Hypomethylation of HOXA4 promoter is common in Silver-Russell syndrome and growth restriction and associates with stature in healthy children

Silver-Russell syndrome (SRS) is a growth retardation syndrome in which loss of methylation on chromosome 11p15 (11p15 LOM) and maternal uniparental disomy for chromosome 7 [UPD(7) mat] explain 20-60% and 10% of the syndrome, respectively. To search for a molecular cause for the remaining SRS cases, and to find a possible common epigenetic change, we studied DNA methylation pattern of more than 450 000 CpG sites in 44 SRS patients. Common to all three SRS subgroups, we found a hypomethylated region at the promoter region of HOXA4 in 55% of the patients. We then tested 39 patients with severe growth restriction of unknown etiology, and found hypomethylation of HOXA4 in 44% of the patients. Finally, we found that methylation at multiple CpG sites in the HOXA4 promoter region was associated with height in a cohort of 227 healthy children, suggesting that HOXA4 may play a role in regulating human growth by epigenetic mechanisms.Peer reviewe

Association of Maternal DNA Methylation and Offspring Birthweight

This study aims to evaluate the association of maternal DNA methylation (DNAm) during pregnancy and offspring birthweight. One hundred twenty-two newborn-mother dyads from the Isle of Wight (IOW) cohort were studied to identify differentially methylated cytosine-phosphate-guanine sites (CpGs) in maternal blood associated with offspring birthweight. Peripheral blood samples were drawn from mothers at 22-38 weeks of pregnancy for epigenome-wide DNAm assessment using the Illumina Infinium HumanMethylation450K array. Candidate CpGs were identified using a course of 100 repetitions of a training and testing process with robust regressions. CpGs were considered informative if they showed statistical significance in at least 80% of training and testing samples. Linear mixed models adjusting for covariates were applied to further assess the selected CpGs. The Swedish Born Into Life cohort was used to replicate our findings (n = 33). Eight candidate CpGs corresponding to the genesLMF1,KIF9,KLHL18,DAB1,VAX2,CD207,SCT,SCYL2,DEPDC4,NECAP1, andSFRS3in mothers were identified as statistically significantly associated with their children's birthweight in the IOW cohort and confirmed by linear mixed models after adjusting for covariates. Of these, in the replication cohort, three CpGs (cg01816814, cg23153661, and cg17722033 withpvalues = 0.06, 0.175, and 0.166, respectively) associated with four genes (LMF1,VAX2,CD207, andNECAP1) were marginally significant. Biological pathway analyses of three of the genes revealed cellular processes such as endocytosis (possibly sustaining an adequate maternal-fetal interface) and metabolic processes such as regulation of lipoprotein lipase activity (involved in providing substrates for the developing fetus). Our results contribute to an epigenetic understanding of maternal involvement in offspring birthweight. Measuring DNAm levels of maternal CpGs may in the future serve as a diagnostic tool recognizing mothers at risk for pregnancies ending with altered birthweights.Peer reviewe

Differential DNA Methylation in Purified Human Blood Cells: Implications for Cell Lineage and Studies on Disease Susceptibility

WOS:000306806600056Peer reviewe

Hypertension and Exposure to Noise Near Airports: the HYENA Study

We compare two approaches for high-level power estimation of DSP components implemented in FPGAs for different sets of data streams from real-world applications. The first model is a power macro-model based on the Hamming distance of input signals. The second model is an analytical high-level power model based on switching activity computation and knowledge about the component’s internal structure, which has been improved to also consider additional information on the signal distribution of two consecutive input vectors. The results show that the accuracy of both models is, in most cases, within 10% of the low-level power estimates given by the tool XPower when cycle-bycycle input signal distributions are taken into account, and that the difference between the model accuracies depends significantly on the nature of the signals. Additionally, the effort required for the characterization and construction of the models for different component structures is discussed in detail

Associations between the 17q21 region and allergic rhinitis in 5 birth cohorts

Non peer reviewe

DNA Methylation in the Neuropeptide S Receptor 1 (NPSR1) Promoter in Relation to Asthma and Environmental Factors

Peer reviewe

DNA Methylation Trajectories During Pregnancy

There is emerging evidence on DNA methylation (DNAm) variability over time; however, little is known about dynamics of DNAm patterns during pregnancy. We performed an epigenome-wide longitudinal DNAm study of a well-characterized sample of young women from the Swedish Born into Life study, with repeated blood sampling before, during and after pregnancy (n = 21), using the Illumina Infinium MethylationEPIC array. We conducted a replication in the Isle of Wight third-generation birth cohort (n = 27), using the Infinium HumanMethylation450k BeadChip. We identified 196 CpG sites displaying intra-individual longitudinal change in DNAm with a false discovery rate (FDR) P 3 differentially methylated CpGs: HOXB3, AVP, LOC100996291, and MicroRNA 10a. Of 36 CpGs available in the replication cohort, 17 were replicated, all but 2 with the same direction of association (replication P <.05). Biological pathway analysis demonstrated that FDR-significant CpGs belong to genes overrepresented in metabolism-related pathways, such as adipose tissue development, regulation of insulin receptor signaling, and mammary gland fat development. These results contribute to a better understanding of the biological mechanisms underlying important physiological alterations and adaptations for pregnancy and lactation.Peer reviewe

Long-term exposure to elemental constituents of particulate matter and cardiovascular mortality in 19 European cohorts: Results from the ESCAPE and TRANSPHORM projects

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The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia : design, results and future prospects

The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.Peer reviewe