Mild parkinsonian signs: the interface between ageing and Parkinson’s disease
Posted in Clinical Review Article on 22nd Jun 2021
Cristina Simonet, MD, is a Consultant in Neurology and Movement Disorders. She finished her Neurology training in Spain in 2016. She has had a special interest in Parkinson’s disease since the beginning of her training. She joined the PREDICT-PD team in September 2018, which was a new challenge for her. She is based at Wolfson Institute of Preventive Medicine and her research is based on studying the early motor features of Parkinson’s disease.
Alastair Noyce, PhD, MRCP, is a Reader in Neurology and Neuroepidemiology at the Preventive Neurology Unit in the Wolfson Institute of Preventive Medicine, Queen Mary University of London, and a Consultant Neurologist at Barts Health NHS Trust. Alastair graduated from Barts and the London School of Medicine and Dentistry in 2007. He pursued integrated training via the Foundation Academic Programme and an NIHR Academic Clinical Fellowship at UCL. In August 2012, he left clinical training to pursue a PhD in Neuroscience at UCL. Between 2014-2016 he undertook an MSc in Epidemiology at the London School of Hygiene and Tropical Medicine. His main research interests are Parkinson’s disease and related disorders, particularly early identification and epidemiology, including environmental, clinical and genetic determinants.
Correspondence to: Alastair Noyce, Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK. E. firstname.lastname@example.org
Conflict of interest statement: None declared.
Provenance and peer review: Submitted and externally reviewed.
Date first submitted: 15/09/2020
Date submitted after peer review: 4/03/2021
Acceptance date: 5/03/2021
Published online: 22/6/2021
To cite: Simonet C, Noyce A. Adv Clin Neurosci Rehabil 2021; Mild parkinsonian signs: the interface between ageing and Parkinson’s disease https://acnr.co.uk/2021/06/mild-parkinsonian-signs
Mild Parkinsonian Signs (MPS) describe a spectrum that exists between the expected motor decline of normal ageing and a more serious motor deterioration resulting from Parkinson’s disease (PD) and neurodegeneration. Although MPS are a feature of the prodromal stage of PD, their formal definition is unclear and still relies somewhat on conventional clinical criteria for PD. This review will summarise the early motor features of PD and methods of assessment, from conventional clinical scales to advances in quantitative measures. Finally, the boundaries of motor decline as part of normal ageing and pathological neurodegeneration will be discussed.
Mild Parkinsonian Signs (MPS) describe the motor spectrum that spans from normal ageing to the early stages of Parkinson’s disease (PD).1 A variety of other terms have been used to describe these features, such as subthreshold parkinsonism and subtle motor/parkinsonian signs. PD is generally a slowly progressive degenerative disease and because it is diagnosed on the basis of established and typical motor features, subtle motor manifestations may be apparent years before the diagnosis.2 However, many MPS are not specific to PD and may not progress in the same manner; substantial overlap with normal ageing is to be expected.3
The phase before a diagnosis of PD has often been referred to as the ‘pre-motor’ phase, but the truth is that motor features in the pre-diagnostic phase have received surprisingly little attention compared to non-motor features.4 As such, it is difficult to say whether there is a definite ‘pre-motor’ phase, when objective motor dysfunction has been observed in many prodromal settings.5-8 Although several studies have objectively documented motor markers of neurodegeneration in PD (see Table below), there is still controversy about when they exactly start and how reliably they can be detected.
MPS in the elderly population without PD cluster into four domains: bradykinesia, tremor rigidity, and gait and posture.9,10 They are known to be present at early stages of PD (see Figure). We will focus on these domains one by one .
