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bioRxiv2017

Diagnostic and Prognostic Implications of Ribosomal Protein Transcript Coordination in Human Cancers

Ribosomes, the organelles responsible for the translation of mRNA, are comprised of rRNA and ~80 ribosomal proteins (RPs). Although canonically assumed to be maintained in equivalent proportions, some RPs have been shown to possess differential expression across tissue types. Dysregulation of RP expression occurs in a variety of human diseases, notably in many cancers, and altered expression of some RPs correlates with different tumor phenotypes and patient survival. To investigate the impact of global RP transcript (RPT) expression patterns on tumor phenotypes, we analyzed RPT expression of ~10,000 human tumors and 700 normal tissues with t-distributed stochastic neighbor embedding (t-SNE). We show here that normal tissues and cancers possess readily discernible RPT expression patterns. In tumors, this patterning is distinct from normal tissues, distinguishes tumor subtypes from one another, and in many cases correlates with molecular, pathological, and clinical features, including survival. Collectively, RPT expression can be used as a powerful and novel method of tumor classification, offering a potential clinical tool for prognosis and therapeutic stratification.

cancer biology↗

bioRxiv2017

Chemical Gating of the Mechanosensitive Piezo1 Channel by Asymmetric Binding of its Agonist Yoda1

Piezo proteins are homotrimeric ion channels that play major roles in normal and pathological mechanotransduction signaling in mammalian organisms. Their pharmacological control hence represents a potential therapeutic avenue. Yoda1, a Piezo1-selective small molecule agonist, is the only known selective Piezo modulator. How Yoda1 selectively interacts with Piezo1 and opens its pore is unknown. Here, by engineering and characterizing chimeras, we identified a minimal region responsible for Yoda1 binding. This region is located at the interface between the pore and the putative mechanosensory domains in each subunit. By characterizing hybrid channels containing Yoda1-insensitive and Yoda1-sensitive monomers, we demonstrate that the presence of only one Yoda1-sensitive Piezo1 subunit is sufficient for chemical activation, implicating that the asymmetric binding of Yoda1 to a single subunit enables channel opening. These findings shed light onto the gating mechanisms of Piezo channels and will pave the way for the rationale design of new Piezo channels modulators.

biochemistry↗

bioRxiv2017

The DNA methylation landscape of glioblastoma disease progression shows extensive heterogeneity in time and space

Glioblastoma is characterized by widespread genetic and transcriptional heterogeneity, yet little is known about the role of the epigenome in glioblastoma disease progression. Here, we present genome-scale maps of the DNA methylation dynamics in matched primary and recurring glioblastoma tumors, based on a national population registry and a comprehensively annotated clinical cohort. We demonstrate the feasibility of DNA methylation mapping in a large set of routinely collected formalin-fixed paraffin-embedded (FFPE) samples, and we validate bisulfite sequencing as a multi-purpose assay that allowed us to infer a range of different genetic, epigenetic, and transcriptional tumor characteristics. Based on these data, we identified characteristic differences between primary and recurring tumors, links between DNA methylation and the tumor microenvironment, and an association of epigenetic tumor heterogeneity with patient survival. In summary, this study provides a resource for dissecting DNA methylation heterogeneity in genetically diverse and heterogeneous tumors, and it demonstrates the feasibility of integrating epigenomics, radiology, and digital pathology in a representative national cohort, leveraging samples and data collected as part of routine clinical practice.

cancer biology↗

bioRxiv2017

The toxic nature of murine amylin and the immune responsivity of pancreatic islet to conformational antibody in mice

The human amylin is a pancreatic peptide hormone cosecreted with amylin and found in hyperhormonemic state along with insulin in subclinical diabetes. Amylin has been associated with the pathology of type 2 diabetes, particularly due to its ability to assembly into toxic oligomers and amyloid speciments. On the other hand, some variants such as murine amylin has been described as non amyloidogenic, either in vitro or in vivo. Recent data have demonstrated the amyloid propensity of murine amylin and the therapeutic analogue pramlintide, suggesting a universality for amylin amyloidosis. Here we report the amyloidogenesis of murine amylin, which showed lower responsivity to the fluorescent probe thioflavin T compared to human amylin, but presented highly organized fibrilar amyloid material. The aggregation of murine amylin also resulted in the formation of cytotoxic specimens, as evaluated in vitro in INS-1 cells. The aggregation product from murine amylin was responsive to a specific antibody raised against amyloid oligomers, the A11 oligomer antibody. Pancreatic islets of swiss mice have also shown responsivity for the anti-oligomer, indicating the natural abundance of such specimen in rodents. These data provide for the first time evidences for the toxic nature of oligomeric assemblies of murine amylin and its existence in non-transgenic mice.\n\nHighlights- Murine amylin forms oligomer species and amyloid fibrils in vitro\n- The murine amylin aggregation product display cellular toxicity\n- A11 anti-oligomer antibody recognizes murine amylin in vitro\n- Non-transgenic mice display immunoresposivity to anti-oligomer in pancreatic islet

