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Maternal educational attainment (MEA) shapes offspring health through multiple potential pathways. Differential DNA methylation may provide a mechanistic understanding of these long-term associations. We aimed to quantify the associations of MEA with offspring DNA methylation levels at birth, in childhood and in adolescence. Using 37 studies from high-income countries, we performed meta-analysis of epigenome-wide association studies (EWAS) to quantify the associations of completed years of MEA at the time of pregnancy with offspring DNA methylation levels at birth (n = 9 881), in childhood (n = 2 017), and adolescence (n = 2 740), adjusting for relevant covariates. MEA was found to be associated with DNA methylation at 473 cytosine-phosphate-guanine sites at birth, one in childhood, and four in adolescence. We observed enrichment for findings from previous EWAS on maternal folate, vitamin-B12 concentrations, maternal smoking, and pre-pregnancy BMI. The associations were directionally consistent with MEA being inversely associated with behaviours including smoking and BMI. Our findings form a bridge between socio-economic factors and biology and highlight potential pathways underlying effects of maternal education. The results broaden our understanding of bio-social associations linked to differential DNA methylation in multiple early stages of life. The data generated also offers an important resource to help a more precise understanding of the social determinants of health.

Background: Long-COVID is defined as the persistency or development of new symptoms 3 months after the initial SARS-CoV-2 infection, with these symptoms lasting for at least 2 months with no other explanation. Common persistent symptoms are fatigue, sleep disturbances, post-exertional malaise (PEM), pain, and cognitive problems. Long-COVID is estimated to be present in about 65 million people. We aimed to explore clinical and biological factors that might contribute to Long-COVID. Methods: Prospective longitudinal cohort study including patients infected with SARS-CoV-2 between March 2020 and March 2022. Patients were assessed between 4 and 12 months after infection at the COVID follow-up clinic at UZ Leuven. We performed a comprehensive clinical assessment (including questionnaires and the 6-min walking test) and biological measures (global DNA methylation, telomere length, mitochondrial DNA copy number, inflammatory cytokines, and serological markers such as C-reactive protein, D-dimer, troponin T). Results: Of the 358 participants, 328 were hospitalised, of which 130 had severe symptoms requiring intensive care admission; 30 patients were ambulatory referrals. Based on their clinical presentation, we could identify 6 main clusters. One-hundred and twenty-seven patients (35.4%) belonged to at least one cluster. The bigger cluster included PEM, fatigue, sleep disturbances, and pain (n = 57). Troponin T and telomere shortening were the two main markers predicting Long-COVID and PEM-fatigue symptoms. Conclusions: Long-COVID is not just one entity. Different clinical presentations can be identified. Cardiac involvement (as measured by troponin T levels) and telomere shortening might be a relevant risk factor for developing PEM-fatigue symptoms and deserve further exploring. [ABSTRACT FROM AUTHOR]

Background: Telomere length is an important indicator of biological age and a complex multi-factor trait. To date, the telomere interactome for comprehending the high-dimensional biological aspects linked to telomere regulation during childhood remains unexplored. Here we describe the multi-omics signatures associated with childhood telomere length. Methods: This study included 1001 children aged 6 to 11 years from the Human Early-life Exposome (HELIX) project. Telomere length was quantified via qPCR in peripheral blood of the children. Blood DNA methylation, gene expression, miRNA expression, plasma proteins and serum and urinary metabolites were measured through microarrays or (semi-) targeted assays. The association between each individual omics feature and telomere length was assessed in omics-wide association analyses. In addition, a literature-guided, sparse supervised integration method was applied to multiple omics, and latent components were extracted as predictors of child telomere length. The association of these latent components with early-life aging risk factors (child lifestyle, body mass index (BMI), exposure to smoking, etc.), were interrogated. Results: After multiple-testing correction, only two CpGs (cg23686403 and cg16238918 at PARD6G gene) out of all the omics features were significantly associated with child telomere length. The supervised multi-omics integration approach revealed robust associations between latent components and child BMI, with metabolites and proteins emerging as the primary contributing features. In these latent components, the contributing molecular features were known as involved in metabolism and immune regulation-related pathways. Conclusions: Findings of this multi-omics study suggested an intricate interplay between telomere length, metabolism and immune responses, providing valuable insights into the molecular underpinnings of the early-life biological aging. [ABSTRACT FROM AUTHOR]

