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

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

WOS:000306806600056Peer reviewe

Amino Acid Signatures to Evaluate the Beneficial Effects of Weight Loss

Aims. We investigated the relationship between circulating amino acid levels and obesity; to what extent weight loss followed by weight maintenance can correct amino acid abnormalities; and whether amino acids are related to weight loss. Methods:. Amino acids associated with waist circumference (WC) and BMI were studied in 804 participants from the Malmö Diet and Cancer Cardiovascular Cohort (MDC-CC). Changes in amino acid levels were analyzed after weight loss and weight maintenance in 12 obese subjects and evaluated in a replication cohort (n = 83). Results:. Out of the eight identified BMI-associated amino acids from the MDC-CC, alanine, isoleucine, tyrosine, phenylalanine, and glutamate decreased after weight loss, while asparagine increased after weight maintenance. These changes were validated in the replication cohort. Scores that were constructed based on obesity-associated amino acids and known risk factors decreased in the ≥10% weight loss group with an associated change in BMI (R2 = 0.16–0.22, p < 0.002), whereas the scores increased in the <10% weight loss group (p < 0.0004). Conclusions:. Weight loss followed by weight maintenance leads to differential changes in amino acid levels associated with obesity. Treatment modifiable scores based on epidemiological and interventional data may be used to evaluate the potential metabolic benefit of weight loss

Age-associated DNA methylation changes in immune genes, histone modifiers and chromatin remodeling factors within 5 years after birth in human blood leukocytes

Abstract Background Age-related changes in DNA methylation occurring in blood leukocytes during early childhood may reflect epigenetic maturation. We hypothesized that some of these changes involve gene networks of critical relevance in leukocyte biology and conducted a prospective study to elucidate the dynamics of DNA methylation. Serial blood samples were collected at 3, 6, 12, 24, 36, 48 and 60 months after birth in ten healthy girls born in Finland and participating in the Type 1 Diabetes Prediction and Prevention Study. DNA methylation was measured using the HumanMethylation450 BeadChip. Results After filtering for the presence of polymorphisms and cell-lineage-specific signatures, 794 CpG sites showed significant DNA methylation differences as a function of age in all children (41.6% age-methylated and 58.4% age-demethylated, Bonferroni-corrected P value <0.01). Age-methylated CpGs were more frequently located in gene bodies and within +5 to +50 kilobases (kb) of transcription start sites (TSS) and enriched in developmental, neuronal and plasma membrane genes. Age-demethylated CpGs were associated to promoters and DNAse-I hypersensitivity sites, located within −5 to +5 kb of the nearest TSS and enriched in genes related to immunity, antigen presentation, the polycomb-group protein complex and cytoplasm. Conclusions This study reveals that susceptibility loci for complex inflammatory diseases (for example, IRF5, NOD2, and PTGER4) and genes encoding histone modifiers and chromatin remodeling factors (for example, HDAC4, KDM2A, KDM2B, JARID2, ARID3A, and SMARCD3) undergo DNA methylation changes in leukocytes during early childhood. These results open new perspectives to understand leukocyte maturation and provide a catalogue of CpG sites that may need to be corrected for age effects when performing DNA methylation studies in children

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

Peer reviewe

Differentially methylated probes for each cell population in comparison to whole blood.

<p>PBMC-Peripheral blood mononuclear cells. Differentially methylated probes were defined by a linear model using the M-values. M-value is the log2 ratio of the intensities of methylated probe versus unmethylated probe, a measurement of how much more a probe is methylated compared to unmethylated <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0041361#pone.0041361-Du2" target="_blank">[46]</a>. *To extract the probes with largest difference in methylation, a gamma fit model was applied to M-values in order to define the three calls: “unmethylated”, “marginal” and “methylated”. Significant probes sharing the same call in the two compared populations were removed. **Variation is based on the estimate of the log2-fold-change corresponding to the effect obtained from the linear model, absolute M-values are presented. The percentages are based on the call distribution.</p

Schematic presentation of the isolation protocol and purity of the cell populations as measured by flow cytometry.

<p>Peripheral blood mononuclear cells (PBMC) and granulocytes were obtained by density gradient centrifugation and seven cell populations were purified by magnetic sorting. Upper panel shows forward and side scatter which confirmed cell morphology and granularity. The lower panel shows the overlay of cell surface markers for all the six donors. The purities of the cell populations were highly similar among all the six donors. Th cells  =  CD4⁺ T cells, Tc cells  =  CD8⁺ T cells, NK cells  =  CD56⁺ NK cells, B cells  =  CD19⁺ B cells, Monocytes  =  CD14⁺ monocytes. Data analyses are based on the comparison of all cell populations to whole blood.</p