Bradykinesia is the only clinical sign that is required to be present in every patient with PD according to the Queen Square Brain Bank Criteria.11 It is described as the ‘slowness of movement initiation with progressive reduction in speed and amplitude (sequence effect) of repetitive actions’.12 It is interpreted by patients as clumsiness or weakness when performing fine and repetitive movements. Compensatory mechanisms help to maintain stable dopaminergic transmission and motor function at early stages of PD.13 However, these compensatory mechanisms can fail when more challenging tasks are performed with associated ‘unmasking’ of subtle motor deficits.4
Changes in handwriting are thought to be an early sign of PD,14 with micrographia (gradual reduction in letter size) being an example of ‘real-world’ bradykinesia.15 In some studies, micrographia has been documented up to four years before diagnosis.16 Recently, the term ‘dysgraphia’ has been introduced. It goes further than micrographia and includes other kinetic variables apart from the script size, such as velocity, fluency, and sentence slope which may help to detect even earlier changes in handwriting.14
Similar to handwriting, speech is an automated task that requires a high level of motor coordination. Abnormalities may appear at early stages of PD; hypophonia, poor articulation, and hesitation are some of the manifestations of vocal hypokinesia.17 The Oxford Discovery Parkinson’s Cohort (OPDC) included smartphone-based voice analysis as part of a motor battery. Speech and tremor were found to be the most discriminatory markers between patients with PD, patients with REM-sleep behaviour disorder (RBD) and controls.18 In a separate case-control study, footage of video recordings from interviews and press conferences on television were used to extract acoustic measurements and demonstrated changes in voice frequency up to five years prior to diagnosis of PD.19 A reduction in spontaneous (involuntary) eye-blinking and lack of normal facial responsiveness are characteristic features of hypomimia, which are often described as early motor signs of PD.20 Unlike spontaneous blinking, rapid voluntary blinking, has been poorly studied in PD, but a recent study suggested that it might be an early marker.21
A self-limiting, stress-induced bout of tremor can be the first symptom of PD.22 In the absence of tremor at rest, the outstretching of hands and a short intermission followed by a re-emergent postural tremor, may also be evident at the early stages of PD.23 Numerous studies support the idea that tremor in general is an early feature of PD. For example, a longitudinal study conducted in central Spain showed that after three-years of follow-up, people with ‘essential tremor’ had four times more likelihood of being diagnosed with PD than those without tremor.24 Similar results were found in another longitudinal study, with isolated action and rest tremor associated with a doubling of the risk of PD.5 In analyses using data from the UK Health Improvement Network (THIN) database, 8166 PD patients were compared with 46455 healthy controls, and revealed that tremor was the most common and earliest motor marker reported in primary care with a subsequent diagnosis of PD up to ten years later.25 Essential tremor, which increases in prevalence and severity with age, might account for some of the tremor which precedes a diagnosis of PD. Epidemiological studies support this idea and find that essential tremor can be associated with PD, mild cognitive impairment (MCI) and dementia.26
Cogwheel rigidity is a distinctive feature of PD.23 In the study undertaken using the THIN database (see above), rigidity and shoulder pain were features that were apparent two years before PD diagnosis.25 Moreover, rigidity and changes in posture were the most prevalent signs in a group of elderly people with MPS studied by Louis and colleagues, with 24% of subjects presenting with isolated rigidity.27 These results may explain the weighting of rigidity in MPS criteria defined by the same authors, with five out of ten items being related to rigidity. However, rigidity is not always easy to detect. It may manifest through non-specific symptoms such as shoulder pain, stiffness, and postural abnormalities when resting or walking. To date there is a lack of tools to objectively assess rigidity beyond traditional clinical examination.
Posture and Gait
The prevalence of gait abnormalities increases with age, but some patterns have been shown to be more PD-specific.28 On examination, a classic early parkinsonism posture when walking includes reduced arm swing, with a flexed elbow and a hand held in a flexed-adducted position. Kinnier Wilson was one of the first authors to introduce the concept of motor symptoms preceding clinical diagnosis. He described that when seated or standing, patients may maintain the same position without making the normal adjustments which one sees in healthy people (Kinnier Wilson, Neurology; Volume II, 1940). Using wearable technology for objective gait analysis, Mirelman and colleagues found that arm swing asymmetry and loss of limb coordination appeared to be less associated with ageing and more likely to occur in early PD.29
Postural instability, so long considered the fourth cardinal sign in the Queen Square Brain Bank Criteria, was excluded from the Movement Disorders Society Criteria for PD that were published in 2015.30 This was mainly because early postural instability should make clinicians consider the possibility of an atypical parkinsonian disorder.
