Study Objectives: The aim of the study was to investigate the relationship between 22 single nucleotide polymorphisms (SNPs) and Parkinson’s disease (PD) in the Chinese population.Methods: A total of 250 PD patients and 240 healthy controls were recruited. The SNaPshot technique and the polymer chain reaction were used to detect 22 SNPs.Results: rs8005172 of GALC, rs9468199 of ZNF184 and rs34043159 of IL1R2, were associated with PD (rs8005172: p = 0.009, OR = 0.69, allele model, p = 0.010, additive model, p = 0.015, OR = 2.17, dominant model; p = 0.020, OR = 2.11, dominant model after adjustment; p = 0.036, OR = 1.47, recessive model after adjustment; rs9468199: p = 0.008, OR = 1.52, allele model, p = 0.008, additive model, p = 0.007, OR = 0.22, recessive model, p = 0.005, OR = 0.20, recessive model after adjustment; rs34043159: p = 0.034, OR = 1.31, allele model, p = 0.036, additive model).Conclusion: Our study revealed that GALC, ZNF184, and IL1R2 were associated with PD in the southern Chinese population. GALC was also associated with LOPD. ELOVL7 and ZNF184 were associated with EOPD. In addition, trends of association to PD, between SATB1, NMD3, and FGF20, were also found.Statement of Significance: Genetic play an important role in the pathogenesis factors of Parkinson’s disease (PD). We found that GALC, ZNF184, and IL1R2 were associated with PD. GALC was also associated with late onset of PD, while ELOVL7 and ZNF184 were associated with early onset PD. This study is the first to find an association between GALC, ZNF184, and rs2280104 with PD.
BackgroundThere is an urgent need for developing objective, effective and convenient measurements to help clinicians accurately identify bradykinesia. The purpose of this study is to evaluate the accuracy of an objective approach assessing bradykinesia in finger tapping (FT) that uses evolutionary algorithms (EAs) and explore whether it can be used to identify early stage Parkinson’s disease (PD).MethodsOne hundred and seven PD, 41 essential tremor (ET) patients and 49 normal controls (NC) were recruited. Participants performed a standard FT task with two electromagnetic tracking sensors attached to the thumb and index finger. Readings from the sensors were transmitted to a tablet computer and subsequently analyzed by using EAs. The output from the device (referred to as "PD-Monitor") scaled from − 1 to + 1 (where higher scores indicate greater severity of bradykinesia). Meanwhile, the bradykinesia was rated clinically using the Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) FT item.ResultsWith an increasing MDS-UPDRS FT score, the PD-Monitor score from the same hand side increased correspondingly. PD-Monitor score correlated well with MDS-UPDRS FT score (right side: r = 0.819, P = 0.000; left side: r = 0.783, P = 0.000). Moreover, PD-Monitor scores in 97 PD patients with MDS-UPDRS FT bradykinesia and each PD subgroup (FT bradykinesia scored from 1 to 3) were all higher than that in NC. Receiver operating characteristic (ROC) curves revealed that PD-Monitor FT scores could detect different severity of bradykinesia with high accuracy (≥89.7%) in the right dominant hand. Furthermore, PD-Monitor scores could discriminate early stage PD from NC, with area under the ROC curve greater than or equal to 0.899. Additionally, ET without bradykinesia could be differentiated from PD by PD-Monitor scores. A positive correlation of PD-Monitor scores with modified Hoehn and Yahr stage was found in the left hand sides.ConclusionsOur study demonstrated that a simple to use device employing classifiers derived from EAs could not only be used to accurately measure different severity of bradykinesia in PD, but also had the potential to differentiate early stage PD from normality.
Objective Lymphocyte activation gene‐3 (LAG‐3) could mediate pathological α‐synuclein transmission in neurodegeneration and may be involved in the pathogenesis of Parkinson's disease (PD). The aim of the present study was to explore soluble LAG‐3 (sLAG‐3) as a potential diagnostic biomarker for PD. Methods Serum sLAG‐3 concentrations were measured by a quantitative ELISA for patients with PD, essential tremor (ET) and age‐ and sex‐matched controls. The relationships between sLAG‐3 and clinical phenotype were assessed via correlation analysis and logistic regression. Results Serum sLAG‐3 levels in patients with PD were significantly higher than those in ET patients and age‐ and sex‐matched controls. The area under the curve of serum sLAG‐3 in differentiating PD from age‐ and sex‐matched controls was 0.82. Serum sLAG‐3 was associated with non‐motor symptoms and excessive daytime sleep. Conclusion sLAG‐3 is a candidate novel biomarker for PD. © 2018 International Parkinson and Movement Disorder Society
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