About NeuroHub
Deep expertise across neurodegenerative diseases.
NeuroHub Analytics LLC was founded to help research teams extract clinically meaningful insight from complex biomedical data.
Dr. Jose A. Santiago has over 15 years of experience analyzing high-throughput data to tackle complex questions across neurodegenerative diseases.
His work spans Parkinson’s disease, Alzheimer’s disease, amyotrophic lateral sclerosis (ALS), atypical parkinsonian disorders, and other neurodegenerative conditions. He has uncovered molecular markers useful for diagnosing Parkinson’s disease and distinguishing it from atypical parkinsonian disorders, biomarkers of disease progression, and prognostic models designed to identify patients at greater risk of clinical decline.
Dr. Santiago has authored numerous peer-reviewed publications focused on neurodegeneration. He is recognized for his work on diagnostic biomarkers for Parkinson’s disease and for elucidating molecular pathways that link Parkinson’s disease and diabetes.
His experience includes biomarker replication and validation across multiple independent clinical cohorts and research programs: Prognostic and Diagnostic Biomarkers for Parkinson’s Disease (PROBE), the Harvard Biomarker Study (HBS), the Parkinson’s Precision Medicine Initiative (PPMI), the Parkinson’s Associated Risk Syndrome Study (PARS), and the Parkinson’s Disease Biomarker Program (PDBP).
Dr. Santiago has employed network-based approaches to decode the molecular links between metabolic diseases and neurodegeneration. He has also studied how disease comorbidities and lifestyle factors may influence the pathogenesis and progression of neurodegenerative diseases.
Through NeuroHub Analytics LLC, he works with investigators and organizations that need to move from a large, complicated dataset to a clear scientific conclusion, a reproducible model, or a focused validation strategy.
How NeuroHub approaches the work
Start with the clinical question
The model is only useful if its endpoint, population, and intended application are clearly defined.
Make the analysis auditable
Assumptions, preprocessing, model choices, sensitivity analyses, and limitations should be visible—not buried.
Demand replication
Promising signals should be evaluated across cohorts, modalities, and plausible confounders before they are treated as discoveries.
Translate without overclaiming
The strongest scientific story is specific about what the data support and equally clear about what must happen next.
Let’s make the data answer the right question.
Explore consulting support for biomarker discovery, multimodal analysis, and neurodegenerative disease research.