The severity of corneal nerve loss differentiates motor subtypes in patients with Parkinson's disease.

Introduction

Parkinson’s disease (PD) is a clinically heterogeneous disease with patients manifesting a diverse spectrum of motor and non-motor symptoms and signs. 1 Motor symptoms such as resting tremor, bradykinesia, and postural instability are characteristic features of PD. 2 Patients can be divided into different clinical motor subtypes with features that are tremor-dominant (TD) or they may predominantly have postural instability and gait disturbance (PIGD). 3 Patients with the TD subtype respond relatively satisfactorily to levodopa administration, are less likely to develop dyskinesia, 4 and have a relatively better prognosis than those with PIGD. 5 , 6 While patients with the PIGD subtype are less responsive to levodopa therapy, progress more rapidly, 5 , 6 and have greater cognitive dysfunction 7 with a lower quality of life.

PD is a complex multi-system neurodegenerative disease, with not only impairment of the central dopaminergic nigrostriatal system but also peripheral nerve degeneration. 8 , 9 Both large-medium (Aα/β) fiber and small (Aδ and C) fiber damage have been demonstrated in PD. 10 , 11 Large fiber dysfunction has been attributed to levodopa therapy, while small fiber neuropathy is thought to be intrinsic to the neurodegenerative process in PD. 11 – 13

Corneal confocal microscopy (CCM) is an in vivo ophthalmic imaging technique that has been widely used to quantify corneal nerve damage in a range of peripheral neuropathies and central neurodegenerative diseases. 14 , 15 Indeed, CCM has a high sensitivity in detecting small fiber loss in mild PD, 16 and we have previously shown that corneal nerve fiber loss was associated with the severity of cognitive and motor dysfunction, 17 as well as autonomic dysfunction. 18 Recently, a longitudinal study by Lim et al. 19 showed that greater corneal nerve loss was associated with more rapid motor progression in a cohort of patients with PD.

In this study, CCM was performed in PD patients to explore whether there was an association between the extent of corneal nerve loss and different motor subtypes. We speculated that the PIGD subtype might show greater corneal nerve fiber loss compared with the TD subtype.

Materials and methods

Participants

Patients with PD were recruited from the Department of Neurology, Henan Provincial People’s Hospital between March 2017 and December 2020. Age, sex, and education level were evaluated in all subjects.

PD patients were diagnosed clinically according to the 2015 Movement Disorder Society clinical diagnostic criteria for Parkinson’s disease. 20 Clinically diagnosed PD and clinically probable PD were recruited. Parkinson-plus syndromes, such as multiple system atrophy, progressive supranuclear palsy, cortical-basal ganglia degeneration, dementia with Lewy bodies, and secondary parkinsonism (vascular, drug-induced, inflammatory, immune-mediated, normal pressure hydrocephalus, infectious, traumatic, etc.), were excluded. Any participants with a suspected family history of a movement disorder were excluded. Healthy controls were recruited from volunteers or spouse of PD patients who had no history of neurodegenerative disease. Subjects younger than 40 or older than 85 years of age were excluded from the study. Subjects with a history of corneal disease, eye surgery, glaucoma, eye inflammation, or thyroid eye disease were excluded. Other causes of peripheral neuropathy were excluded based on a history of excess alcohol use (>150 ml/d) and an assessment of vitamin B 12 and folate, serum electrophoresis to exclude multiple myeloma, and cryoglobulinemia and macroglobulinemia and an oral glucose tolerance test to exclude impaired glucose tolerance and diabetes. The clinical features of each participant were carefully evaluated by an experienced neurologist (H-Q.Y.) who was specialized in movement disorders. All subjects agreed to participate in the study and written informed consent was obtained. The study was approved by the Ethics Committee of Henan Provincial People’s Hospital (No. 202148).

