Substantial variability and severity of dysarthric patterns across Parkinson's disease (PD) patients may reflect distinct phenotypic differences. We aimed to compare patterns of speech disorder in early-onset PD (EOPD) and late-onset PD (LOPD) in drug-naive patients at early stages of disease. Speech samples were acquired from a total of 96 participants, including two subgroups of 24 de-novo PD patients and two subgroups of 24 age- and sex-matched young and old healthy controls. The EOPD group included patients with age at onset below 51 (mean 42.6, standard deviation 6.1) years and LOPD group patients with age at onset above 69 (mean 73.9, standard deviation 3.0) years. Quantitative acoustic vocal assessment of 10 unique speech dimensions related to respiration, phonation, articulation, prosody, and speech timing was performed. Despite similar perceptual dysarthria severity in both PD subgroups, EOPD showed weaker inspirations (p = 0.03), while LOPD was characterized by decreased voice quality (p = 0.02) and imprecise consonant articulation (p = 0.03). In addition, age-independent occurrence of monopitch (p < 0.001), monoloudness (p = 0.008), and articulatory decay (p = 0.04) was observed in both PD subgroups. The worsening of consonant articulation was correlated with the severity of axial gait symptoms (r = 0.38, p = 0.008). Speech abnormalities in EOPD and LOPD share common features but also show phenotype-specific characteristics, likely reflecting the influence of aging on the process of neurodegeneration. The distinct pattern of imprecise consonant articulation can be interpreted as an axial motor symptom of PD.

Department of Circuit Theory Faculty of Electrical Engineering Czech Technical University Prague Prague Czech Republic

Department of Neurology and Centre of Clinical Neuroscience 1st Faculty of Medicine Charles University Prague Czech Republic

Zobrazit více v PubMed

Poewe W, et al. Parkinson disease. Nat. Rev. Dis. Prim. 2017;23:17013. PubMed

Hirsch L, Jette N, Frolkis A, Steeves T, Pringsheim T. The incidence of Parkinson’s disease: a systematic review and meta-analysis. Neuroepidemiology. 2016;46:292–300. PubMed

Schrag A, Schott JM. Epidemiological, clinical, and genetic characteristics of early onset parkinsonism. Lancet Neurol. 2006;5:355–363. PubMed

Gibb WR, Lees AJ. A comparison of clinical and pathological features of young- and old-onset Parkinson’s disease. Neurology. 1988;38:1402–1406. PubMed

Mehanna R, Moore S, Hou JG, Sarwar AI, Lai EC. Comparing clinical features of young onset, middle onset and late onset Parkinson’s disease. Parkinsonism Relat. Disord. 2014;20:530–534. PubMed

Guo X, et al. Gender and onset age-related features of non-motor symptoms of patients with Parkinson’s disease—a study from southwest China. Parkinsonism Relat. Disord. 2013;19:961–965. PubMed

Jankovic J, et al. Variable expression of Parkinson’s disease: a base-line analysis of the DATATOP cohort. The Parkinson Study Group. Neurology. 1990;40:1529–1534. PubMed

Pagano G, Ferrara N, Brooks DJ, Pavese N. Age at onset and Parkinson disease phenotype. Neurology. 2016;86:1400–1407. PubMed PMC

Ho AK, Iansek R, Marigliani C, Bradshaw JL, Gates S. Speech impairment in a large sample of patients with Parkinson’s disease. Behav. Neurol. 1998;11:131–137. PubMed

Duffy JR. Motor Speech Disorders: Substrates, Differential Diagnosis and Management. 4th ed. St. Louis: Mosby; 2019.

Rusz J, Cmejla R, Ruzickova H, Ruzicka E. Quantitative acoustic measurements for characterization of speech and voice disorders in early untreated Parkinson’s disease. J. Acoust. Soc. Am. 2011;129:350–367. PubMed

Sharpe G, Macerollo A, Fabbri M, Tripoliti E. Non-pharmacological treatment challenges in early Parkinson’s disease for axial and cognitive symptoms: a mini review. Front Neurol. 2020;11:576569. PubMed PMC

Tykalová T, et al. Speech disorder and vocal tremor in postural instability/gait difficulty and tremor dominant subtypes of Parkinson’s disease. J. Neural Transm. 2020;127:1295–1304. PubMed

Moreau C, et al. Oral festination in Parkinson’s disease: biochemical analysis and correlation within festination and freezing of gait. Mov. Disord. 2007;22:1503–1506. PubMed

