Educational level and characteristics of invasive breast cancer: findings from a French prospective cohort.

PURPOSE: Breast cancer (BC) characteristics are known to influence patients survival. Social differences have been reported by previous studies for those characteristics but questions persist because of inconsistent conclusions. We aimed to investigate the impact of education on BC stage, grade, and hormone receptor (HR) status, while adjusting for potential confounders including a broad set of health behaviors, anthropometric measures, and reproductive factors. METHODS: In the French E3N cohort, 5236 women developed a primary invasive BC for which there was available information on stage, grade, and HR status. No multivariate analyses was performed for BC stage based on the lack of association in bivariate analyses. Odds ratios and confidence intervals were estimated using multinomial logistic regression models for BC grade or binomial logistic regression models for HR status of BC. RESULTS: Women with a lower education were diagnosed with higher grade BC compared to women with a higher education (1.32 [1.12; 1.57]). This association was slightly attenuated after adjustment for covariates independently and more strongly affected in the fully adjusted model (1.20 [0.99; 1.45]). A significant association was observed between lower education and HR- status of BC (1.20 [1.02; 1.42]) attenuated after adjustment for age at first childbirth (1.12 [0.95; 1.33]). CONCLUSION: In this cohort, education was associated with BC grade and HR status but not stage at diagnosis. The link between education and BC grade was not entirely explained by the different adjustments. A specific mechanism could be at play and deserves further investigations.

Early life stress in relation with risk of overweight, depression, and their comorbidity across adulthood: findings from a British birth cohort.

BACKGROUND: Multimorbidity, known as the co-occurrence of at least two chronic conditions, has become of increasing concern in the current context of ageing populations, though it affects all ages. Early life risk factors of multimorbidity include adverse childhood experiences (ACEs), particularly associated with psychological conditions and weight problems. Few studies have considered related mechanisms and focus on old age participants. We are interested in estimating, from young adulthood, the risk of overweight-depression comorbidity related to ACEs while adjusting for early life confounders and intermediate variables. METHODS: We used data from the 1958 National Child Development Study, a prospective birth cohort study (N = 18 558). A four-category outcome (no condition, overweight only, depression only and, overweight-depression comorbidity) was constructed at 23, 33, and 42 years. Multinomial logistic regression models adjusting for intermediate variables co-occurring with this outcome were created. ACEs and sex interaction on comorbidity risk was tested. RESULTS: In our study sample (N = 7762), we found that ACEs were associated with overweight-depression comorbidity risk throughout adulthood (RRR [95% CI] at 23y = 3.80 [2.10-6.88]) though less overtime. Comorbidity risk was larger than risk of separate conditions. Intermediate variables explained part of the association. After full-adjustment, an association remained (RRR [95% CI] at 23y = 2.00 [1.08-3.72]). Comorbidity risk related to ACEs differed by sex at 42. CONCLUSION: Our study provides evidence on the link and potential mechanisms between ACEs and the co-occurrence of mental and physical diseases throughout the life-course. We suggest addressing ACEs in intervention strategies and public policies to go beyond single disease prevention.

The effect of smoking initiation in adolescence on the subsequent smoking trajectories of people who smoke, and the role of adverse childhood experiences: Results from the 1958 British cohort study.

OBJECTIVE: To examine the association between smoking initiation in adolescence and subsequent different smoking trajectories of people who smoke, and to examine the combined effect of adverse childhood experiences (ACEs) and smoking initiation in adolescence on smoking trajectories of people who smoke. DESIGN AND SAMPLE: Data are from 8757 individuals in Great Britain from the birth cohort National Child Development Study and who reported being smokers or former smokers by age 23. MEASUREMENTS: Smoking initiation in adolescence was measured at 16 y and smoking trajectories were derived from smoking variables from ages 23 to 55. We modelled the relationship between smoking initiation in adolescence with or without ACEs and smoking trajectories. RESULTS: Individuals who initiated smoking in adolescence were more likely to quit later than quitting in twenties (RRR quitting in thirties  = 3.43 [2.40; 4.89] p < .001; RRR quitting in forties  = 5.25 [3.38; 8.14] p < .001; RRR quitting in fifties  = 4.48 [2.95; 6.79] p < .001), to relapse (RRR Relapse  = 3.66 [2.82; 4.76] p < .001) and to be persistent smokers (RRR persistent  = 5.25 [3.81; 7.25] p < .001) compared to those who had initiated smoking in young adulthood. These effects were particularly pronounced in case of ACEs. CONCLUSION: Smoking prevention programs aimed at reducing smoking initiation should be promoted to adolescents to limit the burden of smoking, especially for people who have suffered adversity during childhood.