Clinical evaluation

The assessment of motor and non-motor symptoms was performed in the ‘ON’ state. PD symptoms were assessed with part I, II, III and IV sub-scales of the Movement Disorders Society Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), and Hoehn and Yahr (H-Y) staging was undertaken for all PD patients. 21 Age at onset was defined as the time when the first cardinal motor sign(s) were noted by either the patient or family members. Disease duration was defined as the time interval between presentation with first motor symptoms and enrollment into the present study. The Scale for Outcomes in Parkinson’s Disease for Autonomic Symptoms (SCOPA-AUT), a reliable and validated questionnaire, was undertaken in patients with PD to detect autonomic dysfunction. Montreal cognitive assessment (MoCA, Beijing Version) was used to assess the cognitive status. Quality of life was evaluated with the 39-item Parkinson’s disease questionnaire (PDQ-39) with a higher score indicating a poorer quality of life. Levodopa equivalent daily dose (LEDD) was assessed according to the levodopa conversion formula. 22 Briefly, 100 mg levodopa = 133 mg entacapone = 1 mg pramipexole = 5 mg ropinirole = 10 mg selegiline = 1 mg rasagiline = 100 mg amantadine.

Motor subtypes

Motor subtype classification in PD patients was performed according to Stebbins et al . 23 Briefly, the ratio of the mean MDS-UPDRS tremor scores (11 items) to the mean MDS-UPDRS PIGD scores (5 items) was calculated for each patient. Patients were classified as a PIGD subtype if the ratio was ⩽0.90, as a TD subtype if the ratio was ⩾1.15, and as a mixed subtype if the ratio was between 0.90 and 1.15.

CCM

A Heidelberg Retina Tomograph III with a Rostock Cornea Module (HRT III RCM; Heidelberg Engineering GmbH, Heidelberg, Germany) was used to acquire images of the central corneal sub-basal nerve plexus. To minimize the impact of motor symptoms especially tremor on the results, CCM was completed in PD patients when they were in the ‘ON’ state. Topical lidocaine was used to anesthetize the eye of each subject and they were seated comfortably and instructed to fixate on an outer fixation light. The TomoCap was correctly positioned on the cornea by visualizing with the CCD camera. An experienced examiner took images at the level of the sub-basal nerve plexus in the central cornea using the ‘section’ mode according to an established protocol. 24 Four to six optimal quality CCM images from the central cornea of each eye were selected and analyzed using a validated, manual purpose-written software (CCMetrics, Imaging Science and Biomedical Engineering, Manchester, UK). 25 Three parameters were analyzed: (a) corneal nerve fiber density (CNFD) – the number of main nerve fibers per square millimeter; (b) corneal nerve branch density (CNBD) – the number of primary branches originating from the main nerve; and (c) corneal nerve fiber length (CNFL) – the sum of length of all nerve fibers and branches per square millimeter. 26

Statistical analysis

The Shapiro–Wilk test was used to assess the normality of data. For normal variables, numbers are expressed as mean ± standard deviation (SD). Analysis of variance with Bonferroni’s post hoc test was used for multiple group comparison. For non-normal or non-homoscedasticity variables, numbers are expressed as median (interquartile range). Multiple comparisons were performed by the non-parametric Kruskal–Wallis test. Categorical variables were compared by chi-square tests and Fisher’s exact tests.

Logistic regression was used to examine the relationship between CCM parameters and motor subtypes, adjusting for H-Y stage, SCOPA-AUT, and UPDRS-II. Variables for inclusion were carefully chosen, given the number of events available and univariate relationship. The receiver operating characteristic (ROC) curve was used to analyze the capability of corneal nerve parameters for distinguishing the PIGD subtype from the TD subtype. All analyses were carried out using SPSS version 22.0 (IBM Corporation, Armonk, NY, USA). Scatter plots and ROC curve were generated using GraphPad Prism version 8.0 (GraphPad Software, Inc, San Diego, CA, USA). The value of p < 0.05 was considered statistically significant.

