A Deep Survival EWAS approach estimating risk profile based on pre-diagnostic DNA methylation: An application to breast cancer time to diagnosis.

Previous studies for cancer biomarker discovery based on pre-diagnostic blood DNA methylation (DNAm) profiles, either ignore the explicit modeling of the Time To Diagnosis (TTD), or provide inconsistent results. This lack of consistency is likely due to the limitations of standard EWAS approaches, that model the effect of DNAm at CpG sites on TTD independently. In this work, we aim to identify blood DNAm profiles associated with TTD, with the aim to improve the reliability of the results, as well as their biological meaningfulness. We argue that a global approach to estimate CpG sites effect profile should capture the complex (potentially non-linear) relationships interplaying between sites. To prove our concept, we develop a new Deep Learning-based approach assessing the relevance of individual CpG Islands (i.e., assigning a weight to each site) in determining TTD while modeling their combined effect in a survival analysis scenario. The algorithm combines a tailored sampling procedure with DNAm sites agglomeration, deep non-linear survival modeling and SHapley Additive exPlanations (SHAP) values estimation to aid robustness of the derived effects profile. The proposed approach deals with the common complexities arising from epidemiological studies, such as small sample size, noise, and low signal-to-noise ratio of blood-derived DNAm. We apply our approach to a prospective case-control study on breast cancer nested in the EPIC Italy cohort and we perform weighted gene-set enrichment analyses to demonstrate the biological meaningfulness of the obtained results. We compared the results of Deep Survival EWAS with those of a traditional EWAS approach, demonstrating that our method performs better than the standard approach in identifying biologically relevant pathways.

Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity.

Approximately 1.5 billion people worldwide are overweight or affected by obesity, and are at risk of developing type 2 diabetes, cardiovascular disease and related metabolic and inflammatory disturbances. Although the mechanisms linking adiposity to associated clinical conditions are poorly understood, recent studies suggest that adiposity may influence DNA methylation, a key regulator of gene expression and molecular phenotype. Here we use epigenome-wide association to show that body mass index (BMI; a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci with P < 1 × 10-7, range P = 9.2 × 10-8 to 6.0 × 10-46; n = 10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find that methylation loci are enriched for functional genomic features in multiple tissues (P < 0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P < 9.0 × 10-6, range P = 5.5 × 10-6 to 6.1 × 10-35, n = 1,785 samples). The methylation loci identify genes involved in lipid and lipoprotein metabolism, substrate transport and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future development of type 2 diabetes (relative risk per 1 standard deviation increase in methylation risk score: 2.3 (2.07-2.56); P = 1.1 × 10-54). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type 2 diabetes and other adverse clinical consequences of obesity.

Methylation-based markers of aging and lifestyle-related factors and risk of breast cancer: a pooled analysis of four prospective studies.

BACKGROUND: DNA methylation in blood may reflect adverse exposures accumulated over the lifetime and could therefore provide potential improvements in the prediction of cancer risk. A substantial body of research has shown associations between epigenetic aging and risk of disease, including cancer. Here we aimed to study epigenetic measures of aging and lifestyle-related factors in association with risk of breast cancer. METHODS: Using data from four prospective case-control studies nested in three cohorts of European ancestry participants, including a total of 1,655 breast cancer cases, we calculated three methylation-based measures of lifestyle factors (body mass index [BMI], tobacco smoking and alcohol consumption) and seven measures of epigenetic aging (Horvath-based, Hannum-based, PhenoAge and GrimAge). All measures were regression-adjusted for their respective risk factors and expressed per standard deviation (SD). Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional or unconditional logistic regression and pooled using fixed-effects meta-analysis. Subgroup analyses were conducted by age at blood draw, time from blood sample to diagnosis, oestrogen receptor-positivity status and tumour stage. RESULTS: None of the measures of epigenetic aging were associated with risk of breast cancer in the pooled analysis: Horvath 'age acceleration' (AA): OR per SD = 1.02, 95%CI: 0.95-1.10; AA-Hannum: OR = 1.03, 95%CI:0.95-1.12; PhenoAge: OR = 1.01, 95%CI: 0.94-1.09 and GrimAge: OR = 1.03, 95%CI: 0.94-1.12, in models adjusting for white blood cell proportions, body mass index, smoking and alcohol consumption. The BMI-adjusted predictor of BMI was associated with breast cancer risk, OR per SD = 1.09, 95%CI: 1.01-1.17. The results for the alcohol and smoking methylation-based predictors were consistent with a null association. Risk did not appear to substantially vary by age at blood draw, time to diagnosis or tumour characteristics. CONCLUSION: We found no evidence that methylation-based measures of aging, smoking or alcohol consumption were associated with risk of breast cancer. A methylation-based marker of BMI was associated with risk and may provide insights into the underlying associations between BMI and breast cancer.

