaction: F(2,96) = 3.936; p = .023

Lysozyme IC50-DEX

IC50-Dex = dexamethasone Yehuda R, et al. Front Psychiatry. 2013;4:118.

0

1

2

3

4

5

6

7

8

Lyso

zym

e IC

50-D

EX

PTSD+ PTSD-

0

2

4

6

8

10

Hispanic Black White Ly

sozy

me

IC50

-DE

X PTSD+ PTSD-

PTSD: F(1,98) = 6.477, p = .013 BMI: ns PTSD: F(1,98) = 8.833, p = .004

Race/Ethnicity: ns Interaction: F(2,98) = 3.210, p = .045 BMI: ns

Lysozyme IC50-Dex

● May be a good candidate diagnostic biomarker (but not for all people)

● Correlated with many other glucocorticoid measures: urinary cortisol, total glucocorticoids, cortisol response to the DST, several metabolites

● Correlated with PTSD-related measures: social support, state anger, PTSD symptoms measured by the PCL (PCL = PTSD Checklist)

●  In other studies, associated with childhood adversity, prognosis to treatment, and changes in association with treatment


GR Gene Methylation at 1F Exon Promoter Region


0 10 20 30 40 50 60 70 80

% M

ethy

late

d S

ites

PTSD+ PTSD-

Group: F(1,101) = 5.969; p = .023 Race/Ethnicity: ns Interaction: ns BMI: ns

GR Gene Cytosine Methylation at the 1F Exon Promoter Region


GR Gene Methylation

● Significant group differences ● Correlations with cortisol

(r = -.265, n = 102, p = .007) ● Correlations within PTSD, with:

! IC50-DEX (r = .306, n = 52, p = .027) ! ACTH response to DEX (r = .305, n = 52, p = .028) ! Glucocorticoid metabolic measures

(r = .319, n = 52, p = .022)


Metabolic and Cell-Aging Markers of PTSD

Owen Wolkowitz, MD Synthia Mellon, PhD CR Marmar, MD

Metabolism, Inflammation, and Cell Aging Core

● Is PTSD Associated with Risk Factors for Physical Disease and a Premature Aging Phenotype? ! Cardio-Metabolic syndrome ! Pro-inflammatory cytokines ! Immune (NK) cell senescence ! Metabolomics/ Mitochondrial dysfunction

Wolkowitz O. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

PTSD Associated With the Cardiometabolic Syndrome: Between-Group Differences

1 Independent t-tests used unless covariates (age and/or BMI) applied, in which case ANCOVA used. Raw data are presented in Table, but data were transformed to achieve normal distributions before analysis, when required. As an exploratory study, significance values are not corrected for multiple comparisons, but to limit Type I errors, subsequent analyses use the Metabolic Syndrome Total Score. 2 HOMA-IR values > 3.80 identify insulin resistance with high sensitivity. 3 METABOLIC SYNDROME TOTAL SCORE= Sum of standardized z-scores of HOMA-IR, BMI, Diastolic BP, LDL, and Pulse. HOMA-IR = homeostatic model assessment- insulin resistance; NS = not significant. Wolkowitz O. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

PTSD (-) PTSD (+)

N (-/+) Mean + SD Mean + SD Statistic1 p Fasting Glucose 51/ 51 79 + 11.5 91 +16.2 t = 3.92 .001 Insulin 51/ 51 12.16 + 10.44 19.18 + 16.96 F = 3.16 .08 HOMA-IR2 51/51 2.65 + 3.41 4.66 + 4.75 F = 4.54 .04 Cholesterol 51/51 171.2 + 26.5 175.4 + 35.3 F = 0.05 NS

Triglycerides 51/51 107.7+ 110.4 121.2 + 62.3 F = 1.71 .19

Body mass index (BMI) 51/ 51 28.3 + 4.2 29.9 + 5.1 t = 1.95 .06 Weight 51/ 51 190.4 + 32.2 206.1 + 39.6 t = 2.20 .03 Pulse 51/50 64 + 11 71 + 12 F = 9.24 .003 METABOLIC SYNDROME TOTAL SCORE3 51/51 -0.84 + 3.12 0.84 + 3.15 T = 2.70 .008

Pro-Inflammatory Cytokines Are Elevated in PTSD

1 Values = Medians + Interquartile range. 2 T-tests are based on Ln (extreme values excluded if distribution not normalized by Ln- transformation). 3 As an exploratory study, significance values are not corrected for multiple comparisons. 4 TOTAL PRO-INFLAMMATORY SCORE = Sum of standardized z-scores of IL-6, IL-1b, TNFa, IFNg, and CRP (N = 102). Wolkowitz O. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

.

