Publications by authors named "Xihong Lin"

247 Publications

Federated learning for predicting clinical outcomes in patients with COVID-19.

Nat Med 2021 10 15;27(10):1735-1743. Epub 2021 Sep 15.

Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, South Korea.

Federated learning (FL) is a method used for training artificial intelligence models with data from multiple sources while maintaining data anonymity, thus removing many barriers to data sharing. Here we used data from 20 institutes across the globe to train a FL model, called EXAM (electronic medical record (EMR) chest X-ray AI model), that predicts the future oxygen requirements of symptomatic patients with COVID-19 using inputs of vital signs, laboratory data and chest X-rays. EXAM achieved an average area under the curve (AUC) >0.92 for predicting outcomes at 24 and 72 h from the time of initial presentation to the emergency room, and it provided 16% improvement in average AUC measured across all participating sites and an average increase in generalizability of 38% when compared with models trained at a single site using that site's data. For prediction of mechanical ventilation treatment or death at 24 h at the largest independent test site, EXAM achieved a sensitivity of 0.950 and specificity of 0.882. In this study, FL facilitated rapid data science collaboration without data exchange and generated a model that generalized across heterogeneous, unharmonized datasets for prediction of clinical outcomes in patients with COVID-19, setting the stage for the broader use of FL in healthcare.
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http://dx.doi.org/10.1038/s41591-021-01506-3DOI Listing
October 2021

Trans-ethnic genome-wide association study of severe COVID-19.

Commun Biol 2021 08 31;4(1):1034. Epub 2021 Aug 31.

College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.

COVID-19 has caused numerous infections with diverse clinical symptoms. To identify human genetic variants contributing to the clinical development of COVID-19, we genotyped 1457 (598/859 with severe/mild symptoms) and sequenced 1141 (severe/mild: 474/667) patients of Chinese ancestry. We further incorporated 1401 genotyped and 948 sequenced ancestry-matched population controls, and tested genome-wide association on 1072 severe cases versus 3875 mild or population controls, followed by trans-ethnic meta-analysis with summary statistics of 3199 hospitalized cases and 897,488 population controls from the COVID-19 Host Genetics Initiative. We identified three significant signals outside the well-established 3p21.31 locus: an intronic variant in FOXP4-AS1 (rs1853837, odds ratio OR = 1.28, P = 2.51 × 10, allele frequencies in Chinese/European AF = 0.345/0.105), a frameshift insertion in ABO (rs8176719, OR = 1.19, P = 8.98 × 10, AF = 0.422/0.395) and a Chinese-specific intronic variant in MEF2B (rs74490654, OR = 8.73, P = 1.22 × 10, AF = 0.004/0). These findings highlight an important role of the adaptive immunity and the ABO blood-group system in protection from developing severe COVID-19.
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http://dx.doi.org/10.1038/s42003-021-02549-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8408224PMC
August 2021

Response to Hopkins, Kichenadasse, Logan, et al.

J Natl Cancer Inst 2021 Aug 27. Epub 2021 Aug 27.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, MA, USA.

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http://dx.doi.org/10.1093/jnci/djab161DOI Listing
August 2021

Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program.

Genome Med 2021 08 26;13(1):136. Epub 2021 Aug 26.

Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, 10461, USA.

Background: Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.

Methods: The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.

Results: We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.

Conclusions: We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.
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http://dx.doi.org/10.1186/s13073-021-00917-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8394596PMC
August 2021

Short-term exposure to PM components and renal health: Findings from the Veterans Affairs Normative Aging Study.

J Hazard Mater 2021 10 3;420:126557. Epub 2021 Jul 3.

Laboratory of Environmental Precision Health, Mailman School of Public Health, Columbia University, New York, NY, USA.

There is little evidence on the short-term impact of fine particulate matter (PM) on renal health, and the potential interactions and various influences of PM components on renal health have not been examined. We investigated whether short-term (≤28 days) ambient PM and 15 PM components were associated with serum uric acid (SUA), blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), and odds of incident chronic kidney disease (CKD) using both mixed-effect and Bayesian kernel machine regression (BKMR) models in the Normative Aging Study. This analysis included 2466 study visits from 808 older males enrolled during 1998-2016 with available data. BKMR showed positive relationships of PM mixture with SUA and odds of CKD, and an inverse relationship with eGFR. In the 28-day exposure window, an interquartile range (IQR) increase in vanadium was associated with a 0.244-mg/dL higher SUA. IQR increases in sulfur and lead were associated with a 1.281- and 1.008-mL/min/1.73 m decrease in eGFR, respectively. The same change in sulfur was also associated with a 39% higher odds of CKD. Our findings provide solid evidence supporting short-term adverse effects of PM on renal health and further highlight that components from oil combustion and regional pollution may be major contributors.
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http://dx.doi.org/10.1016/j.jhazmat.2021.126557DOI Listing
October 2021

The Association Between Inflammatory and Oxidative Stress Biomarkers and Plasma Metabolites in a Longitudinal Study of Healthy Male Welders.

J Inflamm Res 2021 29;14:2825-2839. Epub 2021 Jun 29.

Environmental Health, Harvard University T H Chan School of Public Health, Boston, MA, USA.