Human tissue lead (Pb) levels and amyotrophic lateral sclerosis: a systematic review and meta-analysis of case-control studies.

AIM: To combine the current scientific literature evidence and elucidate the differences of lead (Pb) bioaccumulation in human tissues by comparing amyotrophic lateral sclerosis (ALS) patients and healthy controls. METHODS: We systematically searched for case-control studies on the association of Pb levels with ALS, in human cells, tissues, and body fluids (nervous tissue, muscle, blood, cerebrospinal fluid, urine, skin appendages). Then, we performed a meta-analysis for all the tissues in which at least five case-control studies were available: whole blood (9 studies), serum/plasma (5 studies), and cerebrospinal fluid (CSF) (6 studies). Differences between cases and controls were evaluated using standardized mean difference, and combined estimates were derived using random effect maximum likelihood (REML) meta-analyses. RESULTS: Among 1734 records, we identified 46 full-text studies, of which 14 case-control studies met the meta-analysis inclusion criteria. We found higher Pb levels in ALS cases than controls in blood (standardized mean difference (SMD) = 0.61; 95% confidence interval (CI) 0.20, 1.01; p = 0.003), plasma/serum (SMD = 0.27; 95% CI - 0.16, 0.70; p = 0.26), and CSF (SMD = 0.53; 95% CI - 0.09, 1.15; p = 0.09). CONCLUSIONS: This work provides further evidence of the association between Pb bioaccumulation and ALS in body fluids. The lack of association studies in solid tissues did not allow a robust meta-analysis. Future prospective studies are needed to clarify the causality in the association of Pb bioaccumulation with ALS.

Comparative Evaluation of MaxQuant and Proteome Discoverer MS1-Based Protein Quantification Tools.

MS1-based label-free quantification can compare precursor ion peaks across runs, allowing reproducible protein measurements. Among bioinformatic platforms enabling MS1-based quantification, MaxQuant (MQ) is one of the most used, while Proteome Discoverer (PD) has recently introduced the Minora tool. Here, we present a comparative evaluation of six MS1-based quantification methods available in MQ and PD. Intensity (MQ and PD) and area (PD only) of the precursor ion peaks were measured and then subjected or not to normalization. The six methods were applied to data sets simulating various differential proteomics scenarios and covering a wide range of protein abundance ratios and amounts. PD outperformed MQ in terms of quantification yield, dynamic range, and reproducibility, although neither platform reached a fully satisfactory quality of measurements at low-abundance ranges. PD methods including normalization were the most accurate in estimating the abundance ratio between groups and the most sensitive when comparing groups with a narrow abundance ratio; on the contrary, MQ methods generally reached slightly higher specificity, accuracy, and precision values. Moreover, we found that applying an optimized log ratio-based threshold can maximize specificity, accuracy, and precision. Taken together, these results can help researchers choose the most appropriate MS1-based protein quantification strategy for their studies.

Pre-diagnostic DNA methylation patterns differ according to mammographic breast density amongst women who subsequently develop breast cancer: a case-only study in the EPIC-Florence cohort.

