Biology subjects

Jenni, R.

Publications and source records attributed to Jenni, R..

4 recordsLinked to original sources

bioRxiv2026

MRSIPrep: A Standardized Post-Quantification Framework for Preprocessing Whole-Brain Magnetic Resonance Spectroscopic Imaging

Magnetic resonance spectroscopic imaging (MRSI) enables non-invasive mapping of neu-rometabolites levels across the human brain. Although spectral fitting and metabolite quan-tification are increasingly supported by mature software tools, the downstream processing of quantified metabolite maps remains heterogeneous across laboratories. Here, we introduce MRSIPrep, an open-source, modular, and reproducible post-quantification framework for whole-brain MRSI. MRSIPrep standardizes quality control, tissue correction, spatial nor- malization, atlas projection, and derivative generation from quantified metabolite maps and associated quality metrics. The framework produces voxelwise, regional, and connectomics-ready outputs together with automated quality-control reports. We describe the architecture of MRSIPrep and demonstrate its utility for reproducible MRSI analysis across datasets,acquisition protocols, and downstream applications.

neuroscience↗

bioRxiv2026

Sex differences in brain metabolism assessed with whole-brain magnetic resonance spectroscopic imaging

Sex differences in brain disorders span age at onset, symptom profiles, disease course and treatment response, and may partly reflect underlying differences in cellular metabolism. Indeed, in vivo evidence of sex-related neurometabolic variation remains sparse, with heterogenous and conflicting findings. Using fast high-resolution whole-brain three-dimensional magnetic resonance spectroscopic imaging, we mapped five brain metabolites in three independent cohorts of healthy participants (total n = 114). In a discovery sample of adolescents scanned at 3 Tesla (3T) (n = 61), males showed higher total N-acetylaspartate (tNAA) across widespread gray matter regions. Regional analyses further revealed opposing sex patterns with a complementary higher total creatine (tCr) observed in females, motivating examination of their ratio as an integrative metabolic index. The tNAA/tCr ratio was consistently higher in males in the discovery sample and this finding was replicated across two independent young-adult samples (3T, n = 26; 7T, n = 27), with a widespread gray and white matter distribution. This tNAA/tCr ratio may link neuronal mitochondrial metabolism with cellular energy buffering, positioning it as a potential index of bioenergetic balance relevant for conditions showing both sex differences and altered neurometabolism, notably multiple sclerosis, Alzheimer disease, and psychosis. Together, these findings reveal a reproducible, distributed metabolic sexual dimorphism in the human brain, and underscore the importance of accounting for sex-specific neurometabolic profiles in studies of brain health and disease.

neuroscience↗

bioRxiv2025

High-resolution whole-brain magnetic resonance spectroscopic imaging in youth at risk for psychosis

Advances in three-dimensional magnetic resonance spectroscopic imaging (3D-MRSI) allow for the high-resolution mapping of multiple neurometabolites throughout the entire brain in vivo and within clinically compatible time frames. Leveraging this capability, we created a voxel-based pipeline that corrects and spatially normalizes whole-brain maps of total N-acetylaspartate (tNAA), myo-inositol (Ins), choline compounds, glutamate + glutamine, and creatine + phosphocreatine. We examined 2 different 3D-MRSI dataset: first, a clinical sample of adolescents and young adults at risk for psychosis (n= 21) meeting DSM-5 criteria for Attenuated Psychosis Syndrome (APS) or Schizotypal Personality Disorder (SCZT), and age-/sex-matched healthy controls (n =13); and second, a non-clinical sample of adolescents (n = 61) scanned on a different site. The objective of the study was threefold: first, to assess the reproducibility of 3D-MRSI measures across datasets and scanning sites; second, to validate the feasibility of whole-brain, voxel-based analyses on 3D-MRSI data; and third, to test the sensitivity of this approach. Metabolite distributions showed reproducible regional variation in standard space between the two independent samples and scanning sites (r ranging from 0.82 to 0.99). Relative to controls, at-risk participants exhibited higher tNAA levels in frontal grey matter; the SCZT subgroup additionally displayed widespread cortical and subcortical elevations of Ins levels compared with both APS and controls. Voxel-based analyses of structural (i.e., gray and white matter volumes or densities) and diffusion (i.e., generalized fractional anisotropy) parameters yielded no significant differences between patients and controls. These preliminary findings suggest that high-resolution 3D-MRSI may be sensitive enough to detect subtle neurometabolic alterations at the group level in the early stages of psychotic disorders when structural or diffusion measures show no difference. High-resolution whole-brain metabolic mapping may have the potential to help with early identification of young people at risk for psychosis or other mental disorders.

neuroscience↗

bioRxiv2023

Brain network connectivity underlying remission in early psychosis: a whole brain model approach

BackgroundAlterations in brain connectivity occur early during psychosis and underlie the clinical manifestations of the illness as well as patient functioning and outcome. After a first episode of psychosis (FEP), different trajectories are possible and best described by the clinical-staging model that places the patient along a continuum of conditions: from non-remitting chronic symptoms to full-remission, often followed by relapses. However, little is known about the differences in brain connectivity that could underlie these differences in clinical outcome. MethodsIn this study, we included resting-state fMRI and DSI data from a cohort of 128 healthy controls (HC) and 88 patients with early psychosis (EP) stratified based on their ability to remit after the FEP. In particular we focused on differences between stage IIIb,c remitting-relapsing (EP3R) and stage IIIa non-remitting (EP3NR) patients. We investigated alterations in resting-state functional connectivity (FC), and combined information derived from fMRI and DSI into generative whole-brain models of each condition to explore the underlying mechanisms. ResultsOpposite alterations in FC could be found in patients as compared to HC, depending on their stage. In non-remitting patients (EP3NR), we observed a reduction of FC, aligned with the reduced structural connectivity found in previous studies, while remitting-relapsing patients (EP3R) showed increased FC, potentially indicating a relevant compensatory mechanism. By means of a whole-brain network model, we showed that in HC a subset of areas is characterized by increased stability to prevent an oversynchronisation of the network, while in EP3 patients such property is lost. This alteration was more relevant in the EP3R than in EP3NR patients, probably indicating a compensatory response to the reduced effective conductivity (global coupling) highlighted by the model in both EP3 conditions as compared to controls. ConclusionsThese findings highlight the significance of categorizing patients into subgroups based on the progression of their psychotic disorders, providing insights into the factors contributing to heterogeneity in functional alterations. They enhance our understanding of the interplay between structural and functional properties, shedding light on the mechanisms of psychosis emergence, remission and progression, with potential implications for future therapeutic advancements.

neuroscience↗