It is not surprising that gait patterns, as an automated and rhythmic task, may yield clear indications of MPS. These include the emergence of step-to-step variability, arm swing asymmetry and reduced truncal rotation.31 At the early stages of PD, when compensatory mechanisms may be present, dual-tasking during walking is a strategy to make MPS more prominent.32,33 Walking during simple and challenging conditions was evaluated in a cohort of 696 healthy controls followed up between 2009 and 2016. It was found that step-to-step time variability and gait asymmetry were the best parameters preceding PD diagnosis up to four years.33 These results were in line with a longitudinal study in RBD patients using UPDRS and the Timed Up and Go test showing that gait abnormalities were present between 4-6 years prior to the diagnosis of an overt parkinsonian disorder.34
The contribution of cerebrovascular disease to MPS in the ageing population has been studied. For example, brain autopsies were examined from 418 donors in the Religious Order Study cohort who had been evaluated during life for parkinsonian signs.35 Macroscopic infarcts were associated with higher global parkinsonian scores. In particular, subcortical infarcts (macroscopic infarcts and multiple microinfarcts) were related to gait impairment. These associations did not change after adjusting for the presence of dementia.
The motor continuum from natural ageing to neurodegeneration
Parkinsonian signs are common in the elderly. The prevalence of MPS in population-based studies ranges from 30 to 40% in elderly people which is much higher than the prevalence of PD.27 For example, in one study in a community setting, MPS were found in more than one third of individuals over the age of 65 years.28 This suggests that MPS cannot be exclusively considered part of the prodromal spectrum of PD and they may evolve into other conditions with a common denominator of nigrostriatal dysfunction. Numerous studies, which were summarised in a review published by Louis et al, have demonstrated that there is an appreciable increase in the incidence of Alzheimer’s disease (AD) in people with MPS.3 In one study, a third of patients with AD were found to have parkinsonism, which in turn was associated with the presence of neurofibrillary tangles in the substantia nigra.36 On the other hand, MPS may barely progress over time. This observation was made in one longitudinal cohort where one quarter of individuals with MPS remained stable.37 Based on the multiple trajectories that MPS can have, it seems reasonable to focus our attention on distinguishing which individuals with MPS will continue to age normally and which may be in the early stages of PD or dementia.
The boundaries between normal ageing, MPS and pathological nigrostriatal degeneration are difficult to determine. Clinical examination may reveal clues to define these boundaries; a non-progressive course, symmetric distribution, and slowness with a lack of decrement, are all motor features of ageing.3 Axial signs can predominate in older people with MPS and are usually less responsive to L-dopa in patients with PD.38 Several studies have specifically assessed the relative risk of MPS for subsequent diagnosis of PD and, in one example, MPS at baseline had a relative risk of 5.5 (2.4–12.6) for incident PD over 10 years of follow-up.39
Minn Aye and colleagues recently evaluated the presence of MPS in an elderly community.40 They found that one quarter of the group had subtle movement abnormalities and this proportion increased with age, with three out of ten people older than 75 showing some degree of motor dysfunction. After adjusting for age and gender, cognitive dysfunction and symptoms of RBD were found to be associated with MPS, which suggests that in a proportion there may be an underlying neurodegenerative process.40
Although MPS are prevalent in elderly people, the underlying neuropathology remains unclear. The loss of pigmented neurons in the substantia nigra (SN) pars compacta together with the presence of Lewy bodies (LB) are the hallmarks of PD. However, post-mortem studies have shown that Lewy body pathology is not exclusive to PD and have been found incidentally in 2-61% of healthy brain donors.41 Fearnley and Lees found that individuals with incidental LB had an intermediate SN neuronal loss between PD cases and controls, and postulated that they might represent a preclinical stage of PD.42 On the other hand, MPS can be found in elderly people with SN neuronal loss and without LB. Ross and collaborators examined the brains of participants in the Honolulu Heart Program/ Honolulu-Asia Ageing Study (HHP/HAAS). They estimated the density of neurons in the SN in PD cases, individuals with incidental LB, and elderly people without either condition.43 They found that brains from older individuals without LB but who had MPS were associated with lower neuron density in the dorsomedial and dorsolateral quadrants of SN, in contrast to ventrolateral portion of SN which is seen in PD and incidental LB.
