Investigating dopaminergic abnormalities in schizophrenia and first-episode psychosis with normative modelling and multisite molecular neuroimaging

the FDOPA PET imaging working group

doi:10.1038/s41380-025-02938-w

Investigating dopaminergic abnormalities in schizophrenia and first-episode psychosis with normative modelling and multisite molecular neuroimaging

the FDOPA PET imaging working group

Research output: Contribution to journal › Article › peer-review

Abstract

Molecular neuroimaging techniques, like PET and SPECT, offer invaluable insights into the brain’s in-vivo biology and its dysfunction in neuropsychiatric patients. However, the transition of molecular neuroimaging into diagnostics and precision medicine has been limited to a few clinical applications, hindered by issues like practical feasibility, high costs, and high between-subject heterogeneity of neuroimaging measures. In this study, we explore the use of normative modelling (NM) to identify individual patient alterations by describing the physiological variability of molecular functions. NM potentially addresses challenges such as small sample sizes and diverse acquisition protocols typical of molecular neuroimaging studies. We applied NM to two PET radiotracers targeting the dopaminergic system ([¹¹C]-(+)-PHNO and [¹⁸F]FDOPA) to create a reference-cohort model of healthy controls. The models were subsequently utilized on different independent cohorts of patients with psychosis in different disease stages and treatment outcomes. Our results showed that patients with psychosis exhibited a higher degree of extreme deviations (~3-fold increase) than controls, although this pattern was heterogeneous, with minimal overlap of extreme deviations topology (max 20%). We also confirmed that striatal [¹⁸F]FDOPA signal, when referenced to a normative distribution, can predict treatment response (striatal AUC ROC: 0.77–0.83). In conclusion, our results indicate that normative modelling can be effectively applied to molecular neuroimaging after proper harmonization, enabling insights into disease mechanisms and advancing precision medicine. In addition, the method is valuable in understanding the heterogeneity of patient populations and can contribute to maximising cost efficiency in studies aimed at comparing cases and controls.

Original language	English
Article number	e72904
Journal	Molecular Psychiatry
DOIs	https://doi.org/10.1038/s41380-025-02938-w
Publication status	Accepted/In press - 2025

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@article{df4963202f39434fbe8dd8b7af827bfa,

title = "Investigating dopaminergic abnormalities in schizophrenia and first-episode psychosis with normative modelling and multisite molecular neuroimaging",

abstract = "Molecular neuroimaging techniques, like PET and SPECT, offer invaluable insights into the brain{\textquoteright}s in-vivo biology and its dysfunction in neuropsychiatric patients. However, the transition of molecular neuroimaging into diagnostics and precision medicine has been limited to a few clinical applications, hindered by issues like practical feasibility, high costs, and high between-subject heterogeneity of neuroimaging measures. In this study, we explore the use of normative modelling (NM) to identify individual patient alterations by describing the physiological variability of molecular functions. NM potentially addresses challenges such as small sample sizes and diverse acquisition protocols typical of molecular neuroimaging studies. We applied NM to two PET radiotracers targeting the dopaminergic system ([11C]-(+)-PHNO and [18F]FDOPA) to create a reference-cohort model of healthy controls. The models were subsequently utilized on different independent cohorts of patients with psychosis in different disease stages and treatment outcomes. Our results showed that patients with psychosis exhibited a higher degree of extreme deviations (~3-fold increase) than controls, although this pattern was heterogeneous, with minimal overlap of extreme deviations topology (max 20%). We also confirmed that striatal [18F]FDOPA signal, when referenced to a normative distribution, can predict treatment response (striatal AUC ROC: 0.77–0.83). In conclusion, our results indicate that normative modelling can be effectively applied to molecular neuroimaging after proper harmonization, enabling insights into disease mechanisms and advancing precision medicine. In addition, the method is valuable in understanding the heterogeneity of patient populations and can contribute to maximising cost efficiency in studies aimed at comparing cases and controls.",

author = "{the FDOPA PET imaging working group} and Alessio Giacomel and Daniel Martins and Giovanna Nordio and Rubaida Easmin and Oliver Howes and Pierluigi Selvaggi and Williams, {Steven C.R.} and Federico Turkheimer and {De Groot}, Marius and Ottavia Dipasquale and Mattia Veronese and Luke Vano and Talbot, {Peter S.} and Grazia Rutigliano and Maria Rogdaki and Matthew Nour and Chiara Nosarti and Philip McGuire and Robert McCutcheon and Julian Matthews and James Maccabe and Seoyoung Kim and Euitae Kim and Stephen Kaar and Alice Egerton and Jecek Donocik and Arsime Demjaha and Enrico D{\textquoteright}Ambrosio and Tarik Dahoun and Faith Borgan and Ilaria Bonoldi and Micheal Bloomfield and Ilinca Angelescu",

note = "Publisher Copyright: {\textcopyright} Crown 2025.",

year = "2025",

doi = "10.1038/s41380-025-02938-w",

language = "English",

journal = "Molecular Psychiatry",

issn = "1359-4184",

publisher = "Springer Nature [academic journals on nature.com]",

}

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T1 - Investigating dopaminergic abnormalities in schizophrenia and first-episode psychosis with normative modelling and multisite molecular neuroimaging

AU - the FDOPA PET imaging working group

AU - Giacomel, Alessio

AU - Martins, Daniel

AU - Nordio, Giovanna

AU - Easmin, Rubaida

AU - Howes, Oliver

AU - Selvaggi, Pierluigi

AU - Williams, Steven C.R.

