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Charcot-Marie-Tooth type 1A (CMT1A) is typically characterised as a childhood-onset, symmetrical, length-dependent polyneuropathy with a gradual progressive clinical course. Acute to subacute neurological deterioration in CMT1A is rare, and has been reported secondary to overlap pathologies including inflammatory neuropathy. We identified two patients with CMT1A who presented with acute to subacute, atraumatic, entrapment neuropathies as an initial symptom. A superimposed inflammatory neuropathy was excluded. Both patients had a diffuse demyelinating polyneuropathy, with markedly low motor nerve conduction velocities (<20 m/s). In both patients, we demonstrated symptomatic and asymptomatic partial conduction blocks at multiple entrapment sites. Nerve ultrasound findings in our patients demonstrated marked diffuse nerve enlargement, more pronounced at non-entrapment sites compared to entrapment sites. We discuss ways to distinguish this condition from its other differentials. We propose pathophysiological mechanisms underlying this condition. We propose that CMT1A with acute to subacute, atraumatic, entrapment neuropathies to be a distinct phenotypic variant of CMT1A. [ABSTRACT FROM AUTHOR]

Frontotemporal Dementia (FTD) is a common cause of Young Onset Dementia and has diverse clinical manifestations involving behavior, executive function, language and motor function, including parkinsonism. Up to 50% of FTD patients report a positive family history, supporting a strong genetic basis, particularly in cases with both FTD and amyotrophic lateral sclerosis (FTD-ALS). Mutations in three genes are associated with the majority of familial FTD (fFTD) cases - microtubule associated protein tau gene (MAPT), granulin precursor (GRN), and hexanucleotide repeat expansions in chromosome 9 open reading frame 72- SMCR8complex subunit (C9orf72) while mutations in other genes such as optineurin (OPTN) have rarely been reported. Mutations in OPTN have been reported mostly in familial and sporadic cases of ALS, or in rare cases of FTD-ALS, but not in association with pure or predominant FTD and/or parkinsonian phenotype. Here, we report for the first time, a family from the Philippines with four members harboring a novel frameshift insertion at OPTN (Chr 10:13166090 G>GA) p.Lys328GluTer11, three of whom presented with FTD-related phenotypes. Additionally, one sibling heterozygous for the frameshift insertion had a predominantly parkinsonian phenotype resembling corticobasal syndrome, but it remains to be determined if this phenotype is related to the frameshift insertion. Notably, none of the affected members showed any evidence of motor neuron disease or ALS at the time of writing, both clinically and on electrophysiological testing, expanding the phenotypic spectrum of OPTN mutations. Close follow-up of mutation carriers for the development of new clinical features and wider investigation of additional family members with further genetic analyses will be conducted to investigate the possibility of other genetic modifiers in this family which could explain phenotypic heterogeneity. [ABSTRACT FROM AUTHOR]

We screened 662 subjects comprising 462 essential tremor (ET) subjects (285 sporadic, 125 with family history, and 52 probands from well-characterized ET pedigrees) and 200 controls and identified pathogenic NOTCH2NLC GGC repeat expansions in 4 sporadic ET patients. Two patients were followed up for >1 decade; one with 90 repeats remained an ET phenotype that did not evolve after 40 years, whereas another patient with 107 repeats developed motor symptoms and cognitive impairment after 8 to 10 years. Neuroimaging in this patient revealed severe leukoencephalopathy; diffusion-weighted imaging hyperintensity in the corticomedullary junction and skin biopsy revealed intranuclear inclusions suggestive of intranuclear inclusion body disease (NIID). No GGC repeats of >60 units were detected in familial ET cases and controls, although 4 ET patients carried 47 to 53 "intermediate" repeats. NOTCH2NLC GGC repeat expansions can be associated with sporadic ET. Carriers presenting with a pure ET phenotype may or may not convert to NIID up to 4 decades after initial tremor onset. ANN NEUROL 2020;88:614-618. [ABSTRACT FROM AUTHOR]