Analogy with ‘Mild Cognitive Impairment’
The concept of MCI was created to identify individuals who might be in the prodromal stages of AD and other types of dementia. The identification of MPS provides similar opportunities for early detection, but also pitfalls. MCI and MPS can occur simultaneously in the same person, increasing the chance of developing a neurodegenerative disorder. As with MCI, clinical subtypes of MPS could indicate a variety of different underlying parkinsonian disorders.44 Unlike MCI, clinical scales including patient’s subjective impression about their functional impairment are more difficult to use in PD due to lack of awareness of motor disability usually seen in PD patients.45 MPS and MCI also share associations with chronic cerebrovascular disease. The role that cardiovascular risk factors play in brain health is unquestionable.46 What is noteworthy, however, is increasing evidence of a direct relationship between cardiovascular risk factors and AD.47 The study of the interplay between cardiovascular disease and the pathology of common neurodegenerative diseases is an important area, given that some of these interactions are potentially modifiable.
Methods of assessing motor dysfunction
One particular challenge is the development of tests to detect subtle motor abnormalities, because the heterogeneity of the motor phenotype makes it difficult to standardise methods of analysis.4 There is no protocol of motor assessment that is well adapted to early stages of PD. Standardised approaches, adapting current clinical scales and creating objective tools, are required to set the boundaries between prodromal and established PD.48
The Movement Disorders Society (MDS)-Unified Parkinson’s Disease Rating Scale (UPDRS) is a standard means of assessment in PD.49 The motor part (part III) is a semi-quantitative scale based on integer scoring on simple motor tasks addressed to evaluate the cardinal signs of PD. Of note, it was designed for established PD, so it is not expected to be sensitive to detect MPS at the early stages.4
The two most widely accepted criteria for defining subthreshold parkinsonism were published by Louis and colleagues, and Berg and colleagues on behalf an MDS Task Force.27,49 The former was based on binary scoring (present or absent) of ten items assessing facial expression, speech, tremor at rest, rigidity, posture and axial bradykinesia, but not limb bradykinesia (which is necessary for PD diagnosis). MPS were defined when any of the following conditions were met: rating ≥ 1 for one rigidity item (neck, right and left arm and leg) AND axial bradykinesia AND at least 1 of the four remaining items.50 Of note, the Louis definition did not include appendicular bradykinesia. Since limb bradykinesia almost certainly belongs to the spectrum of MPS and, in fact may be essential to detect early forms of neurodegenerative parkinsonism, several groups have gone back to integrate the full MDS-UPDRS into the Louis criteria for identifying MPS.7,51,52 The MDS Task Force definition requires exceeding a cut-off of 6 on the MDS-UPDRS part III, without the inclusion of kinetic and postural tremor, to be defined as subthreshold parkinsonism.49
There exists a modified bradykinesia scale which separately scores three kinetic parameters (frequency, rhythm, and amplitude) for each repetitive movement evaluated in the MDS-UPDRS-III (finger tapping, prono-supination and opening-closing hand).53 However even with these modifications, there are additional important features such as manual dexterity, posture and gait under challenging conditions that are not captured.
Quantitative motor assessments together with sophisticated software analysis have been created to address the limitations of conventional clinical scales mentioned above. Although technology-based tools allow objective detection of subtle motor abnormalities, clinical expertise remains equally important to avoid results misinterpretation.54
The range of technology available has grown exponentially in the last decade. The kinds of devices range from body sensors to smartphone applications but have also been expanded from controlled conditions measured in the laboratory to real life monitoring in the home-environment.
An important question is whether the existing scales ought to be the gold standard of assessment for MPS or whether there is a need to create new signatures of early motor dysfunction in PD, with an increasing reliance on objective measures.55
MPS are an important aspect of the prodromal phase of PD. There are many unanswered questions about where the boundary lies between the ageing process and nigrostriatal degeneration, their progression to early PD or dementia, and the time over which MPS emerge and the best means to quantify early motor dysfunction. The creation of a motor battery that combines a variety of motor assessments under challenging conditions, incorporating technology and clinical acumen, is needed and should be evaluated on a large scale in population-based studies involving elderly people.
1. Mahlknecht P, Seppi K, Poewe W. The Concept of Prodromal Parkinson’s Disease. J Parkinsons Dis. 2015;5:681-97. https://doi.org/10.3233/JPD-150685
2. Gibb WRG, Lees AJ. The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson’s disease. J Neurol Neurosurg Psychiatry. 1988;745-52. https://doi.org/10.1136/jnnp.51.6.745
3. Louis ED, Bennett DA. Mild Parkinsonian signs: An overview of an emerging concept. Mov Disord 2007;22:1681-8. https://doi.org/10.1002/mds.21433
4. Maetzler W, Hausdorff JM. Motor signs in the prodromal phase of Parkinson’s disease. Mov Disord. 2012;27:627-33. https://doi.org/10.1002/mds.24973
5. Alarcón F, Maldonado JC, Cañizares M, et al. Motor Dysfunction as a Prodrome of Parkinson’s Disease. J Parkinsons Dis. 2020;1-7.
