A catalog of tens of thousands of viruses from human metagenomes reveals hidden associations with chronic diseases

Despite remarkable strides in microbiome research, the viral component of the microbiome has generally presented a more challenging target than the bacteriome. This gap persists, even though many thousands of shotgun sequencing runs from human metagenomic samples exist in public databases, and all of them encompass large amounts of viral sequence data. The lack of a comprehensive database for human-associated viruses has historically stymied efforts to interrogate the impact of the virome on human health. This study probes thousands of datasets to uncover sequences from over 45,000 unique virus taxa, with historically high per-genome completeness. Large publicly available case-control studies are reanalyzed, and over 2,200 strong virus–disease associations are found.

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A New Comprehensive Catalog of the Human Virome Reveals Hidden Associations with Chronic Diseases

10.1101/2020.11.01.363820 ◽

2020 ◽

Author(s):

Michael J. Tisza ◽

Christopher B. Buck

Keyword(s):

Virus Disease ◽

High Sensitivity ◽

High Specificity ◽

Metagenomic Data ◽

Case Control Studies ◽

Operational Taxonomic Units ◽

Bioinformatic Tool ◽

Disease Associations ◽

Microbiome Research ◽

Viral Sequences

AbstractWhile there have been remarkable strides in microbiome research, the viral component of the microbiome has generally presented a more challenging target than the bacteriome. This is despite the fact that many thousands of shotgun sequencing runs from human metagenomic samples exist in public databases and all of them encompass large amounts of viral sequences. The lack of a comprehensive database for human-associated viruses, along with inadequate methods for high-throughput identification of highly divergent viruses in metagenomic data, has historically stymied efforts to characterize virus sequences in a comprehensive way. In this study, a new high-specificity and high-sensitivity bioinformatic tool, Cenote-Taker 2, was applied to thousands of human metagenome datasets, uncovering over 50,000 unique virus operational taxonomic units. Publicly available case-control studies were re-analyzed, and over 1,700 strong virus-disease associations were found.

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The impact of social context on socio-demographic risk factors for suicide: a synthesis of data from case-control studies

Journal of Epidemiology & Community Health ◽

10.1136/jech.2008.084145 ◽

2009 ◽

Vol 64 (6) ◽

pp. 530-534 ◽

Cited By ~ 16

Author(s):

M. J. Crawford ◽

B. Kuforiji ◽

P. Ghosh

Keyword(s):

Risk Factors ◽

Social Context ◽

Case Control ◽

Case Control Studies ◽

Demographic Risk ◽

Demographic Risk Factors ◽

The Impact ◽

Risk Factors For Suicide

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Computational Modeling of the Human Microbiome

Microorganisms ◽

10.3390/microorganisms8020197 ◽

2020 ◽

Vol 8 (2) ◽

pp. 197

Author(s):

Shomeek Chowdhury ◽

Stephen S. Fong

Keyword(s):

Computational Modeling ◽

Human Health ◽

Large Scale ◽

Human Microbiome ◽

Human Microbiome Project ◽

Microbial Composition ◽

Site Specific ◽

Microbiome Research ◽

High Level ◽

The Impact

The impact of microorganisms on human health has long been acknowledged and studied, but recent advances in research methodologies have enabled a new systems-level perspective on the collections of microorganisms associated with humans, the human microbiome. Large-scale collaborative efforts such as the NIH Human Microbiome Project have sought to kick-start research on the human microbiome by providing foundational information on microbial composition based upon specific sites across the human body. Here, we focus on the four main anatomical sites of the human microbiome: gut, oral, skin, and vaginal, and provide information on site-specific background, experimental data, and computational modeling. Each of the site-specific microbiomes has unique organisms and phenomena associated with them; there are also high-level commonalities. By providing an overview of different human microbiome sites, we hope to provide a perspective where detailed, site-specific research is needed to understand causal phenomena that impact human health, but there is equally a need for more generalized methodology improvements that would benefit all human microbiome research.