biochemistry↗

bioRxiv2017

PrPSc-induced conformational changes and strain-specific structures of PrPSc revealed by Disulfide-crosslink scanning

There exist many phenotypically-varied prion strains, like viruses, despite the absence of conventional genetic material which codes the phenotypic information. As prion is composed solely of the pathological isoform (PrPSc) of prion protein (PrP), the strain-specific traits are hypothesized to be enciphered in the structural details of PrPSc. Identification of the structures of PrPSc is therefore vital for the understanding of prion biology, though they remain unidentified due to the incompatibility of PrPSc with conventional high-resolution structural analyses. Based on our previous hypothesis that the region between the first and the second -helix (H1[~]H2) and the distal region of the third helix (Ctrm) of the cellular isoform of PrP (PrPC) have important roles for efficient interactions with PrPSc, we created series of mutant PrPs with two cysteine substitutions (C;C-PrP) which were systematically designed to form an intramolecular disulfide crosslink between H1[~]H2 and Ctrm and assessed their conformational changes by prions: Specifically, a cysteine substitution in H1[~]H2 from 165 to 169 was combined with cysteine-scanning along Ctrm from 220 to 229. C;C-PrPs with the crosslinks were expressed normally with the similar glycosylation patterns and subcellular localization as the wild-type PrP albeit with varied expression levels. Interestingly, some of the C;C-PrPs converted to the protease-resistant isoforms in the N2a cells persistently infected with 22L prion strain, whereas the same mutants did not convert in the cells infected with another prion strain Fukuoka1, indicating that local structures of PrPSc in these regions vary among prion strains and contribute to prion-strain diversity. Moreover, patterns of the crosslinks of the convertible C;C-PrPs implied drastic changes in positional relations of H1[~]H2 and Ctrm in the PrPSc-induced conformational changes by 22L prion. Thus, disulfide-crosslink scanning is a useful approach for investigation of strain-specific structures of PrPSc, and would be applicable to other types of amyloids as well.

molecular biology↗

bioRxiv2017

Transcriptome wide analysis of natural antisense transcripts shows their potential role in breast cancer.

Non-coding RNAs (ncRNA) represent at least 1/5 of the mammalian transcript amount, and about 90% of the genome length is actively transcribed. Many ncRNAs have been demonstrated to play a role in cancer. Among them, natural antisense transcripts (NAT) are RNA sequences which are complementary and overlapping to those of protein-coding transcripts (PCT). NATs were punctually described as regulating gene expression, and are expected to act more frequently in cis than other ncRNAs that commonly function in trans. In this work, 22 breast cancers expressing estrogen receptors and their paired healthy tissues were analyzed by strand-specific RNA sequencing. To highlight the potential role of NATs in gene regulations occurring in breast cancer, three different gene extraction methods were used: differential expression analysis of NATs between tumor and healthy tissues, differential correlation analysis of paired NAT/PCT between tumor and healthy tissues, and NAT/PCT read count ratio variation between tumor and healthy tissues. Each of these methods yielded lists of NAT/PCT pairs that were demonstrated to be enriched in survival-associated genes on an independent cohort (TCGA). This work allows to highlight NAT lists that display a strong potential to affect the expression of genes involved in the breast cancer pathology.

genomics↗

bioRxiv2017

Gradual Cerebral Hypoperfusion Impair Fear Conditioning and Object Recognition Learning and Memory in Mice: Potential Roles of Neurodegeneration and Cholinergic Dysfunction

