Thymine DNA glycosylase regulates cell-cycle-driven p53 transcriptional control in pluripotent cells.

Cell cycle progression is linked to transcriptome dynamics and variations in the response of pluripotent cells to differentiation cues, mostly through unknown determinants. Here, we characterized the cell-cycle-associated transcriptome and proteome of mouse embryonic stem cells (mESCs) in naive ground state. We found that the thymine DNA glycosylase (TDG) is a cell-cycle-regulated co-factor of the tumor suppressor p53. Furthermore, TDG and p53 co-bind ESC-specific cis-regulatory elements and thereby control transcription of p53-dependent genes during self-renewal. We determined that the dynamic expression of TDG is required to promote the cell-cycle-associated transcriptional heterogeneity. Moreover, we demonstrated that transient depletion of TDG influences cell fate decisions during the early differentiation of mESCs. Our findings reveal an unanticipated role of TDG in promoting molecular heterogeneity during the cell cycle and highlight the central role of protein dynamics for the temporal control of cell fate during development.

IκB kinase-α coordinates BRD4 and JAK/STAT signaling to subvert DNA damage-based anticancer therapy.

Activation of the IκB kinase (IKK) complex has recurrently been linked to colorectal cancer (CRC) initiation and progression. However, identification of downstream effectors other than NF-κB has remained elusive. Here, analysis of IKK-dependent substrates in CRC cells after UV treatment revealed that phosphorylation of BRD4 by IKK-α is required for its chromatin-binding at target genes upon DNA damage. Moreover, IKK-α induces the NF-κB-dependent transcription of the cytokine LIF, leading to STAT3 activation, association with BRD4 and recruitment to specific target genes. IKK-α abrogation results in defective BRD4 and STAT3 functions and consequently irreparable DNA damage and apoptotic cell death upon different stimuli. Simultaneous inhibition of BRAF-dependent IKK-α activity, BRD4, and the JAK/STAT pathway enhanced the therapeutic potential of 5-fluorouracil combined with irinotecan in CRC cells and is curative in a chemotherapy-resistant xenograft model. Finally, coordinated expression of LIF and IKK-α is a poor prognosis marker for CRC patients. Our data uncover a functional link between IKK-α, BRD4, and JAK/STAT signaling with clinical relevance.

IKKα Kinase Regulates the DNA Damage Response and Drives Chemo-resistance in Cancer.

Phosphorylated IKKα(p45) is a nuclear active form of the IKKα kinase that is induced by the MAP kinases BRAF and TAK1 and promotes tumor growth independent of canonical NF-κB signaling. Insights into the sources of IKKα(p45) activation and its downstream substrates in the nucleus remain to be defined. Here, we discover that IKKα(p45) is rapidly activated by DNA damage independent of ATM-ATR, but dependent on BRAF-TAK1-p38-MAPK, and is required for robust ATM activation and efficient DNA repair. Abolishing BRAF or IKKα activity attenuates ATM, Chk1, MDC1, Kap1, and 53BP1 phosphorylation, compromises 53BP1 and RIF1 co-recruitment to sites of DNA lesions, and inhibits 53BP1-dependent fusion of dysfunctional telomeres. Furthermore, IKKα or BRAF inhibition synergistically enhances the therapeutic potential of 5-FU and irinotecan to eradicate chemotherapy-resistant metastatic human tumors in vivo. Our results implicate BRAF and IKKα kinases in the DDR and reveal a combination strategy for cancer treatment.

Effectiveness of a Meningococcal Group B Vaccine (4CMenB) in Children.

