Mutations in the synaptic nuclear envelope protein 1 (SYNE1) gene are associated with substantial clinical heterogeneity. Here, we report the first case of SYNE1 ataxia in Taiwan due to two novel truncating mutations. Our patient, a 53-year-old female, exhibited pure cerebellar ataxia with c.1922del in exon 18 and c. C3883T mutations in exon 31. Previous studies have indicated that the prevalence of SYNE1 ataxia among East Asian populations is low. In this study, we identified 27 cases of SYNE1 ataxia from 22 families in East Asia. Of the 28 patients recruited in this study (including our patient), 10 exhibited pure cerebellar ataxia, and 18 exhibited ataxia plus syndromes. We could not find an exact correlation between genotypes and phenotypes. Additionally, we established a precise molecular diagnosis in our patient’s family and extended the findings on the ethnic, phenotypic, and genotypic diversity of the SYNE1 mutational spectrum.

Objective: A meta-analysis of locus-based genome-wide association studies recently identified a relationship between AXIN1 and Parkinson’s disease (PD). Few studies of Asian populations, however, have reported such a genetic association. The influences of rs13337493, rs758033, and rs2361988, three PD-associated genetic variants of AXIN1, were investigated in the present study because AXIN1 is related to Wnt/β-catenin signaling. Methods: A total of 2,418 individuals were enrolled in our Taiwanese cohort for analysis of the genotypic and allelic frequency. Polymerase chain reaction–restriction fragment length polymorphism analysis was employed for rs13337493 genotyping, and the Agena MassARRAY platform (Agena Bioscience, San Diego, CA, USA) was used for rs758033 and rs2361988 genotyping in 672 patients with PD and 392 controls. Taiwan Biobank data of another 1,354 healthy controls were subjected to whole-genome sequencing performed using Illumina platforms at approximately 30× average depth. Results: Our results revealed that rs758033 {odds ratios [OR] (95% confidence interval [CI]) = 0.267 [0.064, 0.795], p = 0.014} was associated with the risk of PD, and there was a trend toward a protective effect of rs2361988 (OR [95% CI] = 0.296 [0.071, 0.884], p = 0.026) under the recessive model. The TT genotype of rs758033 (OR [95% CI] = 0.271 [0.065, 0.805], p = 0.015) and the CC genotype of rs2361988 (OR [95% CI] = 0.305 [0.073, 0.913], p = 0.031) were less common in the PD group than in the non-PD group. Conclusion Our findings indicate that the rs758033 and rs2361988 polymorphisms of AXIN1 may affect the risk of PD in the Taiwanese population.

Tubulin beta 4A class IVa (TUBB4A) spectrum disorders include autosomal dominant dystonia type 4 or hypomyelination with atrophy of the basal ganglia and cerebellum (H-ABC syndrome). However, in rare cases, only mild hypomyelination in the cortex with no basal ganglia atrophy may be observed. We report a case of a family with TUBB4A mutation and complicated hereditary spasticity paraplegia (HSP). We performed quadro whole-exome sequencing (WES) on the family to identify the causative gene of progressive spastic paraparesis with isolated hypomyelination leukodystrophy. We identified a novel TUBB4A p.F341L mutation, which was present in all three affected patients but absent in the unaffected father. The affected patients presented with adult-onset TUBB4A disorder, predominant spastic paraparesis with/without ataxia, and brain hypomyelination with no cognitive impairment or extrapyramidal symptoms. In the literature, HSP is considered a TUBB4A spectrum disorder.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.