In the present study, male C57BL/6J mice were subjected to gradual cerebral hypoperfusion by implanting an ameroid constrictor (AC) on the left common carotid artery (CCA) and a stenosis on the right CCA. In the sham group, all surgical procedures were kept the same except no AC was implanted and stenosis was not performed. One month following the surgical procedures, fear conditioning and object recognition tests were conducted to evaluate learning and memory functions and motor functions were assessed using a balance beam test. At the experimental endpoint, mice were perfused and brains were collected for immunostaining and histology. Learning and memory as well as motor functions were significantly impaired in the hypoperfusion group. The immunoreactivity to choline acetyltransferase was decreased in dorsal striatum and basal forebrain of the hypoperfusion group indicating that cholinergic tone in these brain regions was compromised. In addition, an increased number of Fluoro-Jade positive neurons was also found in cerebral cortex, dorsal striatum and hippocampus indicating neurodegeneration in these brain regions. Based on this pattern of data, we argued that this mouse model would be a useful tool to investigate the therapeutic interventions for the treatment of vascular dementia. Additionally, this model could be employed to exploit the effect of microvascular occlusions on cognitive impairment in the absence and presence of Alzheimer pathology.

neuroscience↗

bioRxiv2017

Host-pathogen interactions in urinary tract infection from the structure and diversity of urinary cell-free DNA

Infections of the urinary tract are the most common form of infection in the human population. Here, we tested the utility of urinary cell-free DNA (cfDNA) to comprehensively monitor host and pathogen dynamics in the scope of bacterial and viral urinary tract infections. We assayed cfDNA isolated from 141 urine samples obtained from a cohort of 82 kidney transplant recipients by next-generation sequencing. We find that urinary cfDNA simultaneously informs about the composition of the bacterial and viral components of the microbiome, antimicrobial susceptibility, bacterial growth dynamics, kidney allograft injury, and the host response to infection. These different layers of information are accessible from a single assay and individually agree with corresponding clinical tests based on quantitative PCR, conventional bacterial culture, and urinalysis. In addition, cfDNA reveals the frequent occurrence of pathologies that remain undiagnosed in conventional diagnostic workups. Our work identifies urinary cfDNA as a highly versatile tool to monitor infections of the urinary tract.

genomics↗

bioRxiv2017

Replication of early and recent Zika virus isolates throughout mouse brain development

Fetal infection with Zika virus (ZIKV) can lead to congenital Zika virus syndrome (cZVS), which includes cortical malformations and microcephaly. The aspects of cortical development that are affected during virus infection are unknown. Using organotypic brain slice cultures generated from embryonic mice of various ages, sites of ZIKV replication including the neocortical proliferative zone and radial columns, as well as the developing midbrain, were identified. The infected radial units are surrounded by uninfected cells undergoing apoptosis, suggesting that programmed cell death may limit viral dissemination in the brain and may constrain virus associated injury. Therefore, a critical aspect of ZIKV induced neuropathology may be defined by death of uninfected cells. All ZIKV isolates assayed replicated efficiently in early and mid-gestation cultures, and two isolates examined replicated in late-gestation tissue. Alteration of neocortical cytoarchitecture, such as disruption of the highly-elongated basal processes of the radial glial progenitor cells, and impairment of postmitotic neuronal migration were also observed. These data suggest that all lineages of ZIKV tested are neurotropic, and that ZIKV infection interferes with multiple aspects of neurodevelopment that contribute to the complexity of cZVS.\n\nSignificanceZika virus infection has been associated with multiple pathologies of the central nervous system (CNS) including microcephaly, Guillain-Barre syndrome, lissencephaly, the loss of white and grey matter volume and acute myelitis. Using organotypic brain slice cultures, we determined that ZIKV replicates across different embryonic developmental stages, and viral infection can disrupt proper brain development leading to congenital CNS complications. These data illustrate that all lineages of ZIKV tested are neurotropic, and that infection may disrupt neuronal migration during brain development. The results expand our understanding of neuropathologies associated with congenital Zika virus syndrome.

microbiology↗

bioRxiv2017

Insulin resistance in cavefish as an adaptation to a nutrient-limited environment

Periodic food shortage is one of the biggest challenges organisms face in natural habitats. How animals cope with nutrient limited conditions is an active area of study, of particular relevance in the context of the current increasing destabilization of global climate. Caves represent an extreme setting where animals have adapted to nutrient-limited conditions, as most cave environments lack a primary energy source. Here we show that cave-adapted populations of the Mexican Tetra, Astyanax mexicanus, have dysregulated blood glucose homeostasis and are insulin resistant compared to the river-adapted population. We found that multiple cave populations carry a mutation in the insulin receptor that leads to decreased insulin binding in vitro. Surface/cave hybrid fish carrying the allele weigh more than non-carriers, and zebrafish genetically engineered to carry the mutation similarly have increased body weight and insulin resistance. Higher bodyweight may be advantageous in the cave as a strategy to cope with infrequent food. In humans, the identical mutation in the insulin receptor leads to a severe form of insulin resistance and dramatically reduced life-span. However, cavefish have a similar lifespan to surface fish (of greater than fourteen years) and do not accumulate advanced glycated end products (AGEs) in the blood that are typically associated with progression of diabetes-associated pathologies. Our findings raise the intriguing hypothesis that cavefish have acquired compensatory mechanisms that allow them to circumvent the typical negative effects associated with failure to regulate blood glucose.

