Publications
183 results found
Bodinier B, Vuckovic D, Rodrigues S, et al., 2023, Automated calibration of consensus weighted distance-based clustering approaches using sharp, Bioinformatics, ISSN: 1367-4803
Oosterwegel MJ, Ibi D, Portengen L, et al., 2023, Variability of the Human Serum Metabolome over 3 Months in the EXPOsOMICS Personal Exposure Monitoring Study., Environ Sci Technol, Vol: 57, Pages: 12752-12759
Liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) and untargeted metabolomics are increasingly used in exposome studies to study the interactions between nongenetic factors and the blood metabolome. To reliably and efficiently link detected compounds to exposures and health phenotypes in such studies, it is important to understand the variability in metabolome measures. We assessed the within- and between-subject variability of untargeted LC-HRMS measurements in 298 nonfasting human serum samples collected on two occasions from 157 subjects. Samples were collected ca. 107 (IQR: 34) days apart as part of the multicenter EXPOsOMICS Personal Exposure Monitoring study. In total, 4294 metabolic features were detected, and 184 unique compounds could be identified with high confidence. The median intraclass correlation coefficient (ICC) across all metabolic features was 0.51 (IQR: 0.29) and 0.64 (IQR: 0.25) for the 184 uniquely identified compounds. For this group, the median ICC marginally changed (0.63) when we included common confounders (age, sex, and body mass index) in the regression model. When grouping compounds by compound class, the ICC was largest among glycerophospholipids (median ICC 0.70) and steroids (0.67), and lowest for amino acids (0.61) and the O-acylcarnitine class (0.44). ICCs varied substantially within chemical classes. Our results suggest that the metabolome as measured with untargeted LC-HRMS is fairly stable (ICC > 0.5) over 100 days for more than half of the features monitored in our study, to reflect average levels across this time period. Variance across the metabolome will result in differential measurement error across the metabolome, which needs to be considered in the interpretation of metabolome results.
Whitaker M, Davies B, Atchison C, et al., 2023, SARS-CoV-2 rapid antibody test results and subsequent risk of hospitalisation and death in 361,801 people, Nature Communications, Vol: 14, ISSN: 2041-1723
The value of SARS-CoV-2 lateral flow immunoassay (LFIA) tests for estimating individual disease risk is unclear. The REACT-2 study in England, UK, obtained self-administered SARS-CoV-2 LFIA test results from 361,801 adults in January-May 2021. Here, we link to routine data on subsequent hospitalisation (to September 2021), and death (to December 2021). Among those who had received one or more vaccines, a negative LFIA is associated with increased risk of hospitalisation with COVID-19 (HR: 2.73 [95% confidence interval: 1.15,6.48]), death (all-cause) (HR: 1.59, 95% CI:1.07, 2.37), and death with COVID-19 as underlying cause (20.6 [1.83,232]). For people designated at high risk from COVID-19, who had received one or more vaccines, there is an additional risk of all-cause mortality of 1.9 per 1000 for those testing antibody negative compared to positive. However, the LFIA does not provide substantial predictive information over and above that which is available from detailed sociodemographic and health-related variables. Nonetheless, this simple test provides a marker which could be a valuable addition to understanding population and individual-level risk.
Eales O, de Oliveira Martins L, Page A, et al., 2023, Dynamics and scale of the SARS-CoV-2 variant Omicron epidemic in England, Nature Communications, Vol: 13, ISSN: 2041-1723
The SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant (first detected in November 2021) exhibited a high degree of immune evasion, leading to increased infection rates worldwide. However, estimates of the magnitude of this Omicron wave have often relied on routine testing data, which are prone to several biases. Using data from the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys assessing prevalence of SARS-CoV-2 infection in England, we estimated the dynamics of England’s Omicron wave (from 9 September 2021 to 1 March 2022). We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct variants, intermittent epidemics of similar magnitudes may become the ‘new normal’.
Bowden SJ, Doulgeraki T, Bouras E, et al., 2023, Risk factors for human papillomavirus infection, cervical intraepithelial neoplasia and cervical cancer: an umbrella review and follow-up Mendelian randomisation studies, BMC Medicine, Vol: 21, Pages: 1-15, ISSN: 1741-7015
Background: Persistent infection by oncogenic human papillomavirus (HPV) is necessary although not sufficient for development of cervical cancer. Behavioural, environmental, or comorbid exposures may promote or protect against malignant transformation. Randomised evidence is limited and the validity of observational studies describing these associations remains unclear.Methods: In this umbrella review we searched electronic databases to identify meta-analyses of observational studies that evaluated risk or protective factors and the incidence of HPV infection, cervical intra-epithelial neoplasia (CIN), cervical cancer incidence and mortality. Following re-analysis, evidence was classified and graded based on a pre-defined set of statistical criteria. Quality was assessed with AMSTAR-2. For all associations graded as weak evidence or above, with available genetic instruments, we also performed Mendelian randomisation to examine the potential causal effect of modifiable exposures with risk of cervical cancer. The protocol for this study was registered on PROSPERO (CRD42020189995).Results: We included 171 meta-analyses of different exposure contrasts from 50 studies. Systemic immunosuppression including HIV infection (RR=2.20(95%CI=1.89-2.54)) and immunosuppressive medications for inflammatory bowel disease (RR=1.33(95%CI=1.27-1.39)), as well as an altered vaginal microbiome (RR=1.59(95%CI=1.40-1.81)) were supported by strong and highly suggestive evidence for an association with HPV persistence, CIN or cervical cancer. Smoking, number of sexual partners and young age at first pregnancy were supported by highly suggestive evidence and confirmed by Mendelian randomisation.Conclusions: Our main analysis supported the association of systemic (HIV infection, immunosuppressive medications) and local immunosuppression (altered vaginal microbiota) with increased risk for worse HPV and cervical disease outcomes. Mendelian randomisation confirmed the link for genetically predic
Bodinier B, Filippi S, Haugdahl Nost T, et al., 2023, Automated calibration for stability selection in penalised regression and graphical models, Journal of the Royal Statistical Society Series C: Applied Statistics, ISSN: 0035-9254
Stability selection represents an attractive approach to identify sparse sets of features jointly associated with an outcome in high-dimensional contexts. We introduce an automated calibration procedure via maximisation of an in-house stability score and accommodating a priori-known block structure (e.g. multi-OMIC) data. It applies to [Least Absolute Shrinkage Selection Operator (LASSO)] penalised regression and graphical models. Simulations show our approach outperforms non-stability-based and stability selection approaches using the original calibration. Application to multi-block graphical LASSO on real (epigenetic and transcriptomic) data from the Norwegian Women and Cancer study reveals a central/credible and novel cross-OMIC role of LRRN3 in the biological response to smoking. Proposed approaches were implemented in the R package sharp.
