A cross‐sectional comprehensive assessment of the profile and burden of non‐motor symptoms in relation to motor phenotype in the Nigeria Parkinson Disease Registry cohort

2021 ◽  
Author(s):  
Oluwadamilola O. Ojo ◽  
Kolawole W. Wahab ◽  
Abiodun H. Bello ◽  
Sani A. Abubakar ◽  
Bertha C. Ekeh ◽  
...  
Keyword(s):  
Parkinson Disease ◽  
Comprehensive Assessment ◽  
Motor Symptoms ◽  
Disease Registry ◽  
Cross Sectional ◽  
Non Motor Symptoms ◽  
Motor Phenotype

scholarly journals Parkinson Disease: The Relationship Between Non-motor Symptoms and Motor Phenotype

2015 ◽  
Vol 43 (2) ◽  
pp. 261-267 ◽  
Author(s):  
Fang Ba ◽  
Mona Obaid ◽  
Marguerite Wieler ◽  
Richard Camicioli ◽  
W.R. Wayne Martin
Keyword(s):  
Parkinson Disease ◽  
Rating Scales ◽  
Advanced Disease ◽  
Axial Component ◽  
Motor Symptoms ◽  
Linear Regression Models ◽  
Cross Sectional ◽  
The Relationship ◽  
Non Motor Symptoms ◽  
Motor Phenotype

AbstractBackground: Parkinson disease (PD) presents with motor and non-motor symptoms (NMS). The NMS often precede the onset of motor symptoms, but may progress throughout the disease course. Tremor dominant, postural instability gait difficulty (PIGD), and indeterminate phenotypes can be distinguished using Unified PD Rating scales (UPDRS-III). We hypothesized that the PIGD phenotype would be more likely to develop NMS, and that the non-dopamine–responsive axial signs would correlate with NMS severity. Methods: We conducted a retrospective cross-sectional chart review to assess the relationship between NMS and PD motor phenotypes. PD patients were administered the NMS Questionnaire, the UPDRS-III, and the Mini-Mental State Examination score. The relationship between NMS burden and PD subtypes was examined using linear regression models. The prevalence of each NMS among difference PD motor subtypes was analyzed using chi-square test. Results: PD patients with more advanced disease based on their UPDRS-III had higher NMS Questionnaire scores. The axial component of UPDRS-III correlated with higher NMS. There was no correlation between NMS and tremor scores. There was a significant correlation between PIGD score and higher NMS burden. PIGD group had higher prevalence in most NMS domains when compared with tremor dominant and indeterminate groups independent of disease duration and severity. Conclusions: NMS profile and severity vary according to motor phenotype. We conclude that in the PD population, patients with a PIGD phenotype who have more axial involvement, associated with advanced disease and poor motor response, have a higher risk for a higher NMS burden.

P1.171 Evolving non-motor symptoms in Parkinson disease patients. A cross-sectional study

2009 ◽  
Vol 15 ◽  
pp. S73
Author(s):  
L. Vela ◽  
M.D. Martin Rios ◽  
M. Baron ◽  
F.J. Barriga ◽  
J.L. Dobato ◽  
...  
Keyword(s):  
Parkinson Disease ◽  
Cross Sectional Study ◽  
Motor Symptoms ◽  
Sectional Study ◽  
Cross Sectional ◽  
Non Motor Symptoms

Association between White Matter Lesions and Non-Motor Symptoms in Parkinson Disease

2018 ◽  
Vol 18 (2-3) ◽  
pp. 127-132 ◽  
Author(s):  
Jeong-Yoon Lee ◽  
Ji Sun Kim ◽  
Wooyoung Jang ◽  
Jinse Park ◽  
Eungseok Oh ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
White Matter ◽  
Parkinson Disease ◽  
Cognitive Dysfunction ◽  
Rating Scale ◽  
White Matter Lesions ◽  
Motor Dysfunction ◽  
Motor Symptoms ◽  
Non Motor Symptoms

Background: There are only few studies exploring the relationship between white matter lesions (WMLs) and non-motor symptoms in Parkinson disease (PD). This study aimed to investigate the association between WMLs and the severity of non-motor symptoms in PD. Methods: The severity of motor dysfunction, cognitive impairment, and non-motor symptoms was assessed by various scales in 105 PD patients. We used a visual semiquantitative rating scale and divided the subjects into four groups: no, mild, moderate, and severe WMLs. We compared the means of all scores between the four groups and analyzed the association between the severity of WMLs and the specific domain of non-motor symptoms. Results: The non-motor symptoms as assessed by the Non-Motor Symptoms Scale, Parkinson’s Disease Questionnaire (PDQ-39), Parkinson’s Disease Sleep Scale, Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), Neuropsychiatric Inventory (NPI), and Parkinson Fatigue Scale (PFS) were significantly worse in the patients with moderate and severe WMLs than in those without WMLs. Compared with the no WML group, the scores for motor dysfunction were significantly higher in the mild, moderate, and severe WML groups. The scores for cognitive dysfunction were significantly higher in the patients with severe WMLs than in those without WMLs. The severity of WMLs showed linear associations with PFS, BDI, BAI, NPI, and PDQ-39 scores. The severity of WMLs also correlated linearly with scores for motor and cognitive dysfunction. Conclusions: Among the non-motor symptoms, fatigue, depression, anxiety, and quality of life were significantly affected by WMLs in PD. Confirmation of the possible role of WMLs in non-motor symptoms associated with PD in a prospective manner may be crucial not only for understanding non-motor symptoms but also for the development of treatment strategies.

scholarly journals Change in Cognition and Other Non-Motor Symptoms With Obstructive Sleep Apnea Treatment in Parkinson Disease

