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Increasing evidence points to a role for inflammation in lung carcinogenesis. A small number of circulating inflammatory proteins have been identified as showing elevated levels prior to lung cancer diagnosis, indicating the potential for prospective circulating protein concentration as a marker of early carcinogenesis. To identify novel markers of lung cancer risk, we measured a panel of 92 circulating inflammatory proteins in 648 prediagnostic blood samples from two prospective cohorts in Italy and Norway (women only). To preserve the comparability of results and protect against confounding factors, the main statistical analyses were conducted in women from both studies, with replication sought in men (Italian participants). Univariate and penalized regression models revealed for the first time higher blood levels of CDCP1 protein in cases that went on to develop lung cancer compared with controls, irrespective of time to diagnosis, smoking habits, and gender. This association was validated in an additional 450 samples. Associations were stronger for future cases of adenocarcinoma where CDCP1 showed better explanatory performance. Integrative analyses combining gene expression and protein levels of CDCP1 measured in the same individuals suggested a link between CDCP1 and the expression of transcripts of LRRN3 and SEM1. Enrichment analyses indicated a potential role for CDCP1 in pathways related to cell adhesion and mobility, such as the WNT/β-catenin pathway. Overall, this study identifies lung cancer–related dysregulation of CDCP1 expression years before diagnosis.Significance:Prospective proteomics analyses reveal an association between increased levels of circulating CDCP1 and lung carcinogenesis irrespective of smoking and years before diagnosis, and integrating gene expression indicates potential underlying mechanisms.See related commentary by Itzstein et al., p. 3441.

Supplementary Methods, Figures and Tables.

BackgroundPooled Cohort Equations (PCE) are used to predict cardiovascular disease (CVD) risk. Inclusion of other variables may improve risk prediction.ObjectiveIdentify variables improving CVD risk prediction beyond recalibrated PCE.DesignProspective 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%).SettingUK population.ParticipantsUK Biobank: 121,724 and 182,632 healthy men and women, respectively, aged 38-73 years at baseline.MeasurementsPersonal/family medical history; lifestyle factors; genetic, biochemical, hematological, and metabolomic blood markers. Outcomes were incident hospitalization or mortality from CVD.ResultsThere 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). C-statistics for recalibrated PCE were 0.67 [0.66-0.68] and 0.69 [0.68-0.70] in men and women, respectively, improving to 0.71 [0.70-0.72] and 0.72 [0.71-0.73] with LASSO stably selected variables. Categorical net reclassification improvement (7.5% risk threshold) versus PCE was 0.054 [0.038-0.070] (men) and 0.081 [0.063-0.099] (women). Addition of targeted metabolomic data to LASSO stability selection did not improve predictive accuracy.LimitationsAnalyses were done in a single population study and require external replication.ConclusionAdditional personal/family medical history, blood-based markers and genetic information improve CVD risk prediction beyond PCE.Funding sourceNational Institute for Health Research Academic Clinical Fellowship (JE); Medical Research Council studentship (BB); European Union H2020 (MC-H).

ImportanceHigher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, which of these associations are causal remains unclear.ObjectiveTo explore the relation of maternal pre-pregnancy BMI with pregnancy and perinatal outcomes by integrating evidence from three different methods (i.e. multivariable regression, Mendelian randomization, and paternal negative control analyses).DesignTriangulation of multivariable regression, Mendelian randomization and paternal negative control results from up to 14 studies in the MR-PREG collaboration.SettingEurope and North America.ParticipantsUp to 497,932 women of European ancestry.ExposureMaternal pre- or early-pregnancy BMI based on self-reported or measured weight and height.Main outcomes and MeasuresMiscarriage, stillbirth, hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, maternal anaemia, perinatal depression, pre-labour rupture of membranes, induction of labour, caesarean section, preterm birth, small- and large-for-gestational age, low and high birthweight, low Apgar score at 1 and 5 minutes, neonatal intensive care unit admission, and no initiation of breastfeeding.ResultsMultivariable regression, Mendelian randomization and paternal negative control analyses supported an association of higher maternal BMI with lower risk of small-for-gestational age and higher risk of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, large-for-gestational age, and high birthweight. As an example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR: 1.67; 95% CI: 1.64, 1.71 per standard unit in BMI) and Mendelian randomization (OR: 1.58; 95% CI: 1.29, 1.93), which was not seen for paternal BMI (OR: 1.02; 95% CI: 0.99, 1.05). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomization.Conclusions and RelevanceOur findings support a causal role for maternal pre-/early-pregnancy BMI on a range of adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications.KEY POINTSQuestionWhat is the effect of higher maternal pre-/early-pregnancy body mass index (BMI) on adverse pregnancy and perinatal outcomes?FindingsWe found consistent evidence that higher maternal BMI was related to higher risk of gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, and having a large-for-gestational-age baby, lower risk of having a small-for-gestational-age baby, and not related to perinatal depression.MeaningThese findings highlight the importance of supporting women to achieve/maintain a healthy pre-conception BMI to reduce the burden of obstetric and neonatal complications.