Atchison C, Whitaker M, Donnelly C, et al., 2023, Characteristics and predictors of persistent symptoms post COVID-19 in children and young people: a large community cross-sectional study in England, Archives of Disease in Childhood, Vol: 108, ISSN: 0003-9888
Objective: To estimate the prevalence of, and associated risk factors for, persistent symptoms post-COVID-19 among children aged 5–17 years in England.Design: Serial cross-sectional study.Setting: Rounds 10–19 (March 2021 to March 2022) of the REal-time Assessment of Community Transmission-1 study (monthly cross-sectional surveys of random samples of the population in England).Study population: Children aged 5–17 years in the community.Predictors: Age, sex, ethnicity, presence of a pre-existing health condition, index of multiple deprivation, COVID-19 vaccination status and dominant UK circulating SARS-CoV-2 variant at time of symptom onset.Main outcome measures: Prevalence of persistent symptoms, reported as those lasting ≥3 months post-COVID-19.Results: Overall, 4.4% (95% CI 3.7 to 5.1) of 3173 5–11 year-olds and 13.3% (95% CI 12.5 to 14.1) of 6886 12–17 year-olds with prior symptomatic infection reported at least one symptom lasting ≥3 months post-COVID-19, of whom 13.5% (95% CI 8.4 to 20.9) and 10.9% (95% CI 9.0 to 13.2), respectively, reported their ability to carry out day-to-day activities was reduced ‘a lot’ due to their symptoms. The most common symptoms among participants with persistent symptoms were persistent coughing (27.4%) and headaches (25.4%) in children aged 5–11 years and loss or change of sense of smell (52.2%) and taste (40.7%) in participants aged 12–17 years. Higher age and having a pre-existing health condition were associated with higher odds of reporting persistent symptoms.Conclusions: One in 23 5–11 year-olds and one in eight 12–17 year-olds post-COVID-19 report persistent symptoms lasting ≥3 months, of which one in nine report a large impact on performing day-to-day activities.
Brewer H, Chadeau-Hyam M, Johnson E, et al., 2023, Cancer Loyalty Card Study (CLOCS): feasibility outcomes for an observational case-control study focusing on the patient interval in ovarian cancer, BMJ Open, Vol: 13, Pages: 1-10, ISSN: 2044-6055
Objectives: Ovarian cancer symptoms are often non‐specific and can be normalised before patients seek medical help. The Cancer Loyalty Card Study (CLOCS) investigated self‐management behaviours of ovarian cancer patients prior to their diagnosis using loyaltycard data collected by two United Kingdom (UK)‐based high street retailers. Here, we discuss the feasibility outcomes for this novel research. Design: Observational case‐control study. Setting: Control participants were invited to the study using social media and other sources from the general public. Once consented, control participants were required to submit proof of identification (ID) for their loyalty card data to be shared. Cases were identifiedusing unique National Health Service (NHS) numbers (a proxy for ID) and were recruited through 12 NHS tertiary care clinics.Participants: Women in the UK, 18 years or older, with at least one of the participating high street retailers’ loyalty cards. Those with an ovarian cancer diagnosis within two years of recruitment were considered cases, and those without an ovarian cancer diagnosis were considered controls.Primary Outcome Measures: Recruitment rates, demographics of participants and identification of any barriers to recruitment.Results: In total, 182 cases and 427 controls were recruited with significant differences by age, number of people in participants’ households and the geographical region in the UK. However, only 37% (n=160/427) of control participants provided sufficient ID details and81% (130/160) matched retailers’ records. The majority of the participants provided complete responses to the 24‐Item Ovarian Risk Questionnaire.Conclusions: Our findings show that recruitment to a study aiming to understand self‐care behaviours using loyalty card data is challenging but feasible. The general public were willing to share their data for health research. Barriers in data sharing mechanisms need to be addressed to maximise participant rete
Eales O, Haw D, Wang H, et al., 2023, Dynamics of SARS-CoV-2 infection hospitalisation and infection fatality ratios over 23 months in England, PLoS Biology, Vol: 21, Pages: 1-21, ISSN: 1544-9173
The relationship between prevalence of infection and severe outcomes such as hospitalisation and death changed over the course of the COVID-19 pandemic. Reliable estimates of the infection fatality ratio (IFR) and infection hospitalisation ratio (IHR) along with the time-delay between infection and hospitalisation/death can inform forecasts of the numbers/timing of severe outcomes and allow healthcare services to better prepare for periods of increased demand. The REal-time Assessment of Community Transmission-1 (REACT-1) study estimated swab positivity for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection in England approximately monthly from May 2020 to March 2022. Here, we analyse the changing relationship between prevalence of swab positivity and the IFR and IHR over this period in England, using publicly available data for the daily number of deaths and hospitalisations, REACT-1 swab positivity data, time-delay models, and Bayesian P-spline models. We analyse data for all age groups together, as well as in 2 subgroups: those aged 65 and over and those aged 64 and under. Additionally, we analysed the relationship between swab positivity and daily case numbers to estimate the case ascertainment rate of England's mass testing programme. During 2020, we estimated the IFR to be 0.67% and the IHR to be 2.6%. By late 2021/early 2022, the IFR and IHR had both decreased to 0.097% and 0.76%, respectively. The average case ascertainment rate over the entire duration of the study was estimated to be 36.1%, but there was some significant variation in continuous estimates of the case ascertainment rate. Continuous estimates of the IFR and IHR of the virus were observed to increase during the periods of Alpha and Delta's emergence. During periods of vaccination rollout, and the emergence of the Omicron variant, the IFR and IHR decreased. During 2020, we estimated a time-lag of 19 days between hospitalisation and swab positivity, and 26 days between deaths
