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A systematic strategy for identifying causal single nucleotide polymorphisms and their target genes on Juvenile arthritis risk haplotypes.
Get PDFBACKGROUND: Although genome-wide association studies (GWAS) have identified multiple regions conferring genetic risk for juvenile idiopathic arthritis (JIA), we are still faced with the task of identifying the single nucleotide polymorphisms (SNPs) on the disease haplotypes that exert the biological effects that confer risk. Until we identify the risk-driving variants, identifying the genes influenced by these variants, and therefore translating genetic information to improved clinical care, will remain an insurmountable task. We used a function-based approach for identifying causal variant candidates and the target genes on JIA risk haplotypes.
METHODS: We used a massively parallel reporter assay (MPRA) in myeloid K562 cells to query the effects of 5,226 SNPs in non-coding regions on JIA risk haplotypes for their ability to alter gene expression when compared to the common allele. The assay relies on 180 bp oligonucleotide reporters ( oligos ) in which the allele of interest is flanked by its cognate genomic sequence. Barcodes were added randomly by PCR to each oligo to achieve \u3e 20 barcodes per oligo to provide a quantitative read-out of gene expression for each allele. Assays were performed in both unstimulated K562 cells and cells stimulated overnight with interferon gamma (IFNg). As proof of concept, we then used CRISPRi to demonstrate the feasibility of identifying the genes regulated by enhancers harboring expression-altering SNPs.
RESULTS: We identified 553 expression-altering SNPs in unstimulated K562 cells and an additional 490 in cells stimulated with IFNg. We further filtered the SNPs to identify those plausibly situated within functional chromatin, using open chromatin and H3K27ac ChIPseq peaks in unstimulated cells and open chromatin plus H3K4me1 in stimulated cells. These procedures yielded 42 unique SNPs (total = 84) for each set. Using CRISPRi, we demonstrated that enhancers harboring MPRA-screened variants in the TRAF1 and LNPEP/ERAP2 loci regulated multiple genes, suggesting complex influences of disease-driving variants.
CONCLUSION: Using MPRA and CRISPRi, JIA risk haplotypes can be queried to identify plausible candidates for disease-driving variants. Once these candidate variants are identified, target genes can be identified using CRISPRi informed by the 3D chromatin structures that encompass the risk haplotypes
Leaving no patient behind! Expert recommendation in the use of innovative technologies for diagnosing rare diseases.
Get PDFGenetic diagnosis plays a crucial role in rare diseases, particularly with the increasing availability of emerging and accessible treatments. The International Rare Diseases Research Consortium (IRDiRC) has set its primary goal as: Ensuring that all patients who present with a suspected rare disease receive a diagnosis within one year if their disorder is documented in the medical literature . Despite significant advances in genomic sequencing technologies, more than half of the patients with suspected Mendelian disorders remain undiagnosed. In response, IRDiRC proposes the establishment of a globally coordinated diagnostic and research pipeline . To help facilitate this, IRDiRC formed the Task Force on Integrating New Technologies for Rare Disease Diagnosis. This multi-stakeholder Task Force aims to provide an overview of the current state of innovative diagnostic technologies for clinicians and researchers, focusing on the patient\u27s diagnostic journey. Herein, we provide an overview of a broad spectrum of emerging diagnostic technologies involving genomics, epigenomics and multi-omics, functional testing and model systems, data sharing, bioinformatics, and Artificial Intelligence (AI), highlighting their advantages, limitations, and the current state of clinical adaption. We provide expert recommendations outlining the stepwise application of these innovative technologies in the diagnostic pathways while considering global differences in accessibility. The importance of FAIR (Findability, Accessibility, Interoperability, and Reusability) and CARE (Collective benefit, Authority to control, Responsibility, and Ethics) data management is emphasized, along with the need for enhanced and continuing education in medical genomics. We provide a perspective on future technological developments in genome diagnostics and their integration into clinical practice. Lastly, we summarize the challenges related to genomic diversity and accessibility, highlighting the significance of innovative diagnostic technologies, global collaboration, and equitable access to diagnosis and treatment for people living with rare disease
SAMPLER: unsupervised representations for rapid analysis of whole slide tissue images.
Get PDFBACKGROUND: Deep learning has revolutionized digital pathology, allowing automatic analysis of hematoxylin and eosin (H&E) stained whole slide images (WSIs) for diverse tasks. WSIs are broken into smaller images called tiles, and a neural network encodes each tile. Many recent works use supervised attention-based models to aggregate tile-level features into a slide-level representation, which is then used for downstream analysis. Training supervised attention-based models is computationally intensive, architecture optimization of the attention module is non-trivial, and labeled data are not always available. Therefore, we developed an unsupervised and fast approach called SAMPLER to generate slide-level representations.
