Telomere tracking from birth to adulthood and residential traffic exposure

Background: Telomere attrition is extremely rapid during the first years of life, while lifestyle during adulthood exerts a minor impact. This suggests that early life is an important period in the determination of telomere length. We investigated the importance of the early-life environment on both telomere tracking and adult telomere length. Methods: Among 184 twins of the East Flanders Prospective Twin Survey, telomere length in placental tissue and in buccal cells in young adulthood was measured. Residential addresses at birth and in young adulthood were geocoded and residential traffic and greenness exposure was determined. Results: We investigated individual telomere tracking from birth over a 20 year period (mean age (SD), 22.6 (3.1) years) in association with residential exposure to traffic and greenness. Telomere length in placental tissue and in buccal cells in young adulthood correlated positively (r = 0.31, P < 0.0001). Persons with higher placental telomere length at birth were more likely to have a stronger downward shift in telomere ranking over life (P < 0.0001). Maternal residential traffic exposure correlated inversely with telomere length at birth. Independent of birth placental telomere length, telomere ranking between birth and young adulthood was negatively and significantly associated with residential traffic exposure at the birth address, while traffic exposure at the residential address at adult age was not associated with telomere length. Conclusions: Longitudinal evidence of telomere length tracking from birth to adulthood shows inverse associations of residential traffic exposure in association with telomere length at birth as well as accelerated telomere shortening in the first two decades of life

A systematic review of metabolomic studies of childhood obesity: State of the evidence for metabolic determinants and consequences

Childhood obesity has become a global epidemic and carries significant long-term consequences to physical and mental health. Metabolomics, the global profiling of small molecules or metabolites, may reveal the mechanisms of development of childhood obesity and clarify links between obesity and metabolic disease. A systematic review of metabolomic studies of childhood obesity was conducted, following Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, searching across Scopus, Ovid, Web of Science and PubMed databases for articles published from January 1, 2005 to July 8, 2020, retrieving 1271 different records and retaining 41 articles for qualitative synthesis. Study quality was assessed using a modified Newcastle–Ottawa Scale. Thirty-three studies were conducted on blood, six on urine, three on umbilical cord blood, and one on saliva. Thirty studies were primarily cross-sectional, five studies were primarily longitudinal, and seven studies examined effects of weight-loss following a life-style intervention. A consistent metabolic profile of childhood obesity was observed including amino acids (particularly branched chain and aromatic), carnitines, lipids, and steroids. Although the use of metabolomics in childhood obesity research is still developing, the identified metabolites have provided additional insight into the pathogenesis of many obesity-related diseases. Further longitudinal research is needed into the role of metabolic profiles and child obesity risk

The cord blood insulin and mitochondrial DNA content related methylome

Mitochondrial dysfunction seems to play a key role in the etiology of insulin resistance. At birth, a link has already been established between mitochondrial DNA (mtDNA) content and insulin levels in cord blood. In this study, we explore shared epigenetic mechanisms of the association between mtDNA content and insulin levels, supporting the developmental origins of this link. First, the association between cord blood insulin and mtDNA content in 882 newborns of the ENVIRONAGE birth cohort was assessed. Cord blood mtDNA content was established via qPCR, while cord blood levels of insulin were determined using electrochemiluminescence immunoassays. Then the cord blood DNA methylome and transcriptome were determined in 179 newborns, using the human 450K methylation Illumina and Agilent Whole Human Genome 8 × 60 K microarrays, respectively. Subsequently, we performed an epigenome-wide association study (EWAS) adjusted for different maternal and neonatal variables. Afterward, we focused on the 20 strongest associations based on p-values to assign transcriptomic correlates and allocate corresponding pathways employing the R packages ReactomePA and RDAVIDWebService. On the regional level, we examined differential methylation using the DMRcate and Bumphunter packages in R. Cord blood mtDNA content and insulin were significantly correlated (r = 0.074, p = 0.028), still showing a trend after additional adjustment for maternal and neonatal variables (p = 0.062). We found an overlap of 33 pathways which were in common between the association with cord blood mtDNA content and insulin levels, including pathways of neurodevelopment, histone modification, cytochromes P450 (CYP)-metabolism, and biological aging. We further identified a DMR annotated to Repulsive Guidance Molecule BMP Co-Receptor A (RGMA) linked to cord blood insulin as well as mtDNA content. Metabolic variation in early life represented by neonatal insulin levels and mtDNA content might reflect or accommodate alterations in neurodevelopment, histone modification, CYP-metabolism, and aging, indicating etiological origins in epigenetic programming. Variation in metabolic hormones at birth, reflected by molecular changes, might via these alterations predispose children to metabolic diseases later in life. The results of this study may provide important markers for following targeted studies