Screening for and prevention of osteoporosis and osteoporotic fractures is imperative, given the high burden on individuals and society. This study constructed and validated an aging-related biomarker derived from the urinary proteomic profile (UPP) indicative of osteoporosis (UPPost-age). In a prospective population study done in northern Belgium (1985-2019), participants were invited for a follow-up examination in 2005-2010 and participants in the 2005-2010 examination again invited in 2009-2013. Participants in both the 2005-2010 and 2009-2013 examinations (n = 519) constituted the derivation (2005-2016 data) and time-shifted validation (2009-2013 data) datasets; 187 participants with only 2005-2010 data formed the synchronous validation dataset. The UPP was assessed by capillary electrophoresis coupled with mass spectrometry. Analyses focused on 2372 sequenced urinary peptides (101 proteins) with key roles in maintaining the integrity of bone tissue. In multivariable analyses with correction for multiple testing, chronological age was associated with 99 urinary peptides (16 proteins). Peptides derived from IGF2 and MGP were upregulated in women compared to men, whereas COL1A2, COL3A1, COL5A2, COL10A1 and COL18A1 were downregulated. Via application of a 1000-fold bootstrapped elastic regression procedure, finally, 29 peptides (10 proteins) constituted the UPPost-age biomarker, replicated across datasets. In cross-sectional analyses of 2009-2013 data (n = 706), the body-height-to-arm-span ratio, an osteoporosis marker, was negatively associated with UPPost-age (p<0.0001). Over 4.89 years (median), the 10-year risk of osteoporosis associated with chronological age and UPPost-age (53 cases including 37 fractures in 706 individuals) increased by 21% and 36% (p = 0.044). Among 357 women, the corresponding estimates were 55% and 60% for incident osteoporosis (37 cases; p = 0.0003) and 42% and 44% for osteoporotic fractures (25 cases; p = 0.017). In conclusion, an aging-related UPP signature with focus on peptide fragments derived from bone-related proteins is associated with osteoporosis risk and available for clinical and trial research. [ABSTRACT FROM AUTHOR]

Simple Summary: Dairy cows are essential for milk production, but their productive lifespan—how long they stay healthy and productive—has not increased in recent years. This has led to concerns about animal welfare, environmental sustainability, and farm profitability. Scientists are searching for ways to predict which calves will have longer, healthier lives. One idea is to measure telomeres: tiny structures at the ends of chromosomes that shorten as animals age. In this study, we measured the telomere length of newborn dairy calves and investigated if it could predict their lifespan, milk production, or reproductive performance. We found that telomere length did not predict how long the cows lived or how much milk they produced. However, calves with the longest telomeres were less efficient at producing milk fat and protein. Interestingly, these calves also required fewer inseminations and had slightly longer intervals between calvings, suggesting a possible link to reproductive performance. While telomere length alone may not be a reliable predictor of lifespan or productivity, it could help us better understand the biology of aging and reproduction in dairy cows. Future research could provide more insights into how this information could improve animal welfare and farming efficiency. Telomere length (TL) has gained attention as a biomarker for longevity and productivity in dairy cattle. This study explored the association between neonatal TL in Holstein calves and lifetime parameters (lifespan, milk production, and reproduction). Blood samples were collected from 210 calves (≤10d old) across four dairy farms in Flanders, Belgium. Telomere length was measured using qPCR and analyzed as a continuous variable and across three groups: the 10% shortest, the 10% longest, and the remaining 80%. Survival analyses showed no association between TL and lifespan (p = 0.1) or TL groups (p = 0.8). Similarly, TL showed no significant association with production traits. However, categorical analyses revealed that calves with the longest TL had lower lifetime fat (p = 0.01) and protein yields (p = 0.01) than those with the shortest TL. Reproductive analyses showed cows in the long TL group required fewer inseminations per lactation (p = 0.02) and exhibited longer calving intervals (p = 0.05). These findings suggest that while neonatal TL may not predict productive lifespan, it may provide insight into reproductive efficiency. Future studies should prioritize longitudinal assessments of TL dynamics to better understand their interactions with management practices and application in herd improvement. [ABSTRACT FROM AUTHOR]