Background Most uterine cervical high-risk human papillomavirus (HPV) infections are transient, with only a small fraction developing into cervical cancer. Family aggregation studies and heritability estimates suggest a significant inherited genetic component. Candidate gene studies and previous genome-wide association studies (GWASs) report associations between the HLA region and cervical cancer. Adopting a genome-wide approach, we aimed to compare genetic variation in women with invasive cervical cancer and cervical intraepithelial neoplasia (CIN) grade 3 with that in healthy controls. Methods We did a GWAS in a cohort of unrelated European individuals using data from UK Biobank, a population-based cohort including 273 377 women aged 40-69 years at recruitment between March 13, 2006, and Oct 1, 2010. We used an additive univariate logistic regression model to analyse genetic variants associated with invasive cervical cancer or CIN3. We sought replication of candidate associations in FinnGen, a large independent dataset of 128 123 individuals. We also did a two-sample mendelian randomisation approach to explore the role of risk factors in the genetic risk of cervical cancer. Findings We included 4769 CIN3 and invasive cervical cancer case samples and 145 545 control samples in the GWAS. Of 9 600 464 assayed and imputed single-nucleotide polymorphisms (SNPs), six independent variants were associated with CIN3 and invasive cervical cancer. These included novel loci rs10175462 (PAX8; odds ratio [OR] 0.87, 95% CI 0.84-0.91; p=1.07 x 10(-9)) and rs27069 (CLPTM1L; 0.88, 0.84-0.92; p=2.51 x 10(-9)), and previously reported signals at rs9272050 (HLA-DQA1; 1.27, 1.21-1.32; p=2.51 x 10(-28)), rs6938453 (MICA; 0.79, 0.75-0 .83; p=1.97 x 10-(17)), rs55986091 (HLA-DQB1; 0.66, 0 .60-0.72; p=6.42 x 10-(22)), and rs9266183 (HLA-B; 0.73, 0.64-0.83; p=1.53 x 10(-6)). Three SNPs were replicated in the independent Finnish dataset of 1648 invasive cervical cancer cases: PAX8 (rs10175462; p=0.015), CLPTM1L (rs27069; p=2.54 x 10(-7)), and HLA-DQA1 (rs9272050; p=7.90 x 10(-8)). Mendelian randomisation further supported the complementary role of smoking (OR 2.46, 95% CI 1.64-3.69), older age at first pregnancy (0.80, 0.68-0.95), and number of sexual partners (1.95, 1.44-2.63) in the risk of developing cervical cancer. Interpretation Our results provide new evidence for the genetic susceptibility to cervical cancer, specifically the PAX8, CLPTM1L, and HLA genes, suggesting disruption in apoptotic and immune function pathways. Future studies integrating host and viral, genetic, and epigenetic variation, could further elucidate complex host-viral interactions. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

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 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.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.Our study provides novel empirical evidence for a “sensitive-period” life-course model, whereby adverse socioeconomic circumstances in childhood and adulthood negatively affected epigenetic aging. Counterfactual mediation analyses further showed that the effect of socioeconomic factors in adulthood operated through detrimental lifestyle factors, whereas associations involving early-life socioeconomic factors were less clear.

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 has been monitoring 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 and 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 induced changes in daily activities will become increasingly important.

SummaryThe SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants which have led to substantial changes in the epidemiology of the virus. 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 was first detected in late November 2021 and exhibited a high degree of immune evasion, leading to increased infection rates in many countries. However, estimates of the magnitude of the Omicron wave have relied mainly on routine testing data, which are prone to several biases. Here we infer the dynamics of the Omicron wave in England using PCR testing and genomic sequencing obtained by the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys testing random samples of the population of England. 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 in England during February-March 2022 as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct genomic variants, intermittent epidemics of similar magnitude as the Omicron wave may become the ‘new normal’.

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]), a 1-3 % higher DunedinPoAm38 age acceleration (β: 0.01-0.03 95 %CI[0.00; 0.03-0.04]), and a 10-50 % higher MS score (β: 0.1-0.4 95 %CI[0.0-0.2; 0.3-0.4]) for the aforementioned socioeconomic indicators. 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 (31-89 % mediated proportion). This study provides emerging evidence for an association between disadvantaged life-course socioeconomic circumstances and detrimental epigenetic aging patterns, supporting the "sensitive-period" life-course model. Counterfactual mediation analyses further indicated that the effect of socioeconomic factors in adulthood operates through detrimental lifestyle factors, whereas associations involving early-life socioeconomic factors were less clear.

Background: The third wave of COVID-19 in England peaked in January 2022 resulting from the rapid transmission of the Omicron variant. However, rates of hospitalisations and deaths were substantially lower than in the first and second waves Methods: In 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). Findings: We estimated a weighted mean SARS-CoV-2 prevalence of 2.88% (95% credible interval [CrI] 2.76-3.00), with a within-round 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 1,195 positive samples with sublineages determined, only one (0.1% [0.0-0.5]) corresponded to AY.39 Delta sublineage and the remainder were Omicron: N=390, 32.7% (30.0-35.4) were BA.1; N=473, 39.6% (36.8-42.5) were BA.1.1; and N=331, 27.7% (25.2-30.4) were BA.2. We estimated an R additive advantage for BA.2 (vs BA.1 or BA.1.1) of 0.40 (0.36-0.43). The highest proportion of BA.2 among positives was found in London. Interpretation: In 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. Funding: Department of Health and Social Care, England.