Results

Clinical and demographic profiles

In this study, 87 PD patients were enrolled and 73 were finally included. Eight patients with impaired glucose tolerance, four with corneal disease, and two with multiple system atrophy were excluded. The age of the PD group (52.05% male) was 62.67 ± 7.67 years with age at onset of 59.15 ± 8.02 years and disease duration of 3 (2–4) years. The average H-Y stage of the PD group was 2 (1–3). In the control group ( n = 30), 53.33% were male, with an average age of 62.43 ± 6.16 years.

Of the 73 patients with PD, 29 (40%) were classified with TD, 34 (46%) with PIGD, and 10 (14%) had a mixed subtype. There were no significant differences in age, sex, age at onset, disease duration, LEDD, UPDRS-I, UPDRS-III, and MoCA scores between the different motor subtypes. As shown in Table 1 , H-Y stage [3 (2–4) versus 2 (1–2), p < 0.05], UPDRS-II score [16.50 (8.75–22.00) versus 11.62 ± 5.75, p < 0.05], SCOPA-AUT score (14.56 ± 7.96 versus 8.28 ± 5.96, p < 0.01), and the PDQ39 score (37.94 ± 9.55 versus 28.17 ± 7.37, p < 0.01) were all significantly higher in the PIGD group compared with the TD group.

CCM parameters in different motor subtypes with PD

CNFD [no./mm 2 , 24.09 ± 4.58 versus 28.66 ± 4.27; mean difference, 4.57; 95% confidence interval (CI), 1.96–7.18; p < 0.001] and CNBD (no./mm 2 , 28.22 ± 11.11 versus 37.37 ± 12.76; mean difference, 9.15; 95% CI, 1.41–16.88; p = 0.015) were significantly lower in the PIGD group compared with the TD group. CNFL in the PIGD (mm/mm 2 , 13.11 ± 2.79 versus 16.17 ± 2.37; mean difference, 3.06; 95% CI, 1.42–4.69; p < 0.001) and mixed (mm/mm 2 , 13.72 ± 2.88 versus 16.17 ± 2.37; mean difference, 2.45; 95% CI, 0.07–4.83; p = 0.041) group was significantly lower than in the TD group. CCM parameters in the mixed group lay between the TD and PIGD group, with no significant differences between them, except for a lower CNFL compared with the TD group. The data are shown in Figure 1 , and representative images of the corneal nerve fibers in each subgroup are shown in Figure 2 .

Logistic regression analysis

The logistic regression analyses between corneal nerve parameters and motor subtypes are summarized in Table 2 . Univariate logistic regression analysis with motor subtypes as the dependent variable showed a significant association with CNFD [odds ratio (OR) = 1.278, p = 0.001] and CNFL (OR = 1.691, p < 0.001). To better explore the independent association between corneal nerve fiber measures and the motor subtypes, a multivariate logistic regression model was applied with the PIGD subtype as the reference. Overall, a higher CNFD was significantly associated with the TD motor subtype (OR = 1.265, p = 0.019) after adjusting for confounders, including H-Y stage, SCOPA-AUT, and UPDRS-II. With every unit increase in CNFD, patients were 26.5% more likely to have the TD subtype as opposed to the PIGD subtype. With every unit decrease in CNFD, patients were 20.9% more likely to have the PIGD subtype ( Figure 3(a) ). Similarly, CNFL was associated with the TD subtype (OR = 1.706, p = 0.003) after adjusting for confounders. With every unit increase in CNFL, patients were 70.6% more likely to have the TD subtype as opposed to the PIGD subtype. With every unit decrease in CNFL, patients were 41.4% more likely to have the PIGD subtype ( Figure 3(b) ). There was no relationship between CNBD and motor subtypes in multivariate logistic regression.