Cord blood epigenome-wide meta-analysis in six European-based child cohorts identifies signatures linked to rapid weight growth

BACKGROUND: Rapid postnatal growth may result from exposure in utero or early life to adverse conditions and has been associated with diseases later in life and, in particular, with childhood obesity. DNA methylation, interfacing early-life exposures and subsequent diseases, is a possible mechanism underlying early-life programming. METHODS: Here, a meta-analysis of Illumina HumanMethylation 450K/EPIC-array associations of cord blood DNA methylation at single CpG sites and CpG genomic regions with rapid weight growth at 1 year of age (defined with reference to WHO growth charts) was conducted in six European-based child cohorts (ALSPAC, ENVIRONAGE, Generation XXI, INMA, Piccolipiù, and RHEA, N = 2003). The association of gestational age acceleration (calculated using the Bohlin epigenetic clock) with rapid weight growth was also explored via meta-analysis. Follow-up analyses of identified DNA methylation signals included prediction of rapid weight growth, mediation of the effect of conventional risk factors on rapid weight growth, integration with transcriptomics and metabolomics, association with overweight in childhood (between 4 and 8 years), and comparison with previous findings. RESULTS: Forty-seven CpGs were associated with rapid weight growth at suggestive p-value <1e-05 and, among them, three CpGs (cg14459032, cg25953130 annotated to ARID5B, and cg00049440 annotated to KLF9) passed the genome-wide significance level (p-value <1.25e-07). Sixteen differentially methylated regions (DMRs) were identified as associated with rapid weight growth at false discovery rate (FDR)-adjusted/Siddak p-values < 0.01. Gestational age acceleration was associated with decreasing risk of rapid weight growth (p-value = 9.75e-04). Identified DNA methylation signals slightly increased the prediction of rapid weight growth in addition to conventional risk factors. Among the identified signals, three CpGs partially mediated the effect of gestational age on rapid weight growth. Both CpGs (N=3) and DMRs (N=3) were associated with differential expression of transcripts (N=10 and 7, respectively), including long non-coding RNAs. An AURKC DMR was associated with childhood overweight. We observed enrichment of CpGs previously reported associated with birthweight. CONCLUSIONS: Our findings provide evidence of the association between cord blood DNA methylation and rapid weight growth and suggest links with prenatal exposures and association with childhood obesity providing opportunities for early prevention

The Cord Blood Insulin and Mitochondrial DNA Content Related Methylome

Mitochondrial dysfunction seems to play a key role in the etiology of insulin resistance. At birth, a link has already been established between mitochondrial DNA (mtDNA) content and insulin levels in cord blood. In this study, we explore shared epigenetic mechanisms of the association between mtDNA content and insulin levels, supporting the developmental origins of this link. First, the association between cord blood insulin and mtDNA content in 882 newborns of the ENVIRONAGE birth cohort was assessed. Cord blood mtDNA content was established via qPCR, while cord blood levels of insulin were determined using electrochemiluminescence immunoassays. Then the cord blood DNA methylome and transcriptome were determined in 179 newborns, using the human 450K methylation Illumina and Agilent Whole Human Genome 8 × 60 K microarrays, respectively. Subsequently, we performed an epigenome-wide association study (EWAS) adjusted for different maternal and neonatal variables. Afterward, we focused on the 20 strongest associations based on p-values to assign transcriptomic correlates and allocate corresponding pathways employing the R packages ReactomePA and RDAVIDWebService. On the regional level, we examined differential methylation using the DMRcate and Bumphunter packages in R. Cord blood mtDNA content and insulin were significantly correlated (r = 0.074, p = 0.028), still showing a trend after additional adjustment for maternal and neonatal variables (p = 0.062). We found an overlap of 33 pathways which were in common between the association with cord blood mtDNA content and insulin levels, including pathways of neurodevelopment, histone modification, cytochromes P450 (CYP)-metabolism, and biological aging. We further identified a DMR annotated to Repulsive Guidance Molecule BMP Co-Receptor A (RGMA) linked to cord blood insulin as well as mtDNA content. Metabolic variation in early life represented by neonatal insulin levels and mtDNA content might reflect or accommodate alterations in neurodevelopment, histone modification, CYP-metabolism, and aging, indicating etiological origins in epigenetic programming. Variation in metabolic hormones at birth, reflected by molecular changes, might via these alterations predispose children to metabolic diseases later in life. The results of this study may provide important markers for following targeted studies