Introduction Over the past 20 y, global life expectancy at birth increased from 67.2 to 73.5 y. (1) In line with this remarkable increase in longevity, global exposure to harmful [...], BACKGROUND: A recently developed urinary peptidomics biological aging clock can be used to study accelerated human aging. From 1990 to 2019, exposure to airborne particulate matter (PM) became the leading environmental risk factor worldwide. OBJECTIVES: This study investigated whether air pollution exposure is associated with accelerated urinary peptidomic aging, independent of calendar age, and whether this association is modified by other risk factors. METHODS: In a Flemish population, the urinary peptidomic profile (UPP) age (UPP-age) was derived from the urinary peptidomic profile measured by capillary electrophoresis coupled with mass spectrometry. UPP-age-R was calculated as the residual of the regression of UPP-age on chronological age, which reflects accelerated aging predicted by UPP-age, independent of chronological age. A high-resolution spatial-temporal interpolation method was used to assess each individual&apos;s exposure to P[M.sub.10], P[M.sub.2.5], black carbon (BC), and nitrogen dioxide (N[O.sub.2]). Associations of UPP-age-R with these pollutants were investigated by mixed models, accounting for clustering by residential address and confounders. Effect modifiers of the associations between UPP-age-R and air pollutants that included 18 factors reflecting vascular function, renal function, insulin resistance, lipid metabolism, or inflammation were evaluated. Direct and indirect (via UPP-age-R) effects of air pollution on mortality were evaluated by multivariable-adjusted Cox models. RESULTS: Among 660 participants (50.2% women; mean age: 50.7 y), higher exposure to P[M.sub.10], P[M.sub.2.5], BC, and N[O.sub.2] was associated with a higher UPP-age-R. Studying effect modifiers showed that higher plasma levels of desphospho-uncarboxylated matrix Gla protein (dpucMGP), signifying poorer vitamin K status, steepened the slopes of UPP-age-R on the air pollutants. In further analyses among participants with dpucMGP [greater than or equal to] 4.26 [micro]g/L (median), an interquartile range (IQR) higher level in P[M.sub.10], P[M.sub.2.5], BC, and N[O.sub.2] was associated with a higher UPP-age-R of 2.03 [95% confidence interval (CI): 0.60, 3.46], 2.22 (95% CI: 0.71, 3.74), 2.00 (95% CI: 0.56, 3.43), and 2.09 (95% CI: 0.77, 3.41) y, respectively. UPP-age-R was an indirect mediator of the associations of mortality with the air pollutants [multivariable-adjusted hazard ratios from 1.094 (95% CI: 1.000, 1.196) to 1.110 (95% CI: 1.007, 1.224)] in participants with a high dpucMGP, whereas no direct associations were observed. DISCUSSION: Ambient air pollution was associated with accelerated urinary peptidomics aging, and high vitamin K status showed a potential protective effect in this population. Current guidelines are insufficient to decrease the adverse health effects of airborne pollutants, including healthy aging trajectories. https://doi.org/10.1289/EHP13414