PURPOSE: Mammographic breast density (MBD) is a marker of increased breast cancer (BC) risk, yet much remains to be clarified about the underlying mechanisms. We investigated whether DNA methylation patterns differ between high- vs. low-MBD women who developed BC during an 8.9-year median follow-up in the Florence section of the European Prospective Investigation into Cancer and Nutrition. METHODS: We analysed 96 pairs of women with BC arising on high- vs. low-MBD breasts (BI-RADS category III-IV vs. I). DNA methylation was determined on pre-diagnostic blood samples using the Illumina Infinium MethylationEPIC BeadChip assay. The statistical analysis was conducted by performing an epigenome-wide association study (EWAS), by searching differentially methylated regions (DMRs) in gene promoters (followed by functional enrichment and gene annotation analysis); and through a "candidate pathways" approach focusing on pre-defined inflammation-related pathways. RESULTS: In EWAS, no single CpG site was differentially methylated between high- and low-MBD women after correction for multiple testing. A total of 140 DMRs were identified, of which 131 were hyper- and 9 hypo-methylated amongst high-MBD women. These DMRs encompassed an annotation cluster of 35 genes coding for proteins implicated in transcription regulation and DNA binding. The "apoptosis signalling" was the only inflammation-related candidate pathway differentially methylated between high- and low-MBD women. CONCLUSION: Pre-diagnostic methylation patterns differ between high- vs. low-MBD women who subsequently develop BC, particularly, in genes involved in the regulation of DNA transcription and cell apoptosis. Our study provides novel clues about the mechanisms linking MBD and BC.

Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease.

BACKGROUND: DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS: Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS: Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION: Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.

Agnostic Cys34-albumin adductomics and DNA methylation: Implication of N-acetylcysteine in lung carcinogenesis years before diagnosis.

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.

Phenome-wide association analysis of LDL-cholesterol lowering genetic variants in PCSK9.

BACKGROUND: We characterised the phenotypic consequence of genetic variation at the PCSK9 locus and compared findings with recent trials of pharmacological inhibitors of PCSK9. METHODS: Published and individual participant level data (300,000+ participants) were combined to construct a weighted PCSK9 gene-centric score (GS). Seventeen randomized placebo controlled PCSK9 inhibitor trials were included, providing data on 79,578 participants. Results were scaled to a one mmol/L lower LDL-C concentration. RESULTS: The PCSK9 GS (comprising 4 SNPs) associations with plasma lipid and apolipoprotein levels were consistent in direction with treatment effects. The GS odds ratio (OR) for myocardial infarction (MI) was 0.53 (95% CI 0.42; 0.68), compared to a PCSK9 inhibitor effect of 0.90 (95% CI 0.86; 0.93). For ischemic stroke ORs were 0.84 (95% CI 0.57; 1.22) for the GS, compared to 0.85 (95% CI 0.78; 0.93) in the drug trials. ORs with type 2 diabetes mellitus (T2DM) were 1.29 (95% CI 1.11; 1.50) for the GS, as compared to 1.00 (95% CI 0.96; 1.04) for incident T2DM in PCSK9 inhibitor trials. No genetic associations were observed for cancer, heart failure, atrial fibrillation, chronic obstructive pulmonary disease, or Alzheimer's disease - outcomes for which large-scale trial data were unavailable. CONCLUSIONS: Genetic variation at the PCSK9 locus recapitulates the effects of therapeutic inhibition of PCSK9 on major blood lipid fractions and MI. While indicating an increased risk of T2DM, no other possible safety concerns were shown; although precision was moderate.

Association of DNA Methylation-Based Biological Age With Health Risk Factors and Overall and Cause-Specific Mortality.