BackgroundThe highest-ever recorded numbers of daily severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in England has been observed during December 2021 and have coincided with a rapid rise in the highly transmissible Omicron variant despite high levels of vaccination in the population. Although additional COVID-19 measures have been introduced in England and internationally to contain the epidemic, there remains uncertainty about the spread and severity of Omicron infections among the general population.MethodsThe REal-time Assessment of Community Transmission–1 (REACT-1) study has been monitoring the prevalence of SARS-CoV-2 infection in England since May 2020. REACT-1 obtains self-administered throat and nose swabs from a random sample of the population of England at ages 5 years and over. Swabs are tested for SARS-CoV-2 infection by reverse transcription polymerase chain reaction (RT-PCR) and samples testing positive are sent for viral genome sequencing. To date 16 rounds have been completed, each including ∼100,000 or more participants with data collected over a period of 2 to 3 weeks per month. Socio-demographic, lifestyle and clinical information (including previous history of COVID-19 and symptoms prior to swabbing) is collected by online or telephone questionnaire. Here we report results from round 14 (9-27 September 2021), round 15 (19 October - 05 November 2021) and round 16 (23 November - 14 December 2021) for a total of 297,728 participants with a valid RT-PCR test result, of whom 259,225 (87.1%) consented for linkage to their NHS records including detailed information on vaccination (vaccination status, date). We used these data to estimate community prevalence and trends by age and region, to evaluate vaccine effectiveness against infection in children ages 12 to 17 years, and effect of a third (booster) dose in adults, and to monitor the emergence of the Omicron variant in England.ResultsWe observed a high overall prevalence of 1.41% (1.33%, 1.51%) in the community during round 16. We found strong evidence of an increase in prevalence during round 16 with an estimated reproduction number R of 1.13 (1.06, 1.09) for the whole of round 16 and 1.27 (1.14, 1.40) when restricting to observations from 1 December onwards. The reproduction number in those aged 18-54 years was estimated at 1.23 (1.14, 1.33) for the whole of round 16 and 1.41 (1.23, 1.61) from 1 December. Our data also provide strong evidence of a steep increase in prevalence in London with an estimated R of 1.62 (1.34, 1.93) from 1 December onwards and a daily prevalence reaching 6.07% (4.06%, 9.00%) on 14 December 2021. As of 1 to 11 December 2021, of the 275 lineages determined, 11 (4.0%) corresponded to the Omicron variant. The first Omicron infection was detected in London on 3 December, and subsequent infections mostly appeared in the South of England. The 11 Omicron cases were all aged 18 to 54 years, double-vaccinated (reflecting the large numbers of people who have received two doses of vaccine in this age group) but not boosted, 9 were men, 5 lived in London and 7 were symptomatic (5 with classic COVID-19 symptoms: loss or change of sense of smell or taste, fever, persistent cough), 2 were asymptomatic, and symptoms were unknown for 2 cases. The proportion of Omicron (vs Delta or Delta sub-lineages) was found to increase rapidly with a daily increase of 66.0% (32.7%, 127.3%) in the odds of Omicron (vs. Delta) infection, conditional on swab positivity. Highest prevalence of swab positivity by age was observed in (unvaccinated) children aged 5 to 11 years (4.74% [4.15%, 5.40%]) similar to the prevalence observed at these ages in round 15. In contrast, prevalence in children aged 12 to 17 years more than halved from 5.35% (4.78%, 5.99%) in round 15 to 2.31% (1.91%, 2.80%) in round 16. As of 14 December 2021, 76.6% children at ages 12 to 17 years had received at least one vaccine dose; we estimated that vaccine effectiveness against infection was 57.9% (44.1%, 68.3%) in this age group. In addition, the prevalence of swab positivity in adults aged 65 years and over fell by over 40% from 0.84% (0.72%, 0.99%) in round 15 to 0.48% (0.39%,0.59%) in round 16 and for those aged 75 years and over it fell by two-thirds from 0.63% (0.48%,0.82%) to 0.21% (0.13%,0.32%). At these ages a high proportion of participants (>90%) had received a third vaccine dose; we estimated that adults having received a third vaccine dose had a three- to four-fold lower risk of testing positive compared to those who had received two doses.ConclusionA large fall in swab positivity from round 15 to round 16 among 12 to 17 year olds, most of whom have been vaccinated, contrasts with the continuing high prevalence among 5 to 11 year olds who have largely not been vaccinated. Likewise there were large falls in swab positivity among people aged 65 years and over, the vast majority of whom have had a third (booster) vaccine dose; these results reinforce the importance of the vaccine and booster campaign. However, the rapidly increasing prevalence of SARS-CoV-2 infections in England during December 2021, coincident with the rapid rise of Omicron infections, may lead to renewed pressure on health services. Additional measures beyond vaccination may be needed to control the current wave of infections and prevent health services (in England and other countries) from being overwhelmed.SummaryThe unprecedented rise in SARS-CoV-2 infections is concurrent with rapid spread of the Omicron variant in England and globally. We analysed prevalence of SARS-CoV-2 and its dynamics in England from end of November to mid-December 2021 among almost 100,000 participants from the REACT-1 study. Prevalence was high during December 2021 with rapid growth nationally and in London, and of the proportion of infections due to Omicron. We observed a large fall in swab positivity among mostly vaccinated older children (12-17 years) compared with unvaccinated younger children (5-11 years), and in adults who received a third vs. two doses of vaccine. Our results reiterate the importance of vaccination and booster campaigns; however, additional measures may be needed to control the rapid growth of the Omicron variant.

BackgroundIt has been nearly a year since the first vaccinations against SARS-CoV-2 were delivered in England. The third wave of COVID-19 in England began in May 2021 as the Delta variant began to outcompete and largely replace other strains. The REal-time Assessment of Community Transmission-1 (REACT-1) series of community surveys for SARS-CoV-2 infection has provided insights into transmission dynamics since May 2020. Round 15 of the REACT-1 study was carried out from 19 October to 5 November 2021.MethodsWe estimated prevalence of SARS-CoV2 infection and used multiple logistic regression to analyse associations between SARS-CoV-2 infection in England and demographic and other risk factors, based on RT-PCR results from self-administered throat and nose swabs in over 100,000 participants. We estimated (single-dose) vaccine effectiveness among children aged 12 to 17 years, and among adults compared swab-positivity in people who had received a third (booster) dose with those who had received two vaccine doses. We used splines to analyse time trends in swab-positivity.ResultsDuring mid-October to early-November 2021, weighted prevalence was 1.57% (1.48%, 1.66%) compared to 0.83% (0.76%, 0.89%) in September 2021 (round 14). Weighted prevalence increased between rounds 14 and 15 across most age groups (including older ages, 65 years and over) and regions, with average reproduction number across rounds of R=1.09 (1.08, 1.11). During round 15, there was a fall in prevalence from a maximum around 20-21 October, with an R of 0.76 (0.70, 0.83), reflecting falls in prevalence at ages 17 years and below and 18 to 54 years. School-aged children had the highest weighted prevalence of infection: 4.95% (4.39%, 5.58%) in those aged 5 to 12 years and 5.21% (4.61%, 5.87%) in those aged 13 to 17 years. In multiple logistic regression, age, sex, key worker status and presence of one or more children in the home were associated with swab positivity. There was evidence of heterogeneity between rounds in swab positivity rates among vaccinated individuals at ages 18 to 64 years, and differences in key demographic and other variables between vaccinated and unvaccinated adults at these ages. Vaccine effectiveness against infection in children was estimated to be 56.2% (41.3%, 67.4%) in rounds 13, 14 and 15 combined, adjusted for demographic factors, with a similar estimate obtained for round 15 only. Among adults we found that those who received a third dose of vaccine were less likely to test positive compared to those who received only two vaccine doses, with adjusted odds ratio (OR) =0.38 (0.26, 0.55).DiscussionSwab-positivity was very high at the start of round 15, reaching a maximum around 20 to 21 October 2021, and then falling through late October with an uncertain trend in the last few days of data collection. The observational nature of survey data and the relatively small proportion of unvaccinated adults call into question the comparability of vaccinated and unvaccinated groups at this relatively late stage in the vaccination programme. However, third vaccine doses for eligible adults and the vaccination of children aged 12 years and over are associated with lower infection risk and, thus, remain a high priority (with possible extension to children aged 5-12 years). These should help reduce SARS-CoV-2 transmission during the winter period when healthcare demands typically rise.

