Targeted Methylation Profiling of Single Laser-Capture Microdissected Post-Mortem Brain Cells by Adapted Limiting Dilution Bisulfite Pyrosequencing (LDBSP).

A reoccurring issue in neuroepigenomic studies, especially in the context of neurodegenerative disease, is the use of (heterogeneous) bulk tissue, which generates noise during epigenetic profiling. A workable solution to this issue is to quantify epigenetic patterns in individually isolated neuronal cells using laser capture microdissection (LCM). For this purpose, we established a novel approach for targeted DNA methylation profiling of individual genes that relies on a combination of LCM and limiting dilution bisulfite pyrosequencing (LDBSP). Using this approach, we determined cytosine-phosphate-guanine (CpG) methylation rates of single alleles derived from 50 neurons that were isolated from unfixed post-mortem brain tissue. In the present manuscript, we describe the general workflow and, as a showcase, demonstrate how targeted methylation analysis of various genes, in this case, RHBDF2, OXT, TNXB, DNAJB13, PGLYRP1, C3, and LMX1B, can be performed simultaneously. By doing so, we describe an adapted data analysis pipeline for LDBSP, allowing one to include and correct CpG methylation rates derived from multi-allele reactions. In addition, we show that the efficiency of LDBSP on DNA derived from LCM neurons is similar to the efficiency obtained in previously published studies using this technique on other cell types. Overall, the method described here provides the user with a more accurate estimation of the DNA methylation status of each target gene in the analyzed cell pools, thereby adding further validity to this approach.

Stem Cell Technology for (Epi)genetic Brain Disorders.

Despite the enormous efforts of the scientific community over the years, effective therapeutics for many (epi)genetic brain disorders remain unidentified. The common and persistent failures to translate preclinical findings into clinical success are partially attributed to the limited efficiency of current disease models. Although animal and cellular models have substantially improved our knowledge of the pathological processes involved in these disorders, human brain research has generally been hampered by a lack of satisfactory humanized model systems. This, together with our incomplete knowledge of the multifactorial causes in the majority of these disorders, as well as a thorough understanding of associated (epi)genetic alterations, has been impeding progress in gaining more mechanistic insights from translational studies. Over the last years, however, stem cell technology has been offering an alternative approach to study and treat human brain disorders. Owing to this technology, we are now able to obtain a theoretically inexhaustible source of human neural cells and precursors in vitro that offer a platform for disease modeling and the establishment of therapeutic interventions. In addition to the potential to increase our general understanding of how (epi)genetic alterations contribute to the pathology of brain disorders, stem cells and derivatives allow for high-throughput drugs and toxicity testing, and provide a cell source for transplant therapies in regenerative medicine. In the current chapter, we will demonstrate the validity of human stem cell-based models and address the utility of other stem cell-based applications for several human brain disorders with multifactorial and (epi)genetic bases, including Parkinson's disease (PD), Alzheimer's disease (AD), fragile X syndrome (FXS), Angelman syndrome (AS), Prader-Willi syndrome (PWS), and Rett syndrome (RTT).

Epigenome-wide association studies in Alzheimer's disease; achievements and challenges.

Alzheimer's disease (AD) represents a devastating progressive neurodegenerative disease with a complex pathophysiology, affecting millions of people worldwide. Recent epigenome-wide association studies suggest a key role for epigenetic mechanisms in its development and course. Despite the fact that current evidence on the role of epigenetic dysregulation in aging and AD is convincing, the pioneering field of neuroepigenetics is still facing many challenges that need to be addressed to fundamentally increase our understanding about the underlying mechanisms of this neurodegenerative disorder. This perspective paper describes the current state of play for epigenetic research into AD and discusses how new methodological advances in the field of epigenetics and related data science disciplines could further spur the development of novel therapeutic agents and biomarker assays.

Methylomic profiling in trisomy 21 identifies cognition- and Alzheimer's disease-related dysregulation.