Measures of biological age based on blood DNA methylation, referred to as age acceleration (AA), have been developed. We examined whether AA was associated with health risk factors and overall and cause-specific mortality. At baseline (1990-1994), blood samples were drawn from 2,818 participants in the Melbourne Collaborative Cohort Study (Melbourne, Victoria, Australia). DNA methylation was determined using the Infinium HumanMethylation450 BeadChip array (Illumina Inc., San Diego, California). Mixed-effects models were used to examine the association of AA with health risk factors. Cox models were used to assess the association of AA with mortality. A total of 831 deaths were observed during a median 10.7 years of follow-up. Associations of AA were observed with male sex, Greek nationality (country of birth), smoking, obesity, diabetes, lower education, and meat intake. AA measures were associated with increased mortality, and this was only partly accounted for by known determinants of health (hazard ratios were attenuated by 20%-40%). Weak evidence of heterogeneity in the association was observed by sex (P = 0.06) and cause of death (P = 0.07) but not by other factors. DNA-methylation-based AA measures are associated with several major health risk factors, but these do not fully explain the association between AA and mortality. Future research should investigate what genetic and environmental factors determine AA.

Identification of a novel susceptibility locus at 13q34 and refinement of the 20p12.2 region as a multi-signal locus associated with bladder cancer risk in individuals of European ancestry.

Candidate gene and genome-wide association studies (GWAS) have identified 15 independent genomic regions associated with bladder cancer risk. In search for additional susceptibility variants, we followed up on four promising single-nucleotide polymorphisms (SNPs) that had not achieved genome-wide significance in 6911 cases and 11 814 controls (rs6104690, rs4510656, rs5003154 and rs4907479, P < 1 × 10(-6)), using additional data from existing GWAS datasets and targeted genotyping for studies that did not have GWAS data. In a combined analysis, which included data on up to 15 058 cases and 286 270 controls, two SNPs achieved genome-wide statistical significance: rs6104690 in a gene desert at 20p12.2 (P = 2.19 × 10(-11)) and rs4907479 within the MCF2L gene at 13q34 (P = 3.3 × 10(-10)). Imputation and fine-mapping analyses were performed in these two regions for a subset of 5551 bladder cancer cases and 10 242 controls. Analyses at the 13q34 region suggest a single signal marked by rs4907479. In contrast, we detected two signals in the 20p12.2 region-the first signal is marked by rs6104690, and the second signal is marked by two moderately correlated SNPs (r(2) = 0.53), rs6108803 and the previously reported rs62185668. The second 20p12.2 signal is more strongly associated with the risk of muscle-invasive (T2-T4 stage) compared with non-muscle-invasive (Ta, T1 stage) bladder cancer (case-case P ≤ 0.02 for both rs62185668 and rs6108803). Functional analyses are needed to explore the biological mechanisms underlying these novel genetic associations with risk for bladder cancer.

Epigenome-wide association study of adiposity and future risk of obesity-related diseases.

BACKGROUND: Obesity is an established risk factor for several common chronic diseases such as breast and colorectal cancer, metabolic and cardiovascular diseases; however, the biological basis for these relationships is not fully understood. To explore the association of obesity with these conditions, we investigated peripheral blood leucocyte (PBL) DNA methylation markers for adiposity and their contribution to risk of incident breast and colorectal cancer and myocardial infarction. METHODS: DNA methylation profiles (Illumina Infinium® HumanMethylation450 BeadChip) from 1941 individuals from four population-based European cohorts were analysed in relation to body mass index, waist circumference, waist-hip and waist-height ratio within a meta-analytical framework. In a subset of these individuals, data on genome-wide gene expression level, biomarkers of glucose and lipid metabolism were also available. Validation of methylation markers associated with all adiposity measures was performed in 358 individuals. Finally, we investigated the association of obesity-related methylation marks with breast, colorectal cancer and myocardial infarction within relevant subsets of the discovery population. RESULTS: We identified 40 CpG loci with methylation levels associated with at least one adiposity measure. Of these, one CpG locus (cg06500161) in ABCG1 was associated with all four adiposity measures (P = 9.07×10-8 to 3.27×10-18) and lower transcriptional activity of the full-length isoform of ABCG1 (P = 6.00×10-7), higher triglyceride levels (P = 5.37×10-9) and higher triglycerides-to-HDL cholesterol ratio (P = 1.03×10-10). Of the 40 informative and obesity-related CpG loci, two (in IL2RB and FGF18) were significantly associated with colorectal cancer (inversely, P < 1.6×10-3) and one intergenic locus on chromosome 1 was inversely associated with myocardial infarction (P < 1.25×10-3), independently of obesity and established risk factors. CONCLUSION: Our results suggest that epigenetic changes, in particular altered DNA methylation patterns, may be an intermediate biomarker at the intersection of obesity and obesity-related diseases, and could offer clues as to underlying biological mechanisms.