6. Postuma RB, Iranzo A, Hu M, et al. Risk and predictors of dementia and parkinsonism in idiopathic REM sleep behaviour disorder: A multicentre study. Brain 2019;142:744-59. https://doi.org/10.1093/brain/awz030
7. Noyce AJ, Schrag A, Masters JM, et al. Subtle motor disturbances in PREDICT-PD participants. J Neurol Neurosurg Psychiatry. 2017;88:212-7. https://doi.org/10.1136/jnnp-2016-314524
8. Jennings D, Siderowf A, Stern M, et al. Conversion to Parkinson Disease in the PARS Hyposmic and Dopamine Transporter-Deficit Prodromal Cohort. JAMA Neurol 2017;74:933. https://doi.org/10.1001/jamaneurol.2017.0985
9. Louis ED, Tang MX, Mayeux R. Factor structure of Parkinsonian sings in the community-dwelling elderly. Mov Disord. 2004;19:268-72. https://doi.org/10.1002/mds.20013
10. Bennett DA, Shannon KM, Beckett LA, et al. Dimensionality of Parkinsonian signs in aging and Alzheimer’s disease. Journals Gerontol – Ser A Biol Sci Med Sci. 1999;54. https://doi.org/10.1093/gerona/54.4.M191
11. Hughes AJ, Daniel SE, Blankson S, et al. A Clinicopathologic Study of 100 Cases of Parkinson’s Disease. Arch Neurol 1993;50:140-8. https://doi.org/10.1001/archneur.1993.00540020018011
12. Bologna M, Paparella G, Fasano A, et al. Evolving concepts on bradykinesia. Brain. Published Online First: 2019. https://doi.org/10.1093/brain/awz344
13. Nandhagopal R, Kuramoto L, Schulzer M, et al. Longitudinal evolution of compensatory changes in striatal dopamine processing in Parkinson’s disease. Brain. 2011;134:3290-8. https://doi.org/10.1093/brain/awr233
14. Letanneux A, Danna J, Velay JL, et al. From micrographia to Parkinson’s disease dysgraphia. Mov Disord. 2014;29:1467-75. https://doi.org/10.1002/mds.25990
15. Rosenblum S, Samuel M, Zlotnik S, et al. Handwriting as an objective tool for Parkinson’s disease diagnosis. J Neurol. 2013;260:2357-61. https://doi.org/10.1007/s00415-013-6996-x
16. Mclennan JE, Nakano K, Tyler HR, et al. Micrographia in Parkinson’ s Disease . J Neurol Sci. 1972;141-52.
17. Darley FL, Brown JR, Swenson WM. Language changes after neurosurgery for Parkinsonism. Brain Lang. 1975;2:65-9. https://doi.org/10.1016/S0093-934X(75)80054-X
18. Arora S, Baig F, Lo C, et al. Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD. Neurology 2018;91:E1528-38. https://doi.org/10.1212/WNL.0000000000006366
19. Harel B, Cannizzaro M, Snyder PJ. Variability in fundamental frequency during speech in prodromal and incipient Parkinson’s disease: A longitudinal case study. Brain Cogn. 2004;56:24-9. https://doi.org/10.1016/j.bandc.2004.05.002
20. Karson CN. Spontaneous eye-blink rates and dopaminergic systems. Brain. 1983;106:643-53. https://doi.org/10.1093/brain/106.3.643
21. Agostino R, Bologna M, Dinapoli L, et al. Voluntary, spontaneous, and reflex blinking in Parkinson’s disease. Mov Disord. 2008;23:669-75. https://doi.org/10.1002/mds.21887
22. Djamshidian A, Lees AJ. Can stress trigger Parkinson’s disease? J Neurol Neurosurg Psychiatry. 2014;85:879-82. https://doi.org/10.1136/jnnp-2013-305911
23. Goetz CG. The History of Parkinson’s Disease: Early Clinical Descriptions and Neurological Therapies. Cold Spring Harb Perspect Med. 2011;1:a008862:1-15. https://doi.org/10.1101/cshperspect.a008862
24. Benito-León J, Louis ED, Bermejo-Pareja F. Risk of incident Parkinson’s disease and parkinsonism in essential tremor: A population based study. J Neurol Neurosurg Psychiatry. 2009;80:423-5. https://doi.org/10.1136/jnnp.2008.147223