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The Impact of Selection Bias Due to Increasing Response Rates among Population Controls in Occupational Case-Control Studies

American Journal of Respiratory and Critical Care Medicine ◽

10.1164/ajrccm.185.1.104a ◽

2012 ◽

Vol 185 (1) ◽

pp. 104-106 ◽

Cited By ~ 7

Author(s):

Matthias Möhner

Keyword(s):

Selection Bias ◽

Response Rates ◽

Case Control ◽

Case Control Studies ◽

The Impact ◽

Population Controls

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Evaluating and comparing biomarkers with respect to the area under the receiver operating characteristics curve in two-phase case–control studies

Biostatistics ◽

10.1093/biostatistics/kxw003 ◽

2016 ◽

Vol 17 (3) ◽

pp. 499-522 ◽

Cited By ~ 4

Author(s):

Ying Huang

Keyword(s):

Case Control ◽

Receiver Operating Characteristics ◽

Biased Sampling ◽

Second Phase ◽

Operating Characteristics ◽

Case Control Studies ◽

Two Phase ◽

Receiver Operating Characteristics Curve ◽

The Impact ◽

Receiver Operating

Abstract Two-phase sampling design, where biomarkers are subsampled from a phase-one cohort sample representative of the target population, has become the gold standard in biomarker evaluation. Many two-phase case–control studies involve biased sampling of cases and/or controls in the second phase. For example, controls are often frequency-matched to cases with respect to other covariates. Ignoring biased sampling of cases and/or controls can lead to biased inference regarding biomarkers' classification accuracy. Considering the problems of estimating and comparing the area under the receiver operating characteristics curve (AUC) for a binary disease outcome, the impact of biased sampling of cases and/or controls on inference and the strategy to efficiently account for the sampling scheme have not been well studied. In this project, we investigate the inverse-probability-weighted method to adjust for biased sampling in estimating and comparing AUC. Asymptotic properties of the estimator and its inference procedure are developed for both Bernoulli sampling and finite-population stratified sampling. In simulation studies, the weighted estimators provide valid inference for estimation and hypothesis testing, while the standard empirical estimators can generate invalid inference. We demonstrate the use of the analytical variance formula for optimizing sampling schemes in biomarker study design and the application of the proposed AUC estimators to examples in HIV vaccine research and prostate cancer research.

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Estimating the impact of pneumococcal conjugate vaccines on childhood pneumonia in sub-Saharan Africa: A systematic review

10.1101/865154 ◽

2019 ◽

Cited By ~ 2

Author(s):

Chukwuemeka Onwuchekwa ◽

Edem Bassey ◽

Victor Williams ◽

Emmanuel Oga

Keyword(s):