Toward a conceptual framework of health and its operational definition: an application in the 1958 British birth cohort.

BACKGROUND: Defining and measuring Health presents a challenge, partly due to its conceptual pluralism. To measure Health as an ability to adapt and self-manage, we developed an approach within the theoretical framework of resources and reserves over the life course, recently proposed in the literature. We aimed to (i) use the conceptual framework developed to identify indicators of deteriorating health reserves, (ii) construct an overall health measure from these indicators, (iii) evaluate the association between the overall health measure and subsequent health outcomes and (iv) assess the robustness of our method. METHODS: We used data from 7,043 individuals born in 1958 in Great Britain included in the National Child Development Study. An overall health measure was constructed via the sum of three selected indicators of deteriorating health reserves in mid-life: chronic widespread pain (CWP), Clinical Interview Schedule - revised (CIS-r), and allostatic load (AL). A three-category variable was defined: impaired/medium/optimal overall health. We explored criterion validity by modelling the relationships between the overall health measure, or each reserve taken separately at 44-45 years, and self-rated health at 46 years and mortality up to 58 years, corresponding to 14 years of follow up, using Cox and logistic regressions respectively. We performed comparative analyses to assess the robustness of the method. RESULTS: Having an impaired overall health measure was significantly associated with all-cause premature mortality (HRimpaired = 2.74 [1.86; 4.05]) and an increased risk of later fair/poor/very poor self-rated health (ORimpaired = 7.50 [6.29; 8.95]). The overall health measure had a greater effect on the self-rated health estimates than each indicator of deteriorating health reserves considered separately (ORAL medium = 1.82 [1.59; 2.09]; ORAL high = 2.74 [2.37; 3.16]; ORCIS-r = 5.20 [4.45; 6.08]; ORCWP = 2.85 [2.53; 3.21]). CIS-r and allostatic load were also associated with premature mortality contrary to chronic widespread pain (HRAL medium1.82 [1.27; 2.61]; HRAL high = 3.10 [2.19; 4.40]; HRCIS-r = 1.77 [1.22; 2.56]; HRCWP = 1.32 [0.98; 1.76]). The multiple comparative analyses conducted allowed us to assess the robustness of our method within this cohort. CONCLUSIONS: We proposed a method for measuring Health in mid-life in line with the concept of Health as the ability to adapt and self-manage and the concept of health reserves. This method may be applied and further developed within the field of social and positive epidemiology.

Associations of adverse childhood experiences with smoking initiation in adolescence and persistence in adulthood, and the role of the childhood environment: Findings from the 1958 British birth cohort.

Adverse childhood experiences (ACEs) have been identified as a strong determinant of smoking. We aimed to examine the association between ACEs and early smoking initiation and subsequent persistence and the contribution of five pathways including family factors, parental involvement, material living conditions, social activities and conscientiousness. Data are from 7414 individuals born in 1958 in Great Britain included in the National Child Development Study. ACEs were measured at ages 7, 11, and 16. Smoking initiation was derived from smoking variables from ages 16 to 42 and persistent smoking was derived from smoking variables from ages 23 to 42. We modelled the relationship between ACEs and smoking, and further assessed the contribution of each pathway using multinomial logistic regressions. During childhood, 20.9% of respondents experienced one ACE and 6.4% two or more. Those who experienced ACEs had a higher risk of initiating smoking by age 16 and of persistent smoking (RRR initiation by 16y = 1.89 [1.62; 2.20] for one ACE; RRR initiation by 16y = 2.36 [1.81; 3.08] for two or more ACEs, and RRR persistent smoking = 2.07 [1.73; 2.47] for one ACE, RRR persistent smoking = 2.59 [1.92; 3.49] for two or more ACEs). The factors that contributed most to explaining these associations were parental smoking, sibling order and conscientiousness. ACEs remained associated with persistent smoking after further adjusting for young adulthood variables. Smoking prevention measures may need to be tailored when considering adolescents from communities where ACEs are more prevalent to curtail initiation, intensity and persistence. FUNDING: This work was supported by the Institut National du Cancer & the Institut de recherche en santé publique (grant agreement: No. [2019-204]).

