A novel digital tool for detection and monitoring of amyotrophic lateral sclerosis motor impairment and progression via keystroke dynamics.

Amyotrophic lateral sclerosis (ALS) is a debilitating neurodegenerative condition leading to progressive muscle weakness, atrophy, and ultimately death. Traditional ALS clinical evaluations often depend on subjective metrics, making accurate disease detection and monitoring disease trajectory challenging. To address these limitations, we developed the nQiALS toolkit, a machine learning-powered system that leverages smartphone typing dynamics to detect and track motor impairment in people with ALS. The study included 63 ALS patients and 30 age- and sex-matched healthy controls. We introduce the three core components of this toolkit: the nQiALS-Detection, which differentiated ALS from healthy typing patterns with an AUC of 0.89; the nQiALS-Progression, which separated slow and fast progression at specific thresholds with AUCs ranging between 0.65 and 0.8; and the nQiALS-Fine Motor, which identified subtle progression in fine motor dysfunction, suggesting earlier prediction than the state-of-the-art assessment. Together, these tools represent an innovative approach to ALS assessment, offering a complementary, objective metric to traditional clinical methods and which may reshape our understanding and monitoring of ALS progression.

Tracking amyotrophic lateral sclerosis disease progression using passively collected smartphone sensor data.

BACKGROUND: Passively collected smartphone sensor data provide an opportunity to study physical activity and mobility unobtrusively over long periods of time and may enable disease monitoring in people with amyotrophic lateral sclerosis (PALS). METHODS: We enrolled 63 PALS who used Beiwe mobile application that collected their smartphone accelerometer and GPS data and administered the self-entry ALS Functional Rating Scale-Revised (ALSFRS-RSE) survey. We identified individual steps from accelerometer data and used the Activity Index to summarize activity at the minute level. Walking, Activity Index, and GPS outcomes were then aggregated into day-level measures. We used linear mixed effect models (LMMs) to estimate baseline and monthly change for ALSFRS-RSE scores (total score, subscores Q1-3, Q4-6, Q7-9, Q10-12) and smartphone sensor data measures, as well as the associations between them. FINDINGS: The analytic sample (N = 45) was 64.4% male with a mean age of 60.1 years. The mean observation period was 292.3 days. The ALSFRS-RSE total score baseline mean was 35.8 and had a monthly rate of decline of -0.48 (p-value <0.001). We observed statistically significant change over time and association with ALSFRS-RSE total score for four smartphone sensor data-derived measures: walking cadence from top 1 min and log-transformed step count, step count from top 1 min, and Activity Index from top 1 min. INTERPRETATION: Smartphone sensors can unobtrusively track physical changes in PALS, potentially aiding disease monitoring and future research.

Detailed Clinical Features of PTPRQ-Associated Hearing Loss Identified in a Large Japanese Hearing Loss Cohort.

The PTPRQ gene has been identified as one of the genes responsible for non-syndromic sensorineural hearing loss (SNHL), and assigned as DFNA73 and DFNB84. To date, about 30 causative PTPRQ variants have been reported to cause SNHL. However, the detailed clinical features of PTPRQ-associated hearing loss (HL) remain unclear. In this study, 15,684 patients with SNHL were enrolled and genetic analysis was performed using massively parallel DNA sequencing (MPS) for 63 target deafness genes. We identified 17 possibly disease-causing PTPRQ variants in 13 Japanese patients, with 15 of the 17 variants regarded as novel. The majority of variants identified in this study were loss of function. Patients with PTPRQ-associated HL mostly showed congenital or childhood onset. Their hearing levels at high frequency deteriorated earlier than that at low frequency. The severity of HL progressed from moderate to severe or profound HL. Five patients with profound or severe HL received cochlear implantation, and the postoperative sound field threshold levels and discrimination scores were favorable. These findings will contribute to a greater understanding of the clinical features of PTPRQ-associated HL and may be relevant in clinical practice.

Gene expression of cytokines and prostaglandin metabolism-related proteins in eosinophilic otitis media.

The objective of this study was to investigate the levels of gene expression in the middle ear mucosa of 2 patients diagnosed with eosinophilic otitis media. One patient with severe hearing loss showed high expression levels of genes encoding IL-5 and IL-33 receptors.