Introduction: Human metabolism and inflammation are closely related modulators of homeostasis and immunity. Metabolic profiling is a useful tool to understand the association between metabolism and inflammation at a systemic level.

Objective: To investigate the longitudinal associations between the concentration of plasma metabolites and biomarkers related to inflammation and oxidative stress.

Methods: We conducted a repeated cross-sectional analysis consisting of 8 short-term panels that included 88 healthy adult male welders in Massachusetts, USA. In each panel, we collected 1-6 repeated measurements of blood and urine. We used a human vascular injury panel assay and custom cytokine/chemokine assay to quantify inflammatory biomarker plasma levels, liquid chromatography-mass spectrometry to quantify the concentrations of 665 plasma metabolites, and a competitive enzyme-linked immunoassay to quantify urinary 8-OHdG and 8-isoprostane levels. We used linear mixed effects models to estimate the longitudinal association between each inflammatory and oxidative stress biomarker and each metabolite.

Results: At a 5% FDR threshold, we detected ≥1metabolite association for 8 unique inflammatory and oxidative stress biomarkers: urinary 8-isoprostane, plasma C-reactive protein (CRP), serum amyloid A (SAA), intercellular adhesion molecule 1, circulating vascular cell adhesion molecule-1, interleukin 8 (IL-8), interleukin 10 (IL-10) and vascular endothelial growth factor. Specifically, 3 metabolites in the androgenic steroids pathway were negatively associated with SAA; 3 dihydrosphingomyelins metabolites were positively associated with 1 or more of CRP, SAA, IL-8 and IL-10; 4 metabolites in acyl choline metabolism pathways were negatively associated with IL-8; 7 lysophospholipid metabolites were negatively associated with 1 or more of CRP, SAA and IL-8; 4 sphingomyelins were positively associated with CRP and/or SAA; and 10 metabolites in the xanthine pathway were positively associated with urinary 8-isoprostane.

Conclusion: We found that metabolites in phospholipid groups had strong associations with multiple inflammatory biomarkers, especially CRP, SAA and IL-8. The mechanism of these associations warrants further investigation.
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http://dx.doi.org/10.2147/JIR.S316262DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8254568PMC
June 2021

Smoking History as a Potential Predictor of Immune Checkpoint Inhibitor Efficacy in Metastatic Non-Small Cell Lung Cancer.

J Natl Cancer Inst 2021 Jun 11. Epub 2021 Jun 11.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, 677 Huntington Ave, Boston, MA, USA.

Background: Despite the therapeutic efficacy of immune checkpoint inhibitors (ICIs) in a subset of patients, consistent and easily obtainable predictors of efficacy remain elusive.

Methods: This study was conducted on 644 advanced non-small cell lung cancer (NSCLC) patients treated with ICI monotherapy between April 2013 and September 2020 at the Dana-Farber Cancer Institute and Brigham and Women's Hospital. Patient smoking history, clinicopathological characteristics, tumor mutation burden (TMB) by clinical targeted next generation sequencing, and PD-L1 tumor proportion score (TPS) by immunohistochemistry were prospectively collected. The association of smoking history with clinical outcomes of ICI monotherapy in metastatic NSCLC patients was evaluated after adjusting for other potential predictors. All statistical tests were 2-sided.

Results: Of 644 advanced NSCLC patients 105 (16.3%) were never smokers, 375 (58.2%) were former smokers (median pack-years = 28), and 164 (25.4%) were current smokers (median pack-years = 40). Multivariable logistic and Cox proportional hazards regression analyses suggested that doubling of smoking pack-years is statistically significantly associated with improved clinical outcomes of patients treated with ICI monotherapy (objective response rate odds ratio = 1.21, 95% confidence interval [CI] = 1.09-1.36, P < .001; progression-free survival hazard ratio = 0.92, 95% CI = 0.88-0.95, P < .001; overall survival hazard ratio = 0.94, 95% CI = 0.90-0.99, P = .01). Predictive models incorporating pack-years and PD-L1 TPS yielded additional information and achieved similar model performance compared to using TMB and PD-L1 TPS.

Conclusions: Increased smoking exposure had a statistically significant association with improved clinical outcomes in metastatic NSCLC treated with ICI monotherapy independent of PD-L1 TPS. Pack-years may serve as a consistent and readily obtainable surrogate of ICI efficacy when TMB is not available to inform prompt clinical decisions and allow more patients to benefit from ICIs.
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http://dx.doi.org/10.1093/jnci/djab116DOI Listing
June 2021

DNAm-based signatures of accelerated aging and mortality in blood are associated with low renal function.

Clin Epigenetics 2021 06 2;13(1):121. Epub 2021 Jun 2.

Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.

Background: The difference between an individual's chronological and DNA methylation predicted age (DNAmAge), termed DNAmAge acceleration (DNAmAA), can capture life-long environmental exposures and age-related physiological changes reflected in methylation status. Several studies have linked DNAmAA to morbidity and mortality, yet its relationship with kidney function has not been assessed. We evaluated the associations between seven DNAm aging and lifespan predictors (as well as GrimAge components) and five kidney traits (estimated glomerular filtration rate [eGFR], urine albumin-to-creatinine ratio [uACR], serum urate, microalbuminuria and chronic kidney disease [CKD]) in up to 9688 European, African American and Hispanic/Latino individuals from seven population-based studies.