The impact of lifecourse socio-economic position and individual social mobility on breast cancer risk.

BACKGROUND: Women with an advantaged socioeconomic position (SEP) have a higher risk of developing breast cancer (BC). The reasons for this association do not seem to be limited to reproductive factors and remain to be understood. We aimed to investigate the impact of lifecourse SEP from childhood and social mobility on the risk of BC considering a broad set of potential mediators. METHODS: We used a discovery-replication strategy in two European prospective cohorts, E3N (N = 83,436) and EPIC-Italy (N = 20,530). In E3N, 7877 women were diagnosed with BC during a median 24.4 years of follow-up, while in EPIC-Italy, 893 BC cases were diagnosed within 15.1 years. Hazard ratios (HR) were estimated using Cox proportional hazard models on imputed data. RESULTS: In E3N, women with higher education had a higher risk of BC (HR [95%CI] = 1.21 [1.12, 1.30]). This association was attenuated by adjusting for reproductive factors, in particular age at first childbirth (HR[95%CI] = 1.13 [1.04, 1.22]). Health behaviours, anthropometric variables, and BC screening had a weaker effect on the association. Women who remained in a stable advantaged SEP had a higher risk of BC (HR [95%CI] = 1.24 [1.07; 1.43]) attenuated after adjustment for potential mediators (HR [95%CI] = 1.13 [0.98; 1.31]). These results were replicated in EPIC-Italy. CONCLUSIONS: These results confirm the important role of reproductive factors in the social gradient in BC risk, which does not appear to be fully explained by the large set of potential mediators, including cancer screening, suggesting that further research is needed to identify additional mechanisms.

Patterning of educational attainment across inflammatory markers: Findings from a multi-cohort study.

BACKGROUND: Evidence suggests that the inflammatory reaction, an adaptive response triggered by a variety of harmful stimuli and conditions involved in the risk and development of many chronic diseases, is a potential pathway through which the socioeconomic environment is biologically embedded. Difficulty in interpreting the role of the inflammatory system in the embodiment dynamic arises because of heterogeneity across studies that use a limited but varied number of inflammatory markers. There is no consensus in the literature as to which inflammatory markers beyond the C-reactive protein and to a lesser extent interleukin 6 are related to the social environment. Accordingly, we aimed to investigate the association between educational attainment, and several markers of inflammation - C-reactive protein, fibrinogen, interleukin 6, interleukin 1ß and tumor necrosis factor α- in 6 European cohort studies. METHODS: Up to 17,470 participants from six European cohort studies with data on educational attainment, health behaviors and lifestyle factors, and at least two different inflammatory markers. Four sub-datasets were drawn with varying numbers of participants to allow pairwise comparison of the social patterning of C-reactive protein and any other inflammatory markers. To evaluate within each sub-dataset the importance of the context and cohort specificities, linear regression-based analyses were performed separately for each cohort and combined in a random effect meta-analysis to determine the relationship between educational attainment and inflammation. RESULTS: We found that the magnitude of the relationship between educational attainment and five inflammatory biomarkers (C-reactive protein, fibrinogen, interleukin 6 and 1ß and tumor necrosis factor α) was variable. By far the most socially patterned biomarker was C-reactive protein, followed by fibrinogen and to lesser extent interleukin 6, where a low educational attainment was associated with higher inflammation even after adjusting for health behaviours and body mass index. No association was found with interleukin 1ß and tumor necrosis factor α. CONCLUSIONS: Our study suggests different educational patterning of inflammatory biomarkers. Further large-scale research is needed to explore social differences in the inflammatory cascade in greater detail and the extent to which these differences contribute to social inequalities in health.

Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease.

