Biology subjects

Klauser, P.

Publications and source records attributed to Klauser, P..

9 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

Mapping sex-specific hormone-metabolite coupling in the adolescent brain: a longitudinal whole-brain spectroscopic imaging study

Adolescence is marked by coordinated endocrine and brain maturation, yet how blood circulating steroid hormones relate to neurochemical change in the brain remains largely unknown. We combined longitudinal data from a novel fast whole-brain, high-resolution three-dimensional proton magnetic resonance spectroscopic imaging technique with repeated measurements of sexual hormones and adrenal steroids in the serum of 42 healthy adolescents (13-15 years; 24 females) totalizing 100 scan-visits. Longitudinal voxel-wise models separated within-individual changes from stable between-individual differences and controlled the false discovery rate across whole-brain tests. In the whole sample, increasing age was associated with higher N-acetylaspartate plus N-acetylaspartylglutamate within individuals, whereas age was positively associated with higher glutamate plus glutamine between individuals. We then observed a hormone-metabolite coupling that differed by sex and steroids. In males, within-individual increases in testosterone tracked frontal increases in glutamate plus glutamine and disseminated increases in total N-acetylaspartate. In females, higher mean estradiol between individuals was associated with higher frontal choline-containing compounds. Within-individual changes in cortisone were associated with myo-inositol and choline-containing compounds in a widespread sex-interaction effect, with positive coupling in males and negative in females. The cortisone/cortisol ratio showed a similar sex-interaction for choline-containing compounds. These findings reveal spatially distributed, sex-dependent links between steroid maturation and adolescent brain neurochemical composition and underscore the importance of differentiating within- and between-individual associations. These observational data extend predominantly structural descriptions of pubertal brain development by identifying distinct coupling of gonadal hormones with neuronal-metabolic markers and glucocorticoid interconversion with glia-weighted metabolites.

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↗

bioRxiv2025

Constructing the Human Brain Metabolic Connectome Using MR Spectroscopic Imaging: Insights into Biochemical Organization, Cytoarchitectonic Similarity and Gene Co-expression Networks

Network science has revolutionized our understanding of brain organization by revealing self-organizing patterns underlying its structural and functional connectivity. However, capturing metabolic contrast remains a challenge, leaving a critical gap in connectomics. Using advanced 3D whole-brain proton MR spectroscopic imaging with high spatial resolution and shortened acquisition times, we constructed the first human brain metabolic connectome in 51 healthy subjects, validated on an independent cohort (N=12) scanned at a different site. Our pipeline generates consistent and reliable metabolic similarity matrices. Upon further analysis, metabolic similarity networks display distinct topological features, notably a smoothly varying gradient delineating functionally and spatially distinct yet integrated brain regions via connector hubs. Although metabolic hubs correlate with structural hubs, overall alignment with structural connectivity is poor. However, metabolic organization aligns more closely with cytoarchitectonic and genetic co-expression patterns, suggesting a neurodevelopmental origin. This work puts forward the metabolic similarity gradient as a hallmark of the brains overarching biochemical organization, and provides a foundation for incorporating metabolite imaging into the broader domain of connectomics and its potential applications in health and disease.

neuroscience↗

bioRxiv2024

Mindfulness training impacts brain network dynamics linked to stress response in young adolescents.

Mindfulness-based interventions (MBI) may lead to lower levels of psychological distress, including depression, anxiety, and stress in adolescents. Past research has advanced the discovery of neural architecture recruited by MBI. However, the brain mechanisms through which mindfulness exerts more resilient responses to social stressors in teens remain unclear. Here, we examined how MBI modulates changes in brain network dynamics following social stress with different affective valence (i.e., neutral, negative, and positive). For this aim, we carried out a longitudinal randomized controlled trial in which non-clinical adolescents underwent MBI for 8 weeks. They completed a psychosocial stress task before and following MBI. Functional magnetic resonance imaging (fMRI) and self-reported measurements of psychological distress were collected in both measurement points (i.e., "pre" and "post" MBI). We computed co-activation patterns on fMRI data to characterize dynamic functional connectivity within whole-brain networks. The results depicted how MBI modulates transient co-activation changes in dorsal medial regions of the brain default network (DN) following the experience of stress. However, these brain changes were not specific to the affective valence of stressful stimuli. The relationship between the DN dynamics and the measurements of psychological distress was mediated by MBI. Globally, our findings support a model in which MBI causally mediate brain-behavior interactions related to psychosocial stress in adolescents.

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↗

bioRxiv2020

Whole-Brain High-Resolution Metabolite Mapping with 3D Compressed-Sensing-SENSE-LowRank 1H FID-MRSI

There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time which severely limits its applications for clinical or research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined fast Cartesian 1H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully-sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on the brain of three healthy volunteers resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a brain atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 Tesla MRI successful combinae of the 3D 1H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high-resolution over the whole brain, with an acquisition time suitable for clinical or research settings.

neuroscience↗

bioRxiv2020

Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort

BackgroundThe heterogeneity of schizophrenia has defied efforts to derive reproducible and definitive anatomical maps of structural brain changes associated with the disorder. We aimed to map deviations from normative ranges of brain structure for individual patients and evaluate whether the loci of individual deviations recapitulated group-average brain maps of schizophrenia pathology. MethodsFor each of 48 white matter tracts and 68 cortical regions, normative percentiles of variation in fractional anisotropy (FA) and cortical thickness (CT) were established using diffusion-weighted and structural MRI from healthy adults (n=195). Individuals with schizophrenia (n=322) were classified as either within the normative range for healthy individuals of the same age and sex (5-95% percentiles), infra-normal (<5% percentile) or supra-normal (>95% percentile). Repeating this classification for each tract and region yielded a deviation map for each individual. ResultsCompared to the healthy comparison group, the schizophrenia group showed widespread reductions in FA and CT, involving virtually all white matter tracts and cortical regions. Paradoxically, however, no more than 15-20% of patients deviated from the normative range for any single tract or region, whereas 79% of patients showed infra-normal deviations for at least one locus (healthy individuals: 59{+/-}2%, p<0.001). Higher polygenic risk for schizophrenia associated with a greater number of regions with infra-normal deviations in CT (r=-0.17, p=0.006). ConclusionsAnatomical loci of schizophrenia-related changes are highly heterogeneous across individuals to the extent that group-consensus pathological maps are not representative of most individual patients. Normative modeling can aid in parsing schizophrenia heterogeneity and guiding personalized interventions.

neuroscience↗