Musculoskeletal Features without Ataxia Associated with a Novel de novo Mutation in KCNA1 Impairing the Voltage Sensitivity of Kv1.1 Channel

The KCNA1 gene encodes the subunit of the voltage-gated Kv1.1 potassium channel that critically regulates neuronal excitability in the central and peripheral nervous systems. Mutations in KCNA1 have been classically associated with episodic ataxia type 1 (EA1), a movement disorder triggered by physical and emotional stress. Additional features variably reported in recent years include epilepsy, myokymia, migraine, paroxysmal dyskinesia, hyperthermia, hypomagnesemia, and cataplexy. Interestingly, a few individuals with neuromyotonia, either isolated or associated with skeletal deformities, have been reported carrying variants in the S2–S3 transmembrane segments of Kv1.1 channels in the absence of any other symptoms. Here, we have identified by whole-exome sequencing a novel de novo variant, T268K, in KCNA1 in a boy displaying recurrent episodes of neuromyotonia, muscle hypertrophy, and skeletal deformities. Through functional analysis in heterologous cells and structural modeling, we show that the mutation, located at the extracellular end of the S3 helix, causes deleterious effects, disrupting Kv1.1 function by altering the voltage dependence of activation and kinetics of deactivation, likely due to abnormal interactions with the voltage sensor in the S4 segment. Our study supports previous evidence suggesting that specific residues within the S2 and S3 segments of Kv1.1 result in a distinctive phenotype with predominant musculoskeletal presentation

A multisite study of a breast density deep learning model for full-field digital mammography and synthetic mammography

PURPOSE: To develop a Breast Imaging Reporting and Data System (BI-RADS) breast density deep learning (DL) model in a multisite setting for synthetic two-dimensional mammographic (SM) images derived from digital breast tomosynthesis examinations by using full-field digital mammographic (FFDM) images and limited SM data. MATERIALS AND METHODS: A DL model was trained to predict BI-RADS breast density by using FFDM images acquired from 2008 to 2017 (site 1: 57 492 patients, 187 627 examinations, 750 752 images) for this retrospective study. The FFDM model was evaluated by using SM datasets from two institutions (site 1: 3842 patients, 3866 examinations, 14 472 images, acquired from 2016 to 2017; site 2: 7557 patients, 16 283 examinations, 63 973 images, 2015 to 2019). Each of the three datasets were then split into training, validation, and test. Adaptation methods were investigated to improve performance on the SM datasets, and the effect of dataset size on each adaptation method was considered. Statistical significance was assessed by using CIs, which were estimated by bootstrapping. RESULTS: Without adaptation, the model demonstrated substantial agreement with the original reporting radiologists for all three datasets (site 1 FFDM: linearly weighted Cohen κ [κ CONCLUSION: A BI-RADS breast density DL model demonstrated strong performance on FFDM and SM images from two institutions without training on SM images and improved by using few SM images

The SPTLC1 p.S331 mutation bridges sensory neuropathy and motor neuron disease and has implications for treatment

Aims SPTLC1-related disorder is a late onset sensory-autonomic neuropathy associated with perturbed sphingolipid homeostasis which can be improved by supplementation with the serine palmitoyl-CoA transferase (SPT) substrate, l-serine. Recently, a juvenile form of motor neuron disease has been linked to SPTLC1 variants. Variants affecting the p.S331 residue of SPTLC1 cause a distinct phenotype, whose pathogenic basis has not been established. This study aims to define the neuropathological and biochemical consequences of the SPTLC1 p.S331 variant, and test response to l-serine in this specific genotype. Methods We report clinical and neurophysiological characterisation of two unrelated children carrying distinct p.S331 SPTLC1 variants. The neuropathology was investigated by analysis of sural nerve and skin innervation. To clarify the biochemical consequences of the p.S331 variant, we performed sphingolipidomic profiling of serum and skin fibroblasts. We also tested the effect of l-serine supplementation in skin fibroblasts of patients with p.S331 mutations. Results In both patients, we recognised an early onset phenotype with prevalent progressive motor neuron disease. Neuropathology showed severe damage to the sensory and autonomic systems. Sphingolipidomic analysis showed the coexistence of neurotoxic deoxy-sphingolipids with an excess of canonical products of the SPT enzyme. l-serine supplementation in patient fibroblasts reduced production of toxic 1-deoxysphingolipids but further increased the overproduction of sphingolipids. Conclusions Our findings suggest that p.S331 SPTLC1 variants lead to an overlap phenotype combining features of sensory and motor neuropathies, thus proposing a continuum in the spectrum of SPTLC1-related disorders. l-serine supplementation in these patients may be detrimental