Acid sphingomyelinase deficiency and Gaucher disease: Underdiagnosed and often treatable causes of hepatomegaly, splenomegaly, and low HDL cholesterol in lean individuals.

Background: Acid sphingomyelinase deficiency (ASMD) and Gaucher disease type 1 (GD1) are rare inherited sphingolipid disorders with multisystemic manifestations, including liver disease and dyslipidemia. Despite effective treatments, insufficient disease awareness frequently results in diagnostic delays during which irreversible complications occur. We delineated the shared and distinctive features of hepatic, splenic, and lipoprotein phenotypes in ASMD and GD1.

Biologically defined neuronal synuclein disease as a tool to advance drug development.

In a recent Viewpoint article (. 2024;81:789‒90), Okubadejo et al. raised concerns regarding two recent proposals for biological definitions and staging systems for synucleinopathies (the Neuronal Synuclein Disease Integrated Staging System and SynNeurGe system).

Accelerating Parkinson's Disease drug development with federated learning approaches.

Parkinson's Disease is a progressive neurodegenerative disorder afflicting almost 12 million people. Increased understanding of its complex and heterogenous disease pathology, etiology and symptom manifestations has resulted in the need to design, capture and interrogate substantial clinical datasets. Herein we advocate how advances in the deployment of artificial intelligence models for Federated Data Analysis and Federated Learning can help spearhead coordinated and sustainable approaches to address this grand challenge.

Disease progression strikingly differs in research and real-world Parkinson's populations.

Characterization of Parkinson's disease (PD) progression using real-world evidence could guide clinical trial design and identify subpopulations. Efforts to curate research populations, the increasing availability of real-world data, and advances in natural language processing, particularly large language models, allow for a more granular comparison of populations than previously possible. This study includes two research populations and two real-world data-derived (RWD) populations.

Disease progression strikingly differs in research and real-world Parkinson's populations.

Characterization of Parkinson's disease (PD) progression using real-world evidence could guide clinical trial design and identify subpopulations. Efforts to curate research populations, the increasing availability of real-world data and recent advances in natural language processing, particularly large language models, allow for a more granular comparison of populations and the methods of data collection describing these populations than previously possible. This study includes two research populations and two real-world data derived (RWD) populations.