Evaluation of risk prediction models to select lung cancer screening participants in Europe: a prospective cohort consortium analysis.

BACKGROUND: Lung cancer risk prediction models might efficiently identify individuals who should be offered lung cancer screening. However, their performance has not been comprehensively evaluated in Europe. We aimed to externally validate and evaluate the performance of several risk prediction models that predict lung cancer incidence or mortality in prospective European cohorts. METHODS: We analysed 240 137 participants aged 45-80 years with a current or former smoking history from nine European countries in four prospective cohorts from the pooled database of the Lung Cancer Cohort Consortium: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study (Finland), the Nord-Trøndelag Health Study (Norway), CONSTANCES (France), and the European Prospective Investigation into Cancer and Nutrition (Denmark, Germany, Italy, Spain, Sweden, the Netherlands, and Norway). We evaluated ten lung cancer risk models, which comprised the Bach, the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 2012 model (PLCOm2012), the Lung Cancer Risk Assessment Tool (LCRAT), the Lung Cancer Death Risk Assessment Tool (LCDRAT), the Nord-Trøndelag Health Study (HUNT), the Optimized Early Warning Model for Lung Cancer Risk (OWL), the University College London-Death (UCLD), the University College London-Incidence (UCLI), the Liverpool Lung Project version 2 (LLP version 2), and the Liverpool Lung Project version 3 (LLP version 3) models. We quantified model calibration as the ratio of expected to observed cases or deaths and discrimination using the area under the receiver operating characteristic curve (AUC). For each model, we also identified risk thresholds that would screen the same number of individuals as each of the US Preventive Services Task Force 2021 (USPSTF-2021), the US Preventive Services Task Force 2013 (USPSTF-2013), and the Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON) criteria. FINDINGS: Among the participants, 1734 lung cancer cases and 1072 lung cancer deaths occurred within five years of enrolment. Most models had reasonable calibration in most countries, although the LLP version 2 overpredicted risk by more than 50% in eight countries (expected to observed ≥1·50). The PLCOm2012, LCDRAT, LCRAT, Bach, HUNT, OWL, UCLD, and UCLI models showed similar discrimination in most countries, with AUCs ranging from 0·68 (95% CI 0·59-0·77) to 0·83 (0·78-0·89), whereas the LLP version 2 and LLP version 3 showed lower discrimination, with AUCs ranging from 0·64 (95% CI 0·57-0·72) to 0·78 (0·74-0·83). When pooling data from all countries (but excluding the HUNT cohort), 33·9% (73 313 of 216 387) of individuals were eligible by USPSTF-2021 criteria, which included 74·8% (1185) of lung cancers and 76·3% (730) of lung cancer deaths occurring over 5 years. Fewer individuals were selected by USPSTF-2013 and NELSON criteria. After applying thresholds to select a population of equal size to USPSTF-2021, the PLCOm2012, LCDRAT, LCRAT, Bach, HUNT, OWL, UCLD, and UCLI, models identified 77·6%-79·1% of future cases, although they selected slightly older individuals compared with USPSTF-2021 criteria. Results were similar for USPSTF-2013 and NELSON. INTERPRETATION: Several lung cancer risk prediction models showed good performance in European countries and might improve the efficiency of lung cancer screening if used in place of categorical eligibility criteria. FUNDING: US National Cancer Institute, l'Institut National du Cancer, Cancer Research UK.

Epigenetic Aging and Racialized, Economic, and Environmental Injustice: NIMHD Social Epigenomics Program.