Elliott P, Whitaker M, Tang D, et al., 2023, Design and implementation of a national SARS-CoV-2 monitoring programme in England: REACT-1 Study, American Journal of Public Health, ISSN: 0090-0036
Data System. The REal-time Assessment of Community Transmission-1 (REACT-1) Study was funded by the Department of Health and Social Care in England to provide reliable and timely estimates of prevalence of SARS-CoV-2 infection by time, person and place.Data Collection/Processing. The data were obtained by writing to named individuals aged 5 years and above in random cross-sections of the population of England, using the National Health Service (NHS) list of patients registered with a general practitioner (>99% coverage) as sampling frame. Data were collected 2-3 weekly approximately every month across 19distinct rounds of data collection from May 1, 2020 to March 31, 2022.Data Analysis/Dissemination. The data and study materials are widely disseminated via the study website, preprints, publications in peer-reviewed journals and the media. Data tabulations suitably anonymised to protect participant confidentiality are available on request to the study’s Data Access Committee.Implications. The study provided inter alia real-time data on SARS-CoV-2 prevalence over time, by area, and by socio-demographic variables; estimates of vaccine effectiveness; symptom profiles and detected emergence of new variants based on viral genome sequencing.
Lee J-H, Dixey P, Bhavsar P, et al., 2023, Precision Medicine Intervention in Severe Asthma (PRISM) study: molecular phenotyping of patients with severe asthma and response to biologics., ERJ Open Res, Vol: 9, ISSN: 2312-0541
Severe asthma represents an important clinical unmet need despite the introduction of biologic agents. Although advanced omics technologies have aided researchers in identifying clinically relevant molecular pathways, there is a lack of an integrated omics approach in severe asthma particularly in terms of its evolution over time. The collaborative Korea-UK research project Precision Medicine Intervention in Severe Asthma (PRISM) was launched in 2020 with the aim of identifying molecular phenotypes of severe asthma by analysing multi-omics data encompassing genomics, epigenomics, transcriptomics, proteomics, metagenomics and metabolomics. PRISM is a prospective, observational, multicentre study involving patients with severe asthma attending severe asthma clinics in Korea and the UK. Data including patient demographics, inflammatory phenotype, medication, lung function and control status of asthma will be collected along with biological samples (blood, sputum, urine, nasal epithelial cells and exhaled breath condensate) for omics analyses. Follow-up evaluations will be performed at baseline, 1 month, 4-6 months and 10-12 months to assess the stability of phenotype and treatment responses for those patients who have newly begun biologic therapy. Standalone and integrated omics data will be generated from the patient samples at each visit, paired with clinical information. By analysing these data, we will identify the molecular pathways that drive lung function, asthma control status, acute exacerbations and the requirement for daily oral corticosteroids, and that are involved in the therapeutic response to biological therapy. PRISM will establish a large multi-omics dataset of severe asthma to identify potential key pathophysiological pathways of severe asthma.
Rothwell JA, Bešević J, Dimou N, et al., 2023, Circulating amino acid levels and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition and UK Biobank cohorts, BMC Medicine, Vol: 21, Pages: 1-13, ISSN: 1741-7015
BACKGROUND: Amino acid metabolism is dysregulated in colorectal cancer patients; however, it is not clear whether pre-diagnostic levels of amino acids are associated with subsequent risk of colorectal cancer. We investigated circulating levels of amino acids in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts. METHODS: Concentrations of 13-21 amino acids were determined in baseline fasting plasma or serum samples in 654 incident colorectal cancer cases and 654 matched controls in EPIC. Amino acids associated with colorectal cancer risk following adjustment for the false discovery rate (FDR) were then tested for associations in the UK Biobank, for which measurements of 9 amino acids were available in 111,323 participants, of which 1221 were incident colorectal cancer cases. RESULTS: Histidine levels were inversely associated with colorectal cancer risk in EPIC (odds ratio [OR] 0.80 per standard deviation [SD], 95% confidence interval [CI] 0.69-0.92, FDR P-value=0.03) and in UK Biobank (HR 0.93 per SD, 95% CI 0.87-0.99, P-value=0.03). Glutamine levels were borderline inversely associated with colorectal cancer risk in EPIC (OR 0.85 per SD, 95% CI 0.75-0.97, FDR P-value=0.08) and similarly in UK Biobank (HR 0.95, 95% CI 0.89-1.01, P=0.09) In both cohorts, associations changed only minimally when cases diagnosed within 2 or 5 years of follow-up were excluded. CONCLUSIONS: Higher circulating levels of histidine were associated with a lower risk of colorectal cancer in two large prospective cohorts. Further research to ascertain the role of histidine metabolism and potentially that of glutamine in colorectal cancer development is warranted.