Background: Consumer-grade wearable devices enable detailed recordings of heart rate and step counts in free-living conditions. Recent studies have shown that summary statistics from these wearable recordings have potential uses for longitudinal monitoring of health and disease states. However, the relationship between higher resolution physiological dynamics from wearables and known markers of health and disease remains largely uncharacterized.Objective: We aimed to derive high-resolution digital phenotypes from observational wearable recordings and to examine their associations with modifiable and inherent markers of cardiometabolic disease risk.Methods: We introduced a principled framework to extract interpretable high-resolution phenotypes from wearable data recorded in free-living conditions. The proposed framework standardizes the handling of data irregularities; encodes contextual information regarding the underlying physiological state at any given time; and generates a set of 66 minimally redundant features across active, sedentary, and sleep states. We applied our approach to a multimodal data set, from the SingHEART study (NCT02791152), which comprises heart rate and step count time series from wearables, clinical screening profiles, and whole genome sequences from 692 healthy volunteers. We used machine learning to model nonlinear relationships between the high-resolution phenotypes on the one hand and clinical or genomic risk markers for blood pressure, lipid, weight and sugar abnormalities on the other. For each risk type, we performed model comparisons based on Brier scores to assess the predictive value of high-resolution features over and beyond typical baselines. We also qualitatively characterized the wearable phenotypes for participants who had actualized clinical events.Results: We found that the high-resolution features have higher predictive value than typical baselines for clinical markers of cardiometabolic disease risk: the best models based on high-resolution features had 17.9% and 7.36% improvement in Brier score over baselines based on age and gender and resting heart rate, respectively (P<.001 in each case). Furthermore, heart rate dynamics from different activity states contain distinct information (maximum absolute correlation coefficient of 0.15). Heart rate dynamics in sedentary states are most predictive of lipid abnormalities and obesity, whereas patterns in active states are most predictive of blood pressure abnormalities (P<.001). Moreover, in comparison with standard measures, higher resolution patterns in wearable heart rate recordings are better able to represent subtle physiological dynamics related to genomic risk for cardiometabolic disease (improvement of 11.9%-22.0% in Brier scores; P<.001). Finally, illustrative case studies reveal connections between these high-resolution phenotypes and actualized clinical events, even for borderline profiles lacking apparent cardiometabolic risk markers.Conclusions: High-resolution digital phenotypes recorded by consumer wearables in free-living states have the potential to enhance the prediction of cardiometabolic disease risk and could enable more proactive and personalized health management. [ABSTRACT FROM AUTHOR]

Sleep is associated with various health outcomes. Despite their growing adoption, the potential for consumer wearables to contribute sleep metrics to sleep-related biomedical research remains largely uncharacterized. Here we analyzed sleep tracking data, along with questionnaire responses and multi-modal phenotypic data generated from 482 normal volunteers. First, we compared wearable-derived and self-reported sleep metrics, particularly total sleep time (TST) and sleep efficiency (SE). We then identified demographic, socioeconomic and lifestyle factors associated with wearable-derived TST; they included age, gender, occupation and alcohol consumption. Multi-modal phenotypic data analysis showed that wearable-derived TST and SE were associated with cardiovascular disease risk markers such as body mass index and waist circumference, whereas self-reported measures were not. Using wearable-derived TST, we showed that insufficient sleep was associated with premature telomere attrition. Our study highlights the potential for sleep metrics from consumer wearables to provide novel insights into data generated from population cohort studies. Jing Xian Teo et al. used sleep tracking data from consumer wearables, together with phenotypic data from 482 volunteers to identify factors associated with habitual sleep duration and sleep efficiency. They identified sleep metrics associated with cardiovascular disease risk markers, such as body mass index, and linked insufficient sleep to premature telomere shortening, a biomarker of aging. [ABSTRACT FROM AUTHOR]