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Biology subjects

Yong, W. H.

Publications and source records attributed to Yong, W. H..

5 recordsLinked to original sources

Spatial and single-nucleus transcriptomic analysis of genetic and sporadic forms of Alzheimer's Disease

The pathogenesis of Alzheimers disease (AD) depends on environmental and heritable factors, with remarkable differences evident between individuals at the molecular level. Here we present a transcriptomic survey of AD using spatial transcriptomics (ST) and single-nucleus RNA-seq in cortical samples from early-stage AD, late-stage AD, and AD in Down Syndrome (AD in DS) donors. Studying AD in DS provides an opportunity to enhance our understanding of the AD transcriptome, potentially bridging the gap between genetic mouse models and sporadic AD. Our analysis revealed spatial and cell-type specific changes in disease, with broad similarities in these changes between sAD and AD in DS. We performed additional ST experiments in a disease timecourse of 5xFAD and wildtype mice to facilitate cross-species comparisons. Finally, amyloid plaque and fibril imaging in the same tissue samples used for ST enabled us to directly link changes in gene expression with accumulation and spread of pathology.

neuroscience↗

Learning fast and fine-grained detection of amyloid neuropathologies from coarse-grained expert labels

Precise, scalable, and quantitative evaluation of whole slide images is crucial in neuropathology. We release a deep learning model for rapid object detection and precise information on the identification, locality, and counts of cored plaques and cerebral amyloid angiopathies (CAAs). We trained this object detector using a repurposed image-tile dataset without any human-drawn bounding boxes. We evaluated the detector on a new manually-annotated dataset of whole slide images (WSIs) from three institutions, four staining procedures, and four human experts. The detector matched the cohort of neuropathology experts, achieving 0.64 (model) vs. 0.64 (cohort) average precision (AP) for cored plaques and 0.75 vs. 0.51 AP for CAAs at a 0.5 IOU threshold. It provided count and locality predictions that correlated with gold-standard CERAD-like WSI scoring (p=0.07{+/-} 0.10). The openly-available model can quickly score WSIs in minutes without a GPU on a standard workstation.

pathology↗

HIV, Pathology and epigenetic age acceleration in different human tissues

BackgroundEpigenetic clocks based on patterns of DNA methylation have great importance in understanding aging and disease; however, there are basic questions to be resolved in their application. It remains unknown whether epigenetic age acceleration (EAA) within an individual shows strong correlation between different primary tissue sites, the extent to which tissue pathology and clinical illness correlates with EAA in the target organ, and if EAA variability across tissues differs according to sex. Considering the outsized role of age-related illness in Human Immunodeficiency Virus-1 (HIV), these questions were pursued in a sample enriched for tissue from HIV-infected individuals. MethodsWe used a custom methylation array to generate DNA methylation data from 661 samples representing 11 human tissues (adipose, blood, bone marrow, heart, kidney, liver, lung, lymph node, muscle, spleen, and pituitary gland) from 133 clinically-characterized, deceased individuals, including 75 infected with HIV. We developed a multimorbidity index based on the clinical disease history. ResultsEpigenetic age was moderately correlated across tissues. Blood had the greatest number and degree of correlation, most notably with spleen and bone marrow. However, blood did not correlate with epigenetic age of liver. EAA in liver was weakly correlated with EAA in kidney, adipose, lung, and bone marrow. Clinically, hypertension was associated with EAA in several tissues, consistent with the multi-organ impacts of this illness. HIV infection was associated with positive age acceleration in kidney and spleen. Male sex was associated with increased epigenetic acceleration in several tissues. Preliminary evidence indicates that Amyotrophic Lateral Sclerosis is associated with positive EAA in muscle tissue. Finally, greater multimorbidity was associated with greater EAA across all tissues. ConclusionBlood alone will often fail to detect EAA in other tissues. While hypertension is associated with increased EAA in several tissues, many pathologies are associated with organ-specific age acceleration.

molecular biology↗

Microglia do not restrict SARS-CoV-2 replication following infection of the central nervous system of K18-hACE2 transgenic mice