Cantiniaux S, et al. Comparative analysis of gait and speech in Parkinson’s disease: hypokinetic or dysrhythmic disorders? J. Neurol. Neurosurg. Psychiatry. 2010;166:158–167. PubMed

Park HK, et al. Gait freezing and speech disturbance in Parkinson’s disease. Neurol. Sci. 2014;35:357–363. PubMed

Gomez Arevalo G, Jorge R, Garcia S, Scipioni O, Gershanik O. Clinical and pharmacological differences in early- versus late-onset Parkinson’s disease. Mov. Disord. 1997;12:277–284. PubMed

Pinto S, et al. Treatments for dysarthria in Parkinson’s disease. Lancet Neurol. 2004;3:547–556. PubMed

Shih MC, et al. Higher nigrostriatal dopamine neuron loss in early than late onset Parkinson’s disease?–a [99mTc]-TRODAT-1 SPECT study. Mov. Disord. 2007;22:863–866. PubMed

Rusz J, et al. Speech disorders reflect differing pathophysiology in Parkinson’s disease, progressive supranuclear palsy and multiple system atrophy. J. Neurol. 2015;262:992–1001. PubMed

Tykalova T, Rusz J, Klempir J, Cmejla R, Ruzicka E. Distinct patterns of consonant articulation among Parkinson’s disease, progressive supranuclear palsy and multiple system atrophy. Brain. Lang. 2017;165:1–9. PubMed

Wong DF, et al. Effects of age on dopamine and serotonin receptors measured by positron tomography in the living human brain. Science. 1984;226:1393–1396. PubMed

Skodda S, Visser W, Schlegel U. Gender related patterns of dysprosody in Parkinson’s disease and correlation between speech variables and motor symptoms. J. Voice. 2011;25:76–82. PubMed

Defazio G, Guerrieri M, Liuzzi D, Gigante AF, di Nicola V. Assessment of voice and speech symptoms in early Parkinson’s disease by the Robertson dysarthria profile. Neurol. Sci. 2016;37:443–449. PubMed

Enright PL, Kronmal RA, Manolio MB, Schenker MB, Hyatt RE. Respiratory muscle strength in the elderly. Correlates and reference values. Cardiovascular Health Study Research Group. Am. J. Respir. Crit. Care Med. 1994;149:430–438. PubMed

Baille G, et al. Early occurrence of inspiratory muscle weakness in Parkinson’s disease. PLoS ONE. 2018;13:e0190400. PubMed PMC

Hixon TJ. Kinematics of the chest wall during speech production: volume displacements of the rib cage, abdomen, and lung. J. Speech Hear. Res. 1973;16:78–115. PubMed

Hunker CJ, Abbs JH, Barlow SM. The relationship between parkinsonian rigidity and hypokinesia in the orofacial system: a quantitative analysis. Neurology. 1982;32:749–754. PubMed

Hiss SG, Treole K, Stuart A. Effect of age, gender, and repeated measures on intraoral air pressure in normal adults. J. Voice. 2001;15:159–164. PubMed

Hammer MJ, Barlow SM. Laryngeal somatosensory deficits in Parkinson’s disease: implications for speech respiratory and phonatory control. Exp. Brain Res. 2010;201:401–409. PubMed PMC

Darley FL, Aronson AE, Brown JR. Differential diagnostic patterns of dysarthria. J. Speech Hear. Res. 1969;12:246–269. PubMed

Logemann JA, Fisher HB, Boshes B, Blonsky ER. Frequency and coocurence of vocal tract dysfunction in the speech of a large sample of Parkinson patients. J. Speech Hear. Disord. 1978;43:47–57. PubMed

Rusz J, et al. Speech biomarkers in REM sleep behaviour disorder and Parkinson’s disease. Ann. Neurol. 2021;90:62–75. PubMed PMC

Schenck CH, Boeve BF, Mahowald MW. Delayed emergence of a Parkinsonian disorder or dementia in 81% of older men initially diagnosed with idiopathic rapid eye movement sleep behavior disorder: a 16-year update on a previously reported series. Sleep. Med. 2013;14:744–748. PubMed

Illner V, Sovka P, Rusz J. Validation of freely-available pitch detection algorithms across various noise levels in assessing speech captured by smartphone in Parkinson’s disease. Biomed. Sig. Proces. Control. 2020;58:101831.