Novel approach identifies SNPs in SLC2A10 and KCNK9 with evidence for parent-of-origin effect on body mass index.

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.

H2AX phosphorylation level in peripheral blood mononuclear cells as an event-free survival predictor for bladder cancer.

Bladder cancer (BC) has a typical aetiology characterized by a multistep carcinogenesis due to environmental exposures, genetic susceptibility, and their interaction. Several lines of evidence suggest that DNA repair plays a role in the development and progression of BC. In particular, the study of individual susceptibility to DNA double strand breaks (DSBs) may provide valuable information on BC risk, and help to identify those patients at high-risk of either recurrence or progression of the disease, possibly personalizing both surveillance and treatment. Among the different DSB markers, the most well characterized is phosphorylation of the histone H2AX (γ-H2AX). We assessed any potential role of γ-H2AX as a molecular biomarker in a case-control study (146 cases and 146 controls) to identify individuals with increased BC risk and at high-risk of disease recurrence or progression. We investigated γ-H2AX levels in peripheral blood mononuclear cells before and after their exposure to ionizing radiation (IR). We did not find any significant difference among cases and controls. However, we observed a significant association between γ-H2AX basal levels and risk of disease recurrence or progression. In particular, both BC patients as a whole and the subgroup of non-muscle invasive BC (NMIBC) with high basal H2AX phosphorylation levels had a decreased risk of recurrence or progression (for all BC HR 0.70, 95%CI 0.52-0.94, P = 0.02; for NMIBC HR 0.68, 95%CI 0.50-0.92, P = 0.01), suggesting a protective effect of basal DSB signaling. Our data suggest that γ-H2AX can be considered as a potential molecular biomarker to identify patients with a higher risk of BC recurrence. © 2015 Wiley Periodicals, Inc.

Association between Beta1 -Adrenergic Receptor Polymorphism and Risk of ICD Shock in Heart Failure Patients.

BACKGROUND: Sympathetic activation in heart failure patients favors the development of ventricular arrhythmias, thus leading to an increased risk of sudden cardiac death. ß1 - and ß2 -adrenergic receptor polymorphisms have been linked to the risk of sudden death. Implantable cardioverter-defibrillators (ICD) are implanted in a large percentage of heart failure patients, and beyond preventing sudden cardiac death they provide a continuous monitoring of major ventricular arrhythmias and of their own interventions. We investigated whether functionally relevant ß1 - and ß2 -adrenergic receptor polymorphisms are associated with risk of ICD shocks, as evidenced in ICD memory. METHODS: 311 patients with systolic heart failure were enrolled, and number and timing of shocks in ICD memory were recorded. Four selected polymorphisms were determined: ß1 -adrenergic receptor polymorphisms Ser(49) Gly and Arg(389) Gly and ß2 -adrenergic receptor polymorphisms Arg(16) Gly and Gln(27) Glu. RESULTS: Only Ser(49) Gly was significantly correlated with time free from ICD shocks, both considering time to the first event in a Cox model (hazard ratio 2.117), and modeling repeated events with the Andersen-Gill method (hazard ratio 2.088). Gly allele carriers had a higher probability of ICD shock. The relationship remained significant even after adjusting for ejection fraction and beta-blocker dosage (hazard ratio 1.910). CONCLUSIONS: Data from our study suggest that the ß adrenoreceptor Gly 49 allele of the ß1 -adrenergic receptor Ser(49) Gly polymorphisms may increase the risk of ICD shock in patients with heart failure, independent of beta-blocker dosage.