Systematic Review ◽

Pneumococcal Pneumonia ◽

Data Extraction ◽

Case Control ◽

Sub Saharan Africa ◽

Case Control Studies ◽

Childhood Pneumonia ◽

Vaccine Impact ◽

Sub Saharan ◽

The Impact

AbstractBackgroundThe impact of pneumococcal conjugate vaccine introduction in reducing the incidence of childhood pneumonia has not been well documented in sub-Saharan Africa. Many studies evaluating vaccine impact have used invasive pneumococcal disease or pneumococcal pneumonia as an outcome.ObjectiveTo estimate the impact of routine administration of 10-valent and 13-valent PCV on the incidence of pneumonia in children under five years of age in sub-Saharan Africa.Data sourcesA systematic review was conducted between 16 and 31 July 2019. The review was registered on PROSPERO with registration number CRD42019142369. The literature search was conducted in indexed databases including Medline and Embase, grey literature databases and online libraries of two universities. Manual search of the references of included studies was performed to identify additional relevant studies. The search strategy combined pneumococcal conjugate vaccine, pneumonia and child as search concepts.Study selectionStudies investigating the impact of 10- or13-valent PCV on childhood pneumonia in a sub-Saharan African country were eligible for inclusion. Case-control, cohort, pre-post and time-series study designs were eligible for inclusion. Exclusion criteria were use of 7- or 9-valent PCV, systematic review studies, clinical trials and record publication prior to 2009.Data extractionIndependent data extraction was conducted. Key variables include year study conducted, type of study design, type of PCV used and year of introduction, reported PCV coverage, outcome measure evaluated and the effect measure.Data synthesisEight records were included in the final analysis, 6 records were pre-post or time-series studies, 1 was a case-control study and 1 report combined pre-post and case-control studies. Vaccine impact measured as percentage reduction in risk (%RR) of clinical pneumonia was mostly small and non-significant. The risk reduction was more significant and consistent on radiological and pneumococcal pneumonia. Vaccine effectiveness reported in case-control studies was mostly non-significant.ConclusionEvidence of the positive impact of routine infant pneumococcal vaccination on pneumonia in sub-Saharan Africa is weak. There is a need for more research in this area to evaluate the influence of pathogen or serotype replacement in pneumonia after PCV introduction. Ongoing surveillance is also required to establish the long term trend in pneumonia epidemiology after PCV introduction.

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Uses of pathogen detection data to estimate vaccine direct effects in case–control studies

Journal of The Royal Society Interface ◽

10.1098/rsif.2020.0161 ◽

2020 ◽

Vol 17 (169) ◽

pp. 20200161

Author(s):

Joseph A. Lewnard

Keyword(s):

Pathogen Detection ◽

Epidemiological Studies ◽

Case Control ◽

Host Susceptibility ◽

Mathematical Framework ◽

Direct Effects ◽

Case Control Studies ◽

Study Context ◽

The Impact ◽

Microbiological Data

The fact that many pathogens can be carried or shed without causing symptoms complicates the interpretation of microbiological data when diagnosing certain infectious disease syndromes. Diagnostic criteria that attribute symptoms to a pathogen which is detectable, whether it is or is not the aetiological agent of disease, may lead to outcome misclassification in epidemiological studies. Case–control studies are commonly undertaken to estimate vaccine effectiveness (VE) and present an opportunity to compare pathogen detection among individuals with and without clinically relevant symptoms. Considering this study context, we present a mathematical framework yielding simple estimators for the direct effects of vaccination on various aspects of host susceptibility. These include protection against acquisition of the pathogen of interest and protection against progression of this pathogen to disease following acquisition. We assess the impact of test sensitivity on these estimators and extend our framework to identify a ‘vaccine probe’ estimator for pathogen-specific aetiological fractions. We also derive biases affecting VE estimates under the test-negative design, a special case enrolling only symptomatic persons. Our results provide strategies for estimating pathogen-specific VE in the absence of a diagnostic gold standard. These approaches can inform the design and analysis of studies addressing numerous pathogens and vaccines.

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Systematic Review and Meta-Analysis of Tocilizumab Therapy Versus Standard of Care in Over 15,000 COVID-19 Pneumonia Patients during the First Eight Months of the Pandemic

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18179149 ◽

2021 ◽

Vol 18 (17) ◽

pp. 9149

Author(s):

Naim Mahroum ◽

Abdulla Watad ◽

Charlie Bridgewood ◽

Muhammad Mansour ◽

Ahmad Nasr ◽

...

Keyword(s):

