Biology subjects

Frodl, T.

Publications and source records attributed to Frodl, T..

4 recordsLinked to original sources

bioRxiv2026

Multimodal evidence for impaired glymphatic brain clearance as a mediator of "inflammaging" in schizophrenia - integrating insights from in vivo neuroimaging, omics, and post-mortem single nucleus-RNA-Seq data

Persistent cognitive impairment and reduced life expectancy in schizophrenia may arise from inflammation-driven accelerated aging ("inflammaging"), yet the underlying mechanisms remain unclear. Impaired glymphatic clearance, dependent on polarized aquaporin-4 (AQP4) localization at astrocytic endfeet, offers a plausible mechanistic link between inflammation and brain aging. Here, we integrate in vivo neuroimaging with post-mortem single-nucleus transcriptomics from distinct patient cohorts to demonstrate glymphatic dysfunction in schizophrenia and define its molecular basis. We identify reduced astrocytic expression of components of the dystrophin-associated protein complex (SNTA1, DAG1) required for AQP4 polarization. Both in vivo neuroimaging and post-mortem gene expression signatures of glymphatic dysfunction are restricted to an inflammatory subgroup characterized by peripheral immune activation and pro-inflammatory glial transcriptional profiles. Moreover, imaging signatures of glymphatic impairment are associated with schizophrenia polygenic risk scores enriched for immune - and oxidative stress - related aging pathways as well as cognitive dysfunction. At the cellular level, glymphatic dysfunction coincides with loss of homeostatic programs in microglia and astrocytes, increased inflammatory signaling, and endothelial signatures of blood-brain barrier disruption. Across modalities, glymphatic impairment is linked to accelerated aging, including increased brain and epigenetic age, and aging-related gene expression signatures.

neuroscience↗

bioRxiv2023

Normative Modeling of Brain Morphometry Across the Lifespan using CentileBrain: Algorithm Benchmarking and Model Optimization

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).

bioinformatics↗

bioRxiv2019

Brain Aging in Major Depressive Disorder: Results from the ENIGMA Major Depressive Disorder working group

BackgroundMajor depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in MDD patients, and whether this process is associated with clinical characteristics in a large multi-center international dataset. MethodsWe performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 29 samples worldwide. Normative brain aging was estimated by predicting chronological age (10-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 1,147 male and 1,386 female controls from the ENIGMA MDD working group. The learned model parameters were applied to 1,089 male controls and 1,167 depressed males, and 1,326 female controls and 2,044 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain predicted age difference (brain-PAD). FindingsOn average, MDD patients showed a higher brain-PAD of +0.90 (SE 0.21) years (Cohens d=0.12, 95% CI 0.06-0.17) compared to controls. Relative to controls, first-episode and currently depressed patients showed higher brain-PAD (+1.2 [0.3] years), and the largest effect was observed in those with late-onset depression (+1.7 [0.7] years). In addition, higher brain-PAD was associated with higher self-reported depressive symptomatology (b=0.05, p=0.004). InterpretationThis highly powered collaborative effort showed subtle patterns of abnormal structural brain aging in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the predictive value of these brain-PAD estimates. FundingThis work was supported, in part, by NIH grants U54 EB020403 and R01 MH116147.

neuroscience↗

bioRxiv2019

10Kin1day: A bottom-up neuroimaging initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

neuroscience↗