Bortz J, Guariglia A, Klaric L, et al., 2023, Biological Age Estimation Using Circulating Blood Biomarkers
<jats:title>ABSTRACT</jats:title><jats:p>Biological Age (BA) captures physiological deterioration better than chronological age and is amenable to interventions. Blood-based biomarkers have been identified as suitable candidates for BA estimation. This study aims to improve BA estimation using machine learning models and a feature-set of 60 circulating biomarkers available from the UK Biobank (UKBB) (n = 307,000). We implement an Elastic-Net derived Cox model with 25 selected biomarkers to predict mortality risk, which outperforms the well-known blood-biomarker based PhenoAge model, providing a 9.2% relative increase in predictive value. Importantly, we then show that using common clinical assay panels, with few biomarkers, alongside imputation and the model derived on the full set of biomarkers, does not substantially degrade predictive accuracy from the theoretical maximum achievable for the available biomarkers. BA is estimated as the equivalent age within the same-sex population which corresponds to an individual’s mortality risk. Values ranged between 20-years younger and 20-years older than individuals’ chronological age, exposing the magnitude of ageing signals contained in blood markers. Thus, we demonstrate a practical and cost-efficient method of estimating an improved measure of BA, available to the general population.</jats:p>
Brewer HR, Hirst Y, Chadeau-Hyam M, et al., 2023, Association between purchase of over-the-counter medications and ovarian cancer diagnosis in the Cancer Loyalty Card Study (CLOCS): observational case-control study, JMIR Public Health and Surveillance, Vol: 9, ISSN: 2369-2960
BACKGROUND: Over-the-counter (OTC) medications are frequently used to self-care for nonspecific ovarian cancer symptoms prior to diagnosis. Monitoring such purchases may provide an opportunity for earlier diagnosis. OBJECTIVE: The aim of the Cancer Loyalty Card Study (CLOCS) was to investigate purchases of OTC pain and indigestion medications prior to ovarian cancer diagnosis in women with and without ovarian cancer in the United Kingdom using loyalty card data. METHODS: An observational case-control study was performed comparing purchases of OTC pain and indigestion medications prior to diagnosis in women with (n=153) and without (n=120) ovarian cancer using loyalty card data from two UK-based high street retailers. Monthly purchases of pain and indigestion medications for cases and controls were compared using the Fisher exact test, conditional logistic regression, and receiver operating characteristic (ROC) curve analysis. RESULTS: Pain and indigestion medication purchases were increased among cases 8 months before diagnosis, with maximum discrimination between cases and controls 8 months before diagnosis (Fisher exact odds ratio [OR] 2.9, 95% CI 2.1-4.1). An increase in indigestion medication purchases was detected up to 9 months before diagnosis (adjusted conditional logistic regression OR 1.38, 95% CI 1.04-1.83). The ROC analysis for indigestion medication purchases showed a maximum area under the curve (AUC) at 13 months before diagnosis (AUC=0.65, 95% CI 0.57-0.73), which further improved when stratified to late-stage ovarian cancer (AUC=0.68, 95% CI 0.59-0.78). CONCLUSIONS: There is a difference in purchases of pain and indigestion medications among women with and without ovarian cancer up to 8 months before diagnosis. Facilitating earlier presentation among those who self-care for symptoms using this novel data source could improve ovarian cancer patients' options for treatment and improve survival. TRIAL REGISTRATION: ClinicalTrials.gov NCT03994653; https
Garmendia AT, Gkouzionis I, Triantafyllidis CP, et al., 2023, Towards personalised early prediction of Intra-Operative Hypotension following anesthesia using Deep Learning and phenotypic heterogeneity
<jats:title>Abstract</jats:title><jats:p>Intra-Operative Hypotension (IOH) is a haemodynamic abnormality that is commonly observed in operating theatres following general anesthesia and associates with life-threatening post-operative complications. Using Long Short Term Memory (LSTM) models applied to Electronic Health Records (EHR) and time-series intra-operative data in 604 patients that underwent colorectal surgery we predicted the instant risk of IOH events within the next five minutes. K-means clustering was used to group patients based on pre-clinical data. As part of a sensitivity analysis, the model was also trained on patients clustered according to Mean artelial Blood Pressure (MBP) time-series trends at the start of the operation using K-means with Dynamic Time Warping. The baseline LSTM model trained on all patients yielded a test set Area Under the Curve (AUC) value of 0.83. In contrast, training the model on smaller sized clusters (grouped by EHR) improved the AUC value (0.85). Similarly, the AUC was increased by 4.8% (0.87) when training the model on clusters grouped by MBP. The encouraging results of the baseline model demonstrate the applicability of the approach in a clinical setting. Furthermore, the increased predictive performance of the model after being trained using a clustering approach first, paves the way for a more personalised patient stratification approach to IOH prediction using clinical data.</jats:p>