Results: We identified 23 significant associations in our large trans-ethnic meta-analysis (p < 1.43E-03 and consistent direction of effect across studies). Age acceleration measured by the Extrinsic and PhenoAge estimators, as well as Zhang's 10-CpG epigenetic mortality risk score (MRS), were associated with all parameters of poor kidney health (lower eGFR, prevalent CKD, higher uACR, microalbuminuria and higher serum urate). Six of these associations were independently observed in European and African American populations. MRS in particular was consistently associated with eGFR (β =  - 0.12, 95% CI = [- 0.16, - 0.08] change in log-transformed eGFR per unit increase in MRS, p = 4.39E-08), prevalent CKD (odds ratio (OR) = 1.78 [1.47, 2.16], p = 2.71E-09) and higher serum urate levels (β = 0.12 [0.07, 0.16], p = 2.08E-06). The "first-generation" clocks (Hannum, Horvath) and GrimAge showed different patterns of association with the kidney traits. Three of the DNAm-estimated components of GrimAge, namely adrenomedullin, plasminogen-activation inhibition 1 and pack years, were positively associated with higher uACR, serum urate and microalbuminuria.

Conclusion: DNAmAge acceleration and DNAm mortality predictors estimated in whole blood were associated with multiple kidney traits, including eGFR and CKD, in this multi-ethnic study. Epigenetic biomarkers which reflect the systemic effects of age-related mechanisms such as immunosenescence, inflammaging and oxidative stress may have important mechanistic or prognostic roles in kidney disease. Our study highlights new findings linking kidney disease to biological aging, and opportunities warranting future investigation into DNA methylation biomarkers for prognostic or risk stratification in kidney disease.
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http://dx.doi.org/10.1186/s13148-021-01082-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8170969PMC
June 2021

Identifying US County-level characteristics associated with high COVID-19 burden.

BMC Public Health 2021 05 28;21(1):1007. Epub 2021 May 28.

Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Ave, Building II, Room 419, Boston, MA, 02115, USA.

Background: Identifying county-level characteristics associated with high coronavirus 2019 (COVID-19) burden can help allow for data-driven, equitable allocation of public health intervention resources and reduce burdens on health care systems.

Methods: Synthesizing data from various government and nonprofit institutions for all 3142 United States (US) counties, we studied county-level characteristics that were associated with cumulative and weekly case and death rates through 12/21/2020. We used generalized linear mixed models to model cumulative and weekly (40 repeated measures per county) cases and deaths. Cumulative and weekly models included state fixed effects and county-specific random effects. Weekly models additionally allowed covariate effects to vary by season and included US Census region-specific B-splines to adjust for temporal trends.

Results: Rural counties, counties with more minorities and white/non-white segregation, and counties with more people with no high school diploma and with medical comorbidities were associated with higher cumulative COVID-19 case and death rates. In the spring, urban counties and counties with more minorities and white/non-white segregation were associated with increased weekly case and death rates. In the fall, rural counties were associated with larger weekly case and death rates. In the spring, summer, and fall, counties with more residents with socioeconomic disadvantage and medical comorbidities were associated greater weekly case and death rates.

Conclusions: These county-level associations are based off complete data from the entire country, come from a single modeling framework that longitudinally analyzes the US COVID-19 pandemic at the county-level, and are applicable to guiding government resource allocation policies to different US counties.
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http://dx.doi.org/10.1186/s12889-021-11060-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8162162PMC
May 2021

Integrative omics provide biological and clinical insights into acute respiratory distress syndrome.

Intensive Care Med 2021 07 25;47(7):761-771. Epub 2021 May 25.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, 655 Huntington Avenue, Boston, MA, 02115, USA.

Purpose: Acute respiratory distress syndrome (ARDS) is accompanied by a dysfunctional immune-inflammatory response following lung injury, including during coronavirus disease 2019 (COVID-19). Limited causal biomarkers exist for ARDS development. We sought to identify novel genetic susceptibility targets for ARDS to focus further investigation on their biological mechanism and therapeutic potential.

Methods: Meta-analyses of ARDS genome-wide association studies were performed with 1250 cases and 1583 controls in Europeans, and 387 cases and 387 controls in African Americans. The functionality of novel loci was determined in silico using multiple omics approaches. The causality of 114 factors potentially involved in ARDS development was assessed using Mendelian Randomization analysis.

Results: There was distinct genetic heterogeneity in ARDS between Europeans and African Americans. rs7967111 at 12p13.2 was functionally associated with ARDS susceptibility in Europeans (odds ratio = 1.38; P = 2.15 × 10). Expression of two genes annotated at this locus, BORCS5 and DUSP16, was dynamic but ultimately decreased during ARDS development, as well as downregulated in immune cells alongside COVID-19 severity. Causal inference implied that comorbidity of inflammatory bowel disease and elevated levels of C-reactive protein and interleukin-10 causally increased ARDS risk, while vitamin D supplementation and vasodilator use ameliorated risk.

Conclusion: Our findings suggest a novel susceptibility locus in ARDS pathophysiology that implicates BORCS5 and DUSP16 as potentially acting in immune-inflammatory processes. This locus warrants further investigation to inform the development of therapeutic targets and clinical care strategies for ARDS, including those induced by COVID-19.
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http://dx.doi.org/10.1007/s00134-021-06410-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8144871PMC
July 2021

Genome-wide association study of neck circumference identifies sex-specific loci independent of generalized adiposity.

