30 research outputs found
Allele-Specific, Age-Dependent and BMI-Associated DNA Methylation of Human MCHR1
Background: Melanin-concentrating hormone receptor 1 (MCHR1) plays a significant role in regulation of energy balance, food intake, physical activity and body weight in humans and rodents. Several association studies for human obesity showed contrary results concerning the SNPs rs133072 (G/A) and rs133073 (T/C), which localize to the first exon of MCHR1. The variations constitute two main haplotypes (GT, AC). Both SNPs affect CpG dinucleotides, whereby each haplotype contains a potential methylation site at one of the two SNP positions. In addition, 15 CpGs in close vicinity of these SNPs constitute a weak CpG island. Here, we studied whether DNA methylation in this sequence context may contribute to population- and age-specific effects of MCHR1 alleles in obesity. \ud
Principal Findings: We analyzed DNA methylation of a 315 bp region of MCHR1 encompassing rs133072 and rs133073 and the CpG island in blood samples of 49 individuals by bisulfite sequencing. The AC haplotype shows a significantly higher methylation level than the GT haplotype. This allele-specific methylation is age-dependent. In young individuals (20â\u80\u9330 years) the difference in DNA methylation between haplotypes is significant; whereas in individuals older than 60 years it is not detectable. Interestingly, the GT allele shows a decrease in methylation status with increasing BMI, whereas the methylation of the AC allele is not associated with this phenotype. Heterozygous lymphoblastoid cell lines show the same pattern of allele-specific DNA methylation. The cell line, which exhibits the highest difference in methylation levels between both haplotypes, also shows allele-specific transcription of MCHR1, which can be abolished by treatment with the DNA\ud
methylase inhibitor 5-aza-2'-deoxycytidine.\ud
Conclusions:We show that DNA methylation at MCHR1 is allele-specific, age-dependent, BMI-associated and affects transcription. Conceivably, this epigenetic regulation contributes to the age- and/or population specific effects reported for MCHR1 in several human obesity studies.\ud
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doi: 10.1371/journal.pone.0017711\u
Epigenome-Wide Scans Identify Differentially Methylated Regions for Age and Age-Related Phenotypes in a Healthy Ageing Population
Age-related changes in DNA methylation have been implicated in cellular senescence and longevity, yet the causes and functional consequences of these variants remain unclear. To elucidate the role of age-related epigenetic changes in healthy ageing and potential longevity, we tested for association between whole-blood DNA methylation patterns in 172 female twins aged 32 to 80 with age and age-related phenotypes. Twin-based DNA methylation levels at 26,690 CpG-sites showed evidence for mean genome-wide heritability of 18%, which was supported by the identification of 1,537 CpG-sites with methylation QTLs in cis at FDR 5%. We performed genome-wide analyses to discover differentially methylated regions (DMRs) for sixteen age-related phenotypes (ap-DMRs) and chronological age (a-DMRs). Epigenome-wide association scans (EWAS) identified age-related phenotype DMRs (ap-DMRs) associated with LDL (STAT5A), lung function (WT1), and maternal longevity (ARL4A, TBX20). In contrast, EWAS for chronological age identified hundreds of predominantly hyper-methylated age DMRs (490 a-DMRs at FDR 5%), of which only one (TBX20) was also associated with an age-related phenotype. Therefore, the majority of age-related changes in DNA methylation are not associated with phenotypic measures of healthy ageing in later life. We replicated a large proportion of a-DMRs in a sample of 44 younger adult MZ twins aged 20 to 61, suggesting that a-DMRs may initiate at an earlier age. We next explored potential genetic and environmental mechanisms underlying a-DMRs and ap-DMRs. Genome-wide overlap across cis-meQTLs, genotype-phenotype associations, and EWAS ap-DMRs identified CpG-sites that had cis-meQTLs with evidence for genotype-phenotype association, where the CpG-site was also an ap-DMR for the same phenotype. Monozygotic twin methylation difference analyses identified one potential environmentally-mediated ap-DMR associated with total cholesterol and LDL (CSMD1). Our results suggest that in a small set of genes DNA methylation may be a candidate mechanism of mediating not only environmental, but also genetic effects on age-related phenotypes
Photodynamic therapy for periungual pyogenic granuloma-like during chemotherapy: our preliminary results
The entorhinal cortex of Megachiroptera: a comparative study of Wahlberg's epauletted fruit bat and the straw-coloured fruit bat
This study describes the organisation of the entorhinal cortex of the Megachiroptera, Strawcoloured fruit bat and Wahlberg’s epauletted fruit bat. Using Nissl and Timm stains, parvalbumin and SMI-32 immunohistochemistry, we identified 5 fields within the medial(MEA) and lateral (LEA) entorhinal areas. MEA fields ECL and EC are characterised by a poor differentiation between layers II and III, a distinct layer IV and broad, stratified layers V
and VI. LEA fields EI, ER and EL are distinguished by cell clusters in layer II, a clear differentiation between layers II and III, a wide columnar layer III, and a broad sublayer Va. Clustering in LEA layer II was more typical of the Straw-coloured fruit bat. Timm-staining was most intense in layers Ib and II across all fields, and layer III of field ER. Parvalbuminlike staining varied along a medio-lateral gradient with highest immunoreactivity in layers II and III of MEA and more lateral fields of LEA. Sparse SMI-32-like immunoreactivity was seen only in Wahlberg’s epauletted fruit bat. Of the neurons in MEA layer II, ovoid stellate cells account for ~38%, polygonal stellate cells for ~8%, pyramidal cells for ~18%, oblique
pyramidal cells for ~6%, and other neurons of variable morphology for ~29%. Differences between bats and other species in cellular make-up and cytoarchitecture of layer II may relate to their 3-dimensional habitat. Cytoarchitecture of layer V in conjunction with high
encephalisation and structural changes in the hippocampus suggest similarities in efferent hippocampal-entorhinal-cortical interactions between fruit bats and primates
Recurrence patterns after maximal surgical resection and postoperative radiotherapy in anaplastic gliomas according to the new 2016 WHO classification
Impact of Including Peritumoral Edema in Radiotherapy Target Volume on Patterns of Failure in Glioblastoma following Temozolomide-based Chemoradiotherapy
Tissue specific DNA methylation of CpG islands in normal human adult somatic tissues distinguishes neural from non-neural tissues
Although most CpG islands are generally thought to remain unmethylated in all adult somatic tissues, recent genome-wide approaches have found that some CpG islands have distinct methylation patterns in various tissues, with most differences being seen between germ cells and somatic tissues. Few studies have addressed this among human somatic tissues and fewer still have studied the same sets of tissues from multiple individuals. In the current study, we used Restriction Landmark Genomic Scanning to study tissue specific methylation patterns in a set of 12 human tissues collected from multiple individuals. We identified 34 differentially methylated CpG islands among these tissues, many of which showed consistent patterns in multiple individuals. Of particular interest were striking differences in CpG island methylation, not only among brain regions, but also between white and grey matter of the same region. These findings were confirmed for selected loci by quantitative bisulfite sequencing. Cluster analysis of the RLGS data indicated that several tissues clustered together, but the strongest clustering was in brain. Tissues from different brain regions clustered together, and, as a group, brain tissues were distinct from either mesoderm or endoderm derived tissues which demonstrated limited clustering. These data demonstrate consistent tissue specific methylation for certain CpG islands, with clear differences between white and grey matter of the brain. Furthermore, there was an overall pattern of tissue specifically methylated CpG islands that distinguished neural tissues from non-neural