Elliott J, Bodinier B, Whitaker M, et al., 2023, Improving cardiovascular risk prediction beyond pooled cohort equations: a prospective cohort of 304,356 participants
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Pooled Cohort Equations (PCE) are used to predict cardiovascular disease (CVD) risk. Inclusion of other variables may improve risk prediction.</jats:p></jats:sec><jats:sec><jats:title>Objective</jats:title><jats:p>Identify variables improving CVD risk prediction beyond recalibrated PCE.</jats:p></jats:sec><jats:sec><jats:title>Design</jats:title><jats:p>Prospective cohort study; sex-stratified Cox survival models with LASSO stability selection to predict CVD in non-overlapping subsets: variable selection (40%), model training (30%) and testing (30%).</jats:p></jats:sec><jats:sec><jats:title>Setting</jats:title><jats:p>UK population.</jats:p></jats:sec><jats:sec><jats:title>Participants</jats:title><jats:p>UK Biobank: 121,724 and 182,632 healthy men and women, respectively, aged 38-73 years at baseline.</jats:p></jats:sec><jats:sec><jats:title>Measurements</jats:title><jats:p>Personal/family medical history; lifestyle factors; genetic, biochemical, hematological, and metabolomic blood markers. Outcomes were incident hospitalization or mortality from CVD.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>There were 11,899 (men) and 9,110 (women) incident CVD cases with median 12.1 years follow-up. Variables selected for both men and women were: age, albumin, antihypertensive medication, apolipoprotein B, atrial fibrillation, C-reactive protein, current smoker, cystatin C, family history of coronary artery disease, glycated hemoglobin, polygenic risk score (PRS) for CVD and systolic blood pressure. Also selected: apolipoprotein A1, lipoprotein(a), white blood cell count, deprivation index (men); triglycerides (women).
Petrovic D, Carmeli C, Sandoval JL, et al., 2023, Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study, Psychoneuroendocrinology, Vol: 147, Pages: 1-10, ISSN: 0306-4530
Adverse socioeconomic circumstances negatively affect the functioning of biological systems, but the underlying mechanisms remain only partially understood. Here, we explore the associations between life-course socioeconomic factors and four markers of epigenetic aging in a population-based setting.We included 684 participants (52 % women, mean age 52.6 ± 15.5 years) from a population and family-based Swiss study. We used nine life-course socioeconomic indicators as the main exposure variables, and four blood-derived, second generation markers of epigenetic aging as the outcome variables (Levine’s DNAmPhenoAge, DunedinPoAm38, GrimAge epigenetic age acceleration (EAA), and the mortality risk score (MS)). First, we investigated the associations between socioeconomic indicators and markers of epigenetic aging via mixed-effect linear regression models, adjusting for age, sex, participant’s recruitment center, familial structure (random-effect covariate), seasonality of blood sampling, and technical covariates. Second, we implemented counterfactual mediation analysis to investigate life-course and intermediate mechanisms underlying the socioeconomic gradient in epigenetic aging. Effect-size estimates were assessed using regression coefficients and counterfactual mediation parameters, along with their respective 95 % confidence intervals.Individuals reporting a low father’s occupation, adverse financial conditions in childhood, a low income, having financial difficulties, or experiencing unfavorable socioeconomic trajectories were epigenetically older and had a higher mortality risk score than their more advantaged counterparts. Specifically, this corresponded to an average increase of 1.1–1.5 years for Levine’s epigenetic age (β and 95 %CI range, β (minimum and maximum): 1.1–1.5 95 %CI[0.0–0.2; 2.3–3.0]), 1.1–1.5 additional years for GrimAge (β: 1.1–1.5 95 %CI[0.2–0.6; 1.9–3.0])
Whitaker M, Elliott J, Bodinier B, et al., 2022, Variant-specific symptoms of COVID-19 in a study of 1,542,510 adults in England, Nature Communications, Vol: 13, Pages: 1-10, ISSN: 2041-1723
Infection with SARS-CoV-2 virus is associated with a wide range of symptoms. The REal-time Assessment of Community Transmission -1 (REACT-1) study monitored the spread and clinical manifestation of SARS-CoV-2 among random samples of the population in England from 1 May 2020 to 31 March 2022. We show changing symptom profiles associated with the different variants over that period, with lower reporting of loss of sense of smell or taste for Omicron compared to previous variants, and higher reporting of cold-like and influenza-like symptoms, controlling for vaccination status. Contrary to the perception that recent variants have become successively milder, Omicron BA.2 was associated with reporting more symptoms, with greater disruption to daily activities, than BA.1. With restrictions lifted and routine testing limited in many countries, monitoring the changing symptom profiles associated with SARS-CoV-2 infection and effects on daily activities will become increasingly important.
