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Mario Tranfa

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3 papers
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3

YNICL Journal 2026 Journal Article

Blood-brain barrier water exchange in relation to amyloid, cognition and cerebrovascular burden

  • Beatriz E. Padrela
  • Sandra Tecelão
  • Bjørn-Eivind Kirsebom
  • Oliver Geier
  • Mario Tranfa
  • Federico Masserini
  • Markus H. Sneve
  • Maksim Slivka

Blood-brain barrier (BBB) water exchange may serve as a sensitive early biomarker for Alzheimer's disease and age-related cognitive decline. This study applied a non-invasive multi-echo arterial spin labeling (ASL) technique to measure BBB water exchange time (Tex), cerebral blood flow (CBF), and arterial transit time (ATT) in 160 adults aged 50 years and older. Participants were classified as cognitively normal (CN), having subjective cognitive decline (SCD), or mild cognitive impairment (MCI). They were assessed for amyloid status and cerebrovascular burden. Compared to CN participants, Tex was significantly lower in both SCD (-9.5 %) and MCI (-14.5 %) groups, suggesting that reductions in BBB water exchange emerge early in the course of cognitive decline. In contrast, CBF was reduced only in MCI participants (-20.8 % compared to CN), and ATT was significantly increased only in individuals with severe cerebrovascular burden (Fazekas score 3). Notably, Tex showed a stepwise decrease with increasing Fazekas scores (1-2), supporting its sensitivity to moderate small vessel disease. No associations were found between Tex and amyloid positivity after adjusting for age and sex. These findings indicate that Tex alterations may precede changes in traditional perfusion markers and are more closely related to vascular and early cognitive changes than to amyloid pathology. BBB water exchange mapping may therefore provide a promising, non-invasive tool to detect early neurovascular dysfunction that contributes to cognitive decline in aging populations, potentially offering a useful biomarker for early intervention trials targeting vascular contributions to dementia.

YNICL Journal 2025 Journal Article

Amyloid PET predicts atrophy in older adults without dementia: Results from the AMYPAD Prognostic & Natural History study

  • Leonard Pieperhoff
  • Luigi Lorenzini
  • Sophie Mastenbroek
  • Mario Tranfa
  • Mahnaz Shekari
  • Alle Meije Wink
  • Robin Wolz
  • Sylke Grootoonk

Highlights • Aβ-PET predicts atrophy in key brain regions in older adults without dementia.• Fusiform volumetric loss is linked to Aβ independent of CSF tau levels.• Temporal atrophy is stronger in women with higher Aβ burden.• APOE-ε4 carriers show larger Aβ-driven frontal & hippocampal atrophy.

YNIMG Journal 2025 Journal Article

White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life

  • Max Korbmacher
  • Mario Tranfa
  • Giuseppe Pontillo
  • Dennis van der Meer
  • Meng-Yun Wang
  • Ole A. Andreassen
  • Lars T. Westlye
  • Ivan I. Maximov

Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complementary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno- and phenotypes is still debated. Hence, we investigate how tract-based and whole WM skeleton parameters from different dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52,140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5,844). In general, none of the imaging approaches could explain all examined phenotypes, though the approaches were overall similar in explaining variability of the examined phenotypes. Nevertheless, particular diffusion parameters of the used dMRI approaches stood out in explaining some important phenotypes known to correlate with general human health outcomes. A multi-compartment Bayesian dMRI approach provided the strongest WM associations with age, and together with diffusion tensor imaging, the largest accuracy for sex-classifications. We find a similar pattern of metric and tract-dependent asymmetries across datasets, with stronger asymmetries in ABCD data. The magnitude of WM associations with polygenic scores as well as PP depended more on the sample, and likely age, than dMRI metrics. However, kurtosis was most indicative of BMI and potentially of bipolar disorder polygenic scores. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life.

v2026.09.13