Importance: Epigenetic age acceleration is associated with exposure to social and economic adversity and may increase the risk of premature morbidity and mortality. However, no studies have included measures of structural racism, and few have compared estimates within or across the first and second generation of epigenetic clocks. Objective: To determine whether epigenetic age acceleration is positively associated with exposures to diverse measures of racialized, economic, and environmental injustice measured at different levels and time periods. Design, Setting, and Participants: This cross-sectional study used data from the My Body My Story (MBMS) study between August 8, 2008, and December 31, 2010, and examination 5 of the Multi-Ethnic Atherosclerosis Study (MESA) from April 1, 2010, to February 29, 2012. In the MBMS, DNA extraction was performed in 2021; linkage of structural measures to the MBMS and MESA, in 2022. US-born individuals were randomly selected from 4 community health centers in Boston, Massachusetts (MBMS), and 4 field sites in Baltimore, Maryland; Forsyth County, North Carolina; New York City, New York; and St Paul, Minnesota (MESA). Data were analyzed from November 13, 2021, to August 31, 2023. Main Outcomes and Measures: Ten epigenetic clocks (6 first-generation and 4 second-generation), computed using DNA methylation data (DNAm) from blood spots (MBMS) and purified monocytes (MESA). Results: The US-born study population included 293 MBMS participants (109 men [37.2%], 184 women [62.8%]; mean [SD] age, 49.0 [8.0] years) with 224 Black non-Hispanic and 69 White non-Hispanic participants and 975 MESA participants (492 men [50.5%], 483 women [49.5%]; mean [SD] age, 70.0 [9.3] years) with 229 Black non-Hispanic, 191 Hispanic, and 555 White non-Hispanic participants. Of these, 140 (11.0%) exhibited accelerated aging for all 5 clocks whose estimates are interpretable on the age (years) scale. Among Black non-Hispanic MBMS participants, epigenetic age acceleration was associated with being born in a Jim Crow state by 0.14 (95% CI, 0.003-0.27) SDs and with birth state conservatism by 0.06 (95% CI, 0.01-0.12) SDs, pooling across all clocks. Low parental educational level was associated with epigenetic age acceleration, pooling across all clocks, for both Black non-Hispanic (0.24 [95% CI, 0.08-0.39] SDs) and White non-Hispanic (0.27 [95% CI, 0.03-0.51] SDs) MBMS participants. Adult impoverishment was positively associated with the pooled second-generation clocks among the MESA participants (Black non-Hispanic, 0.06 [95% CI, 0.01-0.12] SDs; Hispanic, 0.07 [95% CI, 0.01-0.14] SDs; White non-Hispanic, 0.05 [95% CI, 0.01-0.08] SDs). Conclusions and Relevance: The findings of this cross-sectional study of MBMS and MESA participants suggest that epigenetic age acceleration was associated with racialized and economic injustice, potentially contributing to well-documented inequities in premature mortality. Future research should test the hypothesis that epigenetic accelerated aging may be one of the biological mechanisms underlying the well-documented elevated risk of premature morbidity and mortality among social groups subjected to racialized and economic injustice.

A novel hypothesis-generating approach for detecting phenotypic associations using epigenetic data.

Aim: Hypotheses about what phenotypes to include in causal analyses, that in turn can have clinical and policy implications, can be guided by hypothesis-free approaches leveraging the epigenome, for example.Materials & methods: Minimally adjusted epigenome-wide association studies (EWAS) using ALSPAC data were performed for example conditions, dysmenorrhea and heavy menstrual bleeding (HMB). Differentially methylated CpGs were searched in the EWAS Catalog and associated traits identified. Traits were compared between those with and without the example conditions in ALSPAC.Results: Seven CpG sites were associated with dysmenorrhea and two with HMB. Smoking and adverse childhood experience score were associated with both conditions in the hypothesis-testing phase.Conclusion: Hypothesis-generating EWAS can help identify associations for future analyses.

To inform policy and improve clinical practice, it is important that researchers who study people's health find out which traits might increase the risk of illness. However, it can be difficult to know which traits should be looked at. In this study, we wanted to look for traits that might increase the risk of painful and heavy periods, using data about the switches that turn our genes on and off. There are some people in the Children of the 90s study that have data on gene switches. We compared all the switches between those with and without painful or heavy periods. For painful periods, we found links with seven switches and for heavy periods, we found two. We then used another data source, called the EWAS Catalog, to see which traits were associated with these switches. The traits we found included body size, smoking and child abuse. Finally, when using data on traits from the wider Children of the 90s group, we found that smoking and more difficult childhoods were some of the traits related to painful and heavy periods. A good thing about this approach is that we could find new traits that might increase the risk of painful or heavy periods; these should be looked at in future studies.

Novel genomic variants related to visceral adiposity index (VAI) and body adiposity index (BAI) in Indian sib-pairs.