BACKGROUND: Trisomy 21 (T21) is associated with intellectual disability that ranges from mild to profound with an average intellectual quotient of around 50. Furthermore, T21 patients have a high risk of developing Alzheimer's disease (AD) early in life, characterized by the presence of senile plaques of amyloid protein and neurofibrillary tangles, leading to neuronal loss and cognitive decline. We postulate that epigenetic factors contribute to the observed variability in intellectual disability, as well as at the level of neurodegeneration seen in T21 individuals. MATERIALS AND METHODS: A genome-wide DNA methylation study was performed using Illumina Infinium® MethylationEPIC BeadChips on whole blood DNA of 3 male T21 patients with low IQ, 8 T21 patients with high IQ (4 males and 4 females), and 21 age- and sex-matched control samples (12 males and 9 females) in order to determine whether DNA methylation alterations could help explain variation in cognitive impairment between individuals with T21. In view of the increased risk of developing AD in T21 individuals, we additionally investigated the T21-associated sites in published blood DNA methylation data from the AgeCoDe cohort (German study on Ageing, Cognition, and Dementia). AgeCoDe represents a prospective longitudinal study including non-demented individuals at baseline of which a part develops AD dementia at follow-up. RESULTS: Two thousand seven hundred sixteen differentially methylated sites and regions discriminating T21 and healthy individuals were identified. In the T21 high and low IQ comparison, a single CpG located in the promoter of PELI1 was differentially methylated after multiple testing adjustment. For the same contrast, 69 differentially methylated regions were identified. Performing a targeted association analysis for the significant T21-associated CpG sites in the AgeCoDe cohort, we found that 9 showed significant methylation differences related to AD dementia, including one in the ADAM10 gene. This gene has previously been shown to play a role in the prevention of amyloid plaque formation in the brain. CONCLUSION: The differentially methylated regions may help understand the interaction between methylation alterations and cognitive function. In addition, ADAM10 might be a valuable blood-based biomarker for at least the early detection of AD.

Targeted Molecular Analysis in Adrenocortical Carcinomas: A Strategy Toward Improved Personalized Prognostication.

Context: Adrenocortical carcinoma (ACC) has a heterogeneous prognosis, and current medical therapies have limited efficacy in its advanced stages. Genome-wide multiomics studies identified molecular patterns associated with clinical outcome. Objective: Here, we aimed at identifying a molecular signature useful for both personalized prognostic stratification and druggable targets, using methods applicable in clinical routine. Design: In total, 117 tumor samples from 107 patients with ACC were analyzed. Targeted next-generation sequencing of 160 genes and pyrosequencing of 4 genes were applied to formalin-fixed, paraffin-embedded (FFPE) specimens to detect point mutations, copy number alterations, and promoter region methylation. Molecular results were combined with clinical/histopathological parameters (tumor stage, age, symptoms, resection status, and Ki-67) to predict progression-free survival (PFS). Results: In addition to known driver mutations, we detected recurrent alterations in genes not previously associated with ACC (e.g., NOTCH1, CIC, KDM6A, BRCA1, BRCA2). Best prediction of PFS was obtained integrating molecular results (more than one somatic mutation, alterations in Wnt/ß-catenin and p53 pathways, high methylation pattern) and clinical/histopathological parameters into a combined score (P < 0.0001, χ2 = 68.6). Accuracy of prediction for early disease progress was 83.3% (area under the receiver operating characteristic curve: 0.872, 95% confidence interval 0.80 to 0.94). Furthermore, 17 potentially targetable alterations were found in 64 patients (e.g., in CDK4, NOTCH1, NF1, MDM2, and EGFR and in DNA repair system). Conclusions: This study demonstrates that molecular profiling of FFPE tumor samples improves prognostication of ACC beyond clinical/histopathological parameters and identifies new potential drug targets. These findings pave the way to precision medicine in this rare disease.