Diagnostic utility of CCM

ROC analysis showed that CNFD, CNBD, and CNFL could distinguish between TD and PIGD subtypes with an area under the curve (AUC) of 77.69% (95% CI, 65.65–89.73%), 67.70% (95% CI, 54.47–80.93%), and 81.74% (95% CI, 71.08–92.41%), respectively. Using a CNFD cutoff of <27.98 no./mm 2 , the sensitivity and specificity for TD was 85.29% and 65.52%, respectively. Using a CNBD cutoff of <25.96 no./mm 2 , the sensitivity and specificity for TD were 44.12% and 89.66%, respectively. Using a CNFL cutoff of <15.02 mm/mm 2 , the sensitivity and specificity for TD were 76.47% and 79.31%, respectively. A combination of all three corneal nerve parameters increased the AUC to 83.16% (95% CI, 72.60–93.73%), with a sensitivity and specificity of 85.29% and 79.31%, respectively ( Figure 4 ).

Discussion

PD is a clinically heterogeneous disease, and the motor phenotype may be a good predictor of disease progression. Not only do the PIGD subtype have an increased risk of falls and gait freezing 27 , 28 but they also have a poorer prognosis with more rapid disease progression, compared with the TD subtype. 5 At present, subtype diagnosis is based primarily on clinical evaluation and reliable biomarkers to differentiate subtypes are lacking.

In the early, de novo , drug-naïve patients from Parkinson’s Progression Markers Initiative (PPMI) study, cerebrospinal fluid (CSF) α-synuclein, Aβ1-42, and phosphorylated-tau181 concentrations were lower in the PIGD subtype compared with the TD subtype. 29 In the BioFIND study of patients with moderate-advanced PD, Goldman et al . 30 showed that lower CSF alpha-synuclein correlated with the PIGD subtype, but not with other motor subtypes. While these CSF proteins may help to differentiate motor subtypes, lumbar puncture is invasive and therefore has limited clinical utility. Plasma neurofilament light chain, a marker of axonal degeneration, may act as a good diagnostic and prognostic biomarker in PIGD, but has a low ability to discriminate between motor subtypes. 31 A recent study from China has shown lower plasma Aβ-42 and higher α-synuclein levels in the PIGD group, 32 but the results need further verification in larger sample.

The presence of peripheral neuropathy is associated with a tripling in the frequency of falls in PD patients. 33 Peripheral neuropathy has also been shown to be an independent marker of a severe PD phenotype, with worse cognitive function, and motor and autonomic symptoms. 34 We previously reported a lower CNFD and higher CNBD indicative of concomitant small fiber degeneration and regeneration in patients with mild-moderate PD. 17 , 35 Furthermore, the severity of corneal nerve loss correlated with the severity of cognitive, autonomic, and motor dysfunction. 17 , 18 In this study, we show that patients with the PIGD subtype have greater corneal nerve loss evidenced by a lower CNFD, CNBD, and CNFL compared with the TD motor subtype. Furthermore, patients with the PIGD subtype had more severe disease severity (higher H-Y stage), autonomic dysfunction (higher SCOPA-AUT score), impairment in activity of daily living (increased UPDRS-II score), and a decreased quality of life (increased PDQ-39 score) compared with the TD subtype, consistent with other studies. 5 , 27 , 36 We have also shown that combined corneal nerve parameters have an excellent diagnostic utility for differentiating the TD from the PIGD subtypes, with an AUC of 0.832, far superior to plasma neurofilament light chain, with an AUC of only 0.656. 31 Furthermore, logistic regression analyses showed that CNFD and CNFL were associated with the TD and PIGD motor subtypes after adjusting for confounders. We speculate that small fiber neuropathy combined with progressive dopaminergic dysfunction may contribute to faster progression and a poorer prognosis in the PIGD subtype of PD.