Chadeau-Hyam M, Tang D, Eales O, et al., 2022, Omicron SARS-CoV-2 epidemic in England during February 2022: A series of cross-sectional community surveys, The Lancet Regional Health Europe, Vol: 21, Pages: 1-11, ISSN: 2666-7762
BackgroundThe Omicron wave of COVID-19 in England peaked in January 2022 resulting from the rapid transmission of the Omicron BA.1 variant. We investigate the spread and dynamics of the SARS-CoV-2 epidemic in the population of England during February 2022, by region, age and main SARS-CoV-2 sub-lineage.MethodsIn the REal-time Assessment of Community Transmission-1 (REACT-1) study we obtained data from a random sample of 94,950 participants with valid throat and nose swab results by RT-PCR during round 18 (8 February to 1 March 2022).FindingsWe estimated a weighted mean SARS-CoV-2 prevalence of 2.88% (95% credible interval [CrI] 2.76–3.00), with a within-round effective reproduction number (R) overall of 0.94 (0·91–0.96). While within-round weighted prevalence fell among children (aged 5 to 17 years) and adults aged 18 to 54 years, we observed a level or increasing weighted prevalence among those aged 55 years and older with an R of 1.04 (1.00–1.09). Among 1,616 positive samples with sublineages determined, one (0.1% [0.0–0.3]) corresponded to XE BA.1/BA.2 recombinant and the remainder were Omicron: N=1047, 64.8% (62.4–67.2) were BA.1; N=568, 35.2% (32.8–37.6) were BA.2. We estimated an R additive advantage for BA.2 (vs BA.1) of 0.38 (0.34–0.41). The highest proportion of BA.2 among positives was found in London.InterpretationIn February 2022, infection prevalence in England remained high with level or increasing rates of infection in older people and an uptick in hospitalisations. Ongoing surveillance of both survey and hospitalisations data is required.FundingDepartment of Health and Social Care, England.
Vlaanderen J, Vermeulen R, Whitaker M, et al., 2022, Impact of long-term exposure to PM2.5 on peripheral blood gene expression pathways involved in cell signaling and immune response, Environment International, Vol: 168, ISSN: 0160-4120
Background:Exposure to ambient air pollution, even at low levels, is a major environmental health risk. The peripheral blood transcriptome provides a potential avenue for the elucidation of ambient air pollution related biological perturbations. We assessed the association between long-term estimates for seven priority air pollutants and perturbations in peripheral blood transcriptomics data collected in the Dutch National Twin Register (NTR) and Netherlands Study of Depression and Anxiety (NESDA) cohorts.Methods:In both the discovery (n = 2438) and replication (n = 1567) cohort, outdoor concentration of 7 air pollutants (NO2, NOx, particulate matter (PM2.5, PM2.5abs, PM10, PMcoarse), and ultrafine particles) was predicted with land use regression models. Gene expression was assessed by Affymetrix U219 arrays. Multi-variable univariate mixed-effect models were applied to test for an association between the air pollutants and the transcriptome. Functional analysis was conducted in DAVID.Results:In the discovery cohort, we observed for 335 genes (374 probes with FDR < 5 %) a perturbation in peripheral blood gene expression that was associated with long-term average levels of PM2.5. For 69 genes pooled effect estimates from the NTR and NESDA cohorts were significant. Identified genes play a role in biological pathways related to cell signaling and immune response. Sixty-two out of 69 genes had a similar direction of effect in an analysis in which we regressed the probes on differential PM2.5 exposure within monozygotic twin pairs, indicating that the observed differences in gene expression were likely driven by differences in air pollution, rather than by confounding by genetic factors.Conclusion:Our results indicate that PM2.5 can elicit a response in cell signaling and the immune system, both hallmarks of environmental diseases. The differential effect that we observed between air pollutants may aid in the understanding of differential health effects that have bee
Gruzieva O, Jeong A, Yu Z, et al., 2022, Air pollution, metabolites and respiratory health across the life-course, European Respiratory Review, Vol: 31, ISSN: 0905-9180
Previous studies have explored relationships of air pollution and metabolic profiles with lung function. However, the metabolites linking air pollution and lung function and associated mechanisms have not been reviewed from a life-course perspective. Here we provide a narrative review summarizing recent evidence on the associations of metabolic profiles with both air pollution exposure and lung function in both children and adults. Twenty-six studies identified through a systematic PubMed search were included with 10 studies analyzing air pollution-related metabolic profiles, and 16 analyzing lung function-related metabolic profiles. A wide range of metabolites were identified being associated with short- and long-term exposure, partly overlapping with those linked to lung function in the general populationand respiratory diseases such as asthma and COPD. The existing studies show that metabolomics offers potential to identify biomarkers linked to both environmental exposures and respiratory outcomes, but many suffer from small sample size, cross-sectional designs, preponderance on adult lung function, heterogeneity in exposure assessment, lack of confounding control and omics integration. The ongoing EXposome Powered tools forhealthy living in urbAN Settings (EXPANSE) project aims at addressing some of these shortcomings by combining biospecimens from large European cohorts, and harmonized air pollution exposure and exposome data.
