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Cited by 238Schizophrenia research and treatmentTryptophan and brain disordersPsychopathy, Forensic Psychiatry, Sexual Offending

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Towards a Psychosis Risk Blood Diagnostic for Persons Experiencing High-Risk Symptoms: Preliminary Results From the NAPLS Project

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Perkins, Diana O., Jeffries, Clark D., Addington, Jean, Bearden, Carrie E., Cadenhead, Kristin S., Cannon, Tyrone D., Cornblatt, Barbara A., Mathalon, Daniel H., McGlashan, Thomas H., Seidman, Larry J., Tsuang, Ming T., Walker, Elaine F., Woods, Scott W., Heinssen, Robert·2015·Schizophrenia Bulletin
DOI 10.1093/schbul/sbu099PMC PMC4332942
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Abstract

INTRODUCTION: A barrier to preventative treatments for psychosis is the absence of accurate identification of persons at highest risk. A blood test that could substantially increase diagnostic accuracy would enhance development of psychosis prevention interventions. METHODS: The North American Prodrome Longitudinal Study project is a multisite endeavor that aims to better understand predictors and mechanisms for the development of psychosis. In this study, we measured expression of plasma analytes reflecting inflammation, oxidative stress, hormones, and metabolism. A "greedy algorithm" selected analytes that best distinguished persons with clinical high-risk symptoms who developed psychosis (CHR-P; n = 32) from unaffected comparison (UC) subjects (n = 35) and from those who did not develop psychosis during a 2-year follow-up (CHR-NP; n = 40). RESULTS: The classifier included 15 analytes (selected from 117), with an area under the receiver operating curve for CHR-P vs UC of 0.91 and CHR-P vs CHR-NP of 0.88. Randomly scrambled group membership followed by reconstructions of the entire classifier method yielded consistently weak classifiers, indicating that the true classifier is highly unlikely to be a chance occurrence. Such randomization methods robustly imply the assays contain consistent information distinguishing the groups which was not obscured by the data normalization method and was revealed by classifier construction. These results support the hypothesis that inflammation, oxidative stress, and dysregulation of hypothalamic-pituitary axes may be prominent in the earliest stages of psychosis. CONCLUSION: If confirmed in other groups of persons at elevated risk of psychosis, a multiplex blood assay has the potential for high clinical utility.

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Crossref · 10.1093/schbul/sbu099

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Figures

Fig. 1. Shown analytes were the most frequently appearing in 20 5-by-5-by-5 cross-validation trials, each trial testing 125 partitions to generate ~80% subsets of UC, CHR-NP, and CHR-P samples.
Fig. 1. Shown analytes were the most frequently appearing in 20 5-by-5-by-5 cross-validation trials, each trial testing 125 partitions to generate ~80% subsets of UC, CHR-NP, and CHR-P samples.CC BY-NC · PubMed Central
Fig. 2. Fifteen-analyte receiver operating curves and 95% confidence intervals: (A) for CHR-P vs UC and (B) CHR-P vs CHR-NP.
Fig. 2. Fifteen-analyte receiver operating curves and 95% confidence intervals: (A) for CHR-P vs UC and (B) CHR-P vs CHR-NP.CC BY-NC · PubMed Central
Fig. 3. Distribution of AUCs for 100 classifiers built with random data. Shown is a beta distribution fit and P value (A) for UC vs CHR-P and (B) CHR-NP vs CHR-P. For UC vs P: the alpha values were >.2 for both Kolmogorov-Smirnov and Anderson-Darling tests of fit with beta distributions. Using the top 15, the area under the receiver operating curve (AUC) for true classifier on true data was 0.91. For the beta fit, this value is out of range and has a P value = 0. For NP vs P: the alpha values were >.2 for both Kolmogorov-Smirnov and Anderson-Darling tests of fit with beta distributions. Using the top 15, the AUC for true classifier on true data was 0.88. For the beta fit, this value has a P value = 6.51E-05.
Fig. 3. Distribution of AUCs for 100 classifiers built with random data. Shown is a beta distribution fit and P value (A) for UC vs CHR-P and (B) CHR-NP vs CHR-P. For UC vs P: the alpha values were >.2 for both Kolmogorov-Smirnov and Anderson-Darling tests of fit with beta distributions. Using the top 15, the area under the receiver operating curve (AUC) for true classifier on true data was 0.91. For the beta fit, this value is out of range and has a P value = 0. For NP vs P: the alpha values were >.2 for both Kolmogorov-Smirnov and Anderson-Darling tests of fit with beta distributions. Using the top 15, the AUC for true classifier on true data was 0.88. For the beta fit, this value has a P value = 6.51E-05.CC BY-NC · PubMed Central

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Research works printed but not linked: 3

  1. First, 2002, Structured Clinical Interview for DSM-IV TR Axis I Disorders, Non-patient Edition (SCID-I/NP)
  2. Drake, 1996, Clinician rating scale: Alcohol Use Scale (AUS), Drug Use Scale (DUS), and Substance Abuse Treatment Scale (SATS), 113
  3. Schwarz, 2011, Identification of a biological signature for schizophrenia in serum, Mol Psychiatry, 17, 1

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Metadata

Authors
Perkins, D. O., Jeffries, C. D., Addington, J., Bearden, C. E., Cadenhead, K. S., Cannon, T. D., Cornblatt, B. A., Mathalon, D. H., McGlashan, T. H., Seidman, L. J., Tsuang, M. T., Walker, E. F., Woods, S. W., & Heinssen, R.
Affiliations
  • University of North Carolina at Chapel Hill (US)
  • University of Calgary (CA)
  • University of California, Los Angeles (US)
  • University of California San Diego (US)
  • Yale University (US)
  • Zucker Hillside Hospital (US)
  • University of California, San Francisco (US)
  • Beth Israel Deaconess Medical Center (US)
  • Emory University (US)
  • National Institute of Mental Health (US)
Corresponding author
  • Perkins, Diana O.
  • Jeffries, Clark D.
ORCID
Venue
Schizophrenia Bulletin
Publisher
Oxford University Press (OUP)
Published
2014-08-06
Volume
41
Issue
2
Pages
419-428
ISSN
  • 0586-7614 (ISSN-L)
  • 1745-1701
DOI
10.1093/schbul/sbu099
PMC
PMC4332942
OpenAlex
W2144107861
Cited by
238
References
60
Citations by year
2026: 8 · 2025: 15 · 2024: 16 · 2023: 28 · 2022: 14 · 2021: 15 · 2020: 25 · 2019: 22 · 2018: 17 · 2017: 20 · 2016: 32 · 2015: 19 · 2014: 7
FWCI
19.85
Type
journal article
Language
en
Open access
Licence
cc-by-nc
Locations
  • Schizophrenia Bulletin (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
  • Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by-nc)
  • UNC Libraries
Funders
National Institute of Mental Health (U01MH081928, U01MH066160, U01MH082022, U01MH076989, U01MH081984, U01MH0818902, U01MH081857, U01MH082004, U01MH081944, P50MH066286, U01MH081988)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
  • Life Sciences › Neuroscience › Biological Psychiatry › Tryptophan and brain disorders
  • Social Sciences › Psychology › Clinical Psychology › Psychopathy, Forensic Psychiatry, Sexual Offending
Keywords
psychosis risk, clinical high risk for psychosis
MeSH terms
Adult, Female, Follow-Up Studies, Humans, Hypothalamo-Hypophyseal System, Inflammation, Male, Pituitary-Adrenal System, Psychotic Disorders, Oxidative Stress, Risk Assessment, Young Adult, Prodromal Symptoms

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