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Single-cell epigenomic identification of inherited risk loci in Alzheimer’s and Parkinson’s disease

ABSTRACT: Single-cell epigenomic identification of inherited risk loci in Alzheimer’s and Parkinson’s disease

PROVIDER: PRJNA616031 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11442400_1.fastq.gz	Fastqsanger.gz
	SRR11442400_2.fastq.gz	Fastqsanger.gz
	SRR11442500_1.fastq.gz	Fastqsanger.gz
	SRR11442500_2.fastq.gz	Fastqsanger.gz
	SRR11442600_1.fastq.gz	Fastqsanger.gz

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Single-cell epigenomic identification of inherited risk loci in Alzheimer’s and Parkinson’s disease

Project description:Genome-wide association studies (GWAS) have identified thousands of variants associated with disease phenotypes. However, the majority of these variants do not alter coding sequences, making it difficult to assign their function. To this end, we present a multi-omic epigenetic atlas of the adult human brain through profiling of the chromatin accessibility landscapes and three-dimensional chromatin interactions of seven brain regions across a cohort of 39 cognitively healthy individuals. Single-cell chromatin accessibility profiling of 70,631 cells from six of these brain regions identifies 24 distinct cell clusters and 359,022 cell type-specific regulatory elements, capturing the regulatory diversity of the adult brain. We develop a machine learning classifier to integrate this multi-omic framework and predict dozens of functional single nucleotide polymorphisms (SNPs), nominating gene and cellular targets for previously orphaned GWAS loci. These predictions both inform well-studied disease-relevant genes, such as BIN1 in microglia for Alzheimer’s disease (AD) and reveal novel gene-disease associations, such as STAB1 in microglia and MAL in oligodendrocytes for Parkinson’s disease (PD). Moreover, we dissect the complex inverted haplotype of the MAPT (encoding tau) PD risk locus, identifying ectopic enhancer-gene contacts in neurons that increase MAPT expression and may mediate this disease association. This work greatly expands our understanding of inherited variation in AD and PD and provides a roadmap for the epigenomic dissection of noncoding regulatory variation in disease.

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Project description:Differential 5-methylcytosine and 5-hydroxymethylcytosine in Parkinson’s and Alzheimer’s Disease.

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Differential 5-methylcytosine and 5-hydroxymethylcytosine in Parkinson’s and Alzheimer’s Disease.

Project description:Background: 5-methylcytosine (5-mC) and its oxidized form, 5-hydroxymethylcytosine (5-hmC), are distinct epigenetic marks that help regulate gene expression in the mammalian brain. Existing studies have identified associations between 5-mC and neurodegenerative disease, but little work has examined the potential role of 5-hmC in Parkinson’s disease (PD) or Alzheimer’s disease (AD). Here, we utilized PD postmortem brain tissue and a public dataset from postmortem AD brains to analyze the effect of neurodegenerative disease on paired 5-mC and 5-hmC levels. Results: In PD samples, we measured genome-wide 5-mC and 5-hmC from control (n=3) and PD (n=6) brains using the Illumina EPIC array combined with bisulfite and oxidative bisulfite treatments (BS/oxBS-EPIC). In publicly sourced data, genome-wide 5-mC and 5-hmC were measured from control (n=25) and AD (n=62) human entorhinal cortex tissue using the Illumina 450K array combined with bisulfite and oxidative bisulfite treatment (BS/oxBS-450K). Paired 5-mC and 5-hmC beta values were generated using a custom pipeline of bioinformatics tools, and we modeled the effect of disease on paired 5-mC and 5-hmC data using a mixed effects beta regression model with a random effect for ID and an interaction term between disease category and DNA modification category (“5-mC” or “5-hmC”). We identified a number of CpG probes (AD: n=699, PD: total n = 80) that showed a significant interaction between disease status and DNA modification category (p-value < 2.4x10-7). Conclusions: While our PD data requires additional validation, our analyses suggest that there are widespread shifts in the balance between 5-mC and 5-hmC in Parkinson’s and Alzheimer’s disease.

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Project description:Single nucleotide variants (SNVs) in regulatory DNA are linked to inherited cancer risk. Massively parallel reporter assays (MPRA) of 5,031 SNVs linked to 14 neoplasms comprising >90% of human malignancies were performed in pertinent diploid cell types then integrated with matching chromatin accessibility, looping, and eQTL data to identify 411 regulatory SNVs and their putative target eGenes. The latter highlighted specific protein networks in lifetime cancer risk, including mitochondrial translation, proliferation, signaling, adhesion, and immunity. This cancer SNV compendium underscores the importance of studying pathogenic variants in disease-relevant cells and implicates specific dysregulated gene networks in cancer predisposition. It also indicates that inherited cancer risk can impact the same gene via orthogonal genetic mechanisms of dysregulated expression as well as protein coding sequence alteration and demonstrates that a subset of germline-encoded risk genes also enable tumor growth of established cancers.

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Project description:Parkinson’s disease (PD) is the second most common neurodegenerative disorder, affecting ~2–3% of people over 65 years of age. Recent studies have revealed that the molecular pathogenesis of PD involves a series of pathways and neurobiological processes, such as protein degradation, mitochondrial dysfunction, oxidative stress, autophagy, calcium homeostasis, axonal transport, and neuroinflammation, all suggesting that both the onset and course of PD is a complex multilevel and systematic process. Accumulating evidence demonstrates that long non-coding RNAs (lncRNAs) affect the pathogenesis of several diseases, such as cancers, immunological diseases, and neurodegenerative disorders, including Alzheimer’s disease and PD. Next generation sequencing provides a high-throughput method for exploring the diverse polyadenylated RNA populations. This approach allows accurate identification and quantitation of mRNAs and other non-coding RNAs, such as lncRNAs. The present study explored mRNAs and lncRNAs expression by using the next generation sequencing analysis (NGS) and the quantitative real-time PCR (qRT-PCR) assay for the confirmation of the NGS results, followed by functional analysis of the results.

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