Int J Obes (Lond) 2021 07 27;45(7):1532-1541. Epub 2021 Apr 27.

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Background/objectives: Neck circumference, an index of upper airway fat, has been suggested to be an important measure of body-fat distribution with unique associations with health outcomes such as obstructive sleep apnea and metabolic disease. This study aims to study the genetic bases of neck circumference.

Methods: We conducted a multi-ethnic genome-wide association study of neck circumference, adjusted and unadjusted for BMI, in up to 15,090 European Ancestry (EA) and African American (AA) individuals. Because sexually dimorphic associations have been observed for anthropometric traits, we conducted both sex-combined and sex-specific analysis.

Results: We identified rs227724 near the Noggin (NOG) gene as a possible quantitative locus for neck circumference in men (N = 8831, P = 1.74 × 10) but not in women (P = 0.08). The association was replicated in men (N = 1554, P = 0.045) in an independent dataset. This locus was previously reported to be associated with human height and with self-reported snoring. We also identified rs13087058 on chromosome 3 as a suggestive locus in sex-combined analysis (N = 15090, P = 2.94 × 10; replication P =0.049). This locus was also associated with electrocardiogram-assessed PR interval and is a cis-expression quantitative locus for the PDZ Domain-containing ring finger 2 (PDZRN3) gene. Both NOG and PDZRN3 interact with members of transforming growth factor-beta superfamily signaling proteins.

Conclusions: Our study suggests that neck circumference may have unique genetic basis independent of BMI.
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http://dx.doi.org/10.1038/s41366-021-00817-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236408PMC
July 2021

Unraveling Attributes of COVID-19 Vaccine Hesitancy and Uptake in the U.S.: A Large Nationwide Study.

medRxiv 2021 Jul 2. Epub 2021 Jul 2.

SARS-CoV-2 vaccines are powerful tools to combat the COVID-19 pandemic, but vaccine hesitancy threatens these vaccines’ effectiveness. To address COVID-19 vaccine hesitancy and ensure equitable distribution, understanding the extent of and factors associated with vaccine acceptance and uptake is critical. We report the results of a large nationwide study conducted December 2020-May 2021 of 34,470 users from COVID-19-focused smartphone-based app How We Feel on their willingness to receive a COVID-19 vaccine. Nineteen percent of respondents expressed vaccine hesitancy, the majority being undecided. Of those who were undecided or unlikely to get a COVID-19 vaccine, 86% reported they ultimately did receive a COVID-19 vaccine. We identified sociodemographic and behavioral factors that were associated with COVID-19 vaccine hesitancy and uptake, and we found several vulnerable groups at increased risk of COVID-19 burden, morbidity, and mortality were more likely to be vaccine hesitant and had lower rates of vaccination. Our findings highlight specific populations in which targeted efforts to develop education and outreach programs are needed to overcome vaccine hesitancy and improve equitable access, diversity, and inclusion in the national response to COVID-19.
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http://dx.doi.org/10.1101/2021.04.05.21254918DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8043469PMC
July 2021

Effect of alloying on the dynamics of coherent acoustic phonons in bismuth double perovskite single crystals.

Opt Express 2021 Mar;29(5):7948-7955

The bismuth double perovskite CsAgBiBr has been regarded as a potential candidate for lead-free perovskite photovoltaics. A detailed study on the coherent acoustic phonon dynamics in the pure, Sb- and Tl-alloyed CsAgBiBr single crystals is performed to understand the effects of alloying on the phonon dynamics and band edge characteristics. The coherent acoustic phonon frequencies are found to be independent of the alloying, while the damping rates are highly dependent on the alloying. Based on the mechanism of coherent acoustic phonon damping, a technique has been successfully developed that can accurately extract the absorption spectra near the indirect band gap for these single crystals with coefficients on the order of 10 cm.
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http://dx.doi.org/10.1364/OE.414857DOI Listing
March 2021

Association between Smoking History and Tumor Mutation Burden in Advanced Non-Small Cell Lung Cancer.

Cancer Res 2021 05 2;81(9):2566-2573. Epub 2021 Mar 2.

Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts.

Lung carcinogenesis is a complex and stepwise process involving accumulation of genetic mutations in signaling and oncogenic pathways via interactions with environmental factors and host susceptibility. Tobacco exposure is the leading cause of lung cancer, but its relationship to clinically relevant mutations and the composite tumor mutation burden (TMB) has not been fully elucidated. In this study, we investigated the dose-response relationship in a retrospective observational study of 931 patients treated for advanced-stage non-small cell lung cancer (NSCLC) between April 2013 and February 2020 at the Dana Farber Cancer Institute and Brigham and Women's Hospital. Doubling smoking pack-years was associated with increased and less frequent and mutations, whereas doubling smoking-free months was associated with more frequent . In advanced lung adenocarcinoma, doubling smoking pack-years was associated with an increase in TMB, whereas doubling smoking-free months was associated with a decrease in TMB, after controlling for age, gender, and stage. There is a significant dose-response association of smoking history with genetic alterations in cancer-related pathways and TMB in advanced lung adenocarcinoma. SIGNIFICANCE: This study clarifies the relationship between smoking history and clinically relevant mutations in non-small cell lung cancer, revealing the potential of smoking history as a surrogate for tumor mutation burden.
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http://dx.doi.org/10.1158/0008-5472.CAN-20-3991DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137661PMC
May 2021

Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program.