The present findings add to the growing body of data showing corneal nerve fiber loss in a range of neurodegenerative diseases, including dementia, 15 , 37 amyotrophic lateral sclerosis, 38 Friedreich’s ataxia, 39 multiple sclerosis, 40 , 41 and PD. 16 – 19 Indeed, progressive corneal nerve fiber loss is evident in subjects with mild cognitive impairment (MCI) and dementia, 15 and is associated with cognitive dysfunction and functional independence. 37 Corneal nerve fiber loss has also been reported in patients with amyotrophic lateral sclerosis and related to disease severity. 38 In patients with Friedreich’s ataxia, corneal nerve fiber loss correlates with increasing clinical severity scores. 39 Corneal nerve loss also occurs in patients with multiple sclerosis, 40 and progressive loss is associated with progression of neurological disability. 41

We acknowledge limitations in our study including a single-center and cross-sectional design and the lack of inclusion of an akinetic rigid (AR) subgroup of patients with PD. We also acknowledge that patients may shift between motor subtypes with disease progression, 42 , 43 which requires further analysis in a longitudinal study. The sample size of this study was relatively small, and future larger studies should include more patients with the mixed subtype and with the AR subtype. The PD patients were all clinically diagnosed, without a pathological diagnosis, and therefore we cannot exclude the possibility that some patients may eventually develop atypical parkinsonism. There was overlap of CCM parameters between groups, and therefore, a single CCM examination is not sufficient for clinical differentiation.

In conclusion, PD patients with the PIGD subtype have evidence of greater corneal nerve fiber loss compared to the TD subtype. CCM had excellent diagnostic utility with a high sensitivity and specificity to distinguish the PIGD from the TD subtype. CCM may represent a rapid convenient ophthalmic imaging technique to identify motor subtypes in PD. Our findings warrant larger, longitudinal studies to establish the utility of CCM in the monitoring and prognostication of PD subtypes.

Supplemental Material

sj-docx-1-tan-10.1177_17562864231165561 – Supplemental material for The severity of corneal nerve loss differentiates motor subtypes in patients with Parkinson’s disease

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Supplemental material, sj-docx-1-tan-10.1177_17562864231165561 for The severity of corneal nerve loss differentiates motor subtypes in patients with Parkinson’s disease by Ning-Ning Che, Qiu-Huan Jiang, Shuai Chen, Si-Yuan Chen, Zhen-Xiang Zhao, Xue Li, Jian-Jun Ma, Jie-Wen Zhang, Rayaz A. Malik and Hong-Qi Yang in Therapeutic Advances in Neurological Disorders

The authors thank the patients and healthy individuals for their participation in this study. They also thank the Manchester Biomedical Research Centre for access to the CCMetrics and ACCMetrics software.

ORCID iDs: Ning-Ning Che https://orcid.org/0000-0002-5470-2003

Jian-Jun Ma https://orcid.org/0000-0001-8136-695X

Rayaz A. Malik https://orcid.org/0000-0002-7188-8903

Hong-Qi Yang https://orcid.org/0000-0002-9277-0920

Supplemental material: Supplemental material for this article is available online.

Declarations

Ethics approval and consent to participate: The study was approved by the Ethics Committee of Henan Provincial People’s Hospital (No. 202148). All subjects agreed to participate in the study and provided a written informed consent.

Consent for publication: Not applicable.

Author contributions: Ning-Ning Che: Conceptualization; Data curation; Formal analysis; Methodology; Writing – original draft.

Qiu-Huan Jiang: Investigation; Methodology.

Shuai Chen: Investigation; Methodology.

Si-Yuan Chen: Investigation; Methodology.

Zhen-Xiang Zhao: Investigation; Methodology.

Xue Li: Funding acquisition; Investigation; Methodology.

Jian-Jun Ma: Investigation; Methodology.

Jie-Wen Zhang: Investigation; Methodology.

Rayaz A. Malik: Methodology; Software.

Hong-Qi Yang: Conceptualization; Funding acquisition; Project administration; Supervision; Writing – review & editing.

Funding: The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The study was funded by Talent project of Henan Provincial People’s Hospital (23456-4), Henan Province Science and Technology Development Plan (192102310085), and Henan Province Medical Science and Technology Research Program (SBGJ202002005).

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Availability of data and materials: The data used and analyzed during this study are available from the corresponding author on reasonable request.