BACKGROUND: In September 2015, the four-component, protein-based meningococcal serogroup B vaccine (4CMenB; Bexsero) became available for private purchase in Spain. METHODS: We conducted a nationwide matched case-control study to assess the effectiveness of 4CMenB in preventing invasive meningococcal disease in children. The study included all laboratory-confirmed cases of invasive meningococcal disease in children younger than 60 months of age between October 5, 2015, and October 6, 2019, in Spain. Each case patient was matched with four controls according to date of birth and province. 4CMenB vaccination status of the case patients and controls was compared with the use of multivariate conditional logistic regression. RESULTS: We compared 306 case patients (243 [79.4%] with serogroup B disease) with 1224 controls. A total of 35 case patients (11.4%) and 298 controls (24.3%) had received at least one dose of 4CMenB. The effectiveness of complete vaccination with 4CMenB (defined as receipt of at least 2 doses, administered in accordance with the manufacturer's recommendations) was 76% (95% confidence interval [CI], 57 to 87) against invasive meningococcal disease caused by any serogroup, and partial vaccination was 54% (95% CI, 18 to 74) effective. Complete vaccination resulted in an effectiveness of 71% (95% CI, 45 to 85) against meningococcal serogroup B disease. Vaccine effectiveness with at least one dose of 4CMenB was 64% (95% CI, 41 to 78) against serogroup B disease and 82% (95% CI, 21 to 96) against non-serogroup B disease. With the use of the genetic Meningococcal Antigen Typing System, serogroup B strains that were expected to be covered by 4CMenB were detected in 44 case patients, none of whom had been vaccinated. CONCLUSIONS: Complete vaccination with 4CMenB was found to be effective in preventing invasive disease by serogroup B and non-serogroup B meningococci in children younger than 5 years of age.

Data-Driven Approach to Modeling Microfabricated Chemical Sensor Manufacturing.

We have developed a statistical model-based approach to the quality analysis (QA) and quality control (QC) of a gas micro pre-concentrator chip (µPC) performance when manufactured at scale for chemical and biochemical analysis of volatile organic compounds (VOCs). To test the proposed model, a medium-sized university-led production batch of 30 wafers of chips were subjected to rigorous chemical performance testing. We quantitatively report the outcomes of each manufacturing process step leading to the final functional chemical sensor chip. We implemented a principal component analysis (PCA) model to score individual chip chemical performance, and we observed that the first two principal components represent 74.28% of chemical testing variance with 111 of 118 viable chips falling into the 95% confidence interval. Chemical performance scores and chip manufacturing data were analyzed using a multivariate regression model to determine the most influential manufacturing parameters and steps. In our analysis, we find the amount of sorbent mass present in the chip (variable importance score = 2.6) and heater and the RTD resistance values (variable importance score = 1.1) to be the manufacturing parameters with the greatest impact on chemical performance. Other non-obvious latent manufacturing parameters also had quantified influence. Statistical distributions for each manufacturing step will allow future large-scale production runs to be statistically sampled during production to perform QA/QC in a real-time environment. We report this study as the first data-driven, model-based production of a microfabricated chemical sensor.

A Metabolomics Assay to Diagnose Citrus Huanglongbing Disease and to Aid in Assessment of Treatments to Prevent or Cure Infection.

Citrus greening disease, or Huanglongbing (HLB), has devastated citrus crops globally in recent years. The causal bacterium, 'Candidatus Liberibacter asiaticus', presents a sampling issue for qPCR diagnostics and results in a high false negative rate. In this work, we compared six metabolomics assays to identify HLB-infected citrus trees from leaf tissue extracted from 30 control and 30 HLB-infected trees. A liquid chromatography-mass spectrometry-based assay was most accurate. A final partial least squares-discriminant analysis (PLS-DA) model was trained and validated on 690 leaf samples with corresponding qPCR measures from three citrus varieties (Rio Red grapefruit, Hamlin sweet orange, and Valencia sweet orange) from orchards in Florida and Texas. Trees were naturally infected with HLB transmitted by the insect vector Diaphorina citri. In a randomized validation set, the assay was 99.9% accurate to classify diseased from nondiseased samples. This model was applied to samples from trees receiving plant defense-inducer compounds or biological treatments to prevent or cure HLB infection. From two trials, HLB-related metabolite abundances and PLS-DA scores were tracked longitudinally and compared with those of control trees. We demonstrate how our assay can assess tree health and the efficacy of HLB treatments and conclude that no trialed treatment was efficacious.

Mass Spectrometry Identification of Biomarkers in Extracellular Vesicles From Plasmodium vivax Liver Hypnozoite Infections.