BackgroundThe third wave of COVID-19 in England coincided with the rapid spread of the Delta variant of SARS-CoV-2 from the end of May 2021. Case incidence data from the national testing programme (Pillar 2) in England may be affected by changes in testing behaviour and other biases. Community surveys may provide important contextual information to inform policy and the public health response.MethodsWe estimated patterns of community prevalence of SARS-CoV-2 infection in England using RT-PCR swab-positivity, demographic and other risk factor data from round 15 (interim) of the REal-time Assessment of Community Transmission-1 (REACT-1) study (round 15a, carried out from 19 to 29 October 2021). We compared these findings with those from round 14 (9 to 27 September 2021).ResultsDuring mid- to late-October 2021 (round 15a) weighted prevalence was 1.72% (1.61%, 1.84%) compared to 0.83% (0.76%, 0.89%) in September 2021 (round 14). The overall reproduction number (R) from round 14 to round 15a was 1.12 (1.11, 1.14) with increases in prevalence over this period (September to October) across age groups and regions except Yorkshire and The Humber. However, within round 15a (mid- to late-October) there was evidence of a fall in prevalence with R of 0.76 (0.65, 0.88). The highest weighted prevalence was observed among children aged 5 to 12 years at 5.85% (5.10%, 6.70%) and 13 to 17 years at 5.75% (5.02%, 6.57%). At regional level, there was an almost four-fold increase in weighted prevalence in South West from round 14 at 0.59% (0.43%,0.80%) to round 15a at 2.18% (1.84%, 2.58%), with highest smoothed prevalence at subregional level also found in South West in round 15a. Age, sex, key worker status, and presence of children in the home jointly contributed to the risk of swab-positivity. Among the 126 sequenced positive swabs obtained up until 23 October, all were Delta variant; 13 (10.3%) were identified as the AY.4.2 sub-lineage.DiscussionWe observed the highest overall prevalence of swab-positivity seen in the REACT-1 study in England to date in round 15a (October 2021), with a two-fold rise in swab-positivity from round 14 (September 2021). Despite evidence of a fall in prevalence from mid- to late-October 2021, prevalence remains high, particularly in school-aged children, with evidence also of higher prevalence in households with one or more children. Thus, vaccination of children aged 12 and over remains a high priority (with possible extension to children aged 5-12) to help reduce within-household transmission and disruptions to education, as well as among adults, to lessen the risk of serious disease among those infected.

BackgroundEngland experienced a third wave of the COVID-19 epidemic from end May 2021 coinciding with the rapid spread of Delta variant. Since then, the population eligible for vaccination against COVID-19 has been extended to include all 12-15-year-olds, and a booster programme has been initiated among adults aged 50 years and over, health care and care home workers, and immunocompromised people. Meanwhile, schoolchildren have returned to school often with few COVID-19-related precautions in place.MethodsIn the REal-time Assessment of Community Transmission-1 (REACT-1) study, throat and nose swabs were sent to non-overlapping random samples of the population aged 5 years and over in England. We analysed prevalence of SARS-CoV-2 using reverse transcription-polymerase chain reaction (RT-PCR) swab-positivity data from REACT-1 round 14 (between 9 and 27 September 2021). We combined results for round 14 with round 13 (between 24 June and 12 July 2021) and estimated vaccine effectiveness and prevalence of swab-positivity among double-vaccinated individuals. Unlike all previous rounds, in round 14, we switched from dry swabs transported by courier on a cold chain to wet swabs using saline. Also, at random, 50% of swabs (not chilled until they reached the depot) were transported by courier and 50% were sent through the priority COVID-19 postal service.ResultsWe observed stable or rising prevalence (with an R of 1.03 (0.94, 1.14) overall) during round 14 with a weighted prevalence of 0.83% (0.76%, 0.89%). The highest weighted prevalence was found in children aged 5 to 12 years at 2.32% (1.96%, 2.73%) and 13 to 17 years at 2.55% (2.11%, 3.08%). All positive virus samples analysed correspond to the Delta variant or sub-lineages of Delta with one instance of the E484K escape mutation detected. The epidemic was growing in those aged 17 years and under with an R of 1.18 (1.03, 1.34), but decreasing in those aged 18 to 54 years with an R of 0.81 (0.68, 0.97). For all participants and all vaccines combined, at ages 18 to 64 years, vaccine effectiveness against infection (rounds 13 and 14 combined) was estimated to be 62.8% (49.3%, 72.7%) after two doses compared to unvaccinated people when adjusted for round, age, sex, index of multiple deprivation, region and ethnicity; the adjusted estimate was 44.8% (22.5%, 60.7%) for AstraZeneca and 71.3% (56.6%, 81.0%) for Pfizer-BioNTech, and for all vaccines combined it was 66.4% (49.6%, 77.6%) against symptomatic infection (one or more of 26 surveyed symptoms in month prior). Across rounds 13 and 14, at ages 18 years and over, weighted prevalence of swab-positivity was 0.55% (0.50%, 0.61%) for those who received their second dose 3-6 months before their swab compared to 0.35% (0.31%, 0.40%) for those whose second dose was within 3 months of their swab, while weighted prevalence among unvaccinated individuals was1.76% (1.60%, 1.95%). In round 14, age group, region, key worker status, and household size jointly contributed to the risk of higher prevalence of swab-positivity.DiscussionIn September 2021 infections were increasing exponentially in the 5-to-17-year age group coinciding with the start of the autumn school term in England. Relatively few schoolchildren aged 5 to 17 years have been vaccinated in the UK though single doses are now being offered to those aged 12 years and over. In adults, the higher prevalence of swab-positivity following two doses of vaccine from 3 to 6 months compared to within 3 months of second dose supports the use of a booster vaccine. It is important that the vaccination programme maintains high coverage and reaches children and unvaccinated or partially vaccinated adults to reduce transmission and associated disruptions to work and education.