The contribution to policies of an exposome-based approach to childhood obesity

Childhood obesity is an increasingly severe public health problem, with a prospective impact on health. We propose an exposome approach to identifying actionable risk factors for this condition. Our assumption is that relationships between external exposures and outcomes such as rapid growth, overweight or obesity in children can be better understood through a “meet-in-the-middle” model. This is based on a combination of external and internal exposome-based approaches, i.e. the study of multiple exposures (in our case dietary patterns) and molecular pathways (metabolomics and epigenetics). This may strengthen causal reasoning by identifying intermediate markers that are associated with both exposures and outcomes. Our biomarker-based studies in the STOP consortium suggest (in several ways, including mediation analysis) that Branched-Chain Amino Acids (BCAAs) could be mediators of the effect of dietary risk factors on childhood overweight/obesity. This is consistent with intervention and animal studies showing that higher intake of BCAAs has a positive impact on body composition, glycemia and satiety. Concerning food, of particular concern is the trend of increasing intake of ultra-processed food (UPF), including among children. Several mechanisms have been proposed to explain the impact of UPF on obesity and overweight, including nutrient intake (particularly proteins), changes in appetite or the role of additives. Research from the ALSPAC cohort has shown a relationship between UPF intake and trajectories in childhood adiposity, while UPF was related to lower blood levels of BCAAs. We suggest that an exposome-based approach can help strengthening causal reasoning and support policies. Intake of UPF in children should be restricted to prevent obesity

A Co-expression Analysis of the Placental Transcriptome in Association With Maternal Pre-pregnancy BMI and Newborn Birth Weight

Maternal body mass index (BMI) before pregnancy is known to affect both fetal growth and later-life health of the newborn, yet the implicated molecular mechanisms remain largely unknown. As the master regulator of the fetal environment, the placenta is a valuable resource for the investigation of processes involved in the developmental programming of metabolic health. We conducted a genome-wide placental transcriptome study aiming at the identification of functional pathways representing the molecular link between maternal BMI and fetal growth. We used RNA microarray (Agilent 8 × 60 K), medical records, and questionnaire data from 183 mother-newborn pairs from the ENVIRONAGE birth cohort study (Flanders, Belgium). Using a weighted gene co-expression network analysis, we identified 17 correlated gene modules. Three of these modules were associated with both maternal pre-pregnancy BMI and newborn birth weight. A gene cluster enriched for genes involved in immune response and myeloid cell differentiation was positively associated with maternal BMI and negatively with low birth weight. Two other gene modules, upregulated in association with maternal BMI as well as birth weight, were involved in processes related to organ and tissue development, with blood vessel morphogenesis and extracellular matrix structure as top Gene Ontology terms. In line with this, erythrocyte-, angiogenesis-, and extracellular matrix-related genes were among the identified hub genes. The association between maternal BMI and newborn weight was significantly mediated by gene expression for 5 of the hub genes (FZD4, COL15A1, GPR124, COL6A1, and COL1A1). As some of the identified hub genes have been linked to obesity in adults, our observation in placental tissue suggests that biological processes may be affected from prenatal life onwards, thereby identifying new molecular processes linking maternal BMI and fetal metabolic programming

Sex-specific associations between particulate matter exposure and gene expression in independent discovery and validation cohorts of middle-aged men and women

BACKGROUND: Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. OBJECTIVES: Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. METHODS: Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM(10) in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM(2.5) and PM(10) exposures over 2-years were estimated for each participant’s residential address using spatiotemporal interpolation in combination with a dispersion model. RESULTS: Average long-term PM(10) was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m(3) in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM(10) and the expression of individual genes differed by sex. In the validation cohort, long-term PM(10) was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 (p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM(10) in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM(10) exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). CONCLUSIONS: Expression of the sex-specific candidate genes identified in the discovery population predicted PM(10) exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects. CITATION: Vrijens K, Winckelmans E, Tsamou M, Baeyens W, De Boever P, Jennen D, de Kok TM, Den Hond E, Lefebvre W, Plusquin M, Reynders H, Schoeters G, Van Larebeke N, Vanpoucke C, Kleinjans J, Nawrot TS. 2017. Sex-specific associations between particulate matter exposure and gene expression in independent discovery and validation cohorts of middle-aged men and women. Environ Health Perspect 125:660–669; http://dx.doi.org/10.1289/EHP37