References

1 Camacho M Macleod AD Maple-Grodem J , et al . Early constipation predicts faster dementia onset in Parkinson’s disease . NPJ Parkinsons Dis 2021 ; 7 : 45 . 34039994 10.1038/s41531-021-00191-w PMC8154963

2 Che NN Yang HQ. Potential use of corneal confocal microscopy in the diagnosis of Parkinson’s disease associated neuropathy . Transl Neurodegener 2020 ; 9 : 28 . 32611440 10.1186/s40035-020-00204-3 PMC7330988

3 Nutt JG. Motor subtype in Parkinson’s disease: different disorders or different stages of disease? Mov Disord 2016 ; 31 : 957 – 961 . 27226220 10.1002/mds.26657

4 Zhang YH Tang BS Song CY , et al . The relationship between the phenotype of Parkinson’s disease and levodopa-induced dyskinesia . Neurosci Lett 2013 ; 556 : 109 – 112 . 24135335 10.1016/j.neulet.2013.10.018

5 van der Heeden JF Marinus J Martinez-Martin P , et al . Postural instability and gait are associated with severity and prognosis of Parkinson disease . Neurology 2016 ; 86 : 2243 – 2250 . 27178702 10.1212/WNL.0000000000002768

6 Aleksovski D Miljkovic D Bravi D , et al . Disease progression in Parkinson subtypes: the PPMI dataset . Neurol Sci 2018 ; 39 : 1971 – 1976 . 30109466 10.1007/s10072-018-3522-z

7 Reijnders JS Ehrt U Lousberg R , et al . The association between motor subtypes and psychopathology in Parkinson’s disease . Parkinsonism Relat Disord 2009 ; 15 : 379 – 382 . 18977165 10.1016/j.parkreldis.2008.09.003

8 Melli G Vacchi E Biemmi V , et al . Cervical skin denervation associates with alpha-synuclein aggregates in Parkinson disease . Ann Clin Transl Neurol 2018 ; 5 : 1394 – 1407 . 30480033 10.1002/acn3.669 PMC6243385

9 Vacchi E Senese C Chiaro G , et al . Alpha-synuclein oligomers and small nerve fiber pathology in skin are potential biomarkers of Parkinson’s disease . NPJ Parkinsons Dis 2021 ; 7 : 119 . 34930911 10.1038/s41531-021-00262-y PMC8688481

10 Ceravolo R Cossu G Bandettini di Poggio M , et al . Neuropathy and levodopa in Parkinson’s disease: evidence from a multicenter study . Mov Disord 2013 ; 28 : 1391 – 1397 . 23836370 10.1002/mds.25585

11 Donadio V Incensi A Leta V , et al . Skin nerve alpha-synuclein deposits: a biomarker for idiopathic Parkinson disease . Neurology 2014 ; 82 : 1362 – 1369 . 24634456 10.1212/WNL.0000000000000316

12 Park JS Park D Ko PW , et al . Serum methylmalonic acid correlates with neuropathic pain in idiopathic Parkinson’s disease . Neurol Sci 2017 ; 38 : 1799 – 1804 . 28726051 10.1007/s10072-017-3056-9

13 Cossu G Melis M. The peripheral nerve involvement in Parkinson disease: a multifaceted phenomenon . Parkinsonism Relat Disord 2016 ; 25 : 17 – 20 . 26857398 10.1016/j.parkreldis.2016.01.026

14 Perkins BA Lovblom LE Lewis EJH , et al . Corneal confocal microscopy predicts the development of diabetic neuropathy: a longitudinal diagnostic multinational consortium study . Diabetes Care 2021 ; 44 : 2107 – 2114 . 34210657 10.2337/dc21-0476 PMC8740920

15 Ponirakis G Hamad HA Khan A , et al . Loss of corneal nerves and brain volume in mild cognitive impairment and dementia . Alzheimers Dement 2022 ; 8 : e12269. 10.1002/trc2.12269 PMC8983001 35415208