Unlike SARS-CoV-1 and MERS-CoV, infection with SARS-CoV-2, the viral pathogen responsible for COVID-19, is often associated with neurologic symptoms that range from mild to severe, yet increasing evidence argues the virus does not exhibit extensive neuroinvasive properties. We demonstrate SARS-CoV-2 can infect and replicate in human iPSC-derived neurons and that infection shows limited anti-viral and inflammatory responses but increased activation of EIF2 signaling following infection as determined by RNA sequencing. Intranasal infection of K18 human ACE2 transgenic mice (K18-hACE2) with SARS-CoV-2 resulted in lung pathology associated with viral replication and immune cell infiltration. In addition, [~]50% of infected mice exhibited CNS infection characterized by wide-spread viral replication in neurons accompanied by increased expression of chemokine (Cxcl9, Cxcl10, Ccl2, Ccl5 and Ccl19) and cytokine (Ifn-{lambda} and Tnf-) transcripts associated with microgliosis and a neuroinflammatory response consisting primarily of monocytes/macrophages. Microglia depletion via administration of colony-stimulating factor 1 receptor inhibitor, PLX5622, in SARS-CoV-2 infected mice did not affect survival or viral replication but did result in dampened expression of proinflammatory cytokine/chemokine transcripts and a reduction in monocyte/macrophage infiltration. These results argue that microglia are dispensable in terms of controlling SARS-CoV-2 replication in in the K18-hACE2 model but do contribute to an inflammatory response through expression of pro-inflammatory genes. Collectively, these findings contribute to previous work demonstrating the ability of SARS-CoV-2 to infect neurons as well as emphasizing the potential use of the K18-hACE2 model to study immunological and neuropathological aspects related to SARS-CoV-2-induced neurologic disease. ImportanceUnderstanding the immunological mechanisms contributing to both host defense and disease following viral infection of the CNS is of critical importance given the increasing number of viruses that are capable of infecting and replicating within the nervous system. With this in mind, the present study was undertaken to evaluate the role of microglia in aiding in host defense following experimental infection of the central nervous system (CNS) of K18-hACE2 with SARS-CoV-2, the causative agent of COVID-19. Neurologic symptoms that range in severity are common in COVID-19 patients and understanding immune responses that contribute to restricting neurologic disease can provide important insight into better understanding consequences associated with SARS-CoV-2 infection of the CNS.

microbiology↗

Quantitative single cell heterogeneity profiling of patient derived tumor initiating gliomaspheres reveals unique signatures of malignancy and response

BackgroundGlioblastoma is a deadly brain tumor with median patient survival of 14.6 months. At the core of this malignancy are rare, highly heterogenous malignant stem-like tumor initiating cells. Aberrant signaling across the EGFR-PTEN-AKT-mTOR signal transduction pathways are common oncogenic drivers in these cells. Though gene-level clustering has determined the importance of the EGFR signaling pathway as a treatment indicator, multiparameter protein-level analyses are necessary to discern functional attributes of signal propagation. Multiparameter single cell analyses is emerging as particularly useful in identifying such attributes. MethodsSingle cell targeted proteomic analysis of EGFR-PTEN-AKT-mTOR proteins profiled heterogeneity in a panel of fifteen patient derived gliomaspheres. A microfluidic cell array chip tool served as a low cost methodology to derive high quality quantitative single cell analytical outputs. Chip design specifications produced extremely high signal-to-noise ratios and brought experimental efficiencies of cell control and minimal cell use to accommodate experimentation with these rare and often slow-growing cell populations. Quantitative imaging software generated datasets to observe similarities and differences within and between cells and patients. Bioinformatic self-organizing maps (SOMs) and hierarchical clustering stratified patients into malignancy and responder groups which were validated by phenotypic and statistical analyses. ResultsFifteen patient dissociated gliomaspheres produced 59,464 data points from 14,866 cells. Forty-nine molecularly defined signaling phenotypes were identified across samples. Bioinformatics resolved two clusters diverging on EGFR expression (p = 0.0003) and AKT/TORC1 activation (p = 0.08 and p = 0.09 respectively). TCGA status of a subset showed genetic heterogeneity with proneural, classical and mesenchymal subtypes represented in both clusters. Phenotypic validation measures indicated drug responsive phenotypes to EGFR blocking were found in the EGFR expressing cluster. EGFR expression in the subset of drug-treated lines was statistically significant (p<.05). The EGFR expressing cluster was of lower tumor initiating potential in comparison to the AKT/TORC1 activated cluster. Though not statistically significant, EGFR expression trended with improved patient prognosis while AKT/TORC1 activated samples trended with poorer outcomes. ConclusionsQuantitative single cell heterogeneity profiling resolves signaling diversity into meaningful non-obvious phenotypic groups suggesting EGFR is decoupled from AKT/TORC1 signalling while identifying potentially valuable targets for personalized therapeutic approaches for deadly tumor-initiating cell populations.

cancer biology↗