Nature 2021 02 10;590(7845):290-299. Epub 2021 Feb 10.

The Broad Institute of MIT and Harvard, Cambridge, MA, USA.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes). In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.
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http://dx.doi.org/10.1038/s41586-021-03205-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7875770PMC
February 2021

RAFFI: Accurate and fast familial relationship inference in large scale biobank studies using RaPID.

PLoS Genet 2021 01 21;17(1):e1009315. Epub 2021 Jan 21.

School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America.

Inference of relationships from whole-genome genetic data of a cohort is a crucial prerequisite for genome-wide association studies. Typically, relationships are inferred by computing the kinship coefficients (ϕ) and the genome-wide probability of zero IBD sharing (π0) among all pairs of individuals. Current leading methods are based on pairwise comparisons, which may not scale up to very large cohorts (e.g., sample size >1 million). Here, we propose an efficient relationship inference method, RAFFI. RAFFI leverages the efficient RaPID method to call IBD segments first, then estimate the ϕ and π0 from detected IBD segments. This inference is achieved by a data-driven approach that adjusts the estimation based on phasing quality and genotyping quality. Using simulations, we showed that RAFFI is robust against phasing/genotyping errors, admix events, and varying marker densities, and achieves higher accuracy compared to KING, the current leading method, especially for more distant relatives. When applied to the phased UK Biobank data with ~500K individuals, RAFFI is approximately 18 times faster than KING. We expect RAFFI will offer fast and accurate relatedness inference for even larger cohorts.
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http://dx.doi.org/10.1371/journal.pgen.1009315DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7853505PMC
January 2021

Federated Learning used for predicting outcomes in SARS-COV-2 patients.

Res Sq 2021 Jan 8. Epub 2021 Jan 8.

'Federated Learning' (FL) is a method to train Artificial Intelligence (AI) models with data from multiple sources while maintaining anonymity of the data thus removing many barriers to data sharing. During the SARS-COV-2 pandemic, 20 institutes collaborated on a healthcare FL study to predict future oxygen requirements of infected patients using inputs of vital signs, laboratory data, and chest x-rays, constituting the "EXAM" (EMR CXR AI Model) model. EXAM achieved an average Area Under the Curve (AUC) of over 0.92, an average improvement of 16%, and a 38% increase in generalisability over local models. The FL paradigm was successfully applied to facilitate a rapid data science collaboration without data exchange, resulting in a model that generalised across heterogeneous, unharmonized datasets. This provided the broader healthcare community with a validated model to respond to COVID-19 challenges, as well as set the stage for broader use of FL in healthcare.
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http://dx.doi.org/10.21203/rs.3.rs-126892/v1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805458PMC
January 2021

Reflections on the 1962 Paper "The Statistician in Medicine" by Sir Austin Bradford Hill.

Authors:
Xihong Lin

Stat Med 2021 01;40(1):32-34

Department of Biostatistics and Department of Statistics, Harvard University, Boston, Massachusetts, USA.

This article provides reflections on the 1962 paper by Sir Austin Bradford Hill, entitled "The Statistician in Medicine." It discusses several key takeaways of this paper, including causal inference for big data, reproducibility and replicability in science, and integration of statistics and data science with domain science.
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http://dx.doi.org/10.1002/sim.8834DOI Listing
January 2021

Identifying US Counties with High Cumulative COVID-19 Burden and Their Characteristics.

medRxiv 2021 Jan 12. Epub 2021 Jan 12.

Identifying areas with high COVID-19 burden and their characteristics can help improve vaccine distribution and uptake, reduce burdens on health care systems, and allow for better allocation of public health intervention resources. Synthesizing data from various government and nonprofit institutions of 3,142 United States (US) counties as of 12/21/2020, we studied county-level characteristics that are associated with cumulative case and death rates using regression analyses. Our results showed counties that are more rural, counties with more White/non-White segregation, and counties with higher percentages of people of color, in poverty, with no high school diploma, and with medical comorbidities such as diabetes and hypertension are associated with higher cumulative COVID-19 case and death rates. We identify the hardest hit counties in US using model-estimated case and death rates, which provide more reliable estimates of cumulative COVID-19 burdens than those using raw observed county-specific rates. Identification of counties with high disease burdens and understanding the characteristics of these counties can help inform policies to improve vaccine distribution, deployment and uptake, prevent overwhelming health care systems, and enhance testing access, personal protection equipment access, and other resource allocation efforts, all of which can help save more lives for vulnerable communities.

Significance Statement: We found counties that are more rural, counties with more White/non-White segregation, and counties with higher percentages of people of color, in poverty, with no high school diploma, and with medical comorbidities such as diabetes and hypertension are associated with higher cumulative COVID-19 case and death rates. We also identified individual counties with high cumulative COVID-19 burden. Identification of counties with high disease burdens and understanding the characteristics of these counties can help inform policies to improve vaccine distribution, deployment and uptake, prevent overwhelming health care systems, and enhance testing access, personal protection equipment access, and other resource allocation efforts, all of which can help save more lives for vulnerable communities.
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http://dx.doi.org/10.1101/2020.12.02.20234989DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7724685PMC
January 2021

Genetic Variant Set-Based Tests Using the Generalized Berk-Jones Statistic with Application to a Genome-Wide Association Study of Breast Cancer.

