Paroxysmal kinesigenic dyskinesias is a paroxysmal movement disorder characterized by recurrent, brief attacks of abnormal involuntary movements induced by sudden voluntary movements. Although several loci, including the pericentromeric region of chromosome 16, have been linked to paroxysmal kinesigenic dyskinesias, the causative gene has not yet been identified. Here, we identified proline-rich transmembrane protein 2 (PRRT2) as a causative gene of paroxysmal kinesigenic dyskinesias by using a combination of exome sequencing and linkage analysis. Genetic linkage mapping with 11 markers that encompassed the pericentromeric of chromosome 16 was performed in 27 members of two families with autosomal dominant paroxysmal kinesigenic dyskinesias. Then, the whole-exome sequencing was performed in three patients from these two families. By combining the defined linkage region (16p12.1–q12.1) and the results of exome sequencing, we identified an insertion mutation c.649_650InsC (p.P217fsX7) in one family and a nonsense mutation c.487C>T (p.Q163X) in another family. To confirm our findings, we sequenced the exons and flanking introns of PRRT2 in another three families with paroxysmal kinesigenic dyskinesias. The c.649_650InsC (p.P217fsX7) mutation was identified in two of these families, whereas a missense mutation, c.796C>T (R266W), was identified in another family with paroxysmal kinesigenic dyskinesias. All of these mutations completely co-segregated with the phenotype in each family. None of these mutations was identified in 500 normal unaffected individuals of matched geographical ancestry. Thus, we have identified PRRT2 as the first causative gene of paroxysmal kinesigenic dyskinesias, warranting further investigations to understand the pathogenesis of this disorder.

Material representations that are compatible with machine learning models play a key role in developing models that exhibit high accuracy for property prediction. Atomic orbital interactions are one of the important factors that govern the properties of crystalline materials, from which the local chemical environments of atoms is inferred. Therefore, to develop robust machine learningmodels for material properties prediction, it is imperative to include features representing such chemical attributes. Here, we propose the Orbital Graph Convolutional Neural Network (OGCNN), a crystal graph convolutional neural network framework that includes atomic orbital interaction features that learns material properties in a robust way. In addition, we embedded an encoder-decoder network into the OGCNN enabling it to learn important features among basic atomic (elemental features), orbitalorbital interactions, and topological features. We examined the performance of this model on a broad range of crystalline material data to predict different properties. We benchmarked the performance of the OGCNN model with that of: 1) the crystal graph convolutional neural network (CGCNN), 2) other state-of-the-art descriptors for material representations including Many-body Tensor Representation (MBTR) and the Smooth Overlap of Atomic Positions (SOAP), and 3) other conventional regression machine learning algorithms where different crystal featurization methods have been used. We find that OGCNN significantly outperforms them. The OGCNN model with high predictive accuracy can be used to discover new materials among the immense phase and compound spaces of materials.

Autosomal recessive cerebellar ataxias are a group of neurodegenerative disorders that are characterized by complex clinical and genetic heterogeneity. Although more than 20 disease-causing genes have been identified, many patients are still currently without a molecular diagnosis. In a two-generation autosomal recessive cerebellar ataxia family, we mapped a linkage to a minimal candidate region on chromosome 16p13.3 flanked by single-nucleotide polymorphism markers rs11248850 and rs1218762. By combining the defined linkage region with the whole-exome sequencing results, we identified a homozygous mutation (c.493CT) in CHIP (NM_005861) in this family. Using Sanger sequencing, we also identified two compound heterozygous mutations (c.389AT/c.441GT; c.621C>G/c.707GC) in CHIP gene in two additional kindreds. These mutations co-segregated exactly with the disease in these families and were not observed in 500 control subjects with matched ancestry. CHIP colocalized with NR2A, a subunit of the N-methyl-D-aspartate receptor, in the cerebellum, pons, medulla oblongata, hippocampus and cerebral cortex. Wild-type, but not disease-associated mutant CHIPs promoted the degradation of NR2A, which may underlie the pathogenesis of ataxia. In conclusion, using a combination of whole-exome sequencing and linkage analysis, we identified CHIP, encoding a U-box containing ubiquitin E3 ligase, as a novel causative gene for autosomal recessive cerebellar ataxia.

Autosomal recessive cerebellar ataxia (ARCA) comprises a large and heterogeneous group of neurodegenerative disorders. For many affected patients, the genetic cause remains undetermined. Through whole-exome sequencing, we identified compound heterozygous mutations in ubiquitin-like modifier activating enzyme 5 gene (UBA5) in two Chinese siblings presenting with ARCA. Moreover, copy number variations in UBA5 or ubiquitin-fold modifier 1 gene (UFM1) were documented with the phenotypes of global developmental delays and gait disturbances in the ClinVar database. UBA5 encodes UBA5, the ubiquitin-activating enzyme of UFM1. However, a crucial role for UBA5 in human neurological disease remains to be reported. Our molecular study of UBA5-R246X revealed a dramatically decreased half-life and loss of UFM1 activation due to the absence of the catalytic cysteine Cys250. UBA5-K310E maintained its interaction with UFM1, although with less stability, which may affect the ability of this UBA5 mutant to activate UFM1. Drosophila modeling revealed that UBA5 knockdown induced locomotive defects and a shortened lifespan accompanied by aberrant neuromuscular junctions (NMJs). Strikingly, we found that UFM1 and E2 cofactor knockdown induced markedly similar phenotypes. Wild-type UBA5, but not mutant UBA5, significantly restored neural lesions caused by the absence of UBA5. The finding of a UBA5 mutation in cerebellar ataxia suggests that impairment of the UFM1 pathway may contribute to the neurological phenotypes of ARCA.

BackgroundThe best treatment for lesions of the long head of the biceps tendon (LHBT) with concomitant reparable rotator cuff tears is still controversial. The purpose of the meta-analysis was to compare clinical outcomes of biceps tenotomy and tenodesis for LHBT lesions.MethodsA literature retrieval was conducted in MEDLINE, Embase, and Cochrane Library from 1979 to March 2018. Comparative studies (level of evidence I or II) comparing tenotomy and tenodesis for LHBT lesions with concomitant reparable rotator cuff tears were included. Risk of bias for all included studies was assessed using the Cochrane Collaboration’s risk of bias tool. Clinical outcomes compared were Popeye sign, Constant score, VAS pain score, cramping pain, elbow flexion and forearm supination strength, and re-tear of the rotator cuff.ResultsTwo randomized controlled trials (RCTs) and five prospective cohort studies (PCS) with 288 biceps tenotomy patients and 303 biceps tenodesis patients were included in this review. Tenotomy resulted in significantly greater rates of Popeye sign (RR, 2.70 [95% CI, 1.80 to 4.04]; P < 0.01) and a less favorable Constant score (MD, − 1.09 [95% CI, − 1.90 to − 0.28]; P < 0.01) compared to tenodesis. No significant heterogeneity was found between the two groups across all parameters except forearm supination strength.ConclusionsThe current evidence indicates that biceps tenodesis for LHBT lesions with concomitant reparable rotator cuff tears results in decreased rate of Popeye sign and improved Constant score compared to biceps tenotomy.Trial registrationPROSPERO, CRD42018105504. Registered on 13 August 2018.