BACKGROUND: Obesity is among the leading public health threats globally. Over the last few years, visceral adiposity index (VAI), and body adiposity index (BAI), derived from anthropometric, and biochemical measures, have gained importance as a measure of obesity. However, unlike other common indices like body mass index, and waist circumference, the genetic predisposition of VAI, and BAI under-examined. METHODS: 2265 sib-pairs from Indian Migration Study were used for examining the association of genetic variants from the Cardio-Metabochip array with VAI, and BAI. Mixed linear regression models were run, and all inferences were based on the within-sib component of the Fulker's association models. Gene-environment/lifestyle interaction analyses were also undertaken. RESULTS: rs6659428 at LOC400796 | SEC16B (ß = 0.26, SE = 0.05), and rs7611535 at DRD3 | LOC645180 (ß = 0.18, SE = 0.04) were associated with VAI at suggestive significance value of <8.21 × 10-6. For BAI, rs73300702 at JAZF1-AS1 (ß = 0.27, SE = 0.06), was the top hit at p value < 8.21 × 10-6. Further, rs6659428 showed marginal effect modification with rural/urban location (ß = 0.26, SE = 0.13, p value = 0.047), and rs73300702 with physical activity (ß = -0.29,SE = 0.14, p value = 0.034). CONCLUSION: We report three novel genetic loci for VAI, and BAI in Indians that are important indicators of adiposity. These findings need to be replicated and validated with larger samples from different ethnicities. Further, functional studies for understanding the biological mechanisms of these adiposity indices need to be undertaken to understand the underlying pathophysiology.

Acute and long-term outcomes of SARS-CoV-2 infection in school-aged children in England: Study protocol for the joint analysis of the COVID-19 schools infection survey (SIS) and the COVID-19 mapping and mitigation in schools (CoMMinS) study.

BACKGROUND: The symptom profiles of acute SARS-CoV-2 infection and long-COVID in children and young people (CYP), risk factors, and associated healthcare needs, are poorly defined. The Schools Infection Survey 1 (SIS-1) was a nationwide study of SARS-CoV-2 infection in primary and secondary schools in England during the 2020/21 school year. The Covid-19 Mapping and Mitigation in Schools (CoMMinS) study was conducted in schools in the Bristol area over a similar period. Both studies conducted testing to identify current and previous SARS-CoV-2 infection, and recorded symptoms and school attendance. These research data have been linked to routine electronic health record (EHR) data. AIMS: To better understand the short- and long-term consequences of SARS-CoV-2 infection, and their risk factors, in CYP. METHODS: Retrospective cohort and nested case-control analyses will be conducted for SIS-1 and CoMMinS data linked to EHR data for the association between (1) acute symptomatic SARS-CoV-2 infection and risk factors; (2) SARS-CoV-2 infection and long-term effects on health: (a) persistent symptoms; (b) any new diagnosis; (c) a new prescription in primary care; (d) health service attendance; (e) a high rate of school absence. RESULTS: Our study will improve understanding of long-COVID in CYP by characterising the trajectory of long-COVID in CYP in terms of things like symptoms and diagnoses of conditions. The research will inform which groups of CYP are more likely to get acute- and long-term outcomes of SARS-CoV-2 infection, and patterns of related healthcare-seeking behaviour, relevant for healthcare service planning. Digested information will be produced for affected families, doctors, schools, and the public, as appropriate. CONCLUSION: Linked SIS-1 and CoMMinS data represent a unique and rich resource for understanding the impact of SARS-CoV-2 infection on children's health, benefiting from enhanced SARS-CoV-2 testing and ability to assess a wide range of outcomes.

Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts.

Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N = 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.

Ultra-processed foods, adiposity and risk of head and neck cancer and oesophageal adenocarcinoma in the European Prospective Investigation into Cancer and Nutrition study: a mediation analysis.