Authors:
Ryan Sun Xihong Lin

J Am Stat Assoc 2020 16;115(531):1079-1091. Epub 2019 Oct 16.

Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115; Department of Statistics, Harvard University, Cambridge, MA 02138.

Studying the effects of groups of single nucleotide polymorphisms (SNPs), as in a gene, genetic pathway, or network, can provide novel insight into complex diseases like breast cancer, uncovering new genetic associations and augmenting the information that can be gleaned from studying SNPs individually. Common challenges in set-based genetic association testing include weak effect sizes, correlation between SNPs in a SNP-set, and scarcity of signals, with individual SNP effects often ranging from extremely sparse to moderately sparse in number. Motivated by these challenges, we propose the Generalized Berk-Jones (GBJ) test for the association between a SNP-set and outcome. The GBJ extends the Berk-Jones statistic by accounting for correlation among SNPs, and it provides advantages over the Generalized Higher Criticism test when signals in a SNP-set are moderately sparse. We also provide an analytic p-value calculation for SNP-sets of any finite size, and we develop an omnibus statistic that is robust to the degree of signal sparsity. An additional advantage of our work is the ability to conduct inference using individual SNP summary statistics from a genome-wide association study (GWAS). We evaluate the finite sample performance of the GBJ through simulation and apply the method to identify breast cancer risk genes in a GWAS conducted by the Cancer Genetic Markers of Susceptibility Consortium. Our results suggest evidence of association between FGFR2 and breast cancer and also identify other potential susceptibility genes, complementing conventional SNP-level analysis.
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http://dx.doi.org/10.1080/01621459.2019.1660170DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7539682PMC
October 2019

Integration of multiomic annotation data to prioritize and characterize inflammation and immune-related risk variants in squamous cell lung cancer.

Genet Epidemiol 2021 02 14;45(1):99-114. Epub 2020 Sep 14.

Faculty of Medical Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.

Clinical trial results have recently demonstrated that inhibiting inflammation by targeting the interleukin-1β pathway can offer a significant reduction in lung cancer incidence and mortality, highlighting a pressing and unmet need to understand the benefits of inflammation-focused lung cancer therapies at the genetic level. While numerous genome-wide association studies (GWAS) have explored the genetic etiology of lung cancer, there remains a large gap between the type of information that may be gleaned from an association study and the depth of understanding necessary to explain and drive translational findings. Thus, in this study we jointly model and integrate extensive multiomics data sources, utilizing a total of 40 genome-wide functional annotations that augment previously published results from the International Lung Cancer Consortium (ILCCO) GWAS, to prioritize and characterize single nucleotide polymorphisms (SNPs) that increase risk of squamous cell lung cancer through the inflammatory and immune responses. Our work bridges the gap between correlative analysis and translational follow-up research, refining GWAS association measures in an interpretable and systematic manner. In particular, reanalysis of the ILCCO data highlights the impact of highly associated SNPs from nuclear factor-κB signaling pathway genes as well as major histocompatibility complex mediated variation in immune responses. One consequence of prioritizing likely functional SNPs is the pruning of variants that might be selected for follow-up work by over an order of magnitude, from potentially tens of thousands to hundreds. The strategies we introduce provide informative and interpretable approaches for incorporating extensive genome-wide annotation data in analysis of genetic association studies.
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http://dx.doi.org/10.1002/gepi.22358DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7855632PMC
February 2021

Evidence in the UK Biobank for the underdiagnosis of erythropoietic protoporphyria.

Genet Med 2021 01 2;23(1):140-148. Epub 2020 Sep 2.

Deparment of Medicine, Division of Pulmonary and Critical Care Medicine, Massachusetts General Hospital, Boston, MA, USA.

Purpose: Erythropoietic protoporphyria (EPP), characterized by painful cutaneous photosensitivity, results from pathogenic variants in ferrochelatase (FECH). For 96% of patients, EPP results from coinheriting a rare pathogenic variant in trans of a common hypomorphic variant c.315-48T>C (minor allele frequency 0.05). The estimated prevalence of EPP derived from the number of diagnosed individuals in Europe is 0.00092%, but this may be conservative due to underdiagnosis. No study has estimated EPP prevalence using large genetic data sets.

Methods: Disease-associated FECH variants were identified in the UK Biobank, a data set of 500,953 individuals including 49,960 exome sequences. EPP prevalence was then estimated. The association of FECH variants with EPP-related traits was assessed.

Results: Analysis of pathogenic FECH variants in the UK Biobank provides evidence that EPP prevalence is 0.0059% (95% confidence interval [CI]: 0.0042-0.0076%), 1.7-3.0 times more common than previously thought in the UK. In homozygotes for the common c.315-48T>C FECH variant, there was a novel decrement in both erythrocyte mean corpuscular volume (MCV) and hemoglobin.