Background Rapid detection, isolation, and contact tracing of community COVID-19 cases are essential measures to limit the community spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to identify a parsimonious set of symptoms that jointly predict COVID-19 and investigated whether predictive symptoms differ between the B.1.1.7 (Alpha) lineage (predominating as of April 2021 in the US, UK, and elsewhere) and wild type. Methods and findings We obtained throat and nose swabs with valid SARS-CoV-2 PCR test results from 1,147,370 volunteers aged 5 years and above (6,450 positive cases) in the REal-time Assessment of Community Transmission-1 (REACT-1) study. This study involved repeated community-based random surveys of prevalence in England (study rounds 2 to 8, June 2020 to January 2021, response rates 22%–27%). Participants were asked about symptoms occurring in the week prior to testing. Viral genome sequencing was carried out for PCR-positive samples with N-gene cycle threshold value < 34 (N = 1,079) in round 8 (January 2021). In univariate analysis, all 26 surveyed symptoms were associated with PCR positivity compared with non-symptomatic people. Stability selection (1,000 penalized logistic regression models with 50% subsampling) among people reporting at least 1 symptom identified 7 symptoms as jointly and positively predictive of PCR positivity in rounds 2–7 (June to December 2020): loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss, and muscle aches. The resulting model (rounds 2–7) predicted PCR positivity in round 8 with area under the curve (AUC) of 0.77. The same 7 symptoms were selected as jointly predictive of B.1.1.7 infection in round 8, although when comparing B.1.1.7 with wild type, new persistent cough and sore throat were more predictive of B.1.1.7 infection while loss or change of sense of smell was more predictive of the wild type. The main limitations of our study are (i) potential participation bias despite random sampling of named individuals from the National Health Service register and weighting designed to achieve a representative sample of the population of England and (ii) the necessary reliance on self-reported symptoms, which may be prone to recall bias and may therefore lead to biased estimates of symptom prevalence in England. Conclusions Where testing capacity is limited, it is important to use tests in the most efficient way possible. We identified a set of 7 symptoms that, when considered together, maximize detection of COVID-19 in the community, including infection with the B.1.1.7 lineage., Joshua Elliot, Matthew Whitaker, and colleagues investigate predictive symptoms for community COVID-19 cases in the REACT-1 study., Author summary Why was this study done? The rapid detection of SARS-CoV-2 infection in the community is key to ensuring efficient control of transmission via isolation. Eligibility for community PCR testing is determined based on the reported presence of several (predetermined) symptoms, which may vary from one country to another. Quantitative evidence measuring which symptoms are the most informative of a COVID-19 infection remains scarce. What did the researchers do and find? Data were collected from over 1 million participants in the REACT-1 study (June 2020 to January 2021), for whom 26 symptoms were assayed and the results of a PCR test were available. Adopting a variable selection approach, we sought to determine the best combination of symptoms jointly and complementarily predictive of PCR positivity and investigated whether these symptoms were the same between individuals infected by the wild-type virus and those infected by the B.1.1.7 variant. We identified 7 symptoms that were jointly predictive of PCR positivity and appeared to vary only marginally across age groups: loss or change of sense of smell, loss or change of sense of taste, fever, new persistent cough, chills, appetite loss, and muscle aches. These symptoms were also predictive of the B.1.1.7 infection, together with sore throat (to a lesser extent). What do these findings mean? Taken together, these 7 symptoms can improve the detection of COVID-19 infection in the community. Using this sparse set of symptoms for test allocation would increase the number of tests performed (up to 30%–40% of symptomatic individuals being tested) but would enable up to 75% of symptomatic cases to be detected. This set of 7 symptoms is also predictive of B.1.1.7 infection and performs similarly across age groups. Its use would maximize the case detection rate in the community and would be particularly relevant in situations where test capacity is limited.

Introduction: Studies of risk factors for severe/fatal COVID-19 to date may not have identified the optimal set of informative predictors. Hypothesis: Use of penalized regression with stability analysis may identify new, sparse sets of risk factors jointly associated with COVID-19 mortality. Methods: We investigated demographic, social, lifestyle, biological (lipids, cystatin C, vitamin D), medical (comorbidities, medications) and air pollution data from UK Biobank (N=473,574) in relation to linked COVID-19 mortality, and compared with non-COVID-19 mortality. We used penalized regression models (LASSO) with stability analysis (80% selection threshold from 1,000 models with 80% subsampling) to identify a sparse set of variables associated with COVID-19 mortality. Results: Among 43 variables considered by LASSO stability selection, cardiovascular disease, hypertension, diabetes, cystatin C, age, male sex and Black ethnicity were jointly predictive of COVID-19 mortality risk at 80% selection threshold (Figure). Of these, Black ethnicity and hypertension contributed to COVID-19 but not non-COVID-19 mortality. Conclusions: Use of LASSO stability selection identified a sparse set of predictors for COVID-19 mortality including cardiovascular disease, hypertension, diabetes and cystatin C, a marker of renal function that has also been implicated in atherogenesis and inflammation. These results indicate the importance of cardiometabolic comorbidities as predisposing factors for COVID-19 mortality. Hypertension was differentially highly selected for risk of COVID-19 mortality, suggesting the need for continued vigilance with good blood pressure control during the pandemic.