Maitre L, Guimbaud J-B, Warembourg C, et al., 2022, State-of-the-art methods for exposure-health studies: results from the exposome data challenge event, Environment International, Vol: 168, ISSN: 0160-4120
The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological factors for disease. However, challenges arise when trying to quantify the health effects of complex exposure mixtures. Analytical challenges include dealing with high dimensionality, studying the combined effects of these exposures and their interactions, integrating causal pathways, and integrating high-throughput omics layers. To tackle these challenges, the Barcelona Institute for Global Health (ISGlobal) held a data challenge event open to researchers from all over the world and from all expertises. Analysts had a chance to compete and apply state-of-the-art methods on a common partially simulated exposome dataset (based on real case data from the HELIX project) with multiple correlated exposure variables (P>100 exposure variables) arising from general and personal environments at different time points, biological molecular data (multi-omics: DNA methylation, gene expression, proteins, metabolomics) and multiple clinical phenotypes in 1301 mother-child pairs. Most of the methods presented included feature selection or feature reduction to deal with the high dimensionality of the exposome dataset. Several approaches explicitly searched for combined effects of exposures and/or their interactions using linear index models or response surface methods, including Bayesian methods. Other methods dealt with the multi-omics dataset in mediation analyses using multiple-step approaches. Here we discuss features of the statistical models used and provide the data and codes used, so that analysts have examples of implementation and can learn how to use these methods. Overall, the exposome data challenge presented a unique opportunity for researchers from different disciplines to create and share state-of-the-art analytical methods, setting a new standard for open science in the exposome and env
Elliott P, Eales O, Bodinier B, et al., 2022, Dynamics of a national Omicron SARS-CoV-2 epidemic during January 2022 in England, Nature Communications, Vol: 13, ISSN: 2041-1723
Rapid transmission of the SARS-CoV-2 Omicron variant has led to record-breaking case incidence rates around the world. Since May 2020, the REal-time Assessment of Community Transmission-1 (REACT-1) study tracked the spread of SARS-CoV-2 infection in England through RT-PCR of self-administered throat and nose swabs from randomly-selected participants aged 5 years and over. In January 2022, we found an overall weighted prevalence of 4.41% (n=102,174), three-fold higher than in November to December 2021; we sequenced 2,374 (99.2%) Omicron infections (19 BA.2), and only 19 (0.79%) Delta, with a growth rate advantage for BA.2 compared to BA.1 or BA.1.1. Prevalence was decreasing overall (reproduction number R=0.95, 95% credible interval [CrI], 0.93, 0.97), but increasing in children aged 5 to 17 years (R=1.13, 95% CrI, 1.09, 1.18). In England during January 2022, we observed unprecedented levels of SARS-CoV-2 infection, especially among children, driven by almost complete replacement of Delta by Omicron.
Eales O, Martins LDO, Page AJ, et al., 2022, Dynamics of competing SARS-CoV-2 variants during the Omicron epidemic in England, Nature Communications, Vol: 13, ISSN: 2041-1723
The SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant (first detected in November 2021) exhibited a high degree of immune evasion, leading to increased infection rates worldwide. However, estimates of the magnitude of this Omicron wave have often relied on routine testing data, which are prone to several biases. Using data from the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys assessing prevalence of SARS-CoV-2 infection in England, we estimated the dynamics of England’s Omicron wave (from 9 September 2021 to 1 March 2022). We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct variants, intermittent epidemics of similar magnitudes may become the ‘new normal’.
Eales O, Wang H, Bodinier B, et al., 2022, SARS-CoV-2 lineage dynamics in England from September to November 2021: high diversity of Delta sub-lineages and increased transmissibility of AY.4.2, BMC Infectious Diseases, Vol: 22, ISSN: 1471-2334
Background: Since the emergence of SARS-CoV-2, evolutionary pressure has driven large increases in the transmissibility of the virus. However, with increasing levels of immunity through vaccination and natural infection the evolutionary pressure will switch towards immune escape. Genomic surveillance in regions of high immunity is crucial in detecting emerging variants that can more successfully navigate the immune landscape. Methods: We present phylogenetic relationships and lineage dynamics within England (a country with high levels of immunity), as inferred from a random community sample of individuals who provided a self-administered throat and nose swab for rt-PCR testing as part of the REal-time Assessment of Community Transmission-1 (REACT-1) study. During round 14 (9 September - 27 September 2021) and 15 (19 October - 5 November 2021) lineages were determined for 1322 positive individuals, with 27.1% of those which reported their symptom status reporting no symptoms in the previous month.Results: We identified 44 unique lineages, all of which were Delta or Delta sub-lineages, and found a reduction in their mutation rate over the study period. The proportion of the Delta sub-lineage AY.4.2 was increasing, with a reproduction number 15% (95% CI, 8%-23%) greater than the most prevalent lineage, AY.4. Further, AY.4.2 was less associated with the most predictive COVID-19 symptoms (p = 0.029) and had a reduced mutation rate (p = 0.050). Both AY.4.2 and AY.4 were found to be geographically clustered in September but this was no longer the case by late October/early November, with only the lineage AY.6 exhibiting clustering towards the South of England.Conclusions: As SARS-CoV-2 moves towards endemicity and new variants emerge, genomic data obtained from random community samples can augment routine surveillance data without the potential biases introduced due to higher sampling rates of symptomatic individuals.
Said S, Pazoki R, Karhunen V, et al., 2022, Genetic analysis of over half a million people characterises C-reactive protein loci (vol 13, 2198, 2022), Nature Communications, Vol: 13, Pages: 1-1, ISSN: 2041-1723
Elliott P, Eales O, Steyn N, et al., 2022, Twin peaks: The Omicron SARS-CoV-2 BA.1 and BA.2 epidemics in England., Science, Vol: 376
Rapid transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant has led to record-breaking incidence rates around the world. The Real-time Assessment of Community Transmission-1 (REACT-1) study has tracked SARS-CoV-2 infection in England using reverse transcription polymerase chain reaction (RT-PCR) results from self-administered throat and nose swabs from randomly selected participants aged 5 years and older approximately monthly from May 2020 to March 2022. Weighted prevalence in March 2022 was the highest recorded in REACT-1 at 6.37% (N = 109,181), with the Omicron BA.2 variant largely replacing the BA.1 variant. Prevalence was increasing overall, with the greatest increase in those aged 65 to 74 years and 75 years and older. This was associated with increased hospitalizations and deaths, but at much lower levels than in previous waves against a backdrop of high levels of vaccination.