evolutionary biology↗

bioRxiv2017

IVIM parameters have good scan-rescan reproducibility when evidential motion contaminated and poorly fitted image data are removed

BackgroundIntravoxel Incoherent Motion (IVIM) diffusion MRI is a promising technique for liver pathology evaluation, but this techniques scan-rescan reproducibility has been reported to be unsatisfactory.\n\nObjectiveTo understand whether IVIM MRI parameters for liver parenchyma can be good after removal of motion contaminated and/or poorly fitted image data.\n\nMaterial and MethodsEighteen healthy volunteers had liver scanned twice at the same session to assess scan-rescan repeatability, and again in another session after an average interval of 13 days to assess reproducibility. Diffusion weighted image were acquired with a 3T scanner using respiratory-triggered echo-planar sequence and 16 b-values (0 to 800 s/mm2). Measurement was performed on the right liver with segmented-unconstrained least square fitting. Image series with evidential anatomical mismatch, apparent artifacts, and poorly fitted signal intensity vs. b-value curve were excluded. A minimum of three slices was deemed necessary for IVIM parameter estimation of a liver.\n\nResultsWith total 54 examinations, 6 scans did not satisfy inclusion criteria, leading to a success rate of 89%; and 14 volunteers were finally included. With each scan a mean of 5.3 slices (range: 3-10 slices) were utilized for analysis. Using threshold b-value=80s/mm2, the coefficient of variation and within-subject coefficient of variation for repeatability and reproducibility were: 2.86% and 4.24% for Dslow, 3.81% and 4.24%, for PF, 18.16% and 24.88% for Dfast; and those for reproducibility were 2.48% and 3.24% for Dslow; 4.91% and 5.38% for PF; 21.18% and 30.89% for Dfast.\n\nConclusionIVIM parameter scan-rescan reproducibility can be potentially good.

biophysics↗

bioRxiv2017

Addiction in a Bounded Rational Model: Role of Environment and its Exploration

Several decision-making vulnerabilities have been identified as underlying causes for addictive behaviours, or the repeated execution of stereotyped actions despite their adverse consequences. These vulnerabilities are mostly associated with brain alterations caused by the consumption of substances of abuse. However, addiction can also happen in the absence of a pharmacological component, such as seen in pathological gambling and videogaming. We use a new reinforcement learning model to highlight a previously neglected vulnerability that we suggest interacts with those already identified, whilst playing a prominent role in non-pharmacological forms of addiction. Specifically, we show that a duallearning system (i.e. combining model-based and model-free) can be vulnerable to highly rewarding, but suboptimal actions, that are followed by a complex ramification of stochastic adverse effects. This phenomenon is caused by the overload of the capabilities of an agent, as time and cognitive resources required for exploration, deliberation, situation recognition, and habit formation, all increase as a function of the depth and richness of detail of an environment. Furthermore, the cognitive overload can be aggravated due to alterations (e.g. caused by stress) in the bounded rationality, i.e. the limited amount of resources available for the model-based component, in turn increasing the agents chances to develop or maintain addictive behaviours. Our study demonstrates that, independent of drug consumption, addictive behaviours can arise in the interaction between the environmental complexity and the biologically finite resources available to explore and represent it.

neuroscience↗

bioRxiv2017

A risk stratification model for lung cancer based on gene coexpression network

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of the previously reported models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray datasets obtained from lung adenocarcinoma, gene coexpression network analysis was performed to identify survival-related network modules. Representative genes of these network modules were selected and then, risk stratification model was constructed exploiting deep learning algorithm. The model was validated in two independent test cohorts. Survival analysis using univariate and multivariate Cox regression was performed using the output of the model to evaluate whether the model could predict patients overall survival independent of clinicopathological variables. Five network modules were significantly associated with patients survival. Considering prognostic significance and representativeness, genes of the two survival-related modules were selected for input data of the risk stratification model. The output of the model was significantly associated with patients overall survival in the two independent test sets as well as training set (p < 0.00001, p < 0.0001 and p = 0.02 for training set, test set 1 and 2, respectively). In multivariate analyses, the model was associated with patients prognosis independent of other clinical and pathological features. Our study presents a new perspective on incorporating gene coexpression networks into the gene expression signature, and the clinical application of deep learning in genomic data science for prognosis prediction.