Introduction: Variable selection methods can provide an unbiased means of identifying informative predictors but have rarely been applied to CVD risk prediction. Hypothesis: Additional variables beyond those in pooled cohort equations may improve CVD risk prediction. Methods: Use of two complementary variable selection methods (LASSO stability selection, parametric, and survival random forests, non-parametric) to identify jointly informative sets of predictors for CVD risk and rank them in order of predictive accuracy. We used a prospective cohort (UK Biobank) of 304,839 participants aged 40-69 years at enrollment (2006—2010) without prior CVD, with follow-up to March 2017. Variables comprised those in pooled cohort equations with additional biochemistry and hematology data and polygenic risk scores for CVD. Outcomes were CVD hospitalization, procedure/operation or mortality. Data were sex-stratified and divided into independent variable selection (40%), training (30%) and test (30%) sets. Variable selection via penalized (LASSO) Cox regression with stability analysis. Variables ranked according to mean change in C statistic after variable permutation in survival random forests. Results: Mean age 55.9 years; 10,267 CVD events (6,277 men [59.0%]), median 8.1 years follow-up. The Figure summarizes results from LASSO stability selection. Jointly informative predictors for both men and women were cystatin C, apolipoprotein B, family history of coronary artery disease and polygenic risk score in addition to age, systolic blood pressure, antihypertensive use and current smoking used in pooled cohort equations. Other than variables already included in pooled cohort equations, cystatin C and apolipoprotein B ranked highest in random forests for men and for women. Conclusions: Use of two complementary data-driven variable selection methods identified variables more highly selected for CVD prediction beyond those included in pooled cohort equations.

SummaryControl of the SARS-CoV-2 epidemic requires rapid identification and isolation of infected individuals and their contacts. Community testing in England (Pillar 2) by polymerase chain reaction (PCR) is reserved for those reporting at least one of four ‘classic’ COVID-19 symptoms (loss or change of sense of smell, loss or change of sense of taste, fever, new continuous cough).1 Detection of positive cases in the community might be improved by including additional symptoms and their combinations. We used data from the REal-time Assessment of Community Transmission-1 (REACT-1) study to investigate symptom profiles for PCR positivity at different ages. Among rounds 2–7 (June to December 2020), an age-stratified, variable selection approach stably selected chills (all ages), headache (5–17 years), appetite loss (18–54 and 55+ years) and muscle aches (18–54 years) as jointly and positively predictive of PCR positivity together with the classic four symptoms. Between round 7 (November to December 2020) and round 8 (January 2021) when new variant B.1.1.7 predominated, only loss or change of sense of smell (more predictive in round 7) and (borderline) new persistent cough (more predictive in round 8) differed between cases. At any level of PCR testing, triage based on the symptoms identified here would result in more cases detected than the current approach.

Increasing evidence points to a role for inflammation in lung carcinogenesis. A small number of circulating inflammatory proteins have been identified as showing elevated levels prior to lung cancer diagnosis, indicating the potential for prospective circulating protein concentration as a marker of early carcinogenesis. To identify novel markers of lung cancer risk, we measured a panel of 92 circulating inflammatory proteins in 648 prediagnostic blood samples from two prospective cohorts in Italy and Norway (women only). To preserve the comparability of results and protect against confounding factors, the main statistical analyses were conducted in women from both studies, with replication sought in men (Italian participants). Univariate and penalized regression models revealed for the first time higher blood levels of CDCP1 protein in cases that went on to develop lung cancer compared with controls, irrespective of time to diagnosis, smoking habits, and gender. This association was validated in an additional 450 samples. Associations were stronger for future cases of adenocarcinoma where CDCP1 showed better explanatory performance. Integrative analyses combining gene expression and protein levels of CDCP1 measured in the same individuals suggested a link between CDCP1 and the expression of transcripts of LRRN3 and SEM1. Enrichment analyses indicated a potential role for CDCP1 in pathways related to cell adhesion and mobility, such as the WNT/β-catenin pathway. Overall, this study identifies lung cancer–related dysregulation of CDCP1 expression years before diagnosis. Significance: Prospective proteomics analyses reveal an association between increased levels of circulating CDCP1 and lung carcinogenesis irrespective of smoking and years before diagnosis, and integrating gene expression indicates potential underlying mechanisms. See related commentary by Itzstein et al., p. 3441.

Background: Socioeconomic position as measured by education may be embodied and affect the functioning of key physiological systems. Links between social disadvantage, its biological imprint, and cause-specific mortality and morbidity have not been investigated in large populations, and yet may point towards areas for public health interventions beyond targeting individual behaviours. Methods: Using data from 366,748 UK Biobank participants with 13 biomarker measurements, we calculated a Biological Health Score (BHS, ranging from 0 to 1) capturing the level of functioning of five physiological systems. Associations between BHS and incidence of cardiovascular disease (CVD) and cancer, and mortality from all, CVD, cancer, and external causes were examined. We explored the role of education in these associations. Mendelian randomisation using genetic evidence was used to triangulate these findings. Findings: An increase in BHS of 0.1 was associated with all-cause (HR = 1.14 [1.12–1.16] and 1.09 [1.07–1.12] in men and women respectively), cancer (HR = 1.11 [1.09–1.14] and 1.07 [1.04–1.10]) and CVD (HR = 1.25 [1.20–1.31] and 1.21 [1.11–1.31]) mortality, CVD incidence (HR = 1.15 [1.13–1.16] and 1.17 [1.15–1.19]). These associations survived adjustment for education, lifestyle-behaviours, body mass index (BMI), co-morbidities and medical treatments. Mendelian randomisation further supported the link between the BHS and CVD incidence (HR = 1.31 [1.21–1.42]). The BHS contributed to CVD incidence prediction (age-adjusted C-statistic = 0.58), other than through education and health behaviours. Interpretation: The BHS captures features of the embodiment of education, health behaviours, and more proximal unknown factors which all complementarily contribute to all-cause, cancer and CVD morbidity and premature death. © 2020 The Author(s)