Lipsmeier F, et al. Evaluation of smartphone-based testing to generate exploratory outcome measures in a phase 1 Parkinson’s disease clinical trial. Mov. Disord. 2018;33:1287–1297. PubMed PMC

Arora S, et al. Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD. Neurology. 2018;91:e1528–e1538. PubMed PMC

Rusz J, et al. Smartphone allows capture of speech abnormalities associated with high risk of developing Parkinson’s disease. IEEE Trans. Neural Syst. Rehabil. Eng. 2018;26:1495–1507. PubMed

Goy H, Fernandes DN, Pichora-Fuller MK, van Lieshout P. Normative voice data for younger and older adults. J. Voice. 2013;27:545–555. PubMed

Bona J. Temporal characteristics of speech: the effect of age and speech style. J. Acoust. Soc. Am. 2014;136:EL116–EL121. PubMed

Tykalova T., et al. Effect of ageing on acoustic characteristics of voice pitch and formants in Czech vowels. J. Voice (2020). 10.1016/j.jvoice.2020.02.022. PubMed

Holden SK, Finseth T, Sillau SH, Berman BD. Progression of MDS-UPDRS scores over five years in de novo Parkinson disease from the Parkinson’s progression markers initiative cohort. Mov. Disord. Clin. Pract. 2018;5:47–53. PubMed PMC

Dušek P, et al. Clinical characteristics of newly diagnosed Parkinson’s disease patients included in the longitudinal BIO-PD study. Cesk. Slov. Neurol. Neurochir. 2020;83/116:633–639.

Yarnall AJ, et al. Characterizing mild cognitive impairment in incident Parkinson disease: the ICICLE-PD study. Neurology. 2014;82:308–316. PubMed PMC

Mollenhauer B, et al. Nonmotor and diagnostic findings in subjects with de novo Parkinson disease of the DeNoPa cohort. Neurology. 2013;81:1226–1234. PubMed

Ciesielska N, et al. Is the Montreal Cognitive Assessment (MoCA) test better suited than the Mini-Mental State Examination (MMSE) in mild cognitive impairment (MCI) detection among people aged over 60? Meta-analysis. Psychiatr. Pol. 2016;50:1039–1052. PubMed

Kopecek M, et al. Montreal cognitive assessment (MoCA): normative data for old and very old Czech adults. Appl. Neuropsychol. Adult. 2017;24:23–29. PubMed

Mazancova, A. F., Růžička, E., Jech, R., Bezdicek, O. Test the best: classification accuracies of four cognitive rating scales for Parkinson’s disease mild cognitive impairment. Arch. Clin. Neuropsychol. (2020). 10.1093/arclin/acaa039. PubMed

Selikhova M, et al. A clinico-pathological study of subtypes in Parkinson’s disease. Brain. 2009;132:2947–2957. PubMed

Postuma RB, et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov. Disord. 2015;30:1591–1601. PubMed

Goetz CG, et al. Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): process, format, and clinimetric testing plan. Mov. Disord. 2007;22:41–47. PubMed

Nasreddine ZS, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J. Am. Geriatr. Soc. 2005;53:695–699. PubMed

Visser M, Marinus J, Stiggelbout A, Van Hilten JJV. Assessment of autonomic dysfuntion in Parkinson’s disease: the SCOPA-AUT. Mov. Disord. 2004;19:1306–1312. PubMed

D’Agostino RB, Wolf PA, Belanger AJ, Kannel WB. Stroke risk profile: adjustment for antihypertensive medication. The Framingham Study. Stroke. 1994;25:40–43. PubMed

Rusz J, Tykalova T, Ramig LO, Tripoliti E. Guidelines for speech recording and acoustic analyses in dysarthrias of movement disorders. Mov. Disord. 2021;36:803–814. PubMed

Hlavnicka J. Ph.D. Thesis, Faculty of Electrical Engineering. Prague, Czechia: Czech Technical University; 2018. Automated analysis of speech disorders in neurodegenerative diseases.

Hlavnicka J, et al. Automated analysis of connected speech reveals early biomarkers of Parkinson’s disease in patients with rapid eye movement sleep behaviour disorder. Sci. Rep. 2017;7:12. PubMed PMC

Hlavnicka J, Cmejla R, Klempir J, Ruzicka E, Rusz J. Acoustic tracking of pitch, modal and subharmonic vibrations of vocal folds in Parkinson’s disease and Parkinsonism. IEEE Access. 2019;7:150339–150354.

Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav. Res. Methods. 2007;39:175–191. PubMed

Digital speech biomarkers can measure acute effects of levodopa in Parkinson's disease

Detecting neuropsychiatric fluctuations in Parkinson's Disease using patients' own words: the potential of large language models