PURPOSE: To investigate the role of adiposity in the associations between ultra-processed food (UPF) consumption and head and neck cancer (HNC) and oesophageal adenocarcinoma (OAC) in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. METHODS: Our study included 450,111 EPIC participants. We used Cox regressions to investigate the associations between the consumption of UPFs and HNC and OAC risk. A mediation analysis was performed to assess the role of body mass index (BMI) and waist-to-hip ratio (WHR) in these associations. In sensitivity analyses, we investigated accidental death as a negative control outcome. RESULTS: During a mean follow-up of 14.13 ± 3.98 years, 910 and 215 participants developed HNC and OAC, respectively. A 10% g/d higher consumption of UPFs was associated with an increased risk of HNC (hazard ratio [HR] = 1.23, 95% confidence interval [CI] 1.14-1.34) and OAC (HR = 1.24, 95% CI 1.05-1.47). WHR mediated 5% (95% CI 3-10%) of the association between the consumption of UPFs and HNC risk, while BMI and WHR, respectively, mediated 13% (95% CI 6-53%) and 15% (95% CI 8-72%) of the association between the consumption of UPFs and OAC risk. UPF consumption was positively associated with accidental death in the negative control analysis. CONCLUSIONS: We reaffirmed that higher UPF consumption is associated with greater risk of HNC and OAC in EPIC. The proportion mediated via adiposity was small. Further research is required to investigate other mechanisms that may be at play (if there is indeed any causal effect of UPF consumption on these cancers).

An epigenome-wide analysis of DNA methylation, racialized and economic inequities, and air pollution.

Importance: DNA methylation (DNAm) provides a plausible mechanism by which adverse exposures become embodied and contribute to health inequities, due to its role in genome regulation and responsiveness to social and biophysical exposures tied to societal context. However, scant epigenome-wide association studies (EWAS) have included structural and lifecourse measures of exposure, especially in relation to structural discrimination. Objective: Our study tests the hypothesis that DNAm is a mechanism by which racial discrimination, economic adversity, and air pollution become biologically embodied. Design: A series of cross-sectional EWAS, conducted in My Body My Story (MBMS, biological specimens collected 2008-2010, DNAm assayed in 2021); and the Multi Ethnic Study of Atherosclerosis (MESA; biological specimens collected 2010-2012, DNAm assayed in 2012-2013); using new georeferenced social exposure data for both studies (generated in 2022). Setting: MBMS was recruited from four community health centers in Boston; MESA was recruited from four field sites in: Baltimore, MD; Forsyth County, NC; New York City, NY; and St. Paul, MN. Participants: Two population-based samples of US-born Black non-Hispanic (Black NH), white non-Hispanic (white NH), and Hispanic individuals (MBMS; n=224 Black NH and 69 white NH) and (MESA; n=229 Black NH, n=555 white NH and n=191 Hispanic). Exposures: Eight social exposures encompassing racial discrimination, economic adversity, and air pollution. Main outcome: Genome-wide changes in DNAm, as measured using the Illumina EPIC BeadChip (MBMS; using frozen blood spots) and Illumina 450k BeadChip (MESA; using purified monocytes). Our hypothesis was formulated after data collection. Results: We observed the strongest associations with traffic-related air pollution (measured via black carbon and nitrogen oxides exposure), with evidence from both studies suggesting that air pollution exposure may induce epigenetic changes related to inflammatory processes. We also found suggestive associations of DNAm variation with measures of structural racial discrimination (e.g., for Black NH participants, born in a Jim Crow state; adult exposure to racialized economic residential segregation) situated in genes with plausible links to effects on health. Conclusions and Relevance: Overall, this work suggests that DNAm is a biological mechanism through which structural racism and air pollution become embodied and may lead to health inequities.

The tumor multi-omic landscape of endometrial cancers developed on a germline genetic background of adiposity.