AIMS: To characterize serum metabolic signatures associated with atherosclerosis in the coronary or carotid arteries and subsequently their association with incident cardiovascular disease (CVD). METHODS AND RESULTS: We used untargeted one-dimensional (1D) serum metabolic profiling by proton nuclear magnetic resonance spectroscopy (1H NMR) among 3867 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), with replication among 3569 participants from the Rotterdam and LOLIPOP studies. Atherosclerosis was assessed by coronary artery calcium (CAC) and carotid intima-media thickness (IMT). We used multivariable linear regression to evaluate associations between NMR features and atherosclerosis accounting for multiplicity of comparisons. We then examined associations between metabolites associated with atherosclerosis and incident CVD available in MESA and Rotterdam and explored molecular networks through bioinformatics analyses. Overall, 30 1H NMR measured metabolites were associated with CAC and/or IMT, P = 1.3 × 10-14 to 1.0 × 10-6 (discovery) and P = 5.6 × 10-10 to 1.1 × 10-2 (replication). These associations were substantially attenuated after adjustment for conventional cardiovascular risk factors. Metabolites associated with atherosclerosis revealed disturbances in lipid and carbohydrate metabolism, branched chain, and aromatic amino acid metabolism, as well as oxidative stress and inflammatory pathways. Analyses of incident CVD events showed inverse associations with creatine, creatinine, and phenylalanine, and direct associations with mannose, acetaminophen-glucuronide, and lactate as well as apolipoprotein B (P < 0.05). CONCLUSION: Metabolites associated with atherosclerosis were largely consistent between the two vascular beds (coronary and carotid arteries) and predominantly tag pathways that overlap with the known cardiovascular risk factors. We present an integrated systems network that highlights a series of inter-connected pathways underlying atherosclerosis.

Pre-diagnostic blood immune markers, incidence and progression of B-cell lymphoma and multiple myeloma: Univariate and functionally informed multivariate analyses.

Recent prospective studies have shown that dysregulation of the immune system may precede the development of B-cell lymphomas (BCL) in immunocompetent individuals. However, to date, the studies were restricted to a few immune markers, which were considered separately. Using a nested case-control study within two European prospective cohorts, we measured plasma levels of 28 immune markers in samples collected a median of 6 years before diagnosis (range 2.01-15.97) in 268 incident cases of BCL (including multiple myeloma [MM]) and matched controls. Linear mixed models and partial least square analyses were used to analyze the association between levels of immune marker and the incidence of BCL and its main histological subtypes and to investigate potential biomarkers predictive of the time to diagnosis. Linear mixed model analyses identified associations linking lower levels of fibroblast growth factor-2 (FGF-2 p = 7.2 × 10-4 ) and transforming growth factor alpha (TGF-α, p = 6.5 × 10-5 ) and BCL incidence. Analyses stratified by histological subtypes identified inverse associations for MM subtype including FGF-2 (p = 7.8 × 10-7 ), TGF-α (p = 4.08 × 10-5 ), fractalkine (p = 1.12 × 10-3 ), monocyte chemotactic protein-3 (p = 1.36 × 10-4 ), macrophage inflammatory protein 1-alpha (p = 4.6 × 10-4 ) and vascular endothelial growth factor (p = 4.23 × 10-5 ). Our results also provided marginal support for already reported associations between chemokines and diffuse large BCL (DLBCL) and cytokines and chronic lymphocytic leukemia (CLL). Case-only analyses showed that Granulocyte-macrophage colony stimulating factor levels were consistently higher closer to diagnosis, which provides further evidence of its role in tumor progression. In conclusion, our study suggests a role of growth-factors in the incidence of MM and of chemokine and cytokine regulation in DLBCL and CLL.

Allostatic load and subsequent all-cause mortality: which biological markers drive the relationship? Findings from a UK birth cohort.

The concept of allostatic load (AL) refers to the idea of a global physiological 'wear and tear' resulting from the adaptation to the environment through the stress response systems over the life span. The link between socioeconomic position (SEP) and mortality has now been established, and there is evidence that AL may capture the link between SEP and mortality. In order to quantitatively assess the role of AL on mortality, we use data from the 1958 British birth cohort including eleven year mortality in 8,113 adults. Specifically, we interrogate the hypothesis of a cumulative biological risk (allostatic load) reflecting 4 physiological systems potentially predicting future risk of death (N = 132). AL was defined using 14 biomarkers assayed in blood from a biosample collected at 44 years of age. Cox proportional hazard regression analysis revealed that higher allostatic load at 44 years old was a significant predictor of mortality 11 years later [HR = 3.56 (2.3 to 5.53)]. We found that this relationship was not solely related to early-life SEP, adverse childhood experiences and young adulthood health status, behaviours and SEP [HR = 2.57 (1.59 to 4.15)]. Regarding the ability of each physiological system and biomarkers to predict future death, our results suggest that the cumulative measure was advantageous compared to evaluating each physiological system sub-score and biomarker separately. Our findings add some evidence of a biological embodiment in response to stress which ultimately affects mortality.