16 Podgorny PJ Suchowersky O Romanchuk KG , et al . Evidence for small fiber neuropathy in early Parkinson’s disease . Parkinsonism Relat Disord 2016 ; 28 : 94 – 99 . 27160569 10.1016/j.parkreldis.2016.04.033

17 Che NN Jiang QH Ding GX , et al . Corneal nerve fiber loss relates to cognitive impairment in patients with Parkinson’s disease . NPJ Parkinsons Dis 2021 ; 7 : 80 . 34504084 10.1038/s41531-021-00225-3 PMC8429586

18 Che NN Chen S Jiang QH , et al . Corneal confocal microscopy differentiates patients with Parkinson’s disease with and without autonomic involvement . NPJ Parkinsons Dis 2022 ; 8 : 114 . 36085290 10.1038/s41531-022-00387-8 PMC9463159

19 Lim SH Ferdousi M Kalteniece A , et al . Corneal confocal microscopy identifies Parkinson’s disease with more rapid motor progression . Mov Disord 2021 ; 36 : 1927 – 1934 . 33826165 10.1002/mds.28602

20 Postuma RB Berg D Stern M , et al . MDS clinical diagnostic criteria for Parkinson’s disease . Mov Disord 2015 ; 30 : 1591 – 1601 . 26474316 10.1002/mds.26424

21 Goetz CG Tilley BC Shaftman SR , et al . Movement disorder society-sponsored revision of the unified Parkinson’s Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results . Mov Disord 2008 ; 23 : 2129 – 2170 . 19025984 10.1002/mds.22340

22 Tomlinson CL Stowe R Patel S , et al . Systematic review of levodopa dose equivalency reporting in Parkinson’s disease . Mov Disord 2010 ; 25 : 2649 – 2653 . 21069833 10.1002/mds.23429

23 Stebbins GT Goetz CG Burn DJ , et al . How to identify tremor dominant and postural instability/gait difficulty groups with the movement disorder society unified Parkinson’s disease rating scale: comparison with the unified Parkinson’s disease rating scale . Mov Disord 2013 ; 28 : 668 – 670 . 23408503 10.1002/mds.25383

24 Tavakoli M Malik RA. Corneal confocal microscopy: a novel non-invasive technique to quantify small fibre pathology in peripheral neuropathies . J Vis Exp 2011 ; 47 : 2194 . 10.3791/2194 PMC3182640 21248693

25 Ferdousi M Azmi S Petropoulos IN , et al . Corneal confocal microscopy detects small fibre neuropathy in patients with upper gastrointestinal cancer and nerve regeneration in chemotherapy induced peripheral neuropathy . PLoS ONE 2015 ; 10 : e0139394. 10.1371/journal.pone.0139394 PMC4592260 26430773

26 Ponirakis G Ghandi R Ahmed A , et al . Abnormal corneal nerve morphology and brain volume in patients with schizophrenia . Sci Rep 2022 ; 12 : 1870 . 35115592 10.1038/s41598-022-05609-w PMC8814184

27 Kwon KY Lee EJ Lee M , et al . Impact of motor subtype on non-motor symptoms and fall-related features in patients with early Parkinson’s disease . Geriatr Gerontol Int 2021 ; 21 : 416 – 420 . 33780137 10.1111/ggi.14156

28 Pelicioni PHS Menant JC Latt MD , et al . Falls in Parkinson’s disease subtypes: risk factors, locations and circumstances . Int J Environ Res Public Health 2019 ; 16 : 2216 . 31234571 10.3390/ijerph16122216 PMC6616496

29 Kang JH Mollenhauer B Coffey CS , et al . CSF biomarkers associated with disease heterogeneity in early Parkinson’s disease: the Parkinson’s progression markers initiative study . Acta Neuropathol 2016 ; 131 : 935 – 949 . 27021906 10.1007/s00401-016-1552-2 PMC5031365