Differentially methylated microRNAs in prediagnostic samples of subjects who developed breast cancer in the European Prospective Investigation into Nutrition and Cancer (EPIC-Italy) cohort.

The crosstalk between microRNAs (miRNAs) and other epigenetic factors may lead to novel hypotheses about carcinogenesis identifying new targets for research. Because a single miRNA can regulate multiple downstream target genes, its altered expression may potentially be a sensitive biomarker to detect early malignant transformation and improve diagnosis and prognosis. In the current study, we tested the hypothesis that altered methylation of miRNA encoding genes, associated with deregulated mature miRNA expression, may be related to dietary and lifestyle factors and may contribute to cancer development. In a case-control study nested in a prospective cohort (EPIC-Italy), we analysed DNA methylation levels of miRNA encoding genes (2191 CpG probes related to 517 genes) that are present in the Infinium Human Methylation450 BeadChip array in prediagnostic peripheral white blood cells of subjects who developed colorectal cancer (CRC, n = 159) or breast cancer (BC, n = 166) and matched subjects who remained clinically healthy. In the whole cohort, several differentially methylated miRNA genes were observed in association with age, sex, smoking habits and physical activity. Interestingly, in the case-control study, eight differentially methylated miRNAs were identified in subjects who went on to develop BC (miR-328, miR-675, miR-1307, miR-1286, miR-1275, miR-1910, miR-24-1 and miR-548a-1; all Bonferroni-adjusted P < 0.05). No significant associations were found with CRC. Assuming that altered methylation of miRNAs detectable in blood may be present before diagnosis, it may represent a biomarker for early detection or risk of cancer and may help to understand the cascade of events preceding tumour onset.

Gene-asbestos interaction in malignant pleural mesothelioma susceptibility.

Asbestos exposure is the main risk factor for malignant pleural mesothelioma (MPM), a rare aggressive tumor. Nevertheless, on average less than 10% of subjects highly exposed to asbestos develop MPM, suggesting the possible involvement of other risk factors. To identify the genetic factors that may modulate the risk of MPM, we conducted a gene-environment interaction analysis including asbestos exposure and 15 single nucleotide polymorphisms (SNPs) previously identified through a genome-wide association study on Italian subjects. In the present study, we assessed gene-asbestos interaction on MPM risk using relative excess risk due to interaction and synergy index for additive interaction and V index for multiplicative interaction. Generalized multifactor dimensionality reduction (GMDR) analyses were also performed. Positive deviation from additivity was found for six SNPs (rs1508805, rs2501618, rs4701085, rs4290865, rs10519201, rs763271), and four of them (rs1508805, rs2501618, rs4701085, rs10519201) deviated also from multiplicative models. However, after Bonferroni correction, deviation from multiplicative model was still significant for rs1508805 and rs4701085 only. GMDR analysis showed a strong MPM risk due to asbestos exposure and suggested a possible synergistic effect between asbestos exposure and rs1508805, rs2501618 and rs5756444. Our results suggested that gene-asbestos interaction may play an additional role on MPM susceptibility, given that asbestos exposure appears as the main risk factor.

Metaproteomic portrait of the healthy human gut microbiota.