Mechanisms underlying adverse birth and later in life health effects from exposure to air pollution during the prenatal period have not been not fully elucidated, especially in the context of mixtures. We assessed the effects of prenatal exposure to mixtures of air pollutants of particulate matter (PM), PM2.5, PM10, nitrogen oxides, NO2, NOx, ultrafine particles (UFP), and oxidative potential (OP) of PM2.5 on infant birthweight in four European birth cohorts and the mechanistic underpinnings through cross-omics of metabolites and inflammatory proteins. The association between mixtures of air pollutants and birthweight z-scores (standardized for gestational age) was assessed for three different mixture models, using Bayesian machine kernel regression (BKMR). We determined the direct effect for PM2.5, PM10, NO2, and mediation by cross-omic signatures (identified using sparse partial least-squares regression) using causal mediation BKMR models. There was a negative association with birthweight z-scores and exposure to mixtures of air pollutants, where up to −0.21 or approximately a 96 g decrease in birthweight, comparing the 75th percentile to the median level of exposure to the air pollutant mixture could occur. Shifts in birthweight z-scores from prenatal exposure to PM2.5, PM10, and NO2 were mediated by molecular mechanisms, represented by cross-omics scores. Interleukin-17 and epidermal growth factor were identified as important inflammatory responses underlyingair pollution-associated shifts in birthweight. Our results signify that by identifying mechanisms through which mixtures of air pollutants operate, the causality of air pollution-associated shifts in birthweight is better supported, substantiating the need for reducing exposure in vulnerable populations.

Background Previous investigations have reported that adverse socioeconomic circumstances across the life-course lead to the alteration of major biological processes, eventually resulting in a higher disease risk and premature death. In particular, a low life-course socioeconomic position (SEP) has been associated with a modified epigenetic signature of loci involved in inflammation, the physiological response to stress, and other regulatory processes. Methods In this study, we investigated the association between nine indicators of SEP across the life-course and the differential methylation of 451'000 genome-wide CpG markers, using data from 690 adults included in a Swiss population-based study. We further examined the interrelations between the SEP-related CpGs, and the biological pathways in which the identified markers are involved. Results Three SEP indicators in adulthood were associated the differential methylation of 161 genome-wide CpG markers, whereby 156 CpGs were less methylated in people with low versus high SEP. Among the identified CpGs, a substantial proportion of markers were no longer associated with SEP upon accounting for health behaviors and cardiometabolic disorders. In addition, the identified CpGs were found to be involved in immune, inflammatory, and cancer-related processes. Conclusions Our results support the hypothesis that adverse socioeconomic circumstances may lead to the dysregulation of inflammatory processes, eventually resulting in the occurrence of serious chronic conditions such as atherosclerosis, diabetes, or cancer. Key messages Socioeconomic position is a major determinant of health-related outcomes. Epigenetic modifications may constitute a biological mechanism through which socioeconomic circumstances affect health.

Importance The incremental value of polygenic risk scores in addition to well-established risk prediction models for coronary artery disease (CAD) is uncertain. Objective To examine whether a polygenic risk score for CAD improves risk prediction beyond pooled cohort equations. Design, Setting, and Participants Observational study of UK Biobank participants enrolled from 2006 to 2010. A case-control sample of 15 947 prevalent CAD cases and equal number of age and sex frequency–matched controls was used to optimize the predictive performance of a polygenic risk score for CAD based on summary statistics from published genome-wide association studies. A separate cohort of 352 660 individuals (with follow-up to 2017) was used to evaluate the predictive accuracy of the polygenic risk score, pooled cohort equations, and both combined for incident CAD. Exposures Polygenic risk score for CAD, pooled cohort equations, and both combined. Main Outcomes and Measures CAD (myocardial infarction and its related sequelae). Discrimination, calibration, and reclassification using a risk threshold of 7.5% were assessed. Results In the cohort of 352 660 participants (mean age, 55.9 years; 205 297 women [58.2%]) used to evaluate the predictive accuracy of the examined models, there were 6272 incident CAD events over a median of 8 years of follow-up. CAD discrimination for polygenic risk score, pooled cohort equations, and both combined resulted in C statistics of 0.61 (95% CI, 0.60 to 0.62), 0.76 (95% CI, 0.75 to 0.77), and 0.78 (95% CI, 0.77 to 0.79), respectively. The change in C statistic between the latter 2 models was 0.02 (95% CI, 0.01 to 0.03). Calibration of the models showed overestimation of risk by pooled cohort equations, which was corrected after recalibration. Using a risk threshold of 7.5%, addition of the polygenic risk score to pooled cohort equations resulted in a net reclassification improvement of 4.4% (95% CI, 3.5% to 5.3%) for cases and −0.4% (95% CI, −0.5% to −0.4%) for noncases (overall net reclassification improvement, 4.0% [95% CI, 3.1% to 4.9%]). Conclusions and Relevance The addition of a polygenic risk score for CAD to pooled cohort equations was associated with a statistically significant, yet modest, improvement in the predictive accuracy for incident CAD and improved risk stratification for only a small proportion of individuals. The use of genetic information over the pooled cohort equations model warrants further investigation before clinical implementation.