bioinformatics↗

bioRxiv2017

Coexistence of multiple endemic and pandemic lineages of the rice blast pathogen

The rice blast fungus Magnaporthe oryzae (syn. Pyricularia oryzae) is both a threat to global food security and a model for plant pathology. Molecular pathologists need an accurate understanding of the origins and line of descent of M. oryzae populations, to identify the genetic and functional bases of pathogen adaptation, and to guide the development of more effective control strategies. We used a whole-genome sequence analysis of samples from different times and places to infer details about the genetic makeup of M. oryzae from a global collection of isolates. Analyses of population structure identified six lineages within M. oryzae, including two pandemic on japonica and indica rice, respectively, and four lineages with more restricted distributions. Tip-dating calibration indicated that M. oryzae lineages separated about a millenium ago, long after the initial domestication of rice. The major lineage endemic to continental Southeast Asia displayed signatures of sexual recombination and evidence of DNA acquisition from multiple lineages. Tests for weak natural selection revealed that the pandemic spread of clonal lineages entailed an evolutionary cost, in terms of the accumulation of deleterious mutations. Our findings reveal the coexistence of multiple endemic and pandemic lineages with contrasting population and genetic characteristics within a widely distributed pathogen.\n\nImportanceThe rice blast fungus Magnaporthe oryzae (syn. Pyricularia oryzae) is a textbook example of a rapidly adapting pathogen, and is responsible for one of the most damaging diseases of rice. Improvements in our understanding of Magnaporthe oryzae diversity and evolution are required, to guide the development of more effective control strategies. We used genome sequencing data for samples from around the world to infer the evolutionary history of M. oryzae. We found that M. oryzae diversified about a thousand years ago ago, separating into six main lineages: two pandemic on japonica and indica rice, respectively, and four with more restricted distributions. We also found that a lineage endemic to continental Southeast Asia displayed signatures of sexual recombination and the acquisition of genetic material from multiple lineages. This work provides a population-level genomic framework for defining molecular markers for the control of rice blast and investigations of the molecular basis of differences in pathogenicity between M. oryzae lineages.

evolutionary biology↗

bioRxiv2017

Prediction of early breast cancer patient survival using ensembles of hypoxia signatures

BackgroundBiomarkers are a key component of precision medicine. However, full clinical integration of biomarkers has been met with challenges, partly attributed to analytical difficulties. It has been shown that biomarker reproducibility is susceptible to data preprocessing approaches. Here, we systematically evaluated machine-learning ensembles of preprocessing methods as a general strategy to improve biomarker performance for prediction of survival from early breast cancer.\n\nResultsWe risk stratified breast cancer patients into either low-risk or high-risk groups based on four published hypoxia signatures (Buffa, Winter, Hu, and Sorensen), using 24 different preprocessing approaches for microarray normalization. The 24 binary risk profiles determined for each hypoxia signature were combined using a random forest to evaluate the efficacy of a preprocessing ensemble classifier. We demonstrate that the best way of merging preprocessing methods varies from signature to signature, and that there is likely no best preprocessing pipeline that is universal across datasets, highlighting the need to evaluate ensembles of preprocessing algorithms. Further, we developed novel signatures for each preprocessing method and the risk classifications from each were incorporated in a meta-random forest model. Interestingly, the classification of these biomarkers and its ensemble show striking consistency, demonstrating that similar intrinsic biological information are being faithfully represented. As such, these classification patterns further confirm that there is a subset of patients whose prognosis is consistently challenging to predict.\n\nConclusionsPerformance of different prognostic signatures varies with pre-processing method. A simple classifier by unanimous voting of classifications is a reliable way of improving on single preprocessing methods. Future signatures will likely require integration of intrinsic and extrinsic clinico-pathological variables to better predict disease-related outcomes.\n\nAbbreviations

bioinformatics↗

bioRxiv2017

Mechanical mapping of spinal cord development and repair in living zebrafish larvae using Brillouin microscopy