Conclusion: The prevalence of EPP has been underestimated secondary to underdiagnosis. The common c.315-48T>C allele is associated with both MCV and hemoglobin, an association that could be important both for those with and without EPP.
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http://dx.doi.org/10.1038/s41436-020-00951-8DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7796935PMC
January 2021

Population-scale longitudinal mapping of COVID-19 symptoms, behaviour and testing.

Nat Hum Behav 2020 09 26;4(9):972-982. Epub 2020 Aug 26.

The How We Feel Project, San Leandro, CA, USA.

Despite the widespread implementation of public health measures, coronavirus disease 2019 (COVID-19) continues to spread in the United States. To facilitate an agile response to the pandemic, we developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behaviour and demographics. Here, we report results from over 500,000 users in the United States from 2 April 2020 to 12 May 2020. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19-positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation; show a variety of exposure, occupational and demographic risk factors for COVID-19 beyond symptoms; reveal factors for which users have been SARS-CoV-2 PCR tested; and highlight the temporal dynamics of symptoms and self-isolation behaviour. These results highlight the utility of collecting a diverse set of symptomatic, demographic, exposure and behavioural self-reported data to fight the COVID-19 pandemic.
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http://dx.doi.org/10.1038/s41562-020-00944-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7501153PMC
September 2020

Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.

Nat Genet 2020 09 24;52(9):969-983. Epub 2020 Aug 24.

Department of Data Sciences, Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.
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http://dx.doi.org/10.1038/s41588-020-0676-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7483769PMC
September 2020

Reconstruction of the full transmission dynamics of COVID-19 in Wuhan.

Nature 2020 08 16;584(7821):420-424. Epub 2020 Jul 16.

Ministry of Education Key Laboratory of Environment and Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

As countries in the world review interventions for containing the pandemic of coronavirus disease 2019 (COVID-19), important lessons can be drawn from the study of the full transmission dynamics of its causative agent-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)- in Wuhan (China), where vigorous non-pharmaceutical interventions have suppressed the local outbreak of this disease. Here we use a modelling approach to reconstruct the full-spectrum dynamics of COVID-19 in Wuhan between 1 January and 8 March 2020 across 5 periods defined by events and interventions, on the basis of 32,583 laboratory-confirmed cases. Accounting for presymptomatic infectiousness, time-varying ascertainment rates, transmission rates and population movements, we identify two key features of the outbreak: high covertness and high transmissibility. We estimate 87% (lower bound, 53%) of the infections before 8 March 2020 were unascertained (potentially including asymptomatic and mildly symptomatic individuals); and a basic reproduction number (R) of 3.54 (95% credible interval 3.40-3.67) in the early outbreak, much higher than that of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS). We observe that multipronged interventions had considerable positive effects on controlling the outbreak, decreasing the reproduction number to 0.28 (95% credible interval 0.23-0.33) and-by projection-reducing the total infections in Wuhan by 96.0% as of 8 March 2020. We also explore the probability of resurgence following the lifting of all interventions after 14 consecutive days of no ascertained infections; we estimate this probability at 0.32 and 0.06 on the basis of models with 87% and 53% unascertained cases, respectively-highlighting the risk posed by substantial covert infections when changing control measures. These results have important implications when considering strategies of continuing surveillance and interventions to eventually contain outbreaks of COVID-19.
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http://dx.doi.org/10.1038/s41586-020-2554-8DOI Listing
August 2020

Association of Neutrophil to Lymphocyte Ratio With Pulmonary Function in a 30-Year Longitudinal Study of US Veterans.

JAMA Netw Open 2020 07 1;3(7):e2010350. Epub 2020 Jul 1.

Laboratory of Environmental Precision Biosciences, Mailman School of Public Health, Columbia University, New York, New York.

Importance: Chronic obstructive pulmonary disease (COPD) is a critical public health burden. The neutrophil to lymphocyte ratio (NLR), an inflammation biomarker, has been associated with COPD morbidity and mortality; however, its associations with lung function decline and COPD development are poorly understood.

Objective: To explore the associations of NLR with lung function decline and COPD risks.

Design, Setting, And Participants: This longitudinal cohort study included white male veterans in the US with more than 30 years of follow-up to investigate the associations of NLR with lung function, COPD, and hypomethylation of cg05575921, the top DNA methylation marker of lung function changes in response to tobacco smoking. This study included 7466 visits from 1549 participants, each examined up to 13 times between 1982 and 2018. A subgroup of 1411 participants without COPD at baseline were selected to analyze the association of NLR with incident COPD. Data were analyzed from September 2019 to January 2020.

Exposures: The primary exposure was NLR, which was estimated using automated whole blood cell counts based on a blood sample collected at each visit. The methylation level of cg05575921 was measured in blood DNA from a subgroup of 1228 visits.

Main Outcomes And Measures: The outcomes of interest were lung function, measured as forced respiratory volume in the first second (FEV1) in liters, forced vital capacity (FVC) in liters, percentage of FVC exhaled in the first second (FEV1/FVC), and maximal midexpiratory flow rate (MMEF) in liters per minute and COPD status, defined as meeting the Global Initiative for Chronic Obstructive Lung Diseases stage II (or higher) criteria. Both outcomes were measured as each visit.

