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      Aiming for Study Comparability in Parkinson's Disease: Proposal for a Modular Set of Biomarker Assessments to be Used in Longitudinal Studies

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          Abstract

          Introduction 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). Materials and methods As a first step, information about the design, markers, and assessments of 21 ongoing cohort studies in various phases of PD represented by members of the JPND working group were collected using a detailed questionnaire. These data served as a basis for the project. Detailed results have been reported previously in Lerche et al. (2015). In a second step, a systematic literature search on assessments and markers in the prodromal and clinical phases of PD was conducted to determine the most useful predictive and progression markers in PD. The outcome of this literature search was combined with the study information derived from the BioLoC-PD studies and the expert clinical knowledge of the principal investigators in their clinical routine. This information were used to establish the proposed assessment battery. A common modular set of biomarker assessments was defined that includes a basic module and different modules for extension, in order to account for the differences in research focus between studies. Results Composition of a modular set of biomarker assessments Based on the analyses, the JPND BioLoC-PD working group suggests the following three-level modular assessment battery to be implemented in new and whenever possible ongoing longitudinal studies for PD (Figure 1). The set comprises a basic module (demographics, diagnosis, etc.), a minimum function and assessment module and several optional extension modules. Figure 1 Suggestion for a modular set of biomarker assessments to be used in longitudinal studies in PD. The number of studies using the assessment in the BioLoC-PD consortium are given in brackets. The basic module is meant to be applied to all participants in longitudinal studies in PD. It may also be applied to existing registers and patients seen routinely in outpatient clinics irrespective of whether they are currently recruited for a longitudinal study. It may also be used for retrospective analyses or identification of potential eligible participants for future randomized controlled trials. The minimum module is suitable for all individuals participating in at risk, prodromal, and clinical longitudinal studies of PD. The functions of the minimum module are in a descending order (sorted by their use within the BioLoC-PD working group). Functions used in all (risk, prodromal, and clinical) PD studies are at the beginning of each of the lists (in the minimum and extension modules). Modes of assessment of these symptoms are based on the frequency and applicability within studies (easy to apply assessments, which still provide sufficient information were preferred). Each of the assessments suggested for the minimum module (Figure 1) takes no more than 10 min, depending on the cognitive capacity of the study participant. For some functions (neuropsychiatric and olfactory), two optional assessments are suggested from which one can be chosen. This is because they are used in almost equal proportion in ongoing studies and are similarly tolerable for the participants. For the neuropsychiatric function we recommend to use the BDI in prodromal studies and in early stage PD studies and the GDS in late stage PD studies. For olfaction two assessments are given because they are used in almost equal proportion in ongoing studies are similarly tolerable for the participants. However, the first mentioned suggestion, is slightly preferred by the BioLoC-PD consortium (used more often). Regarding the use of the MMSE or MoCA, we found that the MMSE is more often applied in existing studies but for new studies we clearly recommend to use the MoCA. The optional extension module can be applied to evaluate study participants in more detail. The selection of the additional function modules depends on the main research focus of the study, on the number of study participants and on the available staff and finance. Optional modules can be applied to interesting sub-groups of participants, if financial or pragmatic/practical factors hinder administration to the whole cohort. The assessments included in the extension modules were chosen based on their implementation in the ongoing BioLoC-PD studies. For each subdomain within the extension modules, the most commonly used assessment is suggested in addition to the minimum module (e.g., motor → gait and balance → accelerometer). In case of the imaging module the methods are in a descending order with the one on the top preferred by the BioLoC-PD consortium. Application of the modular set of biomarker assessments We propose, that each study should as a minimum requirement collect the data specified in the basic module. The basic module is valuable also for genetic or other non-clinical analyses. Once individuals are clinically examined, several motor and non-motor domains should be covered, as suggested in the minimum module which also comprises additional data about medical history. Finally, according to the main research aim of the study, different extension modules can be added. In general, we provide researchers with suggestions for specific assessment tools/scales to allow comparison across studies. For the cognition module, however, it is less important which assessments are used rather, it is important to take a minimum of two tests per domain for a sensitive and specific diagnosis of dementia and Mild Cognitive Impairment (MCI) level II (Goldman et al., 2015). For cognitive analyses, a comparison of studies with different assessments will then be possible by comparing the domain z-scores (Aarsland et al., 2010), equipercentile or item response theory modeling or by using existing conversion algorithms (e.g., conversion between the MMSE and MOCA tests (Lawton et al., 2016)). A list of neuropsychological tests suitable for the optional cognitive extension module can be found in Goldman et al. (2015) and Litvan et al. (2012). Discussion The inventory of assessments used in ongoing longitudinal studies within the working group revealed that there is a consensus about the functions/domains that should be assessed in PD cohort studies, but not about the nature of specific assessments used. The variability in the choice of the assessments may be explained by a number of different factors: (i) Not all scales/questionnaires are available and validated in all languages. (ii) Study designs vary with regard to outcome variables which influences the choice of assessments. (iii) Some assessments require more resources than others (more time-consuming, more costly or requiring trained staff members), which also influenced the selection and composition of the selected assessment battery. (iv) Advances in knowledge about assessments and biomarkers have led to revision or expansion of assessments after the respective study was initiated. (v) Preference for a specific assessment based on previous experience of the individual researchers involved. With our proposed modular set of biomarker assessments, we propose a concept by which we hope to overcome the problem of data comparison due to lack of harmonization and set the stage for broad data sharing, joint data analyses and acceleration of biomarker research. Author contributions SL, SH, GA, PB, SB, YBS, HB, BRB, DBu, RD, DG, GH, MH, MK, RK, ILS, WM, MM, BM, WO, BR, UW, KW, DBe substantial contributed to the conception and design of the work; SL, SH, DBe drafted the work; GA, PB, SB, YBS, HB, BRB, DBu, RD, DG, GH, MH, MK, RK, ILS, WM, MM, BM, WO, BR, UW, KW revised the work critically for important intellectual content; SL, SH, GA, PB, SB, YBS, HB, BRB, DBu, RD, DG, GH, MH, MK, RK, ILS, WM, MM, BM, WO, BR, UW, KW, DBe gave their final approval to the version to be published; SL, SH, GA, PB, SB, YBS, HB, BRB, DBu, RD, DG, GH, MH, MK, RK, ILS, WM, MM, BM, WO, BR, UW, KW, DBe agreed to be accountable for all aspects of the work. Funding The work was funded by the EU Joint Programme—Neurodegenerative Disease Research (JPND) program (BMBF No:01ED1410). Conflict of interest statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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          Mild cognitive impairment in Parkinson disease: a multicenter pooled analysis.

