Deep phenotyping for precision medicine in Parkinson's disease

Abstract

A major challenge in medical genomics is to understand why individuals with the same disorder have different clinical symptoms and why those who carry the same mutation may be affected by different disorders. In every complex disorder, identifying the contribution of different genetic and non-genetic risk factors is a key obstacle to understanding disease mechanisms. Genetic studies rely on precise phenotypes and are unable to uncover the genetic contributions to a disorder when phenotypes are imprecise. To address this challenge, deeply phenotyped cohorts have been developed for which detailed, fine-grained data have been collected. These cohorts help us to investigate the underlying biological pathways and risk factors to identify treatment targets, and thus to advance precision medicine. The neurodegenerative disorder Parkinson's disease has a diverse phenotypical presentation and modest heritability, and its underlying disease mechanisms are still being debated. As such, considerable efforts have been made to develop deeply phenotyped cohorts for this disorder. Here, we focus on Parkinson's disease and explore how deep phenotyping can help address the challenges raised by genetic and phenotypic heterogeneity. We also discuss recent methods for data collection and computation, as well as methodological challenges that have to be overcome.

Emerging perspectives on precision therapy for Parkinson’s disease: multidimensional evidence leading to a new breakthrough in personalized medicine

“…While the underlying disease mechanisms are still being debated, cohorts of deep phenotypes have been developed to collect detailed, fine-grained data. These cohorts will help us study the underlying biological pathways and risk factors in order to identify therapeutic targets for advancing precision medicine ( Schalkamp et al, 2022 ).…”

Navigating the Frontiers of Machine Learning in Neurodegenerative Disease Therapeutics

“…While the complexity of neurological disorders may partly explain the lack of success in drug development in this field, there is a growing amount of evidence supporting heterogeneity among patients with AD [ 14 , 15 , 16 , 17 , 18 ], ALS [ 19 , 20 , 21 ], and PD [ 22 , 23 , 24 ]. For sporadic forms of common neurological disorders, clinical diagnosis has been broadly applied, where patients present varying clinical features, including but not limited to disease onset and progression, symptomology, and clinical outcome.…”

Fox Insight at 5 years - a cohort of 54,000 participants contributing longitudinal patient-reported outcome, genetic, and microbiome data relating to Parkinson’s disease

“…The Fox Insight data is particularly useful in studies of disease phenotyping, disease progression and risk factor analysis requiring large participant cohorts 15 . Examples of research projects that have used data from Fox Insight include a study of deep phenotyping for precision medicine 25 , a study of sex differences in PD presentation and progression 26 , and a study of risk factors such as coffee consumption and smoking 27 .…”