Results: Among 1549 included men (mean [SD] age, 68.3 [9.3] years) with 7466 visits from 1982 to 2018, a 1-unit increase in NLR was associated with statistically significant mean (SE) decreases of 0.021 (0.004) L in FEV1, 0.016 (0.005) L in FVC, 0.290% (0.005) L in FVC, 0.290% (0.065%) in FEV1/FVC, and 3.65 (0.916) L/min MMEF. Changes in NLR up to approximately 10 years were associated with corresponding longitudinal changes in lung function. Furthermore, this increase in NLR was associated with 9% higher odds of COPD (odds ratio, 1.09 [95% CI, 1.03-1.15]) for all visits and 27% higher risk of incident COPD (odds ratio, 1.07 [95% CI, 1.07-1.51]) for participants without COPD at baseline. Additionally, a 1-unit increase in NLR was associated with a mean (SE) decrease of 0.0048 (0.0021 in cg05575921 hypomethylation, which may mediate the adverse association of NLR-related inflammation on lung function.

Conclusions And Relevance: These findings suggest that NLR may be a clinically relevant biomarker associated with high risk of lung function impairment and COPD alone or in combination with DNA methylation profiles.
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http://dx.doi.org/10.1001/jamanetworkopen.2020.10350DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7358911PMC
July 2020

Population-scale Longitudinal Mapping of COVID-19 Symptoms, Behavior, and Testing Identifies Contributors to Continued Disease Spread in the United States.

medRxiv 2020 Jun 11. Epub 2020 Jun 11.

Despite social distancing and shelter-in-place policies, COVID-19 continues to spread in the United States. A lack of timely information about factors influencing COVID-19 spread and testing has hampered agile responses to the pandemic. We developed How We Feel, an extensible web and mobile application that aggregates self-reported survey responses, to fill gaps in the collection of COVID-19-related data. How We Feel collects longitudinal and geographically localized information on users' health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self- reported surveys can be used to build predictive models of COVID-19 test results, which may aid in identification of likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, as well as for household and community exposure, occupation, and demographics being strong risk factors for COVID-19. We further reveal factors for which users have been SARS-CoV-2 PCR tested, as well as the temporal dynamics of self- reported symptoms and self-isolation behavior in positive and negative users. These results highlight the utility of collecting a diverse set of symptomatic, demographic, and behavioral self- reported data to fight the COVID-19 pandemic.
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http://dx.doi.org/10.1101/2020.06.09.20126813DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302230PMC
June 2020

Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China.

JAMA 2020 May;323(19):1915-1923

Department of Occupational and Environmental Health, Ministry of Education Key Laboratory of Environment and Health, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

Importance: Coronavirus disease 2019 (COVID-19) has become a pandemic, and it is unknown whether a combination of public health interventions can improve control of the outbreak.

Objective: To evaluate the association of public health interventions with the epidemiological features of the COVID-19 outbreak in Wuhan by 5 periods according to key events and interventions.

Design, Setting, And Participants: In this cohort study, individual-level data on 32 583 laboratory-confirmed COVID-19 cases reported between December 8, 2019, and March 8, 2020, were extracted from the municipal Notifiable Disease Report System, including patients' age, sex, residential location, occupation, and severity classification.

Exposures: Nonpharmaceutical public health interventions including cordons sanitaire, traffic restriction, social distancing, home confinement, centralized quarantine, and universal symptom survey.

Main Outcomes And Measures: Rates of laboratory-confirmed COVID-19 infections (defined as the number of cases per day per million people), across age, sex, and geographic locations were calculated across 5 periods: December 8 to January 9 (no intervention), January 10 to 22 (massive human movement due to the Chinese New Year holiday), January 23 to February 1 (cordons sanitaire, traffic restriction and home quarantine), February 2 to 16 (centralized quarantine and treatment), and February 17 to March 8 (universal symptom survey). The effective reproduction number of SARS-CoV-2 (an indicator of secondary transmission) was also calculated over the periods.

Results: Among 32 583 laboratory-confirmed COVID-19 cases, the median patient age was 56.7 years (range, 0-103; interquartile range, 43.4-66.8) and 16 817 (51.6%) were women. The daily confirmed case rate peaked in the third period and declined afterward across geographic regions and sex and age groups, except for children and adolescents, whose rate of confirmed cases continued to increase. The daily confirmed case rate over the whole period in local health care workers (130.5 per million people [95% CI, 123.9-137.2]) was higher than that in the general population (41.5 per million people [95% CI, 41.0-41.9]). The proportion of severe and critical cases decreased from 53.1% to 10.3% over the 5 periods. The severity risk increased with age: compared with those aged 20 to 39 years (proportion of severe and critical cases, 12.1%), elderly people (≥80 years) had a higher risk of having severe or critical disease (proportion, 41.3%; risk ratio, 3.61 [95% CI, 3.31-3.95]) while younger people (<20 years) had a lower risk (proportion, 4.1%; risk ratio, 0.47 [95% CI, 0.31-0.70]). The effective reproduction number fluctuated above 3.0 before January 26, decreased to below 1.0 after February 6, and decreased further to less than 0.3 after March 1.

Conclusions And Relevance: A series of multifaceted public health interventions was temporally associated with improved control of the COVID-19 outbreak in Wuhan, China. These findings may inform public health policy in other countries and regions.
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http://dx.doi.org/10.1001/jama.2020.6130DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7149375PMC
May 2020
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