Latent liver stages termed hypnozoites cause relapsing Plasmodium vivax malaria infection and represent a major obstacle in the goal of malaria elimination. Hypnozoites are clinically undetectable, and presently, there are no biomarkers of this persistent parasite reservoir in the human liver. Here, we have identified parasite and human proteins associated with extracellular vesicles (EVs) secreted from in vivo infections exclusively containing hypnozoites. We used P. vivax-infected human liver-chimeric (huHEP) FRG KO mice treated with the schizonticidal experimental drug MMV048 as hypnozoite infection model. Immunofluorescence-based quantification of P. vivax liver forms showed that MMV048 removed schizonts from chimeric mice livers. Proteomic analysis of EVs derived from FRG huHEP mice showed that human EV cargo from infected FRG huHEP mice contain inflammation markers associated with active schizont replication and identified 66 P. vivax proteins. To identify hypnozoite-specific proteins associated with EVs, we mined the proteome data from MMV048-treated mice and performed an analysis involving intragroup and intergroup comparisons across all experimental conditions followed by a peptide compatibility analysis with predicted spectra to warrant robust identification. Only one protein fulfilled this stringent top-down selection, a putative filamin domain-containing protein. This study sets the stage to unveil biological features of human liver infections and identify biomarkers of hypnozoite infection associated with EVs.

Melanoma RBPome identification reveals PDIA6 as an unconventional RNA-binding protein involved in metastasis.

RNA-binding proteins (RBPs) have been relatively overlooked in cancer research despite their contribution to virtually every cancer hallmark. Here, we use RNA interactome capture (RIC) to characterize the melanoma RBPome and uncover novel RBPs involved in melanoma progression. Comparison of RIC profiles of a non-tumoral versus a metastatic cell line revealed prevalent changes in RNA-binding capacities that were not associated with changes in RBP levels. Extensive functional validation of a selected group of 24 RBPs using five different in vitro assays unveiled unanticipated roles of RBPs in melanoma malignancy. As proof-of-principle we focused on PDIA6, an ER-lumen chaperone that displayed a novel RNA-binding activity. We show that PDIA6 is involved in metastatic progression, map its RNA-binding domain, and find that RNA binding is required for PDIA6 tumorigenic properties. These results exemplify how RIC technologies can be harnessed to uncover novel vulnerabilities of cancer cells.

A combination of molecular and clinical parameters provides a new strategy for high-grade serous ovarian cancer patient management.

BACKGROUND: High-grade serous carcinoma (HGSC) is the most common and deadly subtype of ovarian cancer. Although most patients will initially respond to first-line treatment with a combination of surgery and platinum-based chemotherapy, up to a quarter will be resistant to treatment. We aimed to identify a new strategy to improve HGSC patient management at the time of cancer diagnosis (HGSC-1LTR). METHODS: A total of 109 ready-available formalin-fixed paraffin-embedded HGSC tissues obtained at the time of HGSC diagnosis were selected for proteomic analysis. Clinical data, treatment approach and outcomes were collected for all patients. An initial discovery cohort (n = 21) were divided into chemoresistant and chemosensitive groups and evaluated using discovery mass-spectrometry (MS)-based proteomics. Proteins showing differential abundance between groups were verified in a verification cohort (n = 88) using targeted MS-based proteomics. A logistic regression model was used to select those proteins able to correctly classify patients into chemoresistant and chemosensitive. The classification performance of the protein and clinical data combinations were assessed through the generation of receiver operating characteristic (ROC) curves. RESULTS: Using the HGSC-1LTR strategy we have identified a molecular signature (TKT, LAMC1 and FUCO) that combined with ready available clinical data (patients' age, menopausal status, serum CA125 levels, and treatment approach) is able to predict patient response to first-line treatment with an AUC: 0.82 (95% CI 0.72-0.92). CONCLUSIONS: We have established a new strategy that combines molecular and clinical parameters to predict the response to first-line treatment in HGSC patients (HGSC-1LTR). This strategy can allow the identification of chemoresistance at the time of diagnosis providing the optimization of therapeutic decision making and the evaluation of alternative treatment strategies. Thus, advancing towards the improvement of patient outcome and the individualization of HGSC patients' care.

In Utero Exposure to Mercury Is Associated With Increased Susceptibility to Liver Injury and Inflammation in Childhood.

BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most prevalent cause of liver disease in children. Mercury (Hg), a ubiquitous toxic metal, has been proposed as an environmental factor contributing to toxicant-associated fatty liver disease. APPROACH AND RESULTS: We investigated the effect of prenatal exposure to Hg on childhood liver injury by combining epidemiological results from a multicenter mother-child cohort with complementary in vitro experiments on monocyte cells that are known to play a key role in liver immune homeostasis and NAFLD. We used data from 872 mothers and their children (median age, 8.1 years; interquartile range [IQR], 6.5-8.7) from the European Human Early-Life Exposome cohort. We measured Hg concentration in maternal blood during pregnancy (median, 2.0 µg/L; IQR, 1.1-3.6). We also assessed serum levels of alanine aminotransferase (ALT), a common screening tool for pediatric NAFLD, and plasma concentrations of inflammation-related cytokines in children. We found that prenatal Hg exposure was associated with a phenotype in children that was characterized by elevated ALT (≥22.1 U/L for females and ≥25.8 U/L for males) and increased concentrations of circulating IL-1ß, IL-6, IL-8, and TNF-α. Consistently, inflammatory monocytes exposed in vitro to a physiologically relevant dose of Hg demonstrated significant up-regulation of genes encoding these four cytokines and increased concentrations of IL-8 and TNF-α in the supernatants. CONCLUSIONS: These findings suggest that developmental exposure to Hg can contribute to inflammation and increased NAFLD risk in early life.

Short- and medium-term air pollution exposure, plasmatic protein levels and blood pressure in children.

Exposure to air pollution influences children's health, however, the biological mechanisms underlying these effects are not completely elucidated. We investigated the association between short- and medium-term outdoor air pollution exposure with protein profiles and their link with blood pressure in 1170 HELIX children aged 6-11 years. Different air pollutants (NO2, PM10, PM2.5, and PM2.5abs) were estimated based on residential and school addresses at three different windows of exposure (1-day, 1-week, and 1-year before clinical and molecular assessment). Thirty-six proteins, including adipokines, cytokines, or apolipoproteins, were measured in children's plasma using Luminex. Systolic and diastolic blood pressure (SBP and DBP) were measured following a standardized protocol. We performed an association study for each air pollutant at each location and time window and each outcome, adjusting for potential confounders. After correcting for multiple-testing, hepatocyte growth factor (HGF) and interleukin 8 (IL8) levels were positively associated with 1-week home exposure to some of the pollutants (NO2, PM10, or PM2.5). NO2 1-week home exposure was also related to higher SBP. The mediation study suggested that HGF could explain 19% of the short-term effect of NO2 on blood pressure, but other study designs are needed to prove the causal directionality between HGF and blood pressure.

QCloud2: An Improved Cloud-based Quality-Control System for Mass-Spectrometry-based Proteomics Laboratories.

QCloud is a cloud-based system to support proteomics laboratories in daily quality assessment using a user-friendly interface, easy setup, and automated data processing. Since its release, QCloud has facilitated automated quality control for proteomics experiments in many laboratories. QCloud provides a quick and effortless evaluation of instrument performance that helps to overcome many analytical challenges derived from clinical and translational research. Here we present an improved version of the system, QCloud2. This new version includes enhancements in the scalability and reproducibility of the quality-control pipelines, and it features an improved front end for data visualization, user management, and chart annotation. The QCloud2 system also includes programmatic access and a standalone local version.

Use of Linear Ion Traps in Data-Independent Acquisition Methods Benefits Low-Input Proteomics.

The need for a better understanding of cellular heterogeneity has pushed mass spectrometry technologies to the analysis of single-cell and single-cell-type proteomes, although several challenges still limit their widespread implementation. Among the efforts toward single-cell and low-input analyses, there is the adoption of data-independent acquisition methods to increase analytical sensitivity. Here, we revisited the use of linear ion traps mass analyzers in data-independent acquisition methods and demonstrate their benefits to boost peptide and protein identifications in low-input proteomes.

Variability of multi-omics profiles in a population-based child cohort.

BACKGROUND: Multiple omics technologies are increasingly applied to detect early, subtle molecular responses to environmental stressors for future disease risk prevention. However, there is an urgent need for further evaluation of stability and variability of omics profiles in healthy individuals, especially during childhood. METHODS: We aimed to estimate intra-, inter-individual and cohort variability of multi-omics profiles (blood DNA methylation, gene expression, miRNA, proteins and serum and urine metabolites) measured 6 months apart in 156 healthy children from five European countries. We further performed a multi-omics network analysis to establish clusters of co-varying omics features and assessed the contribution of key variables (including biological traits and sample collection parameters) to omics variability. RESULTS: All omics displayed a large range of intra- and inter-individual variability depending on each omics feature, although all presented a highest median intra-individual variability. DNA methylation was the most stable profile (median 37.6% inter-individual variability) while gene expression was the least stable (6.6%). Among the least stable features, we identified 1% cross-omics co-variation between CpGs and metabolites (e.g. glucose and CpGs related to obesity and type 2 diabetes). Explanatory variables, including age and body mass index (BMI), explained up to 9% of serum metabolite variability. CONCLUSIONS: Methylation and targeted serum metabolomics are the most reliable omics to implement in single time-point measurements in large cross-sectional studies. In the case of metabolomics, sample collection and individual traits (e.g. BMI) are important parameters to control for improved comparability, at the study design or analysis stage. This study will be valuable for the design and interpretation of epidemiological studies that aim to link omics signatures to disease, environmental exposures, or both.

