Sexual dimorphism of midbrain catecholaminergic metabolism revealed by neuromelanin-sensitive MRI
Neuromelanin-sensitive magnetic resonance imaging (NM-MRI) is used as a proxy biomarker of midbrain catecholaminergic metabolism and synthesis capacity, particularly within dopaminergic nuclei. However, despite strong translational evidence for sexual dimorphism in dopaminergic systems, inconsistent sex differences in NM-MRI signal limit its interpretability as a non-invasive measure of catecholaminergic synthesis capacity. A source of variability may be the reliance on contrast-to-noise ratio (CNR) normalization, which presupposes NM-MRI signal stability within the reference region, canonically the crus cerebri. To address this limitation, the present study introduced a novel normalization framework combining a data-driven reference region with residual-based, rather than ratio-based, normalization. NM-MRI data were acquired in a transdiagnostic sample of 101 adults, aged 18-40 years, including individuals with elevated familial risk for bipolar disorder or major depressive disorder. Sex effects on NM-MRI signal were compared across the substantia nigra pars compacta (SNc), ventral tegmental area (VTA), and locus coeruleus (LC) using conventional crus cerebri-based CNR versus residual-based normalization. Residual-based normalization revealed higher NM-MRI signal in males compared with females across all catecholaminergic nuclei (SNc, VTA, LC; all adjusted p < 0.001). In contrast, conventional CNR normalization detected no sex differences in any region (all adjusted p > 0.20). Moreover, sex differences in NM-MRI signal were observed within the crus cerebri itself (p < 0.001), indicating that the canonical reference region is not biologically invariant. Sexual dimorphism in midbrain NM-MRI signal is revealed in vivo for the first time using a novel residual-based normalization framework. By reducing reference-region bias, this approach advances NM-MRI toward candidate biomarker deployment for assessing catecholaminergic dysfunction in psychiatric and neurological disorders.
Authors
- Helmet T. Karim (ORCID: https://orcid.org/0000-0002-9286-0694)
- Zachary Freyberg (ORCID: https://orcid.org/0000-0001-6460-0118)
- Megan Atkinson
- Simona Graur (ORCID: https://orcid.org/0000-0003-0063-1657)
- Manan Arora (ORCID: https://orcid.org/0009-0007-9756-9461)
- Michele A. Bertocci (ORCID: https://orcid.org/0000-0002-3857-1226)
- Mary L. Phillips (ORCID: https://orcid.org/0000-0003-4958-1291)
- Yui Asaoka (ORCID: https://orcid.org/0000-0002-0925-7430)
- Deepak K. Sarpal (ORCID: https://orcid.org/0000-0001-5842-6782)
- Robert Raeder (ORCID: https://orcid.org/0009-0003-8958-1330)
- Haris Aslam
- Luke T. Roberts
- Osasumwen Benjamin
- Richelle Stiffler
- Dominique L. DiDomenico (ORCID: https://orcid.org/0009-0001-5557-6969)
- Genna Bebko
- Chan Moon
- Yiming Wang
Institutions
- University of Pittsburgh (US)
- UPMC Health System (US)
- University of Pittsburgh Medical Center (US)
Publication Details
- Journal
- Molecular Psychiatry
- Published
- 2026-08-27
- DOI
- https://doi.org/10.1038/s41380-026-03841-8
- Primary Topic
- Advanced Neuroimaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institute of Mental Health