High body mass index (BMI) is a causal risk factor for endometrial cancer but the tumor molecular mechanisms affected by adiposity and their therapeutic relevance remain poorly understood. Here we characterize the tumor multi-omic landscape of endometrial cancers that have developed on a background of lifelong germline genetic exposure to elevated BMI. We built a polygenic score (PGS) for BMI in women using data on independent, genome-wide significant variants associated with adult BMI in 434,794 women. We performed germline (blood) genotype quality control and imputation on data from 354 endometrial cancer cases from The Cancer Genome Atlas (TCGA). We assigned each case in this TCGA cohort their genetically predicted life-course BMI based on the BMI PGS. Multivariable generalized linear models adjusted for age, stage, microsatellite status and genetic principal components were used to test for associations between the BMI germline PGS and endometrial cancer tumor genome-wide genomic, transcriptomic, proteomic, epigenomic and immune traits in TCGA. High BMI germline PGS was associated with (i) upregulated tumor gene expression in the IL6-JAK-STAT3 pathway (FDR=4.2×10-7); (ii) increased estimated intra-tumor activated mast cell infiltration (FDR=0.008); (iii) increased single base substitution (SBS) mutational signatures 1 (FDR=0.03) and 5 (FDR=0.09) and decreased SBS13 (FDR=0.09), implicating age-related and APOBEC mutagenesis, respectively; and (iv) decreased tumor EGFR protein expression (FDR=0.07). Alterations in IL6-JAK-STAT3 signaling gene and EGFR protein expression were, in turn, significantly associated with both overall survival and progression-free interval. Thus, we integrated germline and somatic data using a novel study design to identify associations between genetically predicted lifelong exposure to higher BMI and potentially actionable endometrial cancer tumor molecular features. These associations inform our understanding of how high BMI may influence the development and progression of this cancer, impacting endometrial tumor biology and clinical outcomes.

Analysis of DNA methylation at birth and in childhood reveals changes associated with season of birth and latitude.

BACKGROUND: Seasonal variations in environmental exposures at birth or during gestation are associated with numerous adult traits and health outcomes later in life. Whether DNA methylation (DNAm) plays a role in the molecular mechanisms underlying the associations between birth season and lifelong phenotypes remains unclear. METHODS: We carried out epigenome-wide meta-analyses within the Pregnancy And Childhood Epigenetic Consortium to identify associations of DNAm with birth season, both at differentially methylated probes (DMPs) and regions (DMRs). Associations were examined at two time points: at birth (21 cohorts, N = 9358) and in children aged 1-11 years (12 cohorts, N = 3610). We conducted meta-analyses to assess the impact of latitude on birth season-specific associations at both time points. RESULTS: We identified associations between birth season and DNAm (False Discovery Rate-adjusted p values < 0.05) at two CpGs at birth (winter-born) and four in the childhood (summer-born) analyses when compared to children born in autumn. Furthermore, we identified twenty-six differentially methylated regions (DMR) at birth (winter-born: 8, spring-born: 15, summer-born: 3) and thirty-two in childhood (winter-born: 12, spring and summer: 10 each) meta-analyses with few overlapping DMRs between the birth seasons or the two time points. The DMRs were associated with genes of known functions in tumorigenesis, psychiatric/neurological disorders, inflammation, or immunity, amongst others. Latitude-stratified meta-analyses [higher (≥ 50°N), lower (< 50°N, northern hemisphere only)] revealed differences in associations between birth season and DNAm by birth latitude. DMR analysis implicated genes with previously reported links to schizophrenia (LAX1), skin disorders (PSORS1C, LTB4R), and airway inflammation including asthma (LTB4R), present only at birth in the higher latitudes (≥ 50°N). CONCLUSIONS: In this large epigenome-wide meta-analysis study, we provide evidence for (i) associations between DNAm and season of birth that are unique for the seasons of the year (temporal effect) and (ii) latitude-dependent variations in the seasonal associations (spatial effect). DNAm could play a role in the molecular mechanisms underlying the effect of birth season on adult health outcomes.

Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics.

Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.

DNA methylation at the suppressor of cytokine signaling 3 (SOCS3) gene influences height in childhood.

Human height is strongly influenced by genetics but the contribution of modifiable epigenetic factors is under-explored, particularly in low and middle-income countries (LMIC). We investigate links between blood DNA methylation and child height in four LMIC cohorts (n = 1927) and identify a robust association at three CpGs in the suppressor of cytokine signaling 3 (SOCS3) gene which replicates in a high-income country cohort (n = 879). SOCS3 methylation (SOCS3m)-height associations are independent of genetic effects. Mendelian randomization analysis confirms a causal effect of SOCS3m on height. In longitudinal analysis, SOCS3m explains a maximum 9.5% of height variance in mid-childhood while the variance explained by height polygenic risk score increases from birth to 21 years. Children's SOCS3m is associated with prenatal maternal folate and socio-economic status. In-vitro characterization confirms a regulatory effect of SOCS3m on gene expression. Our findings suggest epigenetic modifications may play an important role in driving child height in LMIC.