2018 ◽  
Vol 14 (05) ◽  
pp. 819-828 ◽  
Author(s):  
Marta Kaminska ◽  
Victoria P. Mery ◽  
Anne-Louise Lafontaine ◽  
Ann Robinson ◽  
Andrea Benedetti ◽  
...  
Keyword(s):  
Obstructive Sleep Apnea ◽  
Sleep Apnea ◽  
Parkinson Disease ◽  
Motor Symptoms ◽  
Obstructive Sleep ◽  
Non Motor Symptoms ◽  
Sleep Apnea Treatment

scholarly journals Excessive Daytime Sleepiness Is Associated With Non-motor Symptoms of Multiple System Atrophy: A Cross-Sectional Study in China

2022 ◽  
Vol 12 ◽  
Author(s):  
Hui Wang ◽  
Xiangdong Tang ◽  
Junying Zhou ◽  
Yanming Xu
Keyword(s):  
Risk Factors ◽  
Multiple System Atrophy ◽  
Excessive Daytime Sleepiness ◽  
Disease Duration ◽  
Cross Sectional Study ◽  
Motor Dysfunction ◽  
Motor Symptoms ◽  
Sectional Study ◽  
Cross Sectional ◽  
Non Motor Symptoms

Objectives: Excessive daytime sleepiness (EDS) in multiple system atrophy (MSA) has received scant attention in the literature, thus the present cross-sectional study aimed to investigate the prevalence of EDS and its potential risk factors among Chinese patients with MSA.Methods: A total of 66 patients with MSA (60.6% males) were consecutively recruited. Eighteen patients (27.3%, 13 men) with Epworth Sleepiness Scale score >10 were defined as having EDS. Demographic, motor [Unified Multiple-System Atrophy (UMSARS)] and non-motor symptoms [Non-Motor Symptoms Scale (NMSS)], and sleep parameters [polysomnography (PSG)] were compared between patients with MSA with and without EDS. A logistic regression analysis was used to calculate the risk factors of EDS in patients with MSA.Results: There were no significant differences in age, sex, MSA onset age, disease duration, MSA sub-type, and motor symptom severity between MSA patients with and without EDS. However, compared with the MSA patients without EDS, their counterparts with EDS had higher scores of NMSS (65.3 ± 23.1 vs. 43.4 ± 25.3, P = .0002), Hamilton Anxiety (HAMA) [15.3 (10.3–20.0) vs. 9.5 (3.0–15.0), P = 0.006], Hamilton Depression (HAMD) [13.7 (12.5–17.8) vs. 9.0 (4.0–13.0), P = 0.015], and Fatigue Severity Scale (FSS) [29.8 (17.3–47.8) vs. 18.7 (10.3–21.8), P = 0.040]. Conversely, the patients with EDS had lower score of Mini-Mental State Examination (MMSE) [23.3 (20.3–27.0) vs. 25.7 (22.0–29.0), P = 0.023]. Similarly, there was a significantly lower percentage of N3 sleep (%) [0.3 (0–0) vs. 2.0 (0–0), P = 0.007] and a higher apnea-hypopnea index (AHI/h) [30.5 (14.5–47.8) vs. 19.3 (5.0–28.7), P = 0.034] in patients with EDS. After adjusting for age, sex, disease duration, MSA sub-type, and UMSARS score, the odds ratio (OR) (95% CI) of EDS was higher while increasing scores in FSS [1.06 (1.02–1.11)], HAMA [1.16 (1.04–1.28)], HAMD [1.13 (1.02–1.25)], NMSS [1.04 (1.01–1.07)], and AHI [1.03 (1.00–1.10)]. The OR of EDS was lower while the MMSE score was increasing [0.85 (0.72–1.00)].Conclusions: The presence and severity of EDS may be significantly associated with the non-motor dysfunction, including fatigue, anxiety, depression, cognitive dysfunction, and sleep-related breathing disorder, but not with the motor dysfunction in MSA.

scholarly journals Genotype-Phenotype Correlations in Monogenic Parkinson Disease: A Review on Clinical and Molecular Findings

2021 ◽  
Vol 12 ◽  
Author(s):  
Daniele Guadagnolo ◽  
Maria Piane ◽  
Maria Rosaria Torrisi ◽  
Antonio Pizzuti ◽  
Simona Petrucci
Keyword(s):  
Parkinson Disease ◽  
Movement Disorders ◽  
Sleep Disturbances ◽  
Cell Function ◽  
Neurodegenerative Disorder ◽  
Current Knowledge ◽  
Mendelian Inheritance ◽  
Motor Symptoms ◽  
The Many ◽  
Non Motor Symptoms

Parkinson disease (PD) is a complex neurodegenerative disorder, usually with multifactorial etiology. It is characterized by prominent movement disorders and non-motor symptoms. Movement disorders commonly include bradykinesia, rigidity, and resting tremor. Non-motor symptoms can include behavior disorders, sleep disturbances, hyposmia, cognitive impairment, and depression. A fraction of PD cases instead is due to Parkinsonian conditions with Mendelian inheritance. The study of the genetic causes of these phenotypes has shed light onto common pathogenetic mechanisms underlying Parkinsonian conditions. Monogenic Parkinsonisms can present autosomal dominant, autosomal recessive, or even X-linked inheritance patterns. Clinical presentations vary from forms indistinguishable from idiopathic PD to severe childhood-onset conditions with other neurological signs. We provided a comprehensive description of each condition, discussing current knowledge on genotype-phenotype correlations. Despite the broad clinical spectrum and the many genes involved, the phenotype appears to be related to the disrupted cell function and inheritance pattern, and several assumptions about genotype-phenotype correlations can be made. The interest in these assumptions is not merely speculative, in the light of novel promising targeted therapies currently under development.

Sign in / Sign up

Export Citation Format

Share Document