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• Whole-genome sequencing of normal Singaporean volunteers

  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. Among others, male gender (β = -15.539, 95% confidence interval [CI] = -26.245 - -4.832, p = 0.005), older age (β = -0.493, CI = -0.941 - -0.044, p = 0.032) and manual labor (β = -26.856, CI = -49.715 - -3.997, p = 0.022) were associated with reduced TST, whereas alcohol consumption (β = 19.247, CI = 8.008 - 30.486, p = 8.54x10-04) was associated with increased TST. Multi-modal phenotypic data analysis showed that wearable-derived TST and SE were associated with various cardiovascular disease risk markers such as body mass index (β = -0.006, CI = -0.00 - -0.000, p = 0.040) and waist circumference (β = 0.001, CI = -0.015-0.017, p = 0.893), whereas self-reported measures were not. We then showed that insufficient sleep was associated with premature telomere attrition, using telomere length estimated using whole-genome sequencing (β = 1.275, CI = 0.187 - 2.363, p = 0.023) and quantitative PCR (β = 0.001, CI = 8.318x10-05 - 0.001, p = 0.028). Our study highlights the potential for sleep metrics from consumer wearables to provide novel insights into data generated from population cohort studies.

  Study EGAS00001004007

• Atypical B cells and impaired SARS-CoV-2 neutralisation following heterologous vaccination in the elderly

  Age is a major risk factor for hospitalization and death after SARS-CoV-2 infection, even in vaccinees. Suboptimal responses to a primary vaccination course have been reported in the elderly, but there is little information regarding the impact of age on responses to booster third doses. Here we show that individuals 70 or older who received a primary two dose schedule with AZD1222 and booster third dose with mRNA vaccine achieved significantly lower neutralizing antibody responses against SARS-CoV-2 spike pseudotyped virus compared to those below 70 at one month post booster. Neither the concentration of serum binding anti spike IgG antibody, nor the frequency of spike- specific B cells showed differences by age grouping. Impaired neutralization potency and breadth post-third dose in the elderly was associated with enrichment of circulating “atypical” spike-specific B cells expressing CD11c and FCRL5. Presence of these atypical B cells was confirmed by scRNA seq. However, when considering individuals who received three doses of mRNA vaccine, we did not observe statistically significant differences in neutralization or enrichment in atypical B cells by age grouping following dose 3. Together, our data reveal impaired neutralising antibody responses in the elderly after heterologous vaccination with AdV followed by mRNA booster dose, but not in homologous three dose mRNA vaccination highlighting that different vaccine formats differentially instruct the memory B cell response.

  Study EGAS00001007385

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005738

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005747

• The EMC-HEMA-AML data access committee controlling the access to AML sequencing data generated in the Hematology department of Erasmus MC

  Dac EGAC00001002230

• TUM Experimental Neuroimmunology

  This DAC will decide about all data requests to human data deposited at EGA that was primarily produced at the Institute for Experimental Neuroimmunology at the Technical University Munich, Germany.

  Dac EGAC50000000093

• bfast CohortD clinical data

  Clinical data for BFAST Cohort D, including time-to-event, tumor response, and baseline prognostics data.

  Dataset EGAD50000000149

• RCC trial WES dataset

  This dataset includes WES data for 116 runs, corresponding to 58 pairs of normal(PBMC)/tumor samples from 58 patients (116 BAM files).

  Dataset EGAD50000000953

• Targeted sequencing analysis for MDS with HSCT

  Targeted capture sequencing for cases with MDS who were subjected to unrelated bone marrow transplantation via Japan marrow donor program

  Dataset EGAD00001003118

• University College London Great Ormond Street Institute of Child Health DAC

  This DAC oversees access to de-identified datasets generated by the University College London (UCL) Great Ormond Street Institute of Child Health.

  Dac EGAC50000000985