AI Insight
Researchers developed a non-invasive MRI-based method called MitoBrainMap to predict mitochondrial features in living human brains without requiring labels or invasive procedures. The technique successfully detected age-related declines in mitochondrial density and respiratory capacity, identified specific mitochondrial abnormalities in patients with rare mitochondrial diseases including expected compensatory changes, and correlated brain mitochondrial features with blood markers of energetic stress and cognitive performance. The predicted mitochondrial maps showed biologically consistent relationships among different mitochondrial components, supporting the validity of this imaging approach.
Why it matters
This technology could enable researchers and clinicians to study mitochondrial dysfunction in living patients with neurodegenerative diseases, aging-related cognitive decline, and metabolic disorders without invasive biopsies. The ability to non-invasively map brain mitochondria may accelerate research into energy-related brain diseases and provide new biomarkers for monitoring disease progression and treatment responses.
⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Mitochondria support the bioenergetic processes that enable brain function and cognition, but we have lacked a label-free, non-invasive approach to explore how brain mitochondria are linked to ageing, disease, and cognition in humans. A recently introduced MitoBrainMap neuroimaging framework predicts mitochondrial features from magnetic resonance data alone, potentially bridging cellular biology with macroscale brain organization. Here, we tested whether this framework captures meaningful age- and pathology-related mitochondrial variation. Consistent with existing literature, we find that MR-predicted mitochondrial density and tissue respiratory capacity consistently declined with age, whereas mitochondrial respiratory capacity, an index of mitochondrial quality, was relatively preserved across the lifespan. Moreover, the relations among specific mitochondrial features predicted from our algorithm were consistent with their biological organization, supporting preliminary construct validity for MR-predicted mitochondrial features. In patients with rare mitochondrial diseases, predicted maps revealed region-specific alterations in mitochondrial density and respiratory chain components, particularly the expected compensatory upregulation of complex II, but not of other mitochondrial genome-encoded components. Finally, the MR-based mitochondrial features were associated with the energetic stress marker GDF15 measured in blood, as well as with cognitive performance measures, linking the novel predictions of brain mitochondria to systemic stress and behavior. These findings introduce a first-generation, label-free, neuroimaging-based mitochondrial mapping as a non-invasive window into living human brain mitochondria.