Introduction/Background Persistent infection with high-risk human papillomavirus (HPV) is causally associated with cervical cancer. However, only ∼1% of women with HPV infection progress to cervical neoplasia (CIN). It is estimated that heritability may explain 25–30% of total variation in liability for cervical cancer. Common genetic variants have been detected in HLA (Human Leukocyte Antigen) regions responsible for the immune response, but this is not well understood. We aimed to conduct the largest genome-wide association study (GWAS) of cervical cancer to date, using UK Biobank data to identify genetic polymorphisms associated with CIN and cervical cancer. Methodology Using phenotypic data available from linked UK cancer registries, hospital ICD-10 records, operative procedures and participant interviews we identified 6378 women with CIN3/cervical cancer and 198,441 controls. With UK Biobank genotyping calls (Affymetrix UK Biobank Axiom® array) we conducted genome wide analyses, adjusting for population structure and potential confounders. As a stringent correction for multiple testing, we considered a pre-test significance level of 10-8 to declare single nucleotide polymorphisms (SNPs). Results In the first UK Biobank iteration we have identified potential SNPs (p Conclusion We observed genetic variants significantly associated with CIN3/cervical cancer in both cohorts. Loci within the MHC may affect susceptibility to development of CIN3/cervical cancer through altered immune responses. We will next undertake fine-mapping within the UK Biobank cohort, to further classify any novel causal variants that may explain the estimated genetic susceptibility to cervical cancer. Disclosure Funding provided by an NIHR Academic Clinical Fellowship (SL) and a Wellcome Trust Clinician Scientist Fellowship (SL). No conflicts of interest to declare.

Background It now established that social factors impact the quality of ageing, through the lifecourse stimulation/dysregulation of key physiological systems. Composite scores such as allostatic load, focusing on the response to stress, can be used to measure individual physiological wear-and-tear. Methods Using data from the Understanding Society study, a cross-sectional panel study including 9,088 participants representative of the UK population, we defined a synthetic biological health score (BHS) capturing the wear-and-tear of four physiological systems (endocrine, inflammatory, cardiovascular, and metabolic systems), and of two key organs (liver and kidney). We used 16 established blood-derived biomarkers of these systems to calculate the BHS and explored the relative contribution of socio-economic position to the BHS and its main components across age groups. Using data from UK biobank, including over 400,000 UK participants in whom similar biomarkers have been assayed in blood, we sought validation of our results and investigated the role of the BHS on all-cause and disease specific mortality, and disease incidence. Results We identified a systematic decreasing education-related gradient of the BHS (p < 0·001) leading to lower biological risk in participants with higher educational attainment. Education-related differences in the BHS were detected early in life, and were not attributable to lifestyle and behavioural factors. Analyses of the UK biobank data validated these findings and also showed that the BHS contributed in turn, irrespective of established health risk factors, to all-cause and disease specific mortality. Interpretation Our findings highlight the social-to-biological processes ultimately leading to health inequalities, and suggest that such disparities can already be detected in the 20-40 year age group.

Although smoking and oxidative stress are known contributors to lung carcinogenesis, their mechanisms of action remain poorly understood. To shed light into these mechanisms, we applied a novel approach using Cys34-adductomics in a lung cancer nested case-control study (n = 212). Adductomics profiles were integrated with DNA-methylation data at established smoking-related CpG sites measured in the same individuals. Our analysis identified 42 Cys34-albumin adducts, of which 2 were significantly differentially abundant in cases and controls: adduct of N-acetylcysteine (NAC, p = 4.15 × 10-3 ) and of cysteinyl-glycine (p = 7.89 × 10-3 ). Blood levels of the former were found associated to the methylation levels at 11 smoking-related CpG sites. We detect, for the first time in prospective blood samples, and irrespective of time to diagnosis, decreased levels of NAC adduct in lung cancer cases. Altogether, our results highlight the potential role of these adducts in the oxidative stress response contributing to lung carcinogenesis years before diagnosis.

Epidemiological studies provide evidence that environmental exposures may affect health through complex mixtures. Formal investigation of the effect of exposure mixtures is usually achieved by modelling interactions, which relies on strong assumptions relating to the identity and the number of the exposures involved in such interactions, and on the order and parametric form of these interactions. These hypotheses become difficult to formulate and justify in an exposome context, where influential exposures are numerous and heterogeneous. To capture both the complexity of the exposome and its possibly pleiotropic effects, models handling multivariate predictors and responses, such as partial least squares (PLS) algorithms, can prove useful. As an illustrative example, we applied PLS models to data from a study investigating the inflammatory response (blood concentration of 13 immune markers) to the exposure to four disinfection by-products (one brominated and three chlorinated compounds), while swimming in a pool. To accommodate the multiple observations per participant (n=60; before and after the swim), we adopted a multilevel extension of PLS algorithms, including sparse PLS models shrinking loadings coefficients of unimportant predictors (exposures) and/or responses (protein levels). Despite the strong correlation among co-occurring exposures, our approach identified a subset of exposures (n=3/4) affecting the exhaled levels of 8 (out of 13) immune markers. PLS algorithms can easily scale to high-dimensional exposures and responses, and prove useful for exposome research to identify sparse sets of exposures jointly affecting a set of (selected) biological markers. Our descriptive work may guide these extensions for higher dimensional data.

Background The recent COVID-19 outbreak has generated an unprecedented public health crisis, with millions of infections and hundreds of thousands of deaths worldwide. Using hospital-based or mortality data, several COVID-19 risk factors have been identified, but these may be confounded or biased. Methods Using SARS-CoV-2 infection test data (n = 4509 tests; 1325 positive) from Public Health England, linked to the UK Biobank study, we explored the contribution of demographic, social, health risk, medical and environmental factors to COVID-19 risk. We used multivariable and penalized logistic regression models for the risk of (i) being tested, (ii) testing positive/negative in the study population and, adopting a test negative design, (iii) the risk of testing positive within the tested population. Results In the fully adjusted model, variables independently associated with the risk of being tested for COVID-19 with odds ratio >1.05 were: male sex; Black ethnicity; social disadvantage (as measured by education, housing and income); occupation (healthcare worker, retired, unemployed); ever smoker; severely obese; comorbidities; and greater exposure to particulate matter (PM) 2.5 absorbance. Of these, only male sex, non-White ethnicity and lower educational attainment, and none of the comorbidities or health risk factors, were associated with testing positive among tested individuals. Conclusions We adopted a careful and exhaustive approach within a large population-based cohort, which enabled us to triangulate evidence linking male sex, lower educational attainment and non-White ethnicity with the risk of COVID-19. The elucidation of the joint and independent effects of these factors is a high-priority area for further research to inform on the natural history of COVID-19.

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.