Gut metaproteomics can provide direct evidence of microbial functions actively expressed in the colonic environments, contributing to clarify the role of the gut microbiota in human physiology. In this study, we re-analyzed 10 fecal metaproteomics datasets of healthy individuals from different continents and countries, with the aim of identifying stable and variable gut microbial functions and defining the contribution of specific bacterial taxa to the main metabolic pathways. The "core" metaproteome included 182 microbial functions and 83 pathways that were identified in all individuals analyzed. Several enzymes involved in glucose and pyruvate metabolism, along with glutamate dehydrogenase, acetate kinase, elongation factors G and Tu and DnaK, were the proteins with the lowest abundance variability in the cohorts under study. On the contrary, proteins involved in chemotaxis, response to stress and cell adhesion were among the most variable functions. Random-effect meta-analysis of correlation trends between taxa, functions and pathways revealed key ecological and molecular associations within the gut microbiota. The contribution of specific bacterial taxa to the main biological processes was also investigated, finding that Faecalibacterium is the most stable genus and the top contributor to anti-inflammatory butyrate production in the healthy gut microbiota. Active production of other mucosal immunomodulators facilitating host tolerance was observed, including Roseburia flagellin and lipopolysaccharide biosynthetic enzymes expressed by members of Bacteroidota. Our study provides a detailed picture of the healthy human gut microbiota, contributing to unveil its functional mechanisms and its relationship with nutrition, immunity, and environmental stressors.

DNA methylation-based biomarkers for cardiometabolic-related traits and their importance for risk stratification.

Recent findings: The prevalence of cardiometabolic syndrome in adults is increasing worldwide, highlighting the importance of biomarkers for individuals' classification based on their health status. Although cardiometabolic risk scores and diagnostic criteria have been developed aggregating adverse health effects of individual conditions on the overall syndrome, none of them has gained unanimous acceptance. Therefore, novel molecular biomarkers have been developed to better understand the risk, onset and progression of both individual conditions and the overall cardiometabolic syndrome. Summary: Consistent associations between whole blood DNA methylation (DNAm) levels at several single genomic (i.e. CpG) sites and both individual and aggregated cardiometabolic conditions supported the creation of second-generation DNAm-based cardiometabolic-related biomarkers. These biomarkers linearly combine individual DNAm levels from key CpG sites, selected by a two-step machine learning procedures. They can be used, even retrospectively, in populations with extant whole blood DNAm levels and without observed cardiometabolic phenotypes. Purpose of review: Here we offer an overview of the second-generation DNAm-based cardiometabolic biomarkers, discussing methodological advancements and implications on the interpretation and generalizability of the findings. We finally emphasize the contribution of DNAm-based biomarkers for risk stratification beyond traditional factors and discuss limitations and future directions of the field.

Early life adversity and age acceleration at mid-life and older ages indexed using the next-generation GrimAge and Pace of Aging epigenetic clocks.

OBJECTIVE: This retrospective cross-sectional study was designed to explore whether the experience of childhood adversity was associated with epigenetic age acceleration in mid-life and older ages using the next generation GrimAge and Pace of Aging DNA methylation clocks. METHOD: The study involved a sub-sample of 490 individuals aged 50-87 years of age participating in the Irish Longitudinal Study on Aging (TILDA); a large nationally representative prospective cohort study of aging in Ireland. Childhood adversity was ascertained via self-report using 5-items that were deemed to indicate potentially nefarious childhood exposures, including growing up poor, death of a parent, parental substance abuse in the family, childhood physical abuse, and childhood sexual abuse. RESULTS: Only childhood poverty was associated with significant epigenetic age acceleration according to the GrimAge and Pace of Aging clocks, hastening biological aging by 2.04 years [CI= 1.07, 3.00; p < 0.001] and 1.16 years [CI= 0.11, 2.21; p = 0.030] respectively. Analysis of the dose-response pattern revealed each additional adversity was associated with 0.69 years of age acceleration [CI= 0.23, 1.15; p = 0.004] according to the GrimAge clock. Mediation analysis suggested that lifetime smoking explains a substantial portion (>50%) of the excess risk of age acceleration amongst those who experienced childhood poverty. CONCLUSIONS: This study adds to the growing body of evidence which implicates early life adversity, particularly deprivation as a potential precipitant of earlier biological aging, and implicates smoking-related changes to DNA methylation processes as a candidate pathway and mechanism through which the social environment gets transduced at a biological level to hasten the aging process.