The mechanical properties of biological tissues are increasingly recognized as important factors in developmental and pathological processes. Most existing mechanical measurement techniques either necessitate destruction of the tissue for access or provide insufficient spatial resolution. Here, we show for the first time a systematic application of confocal Brillouin microscopy to quantitatively map the mechanical properties of spinal cord tissues during biologically relevant processes in a contact-free and non-destructive manner. Living zebrafish larvae were mechanically imaged in all anatomical planes, during development and after spinal cord injury. These experiments revealed that Brillouin microscopy is capable of detecting the mechanical properties of distinct anatomical structures without interfering with the animals natural development. The Brillouin shift within the spinal cord increased during development and transiently decreased during the repair processes following spinal cord transection. By taking into account the refractive index distribution, we explicitly determined the apparent longitudinal modulus and viscosity of different larval zebrafish tissues. Importantly, mechanical properties differed between tissues in situ and in excised slices. The presented work constitutes the first step towards an in vivo assessment of spinal cord tissue mechanics during regeneration, provides a methodical basis to identify key determinants of mechanical tissue properties and allows to test their relative importance in combination with biochemical and genetic factors during developmental and regenerative processes.

biophysics↗

bioRxiv2017

CXCR4 involvement in neurodegenerative diseases

Neurodegenerative diseases likely share common underlying pathobiology. Although prior work has identified susceptibility loci associated with various dementias, few, if any, studies have systematically evaluated shared genetic risk across several neurodegenerative diseases. Using genome-wide association data from large studies (total n = 82,337 cases and controls), we utilized a previously validated approach to identify genetic overlap and reveal common pathways between progressive supranuclear palsy (PSP), frontotemporal dementia (FTD), Parkinsons disease (PD) and Alzheimers disease (AD). In addition to the MAPT H1 haplotype, we identified a variant near the chemokine receptor CXCR4 that was jointly associated with increased risk for PSP and PD. Using bioinformatics tools, we found strong physical interactions between CXCR4 and four microglia related genes, namely CXCL12, TLR2, RALB and CCR5. Evaluating gene expression from post-mortem brain tissue, we found that expression of CXCR4 and microglial genes functionally related to CXCR4 was dysregulated across a number of neurodegenerative diseases. Furthermore, in a mouse model of tauopathy, expression of CXCR4 and functionally associated genes was significantly altered in regions of the mouse brain that accumulate neurofibrillary tangles most robustly. Beyond MAPT, we show dysregulation of CXCR4 expression in PSP, PD, and FTD brains, and mouse models of tau pathology. Our multi-modal findings suggest that abnormal signaling across a network of microglial genes may contribute to neurodegeneration and may have potential implications for clinical trials targeting immune dysfunction in patients with neurodegenerative diseases.

genetics↗

bioRxiv2017

A histone acetylome-wide association study of Alzheimer’s disease: neuropathology-associated regulatory variation in the human entorhinal cortex

Alzheimers disease (AD) is a chronic neurodegenerative disorder characterized by the progressive accumulation of amyloid-{beta} (A{beta}) plaques and neurofibrillary tangles in the neocortex. Recent studies have implicated a role for regulatory genomic variation in AD progression, finding widespread evidence for altered DNA methylation associated with neuropathology. To date, however, no study has systematically examined other types of regulatory genomic modifications in AD. In this study, we quantified genome-wide patterns of lysine H3K27 acetylation (H3K27ac) - a robust mark of active enhancers and promoters that is strongly correlated with gene expression and transcription factor binding - in entorhinal cortex samples from AD cases and matched controls (n = 47) using chromatin immunoprecipitation followed by highly parallel sequencing (ChIP-seq). Across ~182,000 robustly detected H3K27ac peak regions, we found widespread acetylomic variation associated with AD neuropathology, identifying 4,162 differential peaks (FDR < 0.05) between AD cases and controls. These differentially acetylated peaks are enriched in disease-specific biological pathways and include regions annotated to multiple genes directly involved in the progression of A{beta} and tau pathology (e.g. APP, PSEN1, PSEN2, MAPT), as well as genomic regions containing variants associated with sporadic late-onset AD. This is the first study of variable H3K27ac yet undertaken in AD and the largest study investigating this modification in the entorhinal cortex. In addition to identifying molecular pathways associated with AD neuropathology, we present a framework for genome-wide studies of histone modifications in complex disease, integrating our data with results obtained from genome-wide association studies as well as other epigenetic marks profiled on the same samples.

genomics↗