A human brain map of mitochondrial respiratory capacity and diversity.

Eugene V. Mosharov, Ayelet M. Rosenberg, Anna S. Monzel, Corey A. Osto, Linsey Stiles, Gorazd B. Rosoklija, Andrew J. Dwork, Snehal Bindra, Alex Junker, Ya Zhang, Masashi Fujita, Madeline B. Mariani, Mihran Bakalian, David Sulzer, Philip L. De Jager, Vilas Menon, Orian S. Shirihai, J. John Mann, Mark D. Underwood, Maura Boldrini, Michel Thiebaut de Schotten, Martin Picard
Nature. 2025-03-26; 641(8063): 749-758
DOI: 10.1038/s41586-025-08740-6

PubMed

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https://www.bordeaux-neurocampus.fr/11830

Mosharov EV(1)(2), Rosenberg AM(#)(1), Monzel AS(#)(1), Osto CA(3), Stiles L(3),
Rosoklija GB(2)(4), Dwork AJ(2)(4)(5), Bindra S(1), Junker A(1), Zhang Y(6),
Fujita M(6), Mariani MB(2)(4), Bakalian M(2)(4), Sulzer D(1)(2)(7), De Jager
PL(6), Menon V(6), Shirihai OS(3), Mann JJ(2)(4), Underwood MD(2)(4), Boldrini
M(2)(4), Thiebaut de Schotten M(8)(9), Picard M(10)(11)(12)(13).

Author information:
(1)Department of Psychiatry, Divisions of Molecular Therapeutics and Behavioral
Medicine, Columbia University Irving Medical Center, New York, NY, USA.
(2)New York State Psychiatric Institute, New York, NY, USA.
(3)Department of Medicine, Endocrinology, and Department of Molecular and
Medical Pharmacology, David Geffen School of Medicine, University of California
Los Angeles, Los Angeles, CA, USA.
(4)Department of Psychiatry, Division of Molecular Imaging and Neuropathology,
Columbia University Irving Medical Center, New York, NY, USA.
(5)Department of Pathology and Cell Biology, Columbia University, New York, NY,
USA.
(6)Center for Translational and Computational Neuroimmunology, Neuroimmunology
Division, Department of Neurology and the Taub Institute for Research on
Alzheimer’s Disease and the Aging Brain, Columbia University Irving Medical
Center, New York, NY, USA.
(7)Departments of Neurology and Pharmacology, Columbia University Irving Medical
Center, New York, NY, USA.
(8)Brain Connectivity and Behaviour Laboratory, Paris, France.
.
(9)Groupe d’Imagerie Neurofonctionnelle, Institut des Maladies
Neurodégénératives-UMR 5293, CNRS, CEA University of Bordeaux, Bordeaux, France.
.
(10)Department of Psychiatry, Divisions of Molecular Therapeutics and Behavioral
Medicine, Columbia University Irving Medical Center, New York, NY, USA.
.
(11)New York State Psychiatric Institute, New York, NY, USA.
.
(12)Department of Neurology, H. Houston Merritt Center, Columbia Translational
Neuroscience Initiative, Columbia University Irving Medical Center, New York,
NY, USA. .
(13)Robert N. Butler Columbia Aging Center, Columbia University Mailman School
of Public Health, New York, NY, USA. .
(#)Contributed equally

Erratum in
Nature. 2025 Jun;642(8067):E12. doi: 10.1038/s41586-025-09081-0.

Update of
bioRxiv. 2024 Mar 07:2024.03.05.583623. doi: 10.1101/2024.03.05.583623.
Res Sq. 2024 Mar 22:rs.3.rs-4047706. doi: 10.21203/rs.3.rs-4047706/v1.

Mitochondrial oxidative phosphorylation (OXPHOS) powers brain activity1,2, and
mitochondrial defects are linked to neurodegenerative and neuropsychiatric
disorders3,4. To understand the basis of brain activity and behaviour, there is
a need to define the molecular energetic landscape of the brain5-10. Here, to
bridge the scale gap between cognitive neuroscience and cell biology, we
developed a physical voxelization approach to partition a frozen human coronal
hemisphere section into 703 voxels comparable to neuroimaging resolution
(3 × 3 × 3 mm). In each cortical and subcortical brain voxel, we profiled
mitochondrial phenotypes, including OXPHOS enzyme activities, mitochondrial DNA
and volume density, and mitochondria-specific respiratory capacity. We show that
the human brain contains diverse mitochondrial phenotypes driven by both
topology and cell types. Compared with white matter, grey matter contains >50%
more mitochondria. Moreover, the mitochondria in grey matter are biochemically
optimized for energy transformation, particularly among recently evolved
cortical brain regions. Scaling these data to the whole brain, we created a
backwards linear regression model that integrates several neuroimaging
modalities11 to generate a brain-wide map of mitochondrial distribution and
specialization. This model predicted mitochondrial characteristics in an
independent brain region of the same donor brain. This approach and the
resulting MitoBrainMap of mitochondrial phenotypes provide a foundation for
exploring the molecular energetic landscape that enables normal brain function.
This resource also relates to neuroimaging data and defines the subcellular
basis for regionalized brain processes relevant to neuropsychiatric and
neurodegenerative disorders. All data are available at
http://humanmitobrainmap.bcblab.com .