Latest Publish: publish:2008-12-14

• S-C Wang et al (2008) "Age-Specific Epigenetic Drift in Late-Onset Alzheimer's Disease," PLoS ONE. 3(7): e2698

Despite an enormous research effort, most cases of late-onset Alzheimer's disease (LOAD) still remain unexplained and the current biomedical science is still a long way from the ultimate goal of revealing clear risk factors that can help in the diagnosis, prevention and treatment of the disease. Current theories about the development of LOAD hinge on the premise that Alzheimer's arises mainly from heritable causes. Yet, the complex, non-Mendelian disease etiology suggests that an epigenetic component could be involved. Using MALDI-TOF mass spectrometry in post-mortem brain samples and lymphocytes, we have performed an analysis of DNA methylation across 12 potential Alzheimer's susceptibility loci. In the LOAD brain samples we identified a notably age-specific epigenetic drift, supporting a potential role of epigenetic effects in the development of the disease. Additionally, we found that some genes that participate in amyloid-β processing (PSEN1, APOE) and methylation homeostasis (MTHFR, DNMT1) show a significant interindividual epigenetic variability, which may contribute to LOAD predisposition. The APOE gene was found to be of bimodal structure, with a hypomethylated CpG-poor promoter and a fully methylated 3′-CpG-island, that contains the sequences for the ε4-haplotype, which is the only undisputed genetic risk factor for LOAD. Aberrant epigenetic control in this CpG-island may contribute to LOAD pathology. We propose that epigenetic drift is likely to be a substantial mechanism predisposing individuals to LOAD and contributing to the course of disease.

我們的最新計畫:Cloud-R 針對R設計的雲端計算平台 publish:2008-12-14
R 是一種為統計計算和圖形顯示而設計的語言及環境，它和貝爾實驗室（Bell Laboratories） John Chambers 等人開發的 S 系統相似，提供了一系列統計和圖形顯示工具（線性和非線性模型， 統計檢驗，時間序列分析，分類， 聚類，...等）。 本實驗室以R 語言為基礎，設計出適合生物研究所需要的計算平台，以最新的雲端技術提供疾病研究、microarray數據分析、Go terms 富集分析等需要大量計算資源的生物統計，期許能加速台灣在生物資訊分析領域的進程。Related Link:Cloud-R Plan

Latest Publish: publish:2008-11-1

• J. Mill et al (2008) “Epigenomic Profiling Reveals DNA-Methylation Changes Associated with Major Psychosis,” Am J Hum Genet 82 696-711

Schizophrenia (SZ) [MIM 181500 ] and bipolar disorder (BD) [MIM 125480 ] are etiologically related psychiatric conditions, 1 together termed “major psychosis.” Studies of major psychosis have focused primarily on the interplay between genetic and environmental risk factors. Twin and adoption studies highlight a clear inherited component to both disorders, 2 but whereas replicated findings exist for a number of genes, association studies are characterized by nonreplication, small effect sizes, and significant heterogeneity. 3 Several epidemiological, clinical, and molecular peculiarities associated with major psychosis are difficult to explain with traditional gene- and environment-based approaches. Such peculiarities include the noncomplete concordance between monozygotic twins for both SZ (41%–65%) and BD (60%), [2] and [4] which cannot be accounted for by only environmental factors. [3] and [5] Other complexities of major psychosis include a fluctuating disease course with periods of remission and relapse, sexual dimorphism, peaks of susceptibility to disease coinciding with major hormonal rearrangements, and parent-of-origin effects. 3 These observations have led to speculation about the importance of epigenetic factors in mediating susceptibility to both SZ and BD. 3

Epigenetics refers to the heritable, but reversible, regulation of various genetic functions, including gene expression, mediated through modifications of DNA and histones. 6 Epigenetic processes are essential for normal cellular development and differentiation, and they allow the regulation of gene function through nonmutagenic mechanisms. The impact of DNA methylation on gene activity has been explained by two proven mechanisms. The “critical site” model puts an emphasis on the methylation of specific cytosines in transcription-factor binding sites, responsible for reducing binding affinity and thus the transcription of mRNA. 7 The “methylation density” model suggests that the proportion of methylated cytosines across a region, rather than at any specific position, controls chromatin conformation and thus the transcriptional potential of the gene. 7

The epigenetic model of major psychosis is based upon three general principles. 3 First, like the DNA sequence, the epigenetic profile of somatic cells is mitotically inherited, but unlike the DNA sequence, epigenetic signals are dynamic. The epigenetic status of the genome is tissue-specific, developmentally regulated, and influenced by both stochastic and environmental factors. Second, because epigenetic processes regulate various genetic and genomic functions, epigenetic factors can have profound phenotypic effects. Genes, even those containing no mutations or disease-predisposing polymorphisms, can be harmful if not expressed in the appropriate amount, at the correct time of the cell cycle, or in the correct compartment of the nucleus. Third, some epigenetic signals, rather than being reset and erased during gametogenesis, could be transmitted meiotically across generations. 8 This has obvious ramifications for the identification of the molecular substrate of inherited predisposition, in which heritable phenotypic variation is assumed to result exclusively from DNA-sequence variants.

To date, few studies have investigated the role of epigenetic factors in major psychosis, and none has taken a genome-wide epigenomic approach. DNA-methylation differences have been reported in the vicinity of both catechol-O-methyltransferase ( COMT ) 9 and reelin ( RELN ), 10 although these findings were not confirmed using fully quantitative methylation-profiling methods. [11] and [12] In this article we report findings from a comprehensive epigenomic study of major psychosis. Using DNA from the frontal cortex—a region previously implicated in the etiology of major psychosis 13 —derived from individuals with SZ, BD, and from matched controls (CTRL), we examined DNA methylation by utilizing two complementary approaches. First, we performed a microarray-based epigenomic scan of major psychosis using CpG-island microarrays after enrichment of the unmethylated fraction of brain DNA. Second, we performed a hypothesis-driven analysis of DNA methylation across candidate genes for which a priori evidence for a role in the etiology of major psychosis exists. In addition, to investigate whether epigenetic differences could be observed in the germline, we also used CpG-island microarrays to profile germline DNA methylation in BD patients and controls. Consistent with the epigenetic theory of major psychosis, we find considerable evidence for epigenetic changes associated with schizophrenia and bipolar disorder.