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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]

The use of consumer-grade wearables for purposes beyond fitness tracking has not been comprehensively explored. We generated and analyzed multidimensional data from 233 normal volunteers, integrating wearable data, lifestyle questionnaires, cardiac imaging, sphingolipid profiling, and multiple clinical-grade cardiovascular and metabolic disease markers. We show that subjects can be stratified into distinct clusters based on daily activity patterns and that these clusters are marked by distinct demographic and behavioral patterns. While resting heart rates (RHRs) performed better than step counts in being associated with cardiovascular and metabolic disease markers, step counts identified relationships between physical activity and cardiac remodeling, suggesting that wearable data may play a role in reducing overdiagnosis of cardiac hypertrophy or dilatation in active individuals. Wearable-derived activity levels can be used to identify known and novel activity-modulated sphingolipids that are in turn associated with insulin sensitivity. Our findings demonstrate the potential for wearables in biomedical research and personalized health. [ABSTRACT FROM AUTHOR]

Background: Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection. Methods: To ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes. Results: Amongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant. Conclusions: These findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs. Trial registration: ClinicalTrials.gov NCT02791152. Retrospectively registered on May 31, 2016. [ABSTRACT FROM AUTHOR]

Background: Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection. Methods: To ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes. Results: Amongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant. Conclusions: These findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs. Trial registration: ClinicalTrials.gov NCT02791152. Retrospectively registered on May 31, 2016. [ABSTRACT FROM AUTHOR]

The role of low frequency variants associated with telomere length homeostasis in chronic diseases and mortalities is relatively understudied in the East-Asian population. Here we evaluated low frequency variants, including 1,915,154 Asian specific variants, for leukocyte telomere length (LTL) associations among 25,533 Singapore Chinese samples. Three East Asian specific variants in/near POT1, TERF1 and STN1 genes are associated with LTL (Meta-analysis P 2.49×10−14–6.94×10−10). Rs79314063, a missense variant (p.Asp410His) at POT1, shows effect 5.3 fold higher and independent of a previous common index SNP. TERF1 (rs79617270) and STN1 (rs139620151) are linked to LTL-associated common index SNPs at these loci. Rs79617270 is associated with cancer mortality [HR95%CI = 1.544 (1.173, 2.032), PAdj = 0.018] and 4.76% of the association between the rs79617270 and colon cancer is mediated through LTL. Overall, genetically determined LTL is particularly associated with lung adenocarcinoma [HR95%CI = 1.123 (1.051, 1.201), Padj = 0.007]. Ethnicity-specific low frequency variants may affect LTL homeostasis and associate with certain cancers. Xuling Chang et al. study whether low frequency variants are associated with leukocyte telomere length and whether these variants predispose to incident cancers and mortalities among East Asians. They find that three East Asian specific variants at POT1, TERF1 and STN1 loci are associated with leukocyte telomere length and report a mechanistic pathway linking TERF1, leukocyte telomere length and incident colon cancer. [ABSTRACT FROM AUTHOR]

Background: Family history has traditionally been an essential part of clinical care to assess health risks. However, declining sequencing costs have precipitated a shift towards genomics-first approaches in population screening programs rendering the value of family history unknown. We evaluated the utility of incorporating family history information for genomic sequencing selection. Methods: To ascertain the relationship between family histories on such population-level initiatives, we analysed whole genome sequences of 1750 research participants with no known pre-existing conditions, of which half received comprehensive family history assessment of up to four generations, focusing on 95 cancer genes. Results: Amongst the 1750 participants, 866 (49.5%) had high-quality standardised family history available. Within this group, 73 (8.4%) participants had an increased family history risk of cancer (increased FH risk cohort) and 1 in 7 participants (n = 10/73) carried a clinically actionable variant inferring a sixfold increase compared with 1 in 47 participants (n = 17/793) assessed at average family history cancer risk (average FH risk cohort) (p = 0.00001) and a sevenfold increase compared to 1 in 52 participants (n = 17/884) where family history was not available (FH not available cohort) (p = 0.00001). The enrichment was further pronounced (up to 18-fold) when assessing only the 25 cancer genes in the American College of Medical Genetics (ACMG) Secondary Findings (SF) genes. Furthermore, 63 (7.3%) participants had an increased family history cancer risk in the absence of an apparent clinically actionable variant. Conclusions: These findings demonstrate that the collection and analysis of comprehensive family history and genomic data are complementary and in combination can prioritise individuals for genomic analysis. Thus, family history remains a critical component of health risk assessment, providing important actionable data when implementing genomics screening programs. Trial registration: ClinicalTrials.gov NCT02791152. Retrospectively registered on May 31, 2016. [ABSTRACT FROM AUTHOR]

Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative disorder associated with GGC repeats of >60 to 500 copies in the 5′‐untranslated region of NOTCH2NLC. The clinical and genetic characterization of NIID outside of East Asia remains unknown. We identified twelve patients who underwent genetic testing using long‐read sequencing or repeat primed polymerase chain reaction. All were positive for a GGC repeat expansion; the median repeat length was 107 (range 92‐138). Ten were Chinese and two of Malay ethnicity. Age at onset ranged from 50 to 69 years. Eight (66.7%) patients had dementia, while four (33.3%) patients were oligosymptomatic, without typical NIID symptoms of dementia, Parkinsonism, or muscle weakness. GGA interruptions within the GGC expansion were present in four patients; the number of GGA interruptions was highest (6.71%) in the patient with the earliest age at onset (50 years). Median plasma neurofilament light level was 47.3 pg/mL in seven patients (range 26‐380 pg/mL). The highest level (380 pg/mL) was found in one patient who experienced an encephalitic episode. Overall, we describe a cohort of genetically confirmed NIID patients from Southeast Asia and provide further information that the presence of GGA interruptions within GGC repeat expansions may serve as a potential genetic modifier in NIID. [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]

Reference 1 Bylstra Y. Family history assessment significantly enhances delivery of precision medicine in the genomics era. SAC and PT are supported by the Singapore National Medical Research Council grants (NMRC/STaR/0011/2012 and NMRC/STaR/0026/2015) and SAC is supported by the Tanoto Foundation. [Extracted from the article]