25. Schrag A, Horsfall L, Walters K, et al. Prediagnostic presentations of Parkinson’s disease in primary care: A case-control study. Lancet Neurol 2015;14:57-64. https://doi.org/10.1016/S1474-4422(14)70287-X
26. Louis ED. The roles of age and aging in essential tremor: An epidemiological perspective. Neuroepidemiology. 2019;52:111-8. https://doi.org/10.1159/000492831
27. Louis ED, Luchsinger JA, Tang MX, et al. Parkinsonian signs in older people: Prevalence and associations with smoking and coffee. Neurology 2003;61:24-8. https://doi.org/10.1212/01.WNL.0000072330.07328.D6
28. Bennett DA, Beckett LA, Murray AM, et al. Prevalence of Parkinsonian Signs and Associated Mortality in a Community Population of Older People. N Engl J Med. 1996;334:71-6. https://doi.org/10.1056/NEJM199601113340202
29. Mirelman A, Bernad-Elazari H, Nobel T, et al. Effects of aging on arm swing during gait: The role of gait speed and dual tasking. PLoS One 2015;10:1-11. https://doi.org/10.1371/journal.pone.0136043
30. Postuma RB, Berg D, Stern M, et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord. 2015;30:1591-601. https://doi.org/10.1002/mds.26424
31. Mirelman A, Bonato P, Camicioli R, et al. Gait impairments in Parkinson’s disease. Lancet Neurol 2019;18:697-708. https://doi.org/10.1016/S1474-4422(19)30044-4
32. Maetzler W, Mancini M, Liepelt-Scarfone I, et al. Impaired trunk stability in individuals at high risk for Parkinson’s disease. PLoS One 2012;7. https://doi.org/10.1371/journal.pone.0032240
33. Del Din S, Elshehabi M, Galna B, et al. Gait analysis with wearables predicts conversion to parkinson disease. Ann Neurol. 2019;86:357-67. https://doi.org/10.1002/ana.25548
34. Postuma RB, Lang AE, Gagnon JF, et al. How does parkinsonism start? Prodromal parkinsonism motor changes in idiopathic REM sleep behaviour disorder. Brain 2012;135:1860-70. https://doi.org/10.1093/brain/aws093
35. Buchman AS, Leurgans SE, Nag S, et al. Cerebrovascular disease pathology and parkinsonian signs in old age. Stroke. 2011;42:3183-9. https://doi.org/10.1161/STROKEAHA.111.623462
36. Liu Y, Stern Y, Chun MR, et al. Pathological correlates of extrapyramidal signs in Alzheimer’s disease. Ann Neurol. 1997;41:368-74. https://doi.org/10.1002/ana.410410312
37. Wilson RS, Schneider JA, Beckett LA, et al. Progression of gait disorder and rigidity and risk of death in older persons. Neurology. 2002;58:1815-9. https://doi.org/10.1212/WNL.58.12.1815
38. Newman RP, LeWitt PA, Jaffe M, et al. Motor function in the normal aging population: treatment with levodopa. Neurology. 1985;35:571-3. https://doi.org/10.1212/WNL.35.4.571
39. Mahlknecht P, Stockner H, Marini K, et al. Midbrain hyperechogenicity, hyposmia, mild parkinsonian signs and risk for incident Parkinson’s disease over 10 years: A prospective population-based study. Park Relat Disord. 2020;70:51-4. https://doi.org/10.1016/j.parkreldis.2019.12.008
40. Aye YM, Liew GM, Ng SYE, et al. Mild Parkinsonian Signs in a Community Ambulant Population. J Parkinsons Dis. 2020;1-7. https://doi.org/10.3233/JPD-191849
41. Zaccai J, Brayne C, McKeith I, et al. Patterns and stages of α-synucleinopathy: Relevance in a population-based cohort. Neurology 2008;70:1042-8. https://doi.org/10.1212/01.wnl.0000306697.48738.b6
42. Fearnley JM, Lees AJ. Ageing and Parkinson’s Disease : Substantia Nigra Regional Selectvity. Brain, A J Neurol. 1991;114:2283-301. https://doi.org/10.1093/brain/114.5.2283