          In studies of mild cognitive impairment (MCI) in Parkinson disease (PD), patients without dementia have reported variable prevalences and profiles of MCI, likely to be due to methodologic differences between the studies. The objective of this study was to determine frequency and the profile of MCI in a large, multicenter cohort of well-defined patients with PD using a standardized analytic method and a common definition of MCI. A total of 1,346 patients with PD from 8 different cohorts were included. Standardized analysis of verbal memory, visuospatial, and attentional/executive abilities was performed. Subjects were classified as having MCI if their age- and education-corrected z score on one or more cognitive domains was at least 1.5 standard deviations below the mean of either control subjects or normative data. A total of 25.8% of subjects (95% confidence interval [CI] 23.5-28.2) were classified as having MCI. Memory impairment was most common (13.3%; 11.6-15.3), followed by visuospatial (11.0%; 9.4-13.0) and attention/executive ability impairment (10.1%; 8.6-11.9). Regarding cognitive profiles, 11.3% (9.7-13.1) were classified as nonamnestic single-domain MCI, 8.9% (7.0-9.9) as amnestic single-domain, 4.8% (3.8-6.1) as amnestic multiple-domain, and 1.3% (0.9-2.1) as nonamnestic multiple-domain MCI. Having MCI was associated with older age at assessment and at disease onset, male gender, depression, more severe motor symptoms, and advanced disease stage. MCI is common in patients with PD without dementia, affecting a range of cognitive domains, including memory, visual-spatial, and attention/executive abilities. Future studies of patients with PD with MCI need to determine risk factors for ongoing cognitive decline and assess interventions at a predementia stage.
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            The optimal properties of a comprehensive (level II) neuropsychological battery for determining Parkinson's disease mild cognitive impairment (PD-MCI) by Movement Disorder Society (MDS) Task Force criteria remain unresolved.
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              Clinical prediction of Parkinson's disease: planning for the age of neuroprotection.

