A 20-Year Longitudinal Study of Plasma Chitotriosidase Activity in Treated Gaucher Disease Type 1 and 3 Patients—A Qualitative and Quantitative Approach

Fabry Disease: Cardiac Implications and Molecular Mechanisms

PURPOSE OF REVIEW

This review explores the interplay among metabolic dysfunction, oxidative stress, inflammation, and fibrosis in Fabry disease, focusing on their potential implications for cardiac involvement. We aim to discuss the biochemical processes that operate in parallel to sphingolipid accumulation and contribute to disease pathogenesis, emphasizing the importance of a comprehensive understanding of these processes.

RECENT FINDINGS

Beyond sphingolipid accumulation, emerging studies have revealed that mitochondrial dysfunction, oxidative stress, and chronic inflammation could be significant contributors to Fabry disease and cardiac involvement. These factors promote cardiac remodeling and fibrosis and may predispose Fabry patients to conduction disturbances, ventricular arrhythmias, and heart failure. While current treatments, such as enzyme replacement therapy and pharmacological chaperones, address disease progression and symptoms, their effectiveness is limited. Our review uncovers the potential relationships among metabolic disturbances, oxidative stress, inflammation, and fibrosis in Fabry disease-related cardiac complications. Current findings suggest that beyond sphingolipid accumulation, other mechanisms may significantly contribute to disease pathogenesis. This prompts the exploration of innovative therapeutic strategies and underscores the importance of a holistic approach to understanding and managing Fabry disease.

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways

Background

To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies.

Methods

We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models.

Findings

We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aβ42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89).

Interpretation

Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs.

Funding

Proteomic data generation was supported by NIH: RF1AG044546.