43. Ross GW, Petrovitch H, Abbott RD, et al. Parkinsonian signs and substantia nigra neuron density in decendents elders without PD. Ann Neurol. 2004;56:532-9. https://doi.org/10.1002/ana.20226
44. Gauthier S, Reisberg B, Zaudig M, et al. Mild cognitive impairment. Lancet 2006;367:1262-70. https://doi.org/10.1016/S0140-6736(06)68542-5
45. Amanzio M, Monteverdi S, Giordano A, et al. Impaired awareness of movement disorders in Parkinson’s disease. Brain Cogn. 2010;72:337-46. https://doi.org/10.1016/j.bandc.2009.10.011
46. Parikh NS, Gottesman RF. Midlife Cardiovascular Risk Factors, Subclinical Atherosclerosis, and Cerebral Hypometabolism. J Am Coll Cardiol. 2021;77:899-901. https://doi.org/10.1016/j.jacc.2020.12.046
47. Schneider JA, Arvanitakis Z, Bang W, et al. Mixed brain pathologies account for most dementia cases in community-dwelling older persons. Neurology 2007;69:2197 LP – 2204.http://n.neurology.org/content/69/24/2197.abstract https://doi.org/10.1212/01.wnl.0000271090.28148.24
48. Postuma RB, Berg D. Advances in markers of prodromal Parkinson disease. Nat Rev Neurol. 2016;12:622-34. https://doi.org/10.1038/nrneurol.2016.152
49. Berg D, Postuma RB, Adler CH, et al. MDS research criteria for prodromal Parkinson’s disease. Mov Disord. 2015;30:1600-11.
50. Louis ED, Schupf N, Manly J, et al. Association between mild parkinsonian signs and mild cognitive impairment in a community. Neurology 2005;64:1157-61. https://doi.org/10.1212/01.WNL.0000156157.97411.5E
51. De Laat KF, Van Norden AGW, Gons RAR, et al. Cerebral white matter lesions and lacunar infarcts contribute to the presence of mild parkinsonian signs. Stroke. 2012;43:2574-9. https://doi.org/10.1161/STROKEAHA.112.657130
52. Mahlknecht P, Stockner H, Marini K, et al. Midbrain hyperechogenicity, hyposmia, mild parkinsonian signs and risk for incident Parkinson’s disease over 10 years: A prospective population-based study. Park Relat Disord. 2020;70:51-4. https://doi.org/10.1016/j.parkreldis.2019.12.008
53. Heldman DA, Giuffrida JP, Chen R, et al. The modified bradykinesia rating scale for Parkinson’s disease: Reliability and comparison with kinematic measures. Mov Disord. 2011;26:1859-63. https://doi.org/10.1002/mds.23740
54. Simonet C, Schrag A, Lees AJ, et al. The motor prodromes of parkinson’s disease: from bedside observation to large-scale application. J Neurol Published Online First: 2019. https://doi.org/10.1007/s00415-019-09642-0
55. Espay AJ, Bonato P, Nahab FB, et al. Technology in Parkinson disease: Challenges and Opportunities. Mov Disord. 2016;31:1272-82. https://doi.org/10.1002/mds.26642
56. Darweesh SKL, Verlinden VJA, Stricker BH, et al. Trajectories of prediagnostic functioning in Parkinson’s disease. https://academic.oup.com/brain/article-abstract/140/2/429/2631168 (accessed 29 Jul 2019).
57. Mahlknecht P, Kiechl S, Stockner H, et al. Predictors for mild parkinsonian signs : A prospective population-based study. Park Relat Disord. 2015;21:321-4. https://doi.org/10.1016/j.parkreldis.2014.12.021
58. Gaenslen A, Wurster I, Brockmann K, et al. Prodromal features for Parkinson’s disease – baseline data from the TREND study. Eur J Neurol 2014;21:766-72. https://doi.org/10.1111/ene.12382
59. Siderowf A, Jennings D, Stern M, et al. Clinical and Imaging Progression in the PARS Cohort: Long-Term Follow-up. Mov Disord. 2020;1-9.
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