Petrovic D, Carmeli C, Sandoval JL, et al., 2022, Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study
<jats:title>Abstract</jats:title><jats:p>Adverse socioeconomic circumstances negatively affect the functioning of biological systems, but the underlying mechanisms remain only partially understood. Here, we explore the associations between life-course socioeconomic factors and four markers of epigenetic aging in a population-based setting.</jats:p><jats:p>We used data from a population-based study conducted in Switzerland (SKIPOGH) to assess the association between childhood, adulthood, and life-course socioeconomic indicators, and blood-derived markers of epigenetic aging (Levine’s, DunedinPoAm38, GrimAge epigenetic age acceleration (EAA) and the mortality risk score (MS)). We used mixed regression to explore the associations between socioeconomic indicators and markers of epigenetic aging independently, and counterfactual mediation to investigate the mechanisms underlying the life-course socioeconomic gradient in epigenetic aging.</jats:p><jats:p>Individuals reporting a low father’s occupation, adverse financial conditions in childhood, a low income, having financial difficulties, or experiencing unfavorable socioeconomic trajectories were epigenetically older than their more advantaged counterparts. Specifically, this corresponded to an average increase of 1.0-1.5 years for Levine’s epigenetic age when compared to chronological age, 1.1-1.5 additional years for GrimAge, 5%-8% higher DunedinPoAm38 EAA, and 2%-5% higher MS score. By exploring the life-course mechanisms underlying the socioeconomic gradient in epigenetic aging, we found that both childhood and adulthood socioeconomic factors contributed to epigenetic aging, and that detrimental lifestyle factors mediated the relation between socioeconomic circumstances in adulthood and EAA.</jats:p><jats:p>Our study provides novel empirical evidence for a “sensitive-period” life-course model, whereby adverse socioeconomic circumstanc
Chadeau M, Eales O, Bodinier B, et al., 2022, Breakthrough SARS-CoV-2 infections in double and triple vaccinated adults and single dose vaccine effectiveness among children in Autumn 2021 in England: REACT-1 study, EClinicalMedicine, Vol: 48, Pages: 1-14, ISSN: 2589-5370
Background: Prevalence of SARS-CoV-2 infection with Delta variant was increasing in England in late summer 2021 among children aged 5 to 17 years, and adults who had received two vaccine doses. In September 2021, a third (booster) dose was offered to vaccinated adults aged 50 years and over, vulnerable adults and healthcare/care-home workers, and a single vaccine dose already offered to 16 and 17 year-olds was extended to children aged 12 to 15 years. Methods: SARS-CoV-2 community prevalence in England was available from self-administered throat and nose swabs using reverse transcriptase polymerase chain reaction (RT-PCR) in round 13 (24 June to 12 July 2021, N= 98,233), round 14 (9 to 27 September 2021, N = 100,527) and round 15 (19 October to 5 November 2021, N = 100,112) from the REACT-1 study randomised community surveys. Linking to National Health Service (NHS) vaccination data for consenting participants, we estimated vaccine effectiveness in children aged 12 to 17 years and compared swab-positivity rates in adults who received a third dose with those who received two doses. Findings: Weighted SARS-CoV-2 prevalence was 1.57% (1.48%, 1.66%) in round 15 compared with 0.83% (0.76%, 0.89%) in round 14, and the previously observed link between infections and hospitalisations and deaths had weakened. Vaccine effectiveness against infection in children aged 12 to 17 years was estimated (round 15) at 64.0% (50.9%, 70.6%) and 67.7% (53.8%, 77.5%) for symptomatic infections. Adults who received a third vaccine dose were less likely to test positive compared to those who received two doses, with adjusted odds ratio of 0.36 (0.25, 0.53). Interpretation: Vaccination of children aged 12 to 17 years and third (booster) doses in adults were effective at reducing infection risk. High rates of vaccination, including booster doses, are a key part of the strategy to reduce infection rates in the community.
Tayal U, 2022, Exposure to elevated nitrogen dioxide concentrations and cardiac remodelling in patients with dilated cardiomyopathy, Journal of Cardiac Failure, Vol: 28, Pages: 924-934, ISSN: 1071-9164
Rationale: Empirical evidence suggests a strong link between exposure to air pollution and heart failure incidence, hospitalisations and mortality, but the biological basis of this remains unclear. Objective: To determine the relationship between differential air pollution levels and changes in cardiac structure and function in patients with dilated cardiomyopathy. Methods and Results: We undertook a prospective longitudinal observational cohort study of patients in England with dilated cardiomyopathy (enrollment 2009-2015; n=716, 66% male, 85% Caucasian) and conducted cross sectional analysis at the time of study enrollment. Annual average air pollution exposure estimates for nitrogen dioxide (NO2) and particulate matter with diameter ≤ 2.5µm (PM2.5) at enrolment were assigned to each residential postcode (on average 12 households). The relationship between air pollution and cardiac morphology was assessed using linear regression modelling. Greater ambient exposure to NO2 was associated with higher indexed left ventricular mass (4.3 g/m2 increase per interquartile range (IQR) increase in NO2, 95% CI 1.9 to 7.0 g/m2) and lower left ventricular ejection fraction (-1.5% decrease per IQR increase in NO2, 95% CI -2.7 to -0.2%), independent of age, sex, socio-economic status and clinical covariates. The associations were robust to adjustment for smoking status and geographical clustering by postcode area. The effect of air pollution on left ventricular mass was greatest in women. These effects were specific to NO2 exposure. Conclusion: Exposure to air pollution is associated with raised left ventricular mass and lower left ventricular ejection fraction, with the strongest effect in women. Whilst epidemiological associations between air pollution and heart failure have been established and supported by pre-clinical studies, our findings provide novel empirical evidence of cardiac remodelling and exposure to air pollution with important clinical and public health
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