Systematic Review ◽

Mechanical Ventilation ◽

Corticosteroid Therapy ◽

Bacterial Infections ◽

Meta Analysis ◽

Standard Of Care ◽

Case Control ◽

Case Control Studies ◽

Icu Admission ◽

The Impact

Background. Tocilizumab is an anti-IL-6 therapy widely adopted in the management of the so-called “cytokine storm” related to SARS-CoV-2 virus infection, but its effectiveness, use in relation to concomitant corticosteroid therapy and safety were unproven despite widespread use in numerous studies, mostly open label at the start of the pandemic. Methods: We performed a systematic review and meta-analysis of case-control studies utilising tocilizumab in COVID-19 on different databases (PubMed/MEDLINE/Scopus) and preprint servers (medRxiv and SSRN) from inception until 20 July 2020 (PROSPERO CRD42020195690). Subgroup analyses and meta-regressions were performed. The impact of tocilizumab and concomitant corticosteroid therapy or tocilizumab alone versus standard of care (SOC) on the death rate, need for mechanical ventilation, ICU admission and bacterial infections were assessed. Results. Thirty-nine studies with 15,531 patients (3657 cases versus 11,874 controls) were identified. Unadjusted estimates (n = 28) failed to demonstrate a protective effect of tocilizumab on survival (OR 0.74 ([95%CI 0.55–1.01], p = 0.057), mechanical ventilation prevention (OR 2.21 [95%CI 0.53–9.23], p = 0.277) or prevention of ICU admission (OR 3.79 [95%CI 0.38–37.34], p = 0.254). Considering studies with adjusted, estimated, tocilizumab use was associated with mortality rate reduction (HR 0.50 ([95%CI 0.38–0.64], p < 0.001) and prevention of ICU admission (OR 0.16 ([95%CI 0.06–0.43], p < 0.001). Tocilizumab with concomitant steroid use versus SOC was protective with an OR of 0.49 ([95%CI 0.36–0.65], p < 0.05) as was tocilizumab alone versus SOC with an OR of 0.59 ([95%CI 0.34–1.00], p < 0.001). Risk of infection increased (2.36 [95%CI 1.001–5.54], p = 0.050; based on unadjusted estimates). Conclusion: Despite the heterogeneity of included studies and large number of preprint articles, our findings from the first eight of the pandemic in over 15,000 COVID-19 cases suggested an incremental efficacy of tocilizumab in severe COVID-19 that were confirmed by subsequent meta-analyses of large randomized trials of tocilizumab. This suggests that analysis of case-control studies and pre-print server data in the early stages of a pandemic appeared robust for supporting incremental benefits and lack of major therapeutic toxicity of tocilizumab for severe COVID-19.

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Breastfeeding is associated with reduced risk of multiple sclerosis in males, predominantly among HLA-DRB1*15:01 carriers

Multiple Sclerosis Journal - Experimental Translational and Clinical ◽

10.1177/2055217320928101 ◽

2020 ◽

Vol 6 (2) ◽

pp. 205521732092810

Author(s):

AK Hedström ◽

C Adams ◽

X Shao ◽

C Schaefer ◽

T Olsson ◽

...

Keyword(s):

Multiple Sclerosis ◽

Protective Factor ◽

Meta Analysis ◽

Population Based ◽

Case Control ◽

Carrier Status ◽

Case Control Studies ◽

Biologic Effect ◽

The Impact ◽

Reduced Risk

Background Breastfeeding as an infant appears protective against later development of some autoimmune diseases, but research into its influence on multiple sclerosis (MS) risk has yielded inconclusive results. Objective We investigated the possible impact of breastfeeding on MS risk. Methods We used two population-based case–control studies comprising 3670 cases and 6737 matched controls. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for association between MS and exposure to prolonged breastfeeding (4 months or longer) versus reduced breastfeeding (less than 4 months). A meta-analysis of case–control studies that assessed the impact of breastfeeding on MS risk among women and men was conducted. Results Prolonged breastfeeding was associated with reduced MS risk among men (OR 0.7, 95% CI 0.5–0.9) but not among women (OR 0.9, 95% CI 0.8–1.1). Among men, a synergistic effect was observed between HLA-DRB1*15:01 carrier status and reduced breastfeeding. Conclusions Findings from the current study add to accumulating evidence that breastfeeding may be a modifiable protective factor for reducing the risk of MS in offspring. When possible, mothers should be supported to breastfeed their infants; however, the mechanism of a sex-specific biologic effect of breastfeeding on MS risk is unclear.

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