This repository is under review for potential modification in compliance with Administration directives.
The AMP PD Knowledge Portal was developed to host and share resources related to Parkinson’s disease research and remains fully operational. We continue to maintain and accept Parkinson’s disease and related disorders data and resources throughout this review process.

Joseph Reddy, Ph.D., M.S.

Introduction

 I am a computational biologist in the Department of Quantitative Health Sciences at the Mayo Clinic in Jacksonville, FL. My research focuses on developing computational methods to analyze, integrate, and derive functional insights from multidimensional high-throughput datasets, with a particular emphasis on Alzheimer’s disease and related dementias (ADRD). I am especially interested in integrative approaches for analyzing multi-omic data to enable biomarker discovery and identification of therapeutic targets, with the overarching goal of advancing the detection, treatment, and prevention of complex diseases.

Joseph Reddy, PhD, MS

AMP PD Datasets & the Verily Workbench

Our team, in Dr. Nilufer Ertekin-Taner’s laboratory, is working on the AMP Systems Biology of Inflammation Pilot Project, to identify perturbed inflammatory pathways in dementia, aging, and other metabolic disorders such as type II diabetes and rheumatoid arthritis/systemic lupus erythematosus, utilizing all available transcriptomics data across the AMP programs. Towards identifying perturbed inflammatory pathways in Parkinson's disease (PD), we obtained and analyzed RNAseq data from the Parkinson’s Disease Biomarkers Program (PDBP) and Parkinson’s Progression Markers Initiative (PPMI) cohorts. We have since utilized the Verily Workbench to explore additional datasets for follow-up and replication studies to identify conserved and distinct inflammatory processes across these disorders.

Impact of the AMP PD Resources in My Work

Single-point access to wide-ranging omics measures from the AMP PD program and an environment with consensus processed, quality-controlled data along with analytic tools (R packages, Jupyter notebooks) enable integration of omics measures and available endophenotypes to explore and test hypotheses within the workbench, without the need to download and reprocess data or build expansive workflows. Continued access to the workbench will enable us to utilize new and existing data from PD cohorts, to better understand conserved molecular signatures across blood/brain and across AD/PD