Rare variant analysis of PLXNA1 in Parkinson’s disease in the Chinese population

Recently,p.Glu1121Ter in PLXNA1 was identified as po-tential cause for a patient with parkinsonism.However,no further replication has been conducted in a wider range of Parkinson’s disease(PD)cohorts.To evaluate the genetic association of PLXNA1 with PD,we systematically analyzed the rare protein-coding variants in 1,245 Chinese patients with whole exome sequencing.

Unique characteristics of the genetics epidemiology of amyotrophic lateral sclerosis in China

Continual discoveries of new genes and unraveling the genetic etiology in amyotrophic lateral sclerosis(ALS) have provided greater insight into the underlying pathogenesis in motor neuron degeneration, as well as facilitating the disease modeling and the testing of targeted therapeutics. While, the genetic etiology accounted for two-thirds of FALS and approximately 11% of SALS in Caucasians. However, the contributions of these causative genes to ALS vary among different populations. Furthermore, the prominent difference between Chinese population and other ethnics remains a source of ongoing debate. We systemically reviewed genetics literature of Chinese ALS populations and updated the mutation frequencies of the main ALS-implicated genes aiming to determine the genetic features of ALS in Chinese population. We also reviewed the associations between ALSimplicated single nucleotide polymorphisms(SNPs) and the risk of ALS in Chinese population. A total of 116 studies were included in this analysis(86 gene mutation study articles and 30 SNPs study articles). The results showed that the overall gene mutation rates of ALS-related causative genes were 55.0% in familial ALS(FALS) and 11.7% in sporadic ALS(SALS) in Chinese population. In Chinese FALS, the highest mutation frequency was found in SOD1 gene(25.6%), followed by FUS(5.8%), TARDBP(5.8%), DCTN1(3.6%) and C9 orf 72(3.5%). In Chinese SALS, the highest mutation frequency was also identified in SOD1 gene(1.6%), followed by ANXA11(1.4%), FUS(1.3%), SQSTM1(1.0%), OPTN(0.9%) and CCNF(0.8%).The associations between several SNPs and risk of ALS were also reported in Chinese population. The genetic features of ALS in Chinese population are significantly different from those in Caucasian population, indicating an association between genetic susceptibility and origin of population. Further explorations are required to understand the gene complexity of ALS, including the contribution of most minor genes and the molecular mechanisms in ALS pathologies.

Disruption of the white matter structural network and its correlation with baseline progression rate in patients with sporadic amyotrophic lateral sclerosis

Objective:There is increasing evidence that amyotrophic lateral sclerosis(ALS)is a progressive neurodegenerative disease impacting large-scale brain networks.However,it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression.This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate.Methods:Magnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire difusion-weighted magnetic resonance images and construct white matter(WM)networks using tractography methods.The global and regional network properties were compared between ALS and healthy subjects.The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms.Results:Compared with the healthy participants,the patients with ALS showed signifcantly decreased clustering coefcient C_(p)(P=0.0034,t=2.98),normalized clustering coefcientγ(P=0.039,t=2.08),and small‐worldnessσ(P=0.038,t=2.10)at the global network level.The patients also showed decreased regional centralities in motor and non-motor systems including the frontal,temporal and subcortical regions.Using the single-subject structural connection matrix,our classifcation model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%.Conclusion:Disruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems,extending the classical pathophysiological understanding of ALS as a motor disorder.The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.