Improving Visualization and Interpretation of Metabolome-Wide Association Studies: An Application in a Population-Based Cohort Using Untargeted 1H NMR Metabolic Profiling.

1H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum 1H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.

Dynamics of smoking-induced genome-wide methylation changes with time since smoking cessation.

Several studies have recently identified strong epigenetic signals related to tobacco smoking. However, an aspect that did not receive much attention is the evolution of epigenetic changes with time since smoking cessation. We conducted a series of epigenome-wide association studies to capture the dynamics of smoking-induced epigenetic changes after smoking cessation, using genome-wide methylation profiles obtained from blood samples in 745 women from 2 European populations. Two distinct classes of CpG sites were identified: sites whose methylation reverts to levels typical of never smokers within decades after smoking cessation, and sites remaining differentially methylated, even more than 35 years after smoking cessation. Our results suggest that the dynamics of methylation changes following smoking cessation are driven by a differential and site-specific magnitude of the smoking-induced alterations (with persistent sites being most affected) irrespective of the intensity and duration of smoking. Analyses of the link between methylation and expression levels revealed that methylation predominantly and remotely down-regulates gene expression. Among genes whose expression was associated with our candidate CpG sites, LRRN3 appeared to be particularly interesting as it was one of the few genes whose methylation and expression were directly associated, and the only gene in which both methylation and gene expression were found associated with smoking. Our study highlights persistent epigenetic markers of smoking, which can potentially be detected decades after cessation. Such historical signatures are promising biomarkers to refine individual risk profiling of smoking-induced chronic disease such as lung cancer.

Workflow for Integrated Processing of Multicohort Untargeted 1H NMR Metabolomics Data in Large-Scale Metabolic Epidemiology.

Large-scale metabolomics studies involving thousands of samples present multiple challenges in data analysis, particularly when an untargeted platform is used. Studies with multiple cohorts and analysis platforms exacerbate existing problems such as peak alignment and normalization. Therefore, there is a need for robust processing pipelines that can ensure reliable data for statistical analysis. The COMBI-BIO project incorporates serum from ∼8000 individuals, in three cohorts, profiled by six assays in two phases using both 1H NMR and UPLC-MS. Here we present the COMBI-BIO NMR analysis pipeline and demonstrate its fitness for purpose using representative quality control (QC) samples. NMR spectra were first aligned and normalized. After eliminating interfering signals, outliers identified using Hotelling's T2 were removed and a cohort/phase adjustment was applied, resulting in two NMR data sets (CPMG and NOESY). Alignment of the NMR data was shown to increase the correlation-based alignment quality measure from 0.319 to 0.391 for CPMG and from 0.536 to 0.586 for NOESY, showing that the improvement was present across both large and small peaks. End-to-end quality assessment of the pipeline was achieved using Hotelling's T2 distributions. For CPMG spectra, the interquartile range decreased from 1.425 in raw QC data to 0.679 in processed spectra, while the corresponding change for NOESY spectra was from 0.795 to 0.636, indicating an improvement in precision following processing. PCA indicated that gross phase and cohort differences were no longer present. These results illustrate that the pipeline produces robust and reproducible data, successfully addressing the methodological challenges of this large multifaceted study.

GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm.