Genetic impacts on DNA methylation help elucidate regulatory genomic processes.

BACKGROUND: Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. RESULTS: We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites). CONCLUSIONS: Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk .

Association between the timing of childhood adversity and epigenetic patterns across childhood and adolescence: findings from the Avon Longitudinal Study of Parents and Children (ALSPAC) prospective cohort.

BACKGROUND: Childhood adversity is a potent determinant of health across development and is associated with altered DNA methylation signatures, which might be more common in children exposed during sensitive periods in development. However, it remains unclear whether adversity has persistent epigenetic associations across childhood and adolescence. We aimed to examine the relationship between time-varying adversity (defined through sensitive period, accumulation of risk, and recency life course hypotheses) and genome-wide DNA methylation, measured three times from birth to adolescence, using data from a prospective, longitudinal cohort study. METHODS: We first investigated the relationship between the timing of exposure to childhood adversity between birth and 11 years and blood DNA methylation at age 15 years in the Avon Longitudinal Study of Parents and Children (ALSPAC) prospective cohort study. Our analytic sample included ALSPAC participants with DNA methylation data and complete childhood adversity data between birth and 11 years. We analysed seven types of adversity (caregiver physical or emotional abuse, sexual or physical abuse [by anyone], maternal psychopathology, one-adult households, family instability, financial hardship, and neighbourhood disadvantage) reported by mothers five to eight times between birth and 11 years. We used the structured life course modelling approach (SLCMA) to identify time-varying associations between childhood adversity and adolescent DNA methylation. Top loci were identified using an R2 threshold of 0·035 (ie, ≥3·5% of DNA methylation variance explained by adversity). We attempted to replicate these associations using data from the Raine Study and Future of Families and Child Wellbeing Study (FFCWS). We also assessed the persistence of adversity-DNA methylation associations we previously identified from age 7 blood DNA methylation into adolescence and the influence of adversity on DNA methylation trajectories from ages 0-15 years. FINDINGS: Of 13 988 children in the ALSPAC cohort, 609-665 children (311-337 [50-51%] boys and 298-332 [49-50%] girls) had complete data available for at least one of the seven childhood adversities and DNA methylation at 15 years. Exposure to adversity was associated with differences in DNA methylation at 15 years for 41 loci (R2 ≥0·035). Sensitive periods were the most often selected life course hypothesis by the SLCMA. 20 (49%) of 41 loci were associated with adversities occurring between age 3 and 5 years. Exposure to one-adult households was associated with differences in DNA methylation at 20 [49%] of 41 loci, exposure to financial hardship was associated with changes at nine (22%) loci, and physical or sexual abuse was associated with changes at four (10%) loci. We replicated the direction of associations for 18 (90%) of 20 loci associated with exposure to one-adult household using adolescent blood DNA methylation from the Raine Study and 18 (64%) of 28 loci using saliva DNA methylation from the FFCWS. The directions of effects for 11 one-adult household loci were replicated in both cohorts. Differences in DNA methylation at 15 years were not present at 7 years and differences identified at 7 years were no longer apparent by 15 years. We also identified six distinct DNA methylation trajectories from these patterns of stability and persistence. INTERPRETATION: These findings highlight the time-varying effect of childhood adversity on DNA methylation profiles across development, which might link exposure to adversity to potential adverse health outcomes in children and adolescents. If replicated, these epigenetic signatures could ultimately serve as biological indicators or early warning signs of initiated disease processes, helping identify people at greater risk for the adverse health consequences of childhood adversity. FUNDING: Canadian Institutes of Health Research, Cohort and Longitudinal Studies Enhancement Resources, EU's Horizon 2020, US National Institute of Mental Health.

Investigating causality in the association between DNA methylation and type 2 diabetes using bidirectional two-sample Mendelian randomisation.