AU - Turkheimer, Federico

AU - De Groot, Marius

AU - Dipasquale, Ottavia

AU - Veronese, Mattia

AU - Vano, Luke

AU - Talbot, Peter S.

AU - Rutigliano, Grazia

AU - Rogdaki, Maria

AU - Nour, Matthew

AU - Nosarti, Chiara

AU - McGuire, Philip

AU - McCutcheon, Robert

AU - Matthews, Julian

AU - Maccabe, James

AU - Kim, Seoyoung

AU - Kim, Euitae

AU - Kaar, Stephen

AU - Egerton, Alice

AU - Donocik, Jecek

AU - Demjaha, Arsime

AU - D’Ambrosio, Enrico

AU - Dahoun, Tarik

AU - Borgan, Faith

AU - Bonoldi, Ilaria

AU - Bloomfield, Micheal

AU - Angelescu, Ilinca

PY - 2025

Y1 - 2025

N2 - Molecular neuroimaging techniques, like PET and SPECT, offer invaluable insights into the brain’s in-vivo biology and its dysfunction in neuropsychiatric patients. However, the transition of molecular neuroimaging into diagnostics and precision medicine has been limited to a few clinical applications, hindered by issues like practical feasibility, high costs, and high between-subject heterogeneity of neuroimaging measures. In this study, we explore the use of normative modelling (NM) to identify individual patient alterations by describing the physiological variability of molecular functions. NM potentially addresses challenges such as small sample sizes and diverse acquisition protocols typical of molecular neuroimaging studies. We applied NM to two PET radiotracers targeting the dopaminergic system ([11C]-(+)-PHNO and [18F]FDOPA) to create a reference-cohort model of healthy controls. The models were subsequently utilized on different independent cohorts of patients with psychosis in different disease stages and treatment outcomes. Our results showed that patients with psychosis exhibited a higher degree of extreme deviations (~3-fold increase) than controls, although this pattern was heterogeneous, with minimal overlap of extreme deviations topology (max 20%). We also confirmed that striatal [18F]FDOPA signal, when referenced to a normative distribution, can predict treatment response (striatal AUC ROC: 0.77–0.83). In conclusion, our results indicate that normative modelling can be effectively applied to molecular neuroimaging after proper harmonization, enabling insights into disease mechanisms and advancing precision medicine. In addition, the method is valuable in understanding the heterogeneity of patient populations and can contribute to maximising cost efficiency in studies aimed at comparing cases and controls.

AB - Molecular neuroimaging techniques, like PET and SPECT, offer invaluable insights into the brain’s in-vivo biology and its dysfunction in neuropsychiatric patients. However, the transition of molecular neuroimaging into diagnostics and precision medicine has been limited to a few clinical applications, hindered by issues like practical feasibility, high costs, and high between-subject heterogeneity of neuroimaging measures. In this study, we explore the use of normative modelling (NM) to identify individual patient alterations by describing the physiological variability of molecular functions. NM potentially addresses challenges such as small sample sizes and diverse acquisition protocols typical of molecular neuroimaging studies. We applied NM to two PET radiotracers targeting the dopaminergic system ([11C]-(+)-PHNO and [18F]FDOPA) to create a reference-cohort model of healthy controls. The models were subsequently utilized on different independent cohorts of patients with psychosis in different disease stages and treatment outcomes. Our results showed that patients with psychosis exhibited a higher degree of extreme deviations (~3-fold increase) than controls, although this pattern was heterogeneous, with minimal overlap of extreme deviations topology (max 20%). We also confirmed that striatal [18F]FDOPA signal, when referenced to a normative distribution, can predict treatment response (striatal AUC ROC: 0.77–0.83). In conclusion, our results indicate that normative modelling can be effectively applied to molecular neuroimaging after proper harmonization, enabling insights into disease mechanisms and advancing precision medicine. In addition, the method is valuable in understanding the heterogeneity of patient populations and can contribute to maximising cost efficiency in studies aimed at comparing cases and controls.

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U2 - 10.1038/s41380-025-02938-w

DO - 10.1038/s41380-025-02938-w

M3 - Article

AN - SCOPUS:85219039328

SN - 1359-4184

JO - Molecular Psychiatry

JF - Molecular Psychiatry

M1 - e72904

ER -

Investigating dopaminergic abnormalities in schizophrenia and first-episode psychosis with normative modelling and multisite molecular neuroimaging

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