Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

Publisher: Nature Publishing Group Specialist Journals Country of Publication: England NLM ID: 9607835 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-5578 (Electronic) Linking ISSN: 13594184 NLM ISO Abbreviation: Mol Psychiatry Subsets: MEDLINE

Publication: 2000- : Houndmills, Basingstoke, UK : Nature Publishing Group Specialist Journals
Original Publication: Houndmills, Hampshire, UK ; New York, NY : Stockton Press, c1996-

Psychotic Disorders*/physiopathology ; Biomarkers* ; Corpus Striatum*/diagnostic imaging ; Corpus Striatum*/physiopathology ; Neuroimaging*/methods ; Magnetic Resonance Imaging*/methods ; Schizophrenia*/physiopathology ; Schizophrenia*/diagnostic imaging; Humans ; Male ; Female ; Adult ; Reproducibility of Results ; Connectome/methods ; Young Adult ; Adolescent

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n = 101) from healthy controls (n = 51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n = 97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC = 75.4%, 95% CI = 67.0-83.3%; in non-affective psychosis AUC = 80.5%, 95% CI = 72.1-88.0%, and in affective psychosis AUC = 58.7%, 95% CI = 44.2-72.0%). Test-retest reliability ranged between ICC = 0.48 (95% CI = 0.35-0.59) and ICC = 0.22 (95% CI = 0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC = 0.51 (95% CI = 0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 min, diagnostic classification of the FSA increased from AUC = 71.7% (95% CI = 63.1-80.3%) to 75.4% (95% CI = 67.0-83.3%) and phase encoding direction reliability from ICC = 0.29 (95% CI = 0.14-0.43) to ICC = 0.51 (95% CI = 0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.
(© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Update of: medRxiv. 2023 Jul 23:2023.07.17.23292779. doi: 10.1101/2023.07.17.23292779. (PMID: 37503088)
Update of: Res Sq. 2023 Aug 07:rs.3.rs-3185688. doi: 10.21203/rs.3.rs-3185688/v1. (PMID: 37609149)

Hum Brain Mapp. 2020 Jun 15;41(9):2249-2262. (PMID: 32150312)
JAMA. 2016 Dec 13;316(22):2402-2410. (PMID: 27898976)
Neuroimage. 2019 Aug 1;196:126-141. (PMID: 30974241)
Nat Med. 2016 Nov;22(11):1248-1255. (PMID: 27783066)
Lancet Psychiatry. 2016 Jan;3(1):77-83. (PMID: 26573970)
Lancet Psychiatry. 2016 Apr;3(4):358-66. (PMID: 26922475)
Neuroimage. 2021 Oct 1;239:118254. (PMID: 34118397)
Neuroimage. 2013 Oct 15;80:144-68. (PMID: 23702415)
Neuroimage. 2012 Oct 1;62(4):2222-31. (PMID: 22366334)
Neuroimage. 2020 Jan 15;205:116210. (PMID: 31593793)
Am J Psychiatry. 2021 Jun;178(6):509-521. (PMID: 33397140)
N Engl J Med. 2015 Feb 26;372(9):793-5. (PMID: 25635347)
Sci Bull (Beijing). 2019 Jul 30;64(14):953-954. (PMID: 36659803)
Schizophr Res. 2012 Aug;139(1-3):116-28. (PMID: 22658527)
Lancet. 2022 Jan 29;399(10323):473-486. (PMID: 35093231)
Am J Ment Defic. 1981 Sep;86(2):127-37. (PMID: 7315877)
J Neurosci Methods. 2008 Jul 15;172(1):137-41. (PMID: 18501969)
Neuroimage. 2021 Nov 1;241:118439. (PMID: 34339830)
Front Neuroinform. 2014 Feb 21;8:14. (PMID: 24600388)
Dialogues Clin Neurosci. 2014 Dec;16(4):505-24. (PMID: 25733955)
Neuroimage. 2013 Oct 15;80:105-24. (PMID: 23668970)
World Psychiatry. 2023 Jun;22(2):236-262. (PMID: 37159365)
Neuroimage. 2019 Jun;193:35-45. (PMID: 30831310)
Neuroimage. 2021 Dec 1;244:118617. (PMID: 34600102)
Curr Opin Behav Sci. 2021 Aug;40:27-32. (PMID: 33585666)
Psychol Bull. 1979 Mar;86(2):420-8. (PMID: 18839484)
Schizophr Res. 2021 Nov;237:153-165. (PMID: 34534947)
Neuropsychopharmacology. 2017 Oct;42(11):2214-2221. (PMID: 28294137)
Hum Brain Mapp. 2018 Feb;39(2):902-915. (PMID: 29143409)
Am J Psychiatry. 2017 Mar 1;174(3):216-229. (PMID: 27919182)
Am J Psychiatry. 2019 Jan 1;176(1):21-28. (PMID: 30392411)
Nat Med. 2020 Apr;26(4):558-565. (PMID: 32251404)
Cereb Cortex. 2017 Nov 1;27(11):5415-5429. (PMID: 28968754)
Nature. 2017 Apr 26;545(7655):446-451. (PMID: 28445469)
Schizophr Bull. 2018 Jan 13;44(1):168-181. (PMID: 28338943)
Neuroimage. 2014 Jul 15;95:232-47. (PMID: 24657355)
Neuroimage. 2012 Feb 1;59(3):2142-54. (PMID: 22019881)
Neuroimage. 2014 Apr 15;90:449-68. (PMID: 24389422)
Neuroimage. 2023 Aug 15;277:120238. (PMID: 37364743)
Sci Adv. 2022 Mar 18;8(11):eabj1812. (PMID: 35294251)
Psychopharmacol Bull. 1988;24(1):112-7. (PMID: 3387514)
J Neurophysiol. 2011 Sep;106(3):1125-65. (PMID: 21653723)
Neuroimage. 2020 Nov 1;221:117126. (PMID: 32673748)
Am J Med Genet B Neuropsychiatr Genet. 2019 Jan;180(1):80-85. (PMID: 30516002)
Nat Rev Clin Oncol. 2017 Dec;14(12):749-762. (PMID: 28975929)
World Psychiatry. 2013 Oct;12(3):216-26. (PMID: 24096780)

K23 MH127300 United States MH NIMH NIH HHS; K23MH127300 U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH)

0 (Biomarkers)

Date Created: 20240104 Date Completed: 20240613 Latest Revision: 20240615

20240615

PMC11176002

10.1038/s41380-023-02381-9

38177349