Objective: To explore the association between telomere length (TL) and attention deficit hyperactivity disorder (ADHD) symptoms in children at 6–12 years. Method: Data from 1,759 children belonging to the HELIX project cohorts and the Asturias, Gipuzkoa and Valencia cohorts of INMA project were included. TL was determined by blood sample using a PCR protocol. ADHD symptoms were described by parents using the Conners' Parent Rating Scale-Revised: Short Form. Multiple negative binomial regression models adjusted for potential confounders were used to estimate associations. Results: Overall estimates showed no associations between TL and ADHD symptoms. However, we observed that a longer TL was significantly associated with a lower risk of presenting hyperactivity symptoms in children belonging to the HELIX project (IRR = 0.93, 95% CI [0.87, 0.99]; p =.022). Conclusion: While our study did not find a consistent association between TL and ADHD symptoms across all cohorts, the significant association found within the HELIX cohort suggests that longer TL may be linked to a lower risk of hyperactivity symptoms. Further research is needed to explore this association in more detail. [ABSTRACT FROM AUTHOR]

With urinary proteomics profiling (UPP) as exemplary omics technology, this review describes a workflow for the analysis of omics data in large study populations. The proposed workflow includes: (i) planning omics studies and sample size considerations; (ii) preparing the data for analysis; (iii) preprocessing the UPP data; (iv) the basic statistical steps required for data curation; (v) the selection of covariables; (vi) relating continuously distributed or categorical outcomes to a series of single markers (e.g., sequenced urinary peptide fragments identifying the parental proteins); (vii) showing the added diagnostic or prognostic value of the UPP markers over and beyond classical risk factors, and (viii) pathway analysis to identify targets for personalized intervention in disease prevention or treatment. Additionally, two short sections respectively address multiomics studies and machine learning. In conclusion, the analysis of adverse health outcomes in relation to omics biomarkers rests on the same statistical principle as any other data collected in large population or patient cohorts. The large number of biomarkers, which have to be considered simultaneously requires planning ahead how the study database will be structured and curated, imported in statistical software packages, analysis results will be triaged for clinical relevance, and presented. [ABSTRACT FROM AUTHOR]

BACKGROUND: Wave separation analysis enables individualized evaluation of the aortic pulse wave components. Previous studies focused on the pressure height with overall positive but differing results. In the present analysis, we assessed the associations of the pressure of forward and backward (Pfor and Pref) pulse waves with prospective cardiovascular end points, with extended analysis for time to pressure peak (Tfor and Tref). METHODS: Participants in 3 IDCARS (International Database of Central Arterial Properties for Risk Stratification) cohorts (Argentina, Belgium, and Finland) aged ≥20 years with valid pulse wave analysis and follow-up data were included. Pulse wave analysis was done using the SphygmoCor device, and pulse wave separation was done using the triangular method. The primary end points consisted of cardiovascular mortality and nonfatal cardiovascular and cerebrovascular events. Multivariable-adjusted Cox regression was used to calculate hazard ratios. RESULTS: A total of 2206 participants (mean age, 57.0 years; 55.0% women) were analyzed. Mean±SDs for Pfor, Pref, Tfor, and Tfor/Tref were 31.0±9.1 mm Hg, 20.8±8.4 mm Hg, 130.8±35.5, and 0.51±0.11, respectively. Over a median follow-up of 4.4 years, 146 (6.6%) participants experienced a primary end point. Every 1 SD increment in Pfor, Tfor, and Tfor/Tref was associated with 27% (95% CI, 1.07–1.49), 25% (95% CI, 1.07–1.45), and 32% (95% CI, 1.12–1.56) higher risk, respectively. Adding Tfor and Tfor/Tref to existing risk models improved model prediction (∆Uno's C, 0.020; P <0.01). CONCLUSIONS: Pulse wave components were predictive of composite cardiovascular end points, with Tfor/Tref showing significant improvement in risk prediction. Pending further confirmation, the ratio of time to forward and backward pressure peak may be useful to evaluate increased afterload and signify increased cardiovascular risk. [ABSTRACT FROM AUTHOR]