Genome-wide association studies (GWAS) yielded significant advances in defining the genetic architecture of complex traits and disease. Still, a major hurdle of GWAS is narrowing down multiple genetic associations to a few causal variants for functional studies. This becomes critical in multi-phenotype GWAS where detection and interpretability of complex SNP(s)-trait(s) associations are complicated by complex Linkage Disequilibrium patterns between SNPs and correlation between traits. Here we propose a computationally efficient algorithm (GUESS) to explore complex genetic-association models and maximize genetic variant detection. We integrated our algorithm with a new Bayesian strategy for multi-phenotype analysis to identify the specific contribution of each SNP to different trait combinations and study genetic regulation of lipid metabolism in the Gutenberg Health Study (GHS). Despite the relatively small size of GHS (n  =  3,175), when compared with the largest published meta-GWAS (n > 100,000), GUESS recovered most of the major associations and was better at refining multi-trait associations than alternative methods. Amongst the new findings provided by GUESS, we revealed a strong association of SORT1 with TG-APOB and LIPC with TG-HDL phenotypic groups, which were overlooked in the larger meta-GWAS and not revealed by competing approaches, associations that we replicated in two independent cohorts. Moreover, we demonstrated the increased power of GUESS over alternative multi-phenotype approaches, both Bayesian and non-Bayesian, in a simulation study that mimics real-case scenarios. We showed that our parallel implementation based on Graphics Processing Units outperforms alternative multi-phenotype methods. Beyond multivariate modelling of multi-phenotypes, our Bayesian model employs a flexible hierarchical prior structure for genetic effects that adapts to any correlation structure of the predictors and increases the power to identify associated variants. This provides a powerful tool for the analysis of diverse genomic features, for instance including gene expression and exome sequencing data, where complex dependencies are present in the predictor space.

Integrating genome-wide genetic variations and monocyte expression data reveals trans-regulated gene modules in humans.

One major expectation from the transcriptome in humans is to characterize the biological basis of associations identified by genome-wide association studies. So far, few cis expression quantitative trait loci (eQTLs) have been reliably related to disease susceptibility. Trans-regulating mechanisms may play a more prominent role in disease susceptibility. We analyzed 12,808 genes detected in at least 5% of circulating monocyte samples from a population-based sample of 1,490 European unrelated subjects. We applied a method of extraction of expression patterns-independent component analysis-to identify sets of co-regulated genes. These patterns were then related to 675,350 SNPs to identify major trans-acting regulators. We detected three genomic regions significantly associated with co-regulated gene modules. Association of these loci with multiple expression traits was replicated in Cardiogenics, an independent study in which expression profiles of monocytes were available in 758 subjects. The locus 12q13 (lead SNP rs11171739), previously identified as a type 1 diabetes locus, was associated with a pattern including two cis eQTLs, RPS26 and SUOX, and 5 trans eQTLs, one of which (MADCAM1) is a potential candidate for mediating T1D susceptibility. The locus 12q24 (lead SNP rs653178), which has demonstrated extensive disease pleiotropy, including type 1 diabetes, hypertension, and celiac disease, was associated to a pattern strongly correlating to blood pressure level. The strongest trans eQTL in this pattern was CRIP1, a known marker of cellular proliferation in cancer. The locus 12q15 (lead SNP rs11177644) was associated with a pattern driven by two cis eQTLs, LYZ and YEATS4, and including 34 trans eQTLs, several of them tumor-related genes. This study shows that a method exploiting the structure of co-expressions among genes can help identify genomic regions involved in trans regulation of sets of genes and can provide clues for understanding the mechanisms linking genome-wide association loci to disease.

Educational patterning in biological health seven years apart: Findings from the Tromsø Study.

BACKGROUND: Social-to-biological processes is one set of mechanisms underlying the relationship between social position and health. However, very few studies have focused on the relationship between social factors and biology at multiple time points. This work investigates the relationship between education and the dynamic changes in a composite Biological Health Score (BHS) using two time points seven years apart in a Norwegian adult population. METHODS: We used data from individuals aged 30 years and above who participated in Tromsø6 (2007-2008) and Tromsø7 (2015-2016) (n = 8117). BHS was defined using ten biomarkers measured from blood samples and representing three physiological systems (cardiovascular, metabolic, inflammatory). The higher the BHS, the poorer the health status. FINDINGS: Linear regression models carried out on BHS revealed a strong educational gradient at two distinct time points but also over time. People with lower educational attainment were at higher risk of poor biological health at a given time point (ßlow education Tromsø6=0.30 [95 %-CI=0.18-0.43] and ßlow education Tromsø7=0.30 [95 %-CI=0.17-0.42]). They also presented higher longitudinal BHS compared to people with higher education (ßlow education = 0.89 [95 %-CI=0.56-1.23]). Certain biomarkers related to the cardiovascular system and the metabolic system were strongly socially distributed, even after adjustment for sex, age, health behaviours and body mass index. CONCLUSION: This longitudinal analysis highlights that participants with lower education had their biological health deteriorated to a greater extent over time compared to people with higher education. Our findings provide added evidence of the biological embodiment of social position, particularly with respect to dynamic aspects for which little evidence exists.