              As a chronic progressive disease, Parkinson's disease (PD) has a presymptomatic interval; that is, a period during which the pathological process has begun, but motor signs required for the clinical diagnosis are absent. The ability to identify this preclinical stage may be critical in the development and eventual use of neuroprotective therapy. Recently proposed staging systems of PD have suggested that degeneration may occur initially in areas outside the substantia nigra, suggesting that non-motor manifestations may be markers of presymptomatic PD. Decreased olfaction has recently been demonstrated to predict PD in prospective pathological studies, although the lead time may be relatively short, and the positive predictive value is low. Idiopathic RBD has a very high predictive value, with approximately 50% of affected individuals developing PD or dementia within 10 years. This implies that idiopathic RBD patients are ideal candidates to test potential preclinical markers. However, the specificity of symptom screens for RBD is not established, not all persons with PD develop RBD, and there are only limited ways to predict which RBD patients will develop PD. Other simple screens based upon autonomic symptoms, depression and personality changes, quantitative motor testing and other sleep disorders may also be useful markers, but have not been extensively tested. Other more expensive measures such as detailed autonomic testing, cardiac MIBG-scintigraphy, dopaminergic imaging and transcranial ultrasound may be especially useful in defining disease risk in those identified through primary screening.
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                Author and article information

                Contributors
                Journal
                Front Aging Neurosci
                Front Aging Neurosci
                Front. Aging Neurosci.
                Frontiers in Aging Neuroscience
                Frontiers Media S.A.
                1663-4365
                27 May 2016
                2016
                : 8
                : 121
                Affiliations
                [1] 1Center of Neurology, Department of Neurodegeneration and Hertie-Institute for Clinical Brain Research, University of Tuebingen Tuebingen, Germany
                [2] 2German Center for Neurodegenerative Diseases, University of Tuebingen Tuebingen, Germany
                [3] 3Norwegian Centre for Movement Disorders, Stavanger University Hospital Stavanger, Norway
                [4] 4Neuroscience Section, Center for Neurodegenerative Diseases (CEMAND), Department of Medicine and Surgery, University of Salerno Salerno, Italy
                [5] 5Department of Neurology, Saarland University Hospital Homburg, Germany
                [6] 6School of Social and Community Medicine, University of Bristol Bristol, UK
                [7] 7Department of Neurology and Neuroscience Campus Amsterdam, VU University Hospital Amsterdam, Netherlands
                [8] 8Department of Neurology, Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior Nijmegen, Netherlands
                [9] 9Institute of Neuroscience, Newcastle University Newcastle, UK
                [10] 10Department of Neurology, Philipps-Universität Marburg Marburg, Germany
                [11] 11Institute of Neurological Sciences, Queen Elizabeth University Hospital Glasgow, UK
                [12] 12Clinical and Experimental Neuroscience, Luxembourg Centre for Systems Biomedicine, University of Luxembourg Belval, Luxembourg
                [13] 13Centre Hospitalier Luxembourg Luxembourg, Luxembourg
                [14] 14Nuffield Department of Clinical Neurosciences, Oxford Parkinson's Disease Centre, University of Oxford Oxford, UK
                [15] 15Institute of Neurogenetics, University of Lübeck Lübeck, Germany
                [16] 16Paracelsus-Elena-Klinik Kassel, Germany
                [17] 17University Medical Center, Georg-August-Universität Göttingen Göttingen, Germany
                [18] 18Department of Neurology, University of Rostock Rostock, Germany
                [19] 19Department of Epidemiology and Biostatistics, Karolinska Institutet Stockholm, Sweden
                [20] 20Department of Clinical Neuroscience, Karolinska Institutet Stockholm, Sweden
                [21] 21Department of Neurology, Christian-Albrechts University Kiel, Germany
                Author notes

                Edited by: J. Arturo García-Horsman, University of Helsinki, Finland

                Reviewed by: Claire O'Callaghan, University of Cambridge, UK; Lena Köstering, University of Freiburg, Germany

                *Correspondence: Stefanie Lerche stefanie.lerche@ 123456uni-tuebingen.de

                †These authors have contributed equally to this work.

                Article
                10.3389/fnagi.2016.00121
                4882324
                27303289
                94e18bac-ccbc-4253-bd0e-271e984f3e5c
                Copyright © 2016 Lerche, Heinzel, Alves, Barone, Behnke, Ben-Shlomo, Berendse, Bloem, Burn, Dodel, Grosset, Hipp, Hu, Kasten, Krüger, Liepelt-Scarfone, Maetzler, Moccia, Mollenhauer, Oertel, Roeben, Walter, Wirdefeldt and Berg.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 21 March 2016
                : 12 May 2016
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 6, Pages: 4, Words: 2472
                Funding
                Funded by: BMBF 10.13039/501100002347
                Award ID: 01ED1410
                Categories
                Neuroscience
                Opinion

                Neurosciences
                parkinson's disease,marker,harmonization,cohort studies
                Neurosciences
                parkinson's disease, marker, harmonization, cohort studies

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