AIMS/HYPOTHESIS: Several studies have identified associations between type 2 diabetes and DNA methylation (DNAm). However, the causal role of these associations remains unclear. This study aimed to provide evidence for a causal relationship between DNAm and type 2 diabetes. METHODS: We used bidirectional two-sample Mendelian randomisation (2SMR) to evaluate causality at 58 CpG sites previously detected in a meta-analysis of epigenome-wide association studies (meta-EWAS) of prevalent type 2 diabetes in European populations. We retrieved genetic proxies for type 2 diabetes and DNAm from the largest genome-wide association study (GWAS) available. We also used data from the Avon Longitudinal Study of Parents and Children (ALSPAC, UK) when associations of interest were not available in the larger datasets. We identified 62 independent SNPs as proxies for type 2 diabetes, and 39 methylation quantitative trait loci as proxies for 30 of the 58 type 2 diabetes-related CpGs. We applied the Bonferroni correction for multiple testing and inferred causality based on p<0.001 for the type 2 diabetes to DNAm direction and p<0.002 for the opposing DNAm to type 2 diabetes direction in the 2SMR analysis. RESULTS: We found strong evidence of a causal effect of DNAm at cg25536676 (DHCR24) on type 2 diabetes. An increase in transformed residuals of DNAm at this site was associated with a 43% (OR 1.43, 95% CI 1.15, 1.78, p=0.001) higher risk of type 2 diabetes. We inferred a likely causal direction for the remaining CpG sites assessed. In silico analyses showed that the CpGs analysed were enriched for expression quantitative trait methylation sites (eQTMs) and for specific traits, dependent on the direction of causality predicted by the 2SMR analysis. CONCLUSIONS/INTERPRETATION: We identified one CpG mapping to a gene related to the metabolism of lipids (DHCR24) as a novel causal biomarker for risk of type 2 diabetes. CpGs within the same gene region have previously been associated with type 2 diabetes-related traits in observational studies (BMI, waist circumference, HDL-cholesterol, insulin) and in Mendelian randomisation analyses (LDL-cholesterol). Thus, we hypothesise that our candidate CpG in DHCR24 may be a causal mediator of the association between known modifiable risk factors and type 2 diabetes. Formal causal mediation analysis should be implemented to further validate this assumption.

The association between genetically elevated polyunsaturated fatty acids and risk of cancer.

BACKGROUND: The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain. METHODS: Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures. FINDINGS: Genetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07-1.11]), esophageal squamous cell carcinoma (1.16 [1.06-1.26]), lung cancer (1.06 [1.03-1.08]) and basal cell carcinoma (1.05 [1.02-1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99-1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99-1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95-1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98-1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding. INTERPRETATION: The PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease. FUNDING: Cancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

Role of DNA methylation in the relationship between glioma risk factors and glioma incidence: a two-step Mendelian randomization study.

Genetic evidence suggests glioma risk is altered by leukocyte telomere length, allergic disease (asthma, hay fever or eczema), alcohol consumption, childhood obesity, low-density lipoprotein cholesterol (LDLc) and triglyceride levels. DNA methylation (DNAm) variation influences many of these glioma-related traits and is an established feature of glioma. Yet the causal relationship between DNAm variation with both glioma incidence and glioma risk factors is unknown. We applied a two-step Mendelian randomization (MR) approach and several sensitivity analyses (including colocalization and Steiger filtering) to assess the association of DNAm with glioma risk factors and glioma incidence. We used data from a recently published catalogue of germline genetic variants robustly associated with DNAm variation in blood (32,851 participants) and data from a genome-wide association study of glioma risk (12,488 cases and 18,169 controls, sub-divided into 6191 glioblastoma cases and 6305 non-glioblastoma cases). MR evidence indicated that DNAm at 3 CpG sites (cg01561092, cg05926943, cg01584448) in one genomic region (HEATR3) had a putative association with glioma and glioblastoma risk (False discovery rate [FDR] < 0.05). Steiger filtering provided evidence against reverse causation. Colocalization presented evidence against genetic confounding and suggested that differential DNAm at the 3 CpG sites and glioma were driven by the same genetic variant. MR provided little evidence to suggest that DNAm acts as a mediator on the causal pathway between risk factors previously examined and glioma onset. To our knowledge, this is the first study to use MR to appraise the causal link of DNAm with glioma risk factors and glioma onset. Subsequent analyses are required to improve the robustness of our results and rule out horizontal pleiotropy.