Cytokine (pg/ml) PTSD (-)1

(N = 51) PTSD (+)1

(N = 51) T-test2 p3

IFNg 0.58 (0.45-0.69)

0.76 (0.42-1.42) 2.04 .001

TNFa 2.98 (2.52-3.51)

3.69 (2.48-4.49) 1.93 .058

IL-1b 0.08 (0.05-0.13)

0.10 (0.05-0.18) 0.93 .354

IL-6 0.51 (0.44-0.76)

0.79 (0.60-1.12) 2.92 .004

IL-10 1.53 (1.26-1.87)

1.56 (1.25-2.32) 0.89 .373

hsCRP 1.00 (0.40-1.80)

1.33 (0.50-3.95) 1.95 .054

TOTAL PRO-INFLAMMATORY

SCORE4

-1.32 (-2.54 – -0.05)

0.83 (-1.24 – -3.56) 3.58 .001

Natural Killer Cell Senescence Fluorescence-Activated Cell Sorting

●  CD16-CD56+ (“bright”) NK cells are more efficient at producing cytokines, have less natural cytotoxicity, and are more resistant to oxidative stress and apoptosis. They have intact telomeres.

●  CD16+CD56- (“dim”) NK cells are dysfunctional, pro-inflammatory, cytotoxic, and less responsive to proliferation. They have shortened telomeres and are increased with aging.

Figure modified from: Camous X, et al., J Biomed Biotechnol. 2012;2012:195956. PMID: 23251076 Ouyang Q, et al. Ann N Y Acad Sci. 2007:1106:240-252. PMID: 17303822 Wolkowitz O. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Frequency of CD16+CD56-

Frequency of CD56 “dim”

Frequency of CD56 “bright”

Aging

Natural Killer Cell Senescence in PTSD Fluorescence-Activated Cell Sorting

% NK Cell PTSD (-) (N = 39)

PTSD (+) (N = 37) t (p)

CD16-CD56+ (Ln) “Bright”

1.97 + 0.63 1.73 + 0.49 1.93 (p < .06)

CD16+CD56- (Ln) “Dim”

1.83 + 0.72 2.14 + 0.69 2.02 (p < .05)

Wolkowitz O. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24. Ouyang Q, et al. Ann N Y Acad Sci. 2007:1106:240-252. PMID: 17303822

•  CD16-CD56+ (“bright”) NK cells tend to be decreased in PTSD

•  CD16+CD56- (“dim”) NK cells are significantly increased in PTSD, which is conducive to a pro-inflammatory state and suggests NK cellular aging

Signatures of Mitochondrial Dysfunction in PTSD: Reduced Citrate and Increased Pyruvate and Lactate

TCA = tricarboxylic acid. Wolkowitz O. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Red: Elevated in PTSD Green: Decreased in PTSD

●  Many pathways converge on mitochondrial metabolism !  Reduced abundance of mitochondrial metabolites !  Increased abundance of “pre-mitochondrial” metabolites

Biomarkers for PTSD: Human Pan-Omic Studies of PTSD

Rasha Hammamieh, PhD Marti Jett, PhD Integrative Systems Biology U.S. Army Medical Research and Material Command, USA CEHR

Multi-Omics to Integrate With Clinical Findings (Blood Samples) ● Transcriptomics (gene expression) ● DNA methylation ● MicroRNA ● Organ – specific and targeted proteomics ● Integration with clinical information

Hammamieh R. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

Analyzing Circulating microRNA

* CAPSTOT = Clinician-administered PTSD scale Hammamieh R. 166th Annual Meeting of the American Psychiatric Association. 2013. Symposium 24.

From initial survey, 218 miRNAs are expressed in 31 of 31 human plasma samples (N = 17 controls and 14 PTSD patients; all samples are male)

Identified a set of miRNAs that may be used to identify patients with PTSD from normals

PTSD Patients

The individual miRNAs showed good specificity and sensitivity

Clinical Connections

●  PTSD prevalence in Operations Enduring Freedom and Iraqi Freedom (OEF/OIF) is estimated at 20%

●  Self-reports are unreliable and limit efforts to identify and treat soldiers

●  Identification of objective biomarkers will aid efforts to respond most effectively to the mental health needs of soldiers

●  PTSD is associated with volume loss in a number of brain areas

●  PTSD is associated with the cardiometabolic syndrome

Questions & Answers

Co-sponsored by

advancing diagnostic biomarkers for posttraumatic...

Documents