Novel Protein Biomarkers of Monoamine Metabolism Defects Correlate with Disease Severity.

BACKGROUND: Genetic defects of monoamine neurotransmitters are rare neurological diseases amenable to treatment with variable response. They are major causes of early parkinsonism and other spectrum of movement disorders including dopa-responsive dystonia. OBJECTIVES: The objective of this study was to conduct proteomic studies in cerebrospinal fluid (CSF) samples of patients with monoamine defects to detect biomarkers involved in pathophysiology, clinical phenotypes, and treatment response. METHODS: A total of 90 patients from diverse centers of the International Working Group on Neurotransmitter Related Disorders were included in the study (37 untreated before CSF collection, 48 treated and 5 unknown at the collection time). Clinical and molecular metadata were related to the protein abundances in the CSF. RESULTS: Concentrations of 4 proteins were significantly altered, detected by mass spectrometry, and confirmed by immunoassays. First, decreased levels of apolipoprotein D were found in severe cases of aromatic L-amino acid decarboxylase deficiency. Second, low levels of apolipoprotein H were observed in patients with the severe phenotype of tyrosine hydroxylase deficiency, whereas increased concentrations of oligodendrocyte myelin glycoprotein were found in the same subset of patients with tyrosine hydroxylase deficiency. Third, decreased levels of collagen6A3 were observed in treated patients with tetrahydrobiopterin deficiency. CONCLUSION: This study with the largest cohort of patients with monoamine defects studied so far reports the proteomic characterization of CSF and identifies 4 novel biomarkers that bring new insights into the consequences of early dopaminergic deprivation in the developing brain. They open new possibilities to understand their role in the pathophysiology of these disorders, and they may serve as potential predictors of disease severity and therapies. © 2020 International Parkinson and Movement Disorder Society.

An environmental air sampler to evaluate personal exposure to volatile organic compounds.

A micro fabricated chip-based wearable air sampler was used to monitor the personnel exposure of volatile chemical concentrations in microenvironments. Six teenagers participated in this study and 14 volatile organic compounds (VOCs) including naphthalene, 3-decen-1-ol, hexanal, nonanal, methyl salicylate and limonene gave the highest abundance during routine daily activity. VOC exposure associated with daily activities and the location showed strong agreements with two of the participant's results. One of these subjects had the highest exposure to methyl salicylate that was supported by the use of a topical analgesic balm containing this compound. Environmental based air quality monitoring followed by the personnel exposure studies provided additional evidence associated to the main locations where the participants traveled. Toluene concentrations observed at a gas station were exceptionally high, with the highest amount observed at 1213.1 ng m-3. One subject had the highest exposure to toluene and the GPS data showed clear evidence of activities neighboring a gas station. This study shows that this wearable air sampler has potential applications including hazardous VOC exposure monitoring in occupational hazard assessment for certain professions, for example in industries that involve direct handling of petroleum products.

Molecular signature of cardiogenic shock.

The incidence of cardiogenic shock (CS) has increased remarkably over the past decade and remains a challenging condition with mortality rates of ∼50%. Cardiogenic shock encompasses cardiac contractile dysfunction; however, it is also a multiorgan dysfunction syndrome, often complicated by a systemic inflammatory response with severe cellular and metabolic dysregulations. Here, we review the evidence on the biochemical manifestations of CS, elaborating on current gold standard biomarkers and novel candidates from molecular signatures of CS. Glucose and lactate, both identified over a century ago, remain the only clinically used biomarkers in current predictive risk scores. Novel genomic, transcriptomic, and proteomic data are discussed, and a recently reported molecular score derived from unbiased proteomic discovery, the CS4P, which includes liver fatty acid-binding protein, beta-2-microglobulin, fructose-bisphosphate aldolase B, and SerpinG1 is comprehensively described. Recent advances in -omics technologies provide new insight into a more holistic molecular signature of CS. Thus, we need to open new diagnostic and therapeutic avenues if we aim to improve outcomes.

