Abstract
Parkinson's disease (PD) is an example for a complex field of research, which is driven by the multifactorial etiology, the heterogeneity in phenotype and the variability in disease progression, as well as the presence of a long pre-diagnostic period, called prodromal PD, lasting up to decades (Postuma et al., 2010). The very slow, so far inevitably progressive, neurodegenerative process and the multidimensional heterogeneity of symptoms in kind (motor and non-motor), time of onset and speed of progression call for prediction markers and progression markers to understand the onset of neurodegeneration and its course. These markers would also help to establish endpoints for neuroprotective treatment strategies aiming to modify disease progression. Because of the complexity, heterogeneity, and the progressive nature of PD, such predictive and progression markers can only be identified in large cohorts and in studies with a longitudinal design. A considerable number of longitudinal cohort studies in PD patients, as well as in individuals at risk, are currently being performed, and extensive effort has gone into the characterization of the individuals assessed. Although each study has its own value and merits, many important research questions cannot be answered as the numbers of participants are too small (e.g., when studying conversion to PD in at-risk populations). Moreover, the pivotal combination of data and findings across studies is hampered by the lack of comparability of symptoms/factors that are being assessed and the specific assessments that are being applied. Therefore, a common approach is needed to enable harmonization and combination of data across studies to define and validate predictive and progression markers. Based on the need for harmonized assessments of symptoms/markers in PD, the working group: Harmonization of biomarker assessment in longitudinal cohort studies in Parkinson's Disease (BioLoC-PD) of the Joint Programme for Neurodegenerative Diseases (JPND), set out to develop an assessment battery that includes the most useful clinical, laboratory, and brain imaging assessments for (longitudinal) studies in PD. We here describe the result of the process to find a way to harmonize assessments across studies and propose a modular set of biomarker assessments agreed upon by the group of experts who were included in the working group (all authors of this manuscript).
Highlights
Parkinson’s disease (PD) is an example for a complex field of research, which is driven by the multifactorial etiology, the heterogeneity in phenotype and the variability in disease progression, as well as the presence of a long pre-diagnostic period, called prodromal PD, lasting up to decades (Postuma et al, 2010)
Functions used in all PD studies are at the beginning of each of the lists
Regarding the use of the Mini-Mental State Examination (MMSE) or Montreal Cognitive Assessment (MoCA), we found that the MMSE is more often applied in existing studies but for new studies we clearly recommend to use the MoCA
Summary
Parkinson’s disease (PD) is an example for a complex field of research, which is driven by the multifactorial etiology, the heterogeneity in phenotype and the variability in disease progression, as well as the presence of a long pre-diagnostic period, called prodromal PD, lasting up to decades (Postuma et al, 2010). The very slow, so far inevitably progressive, neurodegenerative process and the multidimensional heterogeneity of symptoms in kind (motor and non-motor), time of onset and speed of progression call for prediction markers and progression markers to understand the onset of neurodegeneration and its course. These markers would help to establish endpoints for neuroprotective treatment strategies aiming to modify disease progression. A considerable number of longitudinal cohort studies in PD patients, as well as in individuals at risk, are currently being performed, and extensive effort has gone into the characterization of the Modular Assessment Set in Parkinson’s Disease individuals assessed. A common approach is needed to enable harmonization and combination of data across studies to define and validate predictive and progression markers
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have