Despite 200 years of research, the molecular etiology of Parkinson disease (PD) remains unknown. Moreover, clinical trials of potential disease-modifying agents have been invariably unsuccessful, in spite of encouraging preclinical results. A major bottleneck hindering breakthroughs in PD research is the disorder’s vast biological heterogeneity.
To understand and combat PD, we need to decode disease heterogeneity and reclassify the disorder in a biologically meaningful manner, reflecting the underlying molecular pathogenesis. We propose DECODE-PD, a groundbreaking and highly transdisciplinary discovery platform integrating detailed clinicopathological data with high-resolution multi-omics, computational science and population registries. At the heart of DECODE-PD, advanced computational algorithms comprising supervised and unsupervised approaches, will extract molecular signatures underlying the pathogenesis of PD and subclassify the disorder into clusters based on molecular similarity. Being free of human “mislabeling”, this approach will mitigate the problem of heterogeneity and enable us to identify molecularly homogeneous subclasses of disease that can be targeted by tailored therapies. Thus, the outcome of these studies will enable major mechanistic and therapeutic breakthroughs including: 1) Elucidate the molecular pathways driving neurodegeneration in PD; 2) Develop precision biomarkers for accurate diagnosis, prognosis and molecular patient stratification in clinical practice; 3) Identify therapeutic targets tailored to the molecular profile of patients and nominate candidate drugs for clinical trials. Biomarkers and therapeutic targets emerging from these studies will lead to commercialization and value generation via collaborations with the industry. We expect this work to have a substantial impact on patient care and society by helping address PD, one of the most common and devastating diseases on a global scale.