30 Goldman JG Andrews H Amara A , et al . Cerebrospinal fluid, plasma, and saliva in the BioFIND study: relationships among biomarkers and Parkinson’s disease features . Mov Disord 2018 ; 33 : 282 – 288 . 29205509 10.1002/mds.27232 PMC5836918

31 Ng ASL Tan YJ Yong ACW , et al . Utility of plasma neurofilament light as a diagnostic and prognostic biomarker of the postural instability gait disorder motor subtype in early Parkinson’s disease . Mol Neurodegener 2020 ; 15 : 33 . 32503574 10.1186/s13024-020-00385-5 PMC7275464

32 Ding J Zhang J Wang X , et al . Relationship between the plasma levels of neurodegenerative proteins and motor subtypes of Parkinson’s disease . J Neural Transm 2017 ; 124 : 353 – 360 . 27878377 10.1007/s00702-016-1650-2

33 Beaulieu ML Müller MLTM Bohnen NI. Peripheral neuropathy is associated with more frequent falls in Parkinson’s disease . Parkinsonism Relat Disord 2018 ; 54 : 46 – 50 . 29625874 10.1016/j.parkreldis.2018.04.006 PMC6163065

34 Merola A Rosso M Romagnolo A , et al . Peripheral neuropathy as marker of severe Parkinson’s disease phenotype . Mov Disord 2017 ; 32 : 1256 – 1258 . 28582598 10.1002/mds.27025

35 Kass-Iliyya L Javed S Gosal D , et al . Small fiber neuropathy in Parkinson’s disease: a clinical, pathological and corneal confocal microscopy study . Parkinsonism Relat Disord 2015 ; 21 : 1454 – 1460 . 26578039 10.1016/j.parkreldis.2015.10.019 PMC4671992

36 Wang JY Wang MY Liu RP , et al . Association analyses of autonomic dysfunction and sympathetic skin response in motor subtypes of Parkinson’s disease . Front Neurol 2020 ; 11 : 577128 . 33224091 10.3389/fneur.2020.577128 PMC7669620

37 Ponirakis G Al Hamad H Sankaranarayanan A , et al . Association of corneal nerve fiber measures with cognitive function in dementia . Ann Clin Transl Neurol 2019 ; 6 : 689 – 697 . 31019993 10.1002/acn3.746 PMC6469344

38 Fu J He J Zhang Y , et al . Small fiber neuropathy for assessment of disease severity in amyotrophic lateral sclerosis: corneal confocal microscopy findings . Orphanet J Rare Dis 2022 ; 17 : 7 . 34991673 10.1186/s13023-021-02157-w PMC8734326

39 Pagovich OE Vo ML Zhao ZZ , et al . Corneal confocal microscopy: neurologic disease biomarker in Friedreich ataxia . Ann Neurol 2018 ; 84 : 893 – 904 . 30294800 10.1002/ana.25355

40 Bitirgen G Akpinar Z Malik RA , et al . Use of corneal confocal microscopy to detect corneal nerve loss and increased dendritic cells in patients with multiple sclerosis . JAMA Ophthalmol 2017 ; 135 : 777 – 782 . 28570722 10.1001/jamaophthalmol.2017.1590 PMC5710203

41 Bitirgen G Akpinar Z Uca AU , et al . Progressive loss of corneal and retinal nerve fibers in patients with multiple sclerosis: a 2-year follow-up study . Transl Vis Sci Technol 2020 ; 9 : 37 . 10.1167/tvst.9.13.37 PMC7757607 33384891

42 Alves G Larsen JP Emre M , et al . Changes in motor subtype and risk for incident dementia in Parkinson’s disease . Mov Disord 2006 ; 21 : 1123 – 1130 . 16637023 10.1002/mds.20897

43 Eisinger RS Hess CW Martinez-Ramirez D , et al . Motor subtype changes in early Parkinson’s disease . Parkinsonism Relat Disord 2017 ; 43 : 67 – 72 . 28754232 10.1016/j.parkreldis.2017.07.018 PMC5842811