A Proteomic Approach for Systematic Mapping of Substrates of Human Deubiquitinating Enzymes.

The human genome contains nearly 100 deubiquitinating enzymes (DUBs) responsible for removing ubiquitin moieties from a large variety of substrates. Which DUBs are responsible for targeting which substrates remain mostly unknown. Here we implement the bioUb approach to identify DUB substrates in a systematic manner, combining gene silencing and proteomics analyses. Silencing of individual DUB enzymes is used to reduce their ubiquitin deconjugating activity, leading to an increase of the ubiquitination of their substrates, which can then be isolated and identified. We report here quantitative proteomic data of the putative substrates of 5 human DUBs. Furthermore, we have built a novel interactive database of DUB substrates to provide easy access to our data and collect DUB proteome data from other groups as a reference resource in the DUB substrates research field.

Environmental sampling of volatile organic compounds during the 2018 Camp Fire in Northern California.

Trace analysis of volatile organic compounds (VOCs) during wildfires is imperative for environmental and health risk assessment. The use of gas sampling devices mounted on unmanned aerial vehicles (UAVs) to chemically sample air during wildfires is of great interest because these devices move freely about their environment, allowing for more representative air samples and the ability to sample areas dangerous or unreachable by humans. This work presents chemical data from air samples obtained in Davis, CA during the most destructive wildfire in California's history - the 2018 Camp Fire - as well as the deployment of our sampling device during a controlled experimental fire while fixed to a UAV. The sampling mechanism was an in-house manufactured micro-gas preconcentrator (µPC) embedded onto a compact battery-operated sampler that was returned to the laboratory for chemical analysis. Compounds commonly observed in wildfires were detected during the Camp Fire using gas chromatography mass spectrometry (GC-MS), including BTEX (benzene, toluene, ethylbenzene, m+p-xylene, and o-xylene), benzaldehyde, 1,4-dichlorobenzene, naphthalene, 1,2,3-trimethylbenzene and 1-ethyl-3-methylbenzene. Concentrations of BTEX were calculated and we observed that benzene and toluene were highest with average concentrations of 4.7 and 15.1 µg/m3, respectively. Numerous fire-related compounds including BTEX and aldehydes such as octanal and nonanal were detected upon experimental fire ignition, even at a much smaller sampling time compared to samples taken during the Camp Fire. Analysis of the air samples taken both stationary during the Camp Fire and mobile during an experimental fire show the successful operation of our sampler in a fire environment.

In utero and childhood exposure to tobacco smoke and multi-layer molecular signatures in children.

BACKGROUND: The adverse health effects of early life exposure to tobacco smoking have been widely reported. In spite of this, the underlying molecular mechanisms of in utero and postnatal exposure to tobacco smoke are only partially understood. Here, we aimed to identify multi-layer molecular signatures associated with exposure to tobacco smoke in these two exposure windows. METHODS: We investigated the associations of maternal smoking during pregnancy and childhood secondhand smoke (SHS) exposure with molecular features measured in 1203 European children (mean age 8.1 years) from the Human Early Life Exposome (HELIX) project. Molecular features, covering 4 layers, included blood DNA methylation and gene and miRNA transcription, plasma proteins, and sera and urinary metabolites. RESULTS: Maternal smoking during pregnancy was associated with DNA methylation changes at 18 loci in child blood. DNA methylation at 5 of these loci was related to expression of the nearby genes. However, the expression of these genes themselves was only weakly associated with maternal smoking. Conversely, childhood SHS was not associated with blood DNA methylation or transcription patterns, but with reduced levels of several serum metabolites and with increased plasma PAI1 (plasminogen activator inhibitor-1), a protein that inhibits fibrinolysis. Some of the in utero and childhood smoking-related molecular marks showed dose-response trends, with stronger effects with higher dose or longer duration of the exposure. CONCLUSION: In this first study covering multi-layer molecular features, pregnancy and childhood exposure to tobacco smoke were associated with distinct molecular phenotypes in children. The persistent and dose-dependent changes in the methylome make CpGs good candidates to develop biomarkers of past exposure. Moreover, compared to methylation, the weak association of maternal smoking in pregnancy with gene expression suggests different reversal rates and a methylation-based memory to past exposures. Finally, certain metabolites and protein markers evidenced potential early biological effects of postnatal SHS, such as fibrinolysis.