SIC Task Force appraisal of clinical diagnostic criteria for parkinsonian disorders

Litvan, Irene; Bhatia, Kailash P.; Burn, David J.; Goetz, Christopher G.; Lang, Anthony E.; McKeith, Ian G.; Quinn, Niall; Sethi, Kapil D.; Shults, Cliff; Wenning, Gregor K.

doi:10.1002/mds.10459

Cited by 905 publications

(636 citation statements)

References 129 publications

(188 reference statements)

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“…For cohort studies, definition of PD diagnosis, exposure ascertainment and the choice of the non-exposed comparison groups are key factors. Diagnostic criteria are another potentially important source of bias, as reviewed by Litvan et al 3 Potential confounding factors include age, wellwater consumption, farming, rural living, head trauma, a family history of PD, smoking and caffeine intake, and infectious diseases such as Nocardiosis, as all of these have been suggested to affect the incidence of PD.…”

Section: Epidemiological Studiesmentioning

confidence: 99%

Paraquat and Parkinson's disease

2010

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Section: Epidemiological Studiesmentioning

confidence: 99%

Paraquat and Parkinson's disease

2010

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“…We used the Unified Parkinson's Disease Rating Scale, part III (UPDRS-III), and a diagnosis of PD was made according to the Queen Square Brain Bank Criteria. 4 All participants were assessed at a single center and by the same research team involved in the baseline evaluation, in which examiners were blind to the genetic status of LRRK2 relatives. 3 Clinical examination was done before the rest of the tests were available so examiners were blind to these results.…”

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confidence: 99%

Prospective clinical and DaT-SPECT imaging in premotor LRRK2 G2019S-associated Parkinson disease

et al. 2017

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Objective: To assess the value of baseline clinical and imaging biomarkers in a cohort of asymptomatic LRRK2 G2019S carriers for predicting conversion to Parkinson disease (PD) at 4 years.Methods: Thirty-two asymptomatic carriers of LRRK2 G2019S mutation underwent baseline and Results: Three carriers, asymptomatic at baseline, had converted to PD at 4-year evaluation.Twenty-three participants were fully evaluated. PD converters had lower striatal DaT binding at baseline than nonconverters (p 5 0.002). A baseline scan with a ratio of bilateral striatal uptake below 1 predicted conversion to PD within the 4-year period with high sensitivity and specificity (area under the curve 1; p 5 0.006). The slope of DaT binding decline between the 2 scans was similar in PD converters and nonconverters. Age-adjusted UPSIT score at baseline and at 4 years was similar in both groups.Conclusions: Semiquantitative DaT-SPECT could be used to predict early conversion to PD in asymptomatic carriers of the LRRK2 G2019S mutation. Rate of conversion to PD at 4 years in this cohort aged ;64 years was 12%. The slope of DaT binding decline on DaT-SPECT imaging seems to be similar across different stages of the premotor period. The G2019S mutation of the LRRK2 gene is the commonest known cause of Parkinson disease (PD). 1 Clinically and pathologically, this form of the disease is indistinguishable from idiopathic PD, and therefore it constitutes an ideal scenario in which to deepen our knowledge about the disease. The identification and follow-up of carriers of the LRRK2 G2019S mutation who still have not developed motor symptoms of PD represents a unique opportunity for studying the prodromal stage of PD. We lack information on the timing between the beginning of the neurodegenerative process and the appearance of the motor symptoms of PD and the pace of cell loss at the substantia nigra (SN) at the premotor stage. Shedding light into the prodromal stages of the disease is going to be crucial for planning drug trials aiming to modify the disease process early, before most of the damage is already done. The penetrance of the LRRK2 G2019S mutation is age-dependent and only a proportion of LRRK2 G2019S mutation carriers will develop motor symptoms of PD. 2 Besides age, no other clinical marker has been proven to be useful to predict conversion to manifest PD in asymptomatic carriers. In a previous study by our group, we characterized a cohort of 32 asymptomatic carriers of the LRRK2 G2019S mutation with brain imaging ( 123 I-ioflupane SPECT and transcranial sonography) and olfaction tests. 3

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“…1 Emission tomography (SPECT or PET) has a role but it can be expensive, with limited availability, and requires radioactive tracers. 2 There is particular interest in the potential of advanced structural MRI techniques to differentiate among parkinsonian syndromes and to offer candidate biomarkers, facilitating early or premanifest diagnosis and monitoring of disease progression.…”

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Diffusion tensor imaging in parkinsonian syndromes

2013

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Objectives: We performed a systematic review to assess alterations in measures of diffusion tensor imaging (DTI) in parkinsonian syndromes, exploring the potential role of DTI in diagnosis and as a candidate biomarker. Methods:We searched EMBASE and Medline databases for DTI studies comparing parkinsonian syndromes or related dementias with controls or another defined parkinsonian syndrome. Key details for each study regarding participants, imaging methods, and results were extracted. Estimates were pooled, where appropriate, by random-effects meta-analysis. Results:Of 333 results, we identified 43 studies suitable for inclusion (958 patients, 764 controls). DTI measures detected alterations in all parkinsonian syndromes, with distribution varying differentially with disease type. Nine studies were included in a meta-analysis of the substantia nigra in Parkinson disease. A notable effect size was found for lowered fractional anisotropy in the substantia nigra for patients with Parkinson disease vs controls (20.639, 95% confidence interval 20.860 to 20.417, p , 0.0001).Conclusion: DTI may be a promising biomarker in parkinsonian syndromes and have a future role in differential diagnosis. Larger cohort studies are required to investigate some encouraging preliminary findings. Given the complexity of the parkinsonian syndromes, it is likely that any potential DTI biomarker would be used in combination with other relevant biomarkers. Differences in natural history and therapy options make early and accurate diagnosis of parkinsonian syndromes important. 1 Emission tomography (SPECT or PET) has a role but it can be expensive, with limited availability, and requires radioactive tracers. 2 There is particular interest in the potential of advanced structural MRI techniques to differentiate among parkinsonian syndromes and to offer candidate biomarkers, facilitating early or premanifest diagnosis and monitoring of disease progression.Diffusion tensor imaging (DTI) is an MRI technique assessing the orientation and integrity of white matter tracts in vivo by measuring the diffusion of water molecules in neural fibers 3 and it also shows promise for studying gray matter areas. It estimates both the degree of directionality using anisotropy (frequently fractional anisotropy [FA]) and the overall movement of molecules (mean diffusivity [MD]; trace; apparent diffusion coefficient [ADC]). These measurements can either be extracted locally in predefined regions using region of interest (ROI) analysis or tractography or, alternatively, globally using voxel-based analysis (VBA) or tract-based spatial statistics (TBSS). Disruptions to microstructural tissue integrity, such as those found in the neurodegeneration of parkinsonian syndromes can be associated with alterations in anisotropy and diffusivity measures. 3 We therefore performed a systematic review of the literature to assess

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SIC Task Force appraisal of clinical diagnostic criteria for parkinsonian disorders

Cited by 905 publications

References 129 publications

Paraquat and Parkinson's disease

Paraquat and Parkinson's disease

Prospective clinical and DaT-SPECT imaging in premotor LRRK2 G2019S-associated Parkinson disease

Diffusion tensor imaging in parkinsonian syndromes

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