Population-based meta-analysis in Caucasians confirms association with COL5A1 and ZNF469 but not COL8A2 with central corneal thickness.

Central corneal thickness (CCT) has become an endophenotype of major interest for the genetically complex disorder glaucoma. CCT has a high heritability, and thin CCT is an independent risk factor for the diagnosis and progression of open-angle glaucoma. Genome-wide association studies thus provide genetic loci associated with CCT and potentially related to open-angle glaucoma. The distribution of CCT and prevalence of glaucoma in population-based studies have demonstrated ethnic differences suggesting ethnic-dependent variations in the genetic determinants of CCT. We conducted a genome-wide association study in Caucasians (n = 3,931) from the Gutenberg Health Study (Germany) followed by replication of 30 genome-wide significant SNPs or SNPs of interest (P < 10(-5)) in the Rotterdam Study (The Netherlands, n = 1,418). In a combined analysis, we confirmed quantitative trait loci on chromosomes 9q34 and 16q24 for association with CCT. On chromosome 16q24, the locus is located in an intergenic region near the ZNF469 gene (top SNP: rs9938149, P = 1.45 × 10(-12)). ZNF469 missense mutation is involved in a syndrome with very thin cornea (brittle cornea syndrome). The second locus on chromosome 9q34 represents the intergenic region between the RXRA and COL5A1 gene (top SNP: rs3132306, P = 2.71 × 10(-10)). Collagen type 5 determines the diameter of the corneal collagen fibrils. In our Caucasian population-based GWA study, we reinforce the involvement of collagen-related genes influencing CCT in Caucasians. We could not confirm the collagen type 8 locus on chromosome 1 as reported in Asian studies.

Influence of sex and genetic variability on expression of X-linked genes in human monocytes.

In humans, the fraction of X-linked genes with higher expression in females has been estimated to be 5% from microarray studies, a proportion lower than the 25% of genes thought to escape X inactivation. We analyzed 715 X-linked transcripts in circulating monocytes from 1,467 subjects and found an excess of female-biased transcripts on the X compared to autosomes (9.4% vs 5.5%, p<2×10(-5)). Among the genes not previously known to escape inactivation, the most significant one was EFHC2 whose 20% of variability was explained by sex. We also investigated cis expression quantitative trait loci (eQTLs) by analyzing 15,703 X-linked SNPs. The frequency and magnitude of X-linked cis eQTLs were quite similar in males and females. Few genes exhibited a stronger genetic effect in females than in males (ARSD, DCX, POLA1 and ITM2A). These genes would deserve further investigation since they may contribute to sex pathophysiological differences.

Assessing How Social Exposures Are Integrated in Exposome Research: A Scoping Review.

BACKGROUND: Exposome research aims to describe and understand the extent to which all the exposures in human environments may affect our health over the lifetime. However, the way in which humans interact with their environment is socially patterned. Failing to account for social factors in research exploring the exposome may underestimate the magnitude of the effect of exposures or mask inequalities in the distribution of both exposures and outcomes. OBJECTIVES: We aimed to describe the extent to which social factors appear in the exposome literature, the manner in which they are used in empirical analyses and statistical modeling, and the way in which they are considered in the overall scientific approach. METHODS: We conducted a scoping review of the literature using three databases (PubMed, Embase, and Web of Science) up to January 2022. We grouped studies based on the way in which the social variables were used in the analyses and quantified the type and frequency of social variables mentioned in the articles. We also qualitatively described the scientific approach used by authors to integrate social variables. RESULTS: We screened 1,001 records, and 73 studies were included in the analysis. Fifty-five (∼75%) used social variables as exposures or confounders or both, and a wide array of social variables were represented in the articles. Individual-level social variables were more often found, especially education and race/ethnicity, as well as neighborhood-level deprivation indices. Half of the studies used a hypothesis-free approach and the other half, a hypothesis-driven approach. However, in the latter group, of 35 studies, only 8 reported and discussed at least one possible social mechanism underlying the relationship observed between the social variable and the outcome. DISCUSSION: Social factors in exposome research should be considered in a more systematic way, considering their role in structuring both the specific external and the internal exposome. Doing so could help to understand the mechanisms of construction and, potentially, alleviate social inequalities in health and mitigate the emergence of new ones. https://doi.org/10.1289/EHP11015.