METHODS: Slide-level representations of SAMPLER are generated by encoding the cumulative distribution functions of multiscale tile-level features. To assess effectiveness of SAMPLER, slide-level representations of breast carcinoma (BRCA), non-small cell lung carcinoma (NSCLC), and renal cell carcinoma (RCC) WSIs of The Cancer Genome Atlas (TCGA) were used to train separate classifiers distinguishing tumor subtypes in FFPE and frozen WSIs. In addition, BRCA and NSCLC classifiers were externally validated on frozen WSIs. Moreover, SAMPLER\u27s attention maps identify regions of interest, which were evaluated by a pathologist. To determine time efficiency of SAMPLER, we compared runtime of SAMPLER with two attention-based models. SAMPLER concepts were used to improve the design of a context-aware multi-head attention model (context-MHA).
FINDINGS: SAMPLER-based classifiers were comparable to state-of-the-art attention deep learning models to distinguish subtypes of BRCA (AUC = 0.911 ± 0.029), NSCLC (AUC = 0.940 ± 0.018), and RCC (AUC = 0.987 ± 0.006) on FFPE WSIs (internal test sets). However, training SAMLER-based classifiers was \u3e100 times faster. SAMPLER models successfully distinguished tumor subtypes on both internal and external test sets of frozen WSIs. Histopathological review confirmed that SAMPLER-identified high attention tiles contained subtype-specific morphological features. The improved context-MHA distinguished subtypes of BRCA and RCC (BRCA-AUC = 0.921 ± 0.027, RCC-AUC = 0.988 ± 0.010) with increased accuracy on internal test FFPE WSIs.
INTERPRETATION: Our unsupervised statistical approach is fast and effective for analyzing WSIs, with greatly improved scalability over attention-based deep learning methods. The high accuracy of SAMPLER-based classifiers and interpretable attention maps suggest that SAMPLER successfully encodes the distinct morphologies within WSIs and will be applicable to general histology image analysis problems.
FUNDING: This study was supported by the National Cancer Institute (Grant No. R01CA230031 and P30CA034196)
Lessons Learned in Building Expertly Annotated Multi-Institution Datasets and Hosting the RSNA AI Challenges.
No full textThe Radiological Society of North America (RSNA) has held artificial intelligence competitions to tackle real-world medical imaging problems at least annually since 2017. This article examines the challenges and processes involved in organizing these competitions, with a specific emphasis on the creation and curation of high-quality datasets. The collection of diverse and representative medical imaging data involves dealing with issues of patient privacy and data security. Furthermore, ensuring quality and consistency in data, which includes expert labeling and accounting for various patient and imaging characteristics, necessitates substantial planning and resources. Overcoming these obstacles requires meticulous project management and adherence to strict timelines. The article also highlights the potential of crowdsourced annotation to progress medical imaging research. Through the RSNA competitions, an effective global engagement has been realized, resulting in innovative solutions to complex medical imaging problems, thus potentially transforming health care by enhancing diagnostic accuracy and patient outcomes
Exploring the Role of TIE2 Activation in Modulating CAA Pathology: Focus on BBB Integrity and Hemorrhagic Lesions in Aged BXW.APP/PSl Mice
No full textCerebral amyloid angiopathy (CAA) is a significant and understudied component of Alzheimer\u27s disease (AD), characterized by the deposition of amyloid-beta (Aβ) within cerebral blood vessels. This leads to blood-brain barrier (BBB) breakdown, exacerbating neurodegeneration and increasing the risk of hemorrhagic stroke. Despite the prevalence and impact of CAA on AD progression, current therapeutic strategies are limited due to insufficient models that accurately reflect human pathology. This study addresses this gap by investigating the therapeutic potential of Angpt2 heterozygosity in modulating CAA pathology and preserving BBB integrity in aged BXW.APP/PS1 mice. Angiopoietin 2 (ANGPT2) is an endogenous antagonist of TIE2, a receptor that, when phosphorylated, maintains vascular integrity. Dysregulation of this pathway leads to increased BBB permeability, a hallmark of CAA and a contributor to AD progression. By exploring Angpt2 heterozygosity, which enhances TIE2 activation and stabilizes the BBB, we aim to uncover a novel therapeutic approach for CAA and AD. To evaluate the impact of Angpt2 heterozygosity, we utilized seven genotypes of aged mice (Aim 1; Aim 2; Aim 3): BXW (n=0; n=12; n=4), BXW.Angpt2 +/- (n=0; n=9; n=1), BXW.APP/PS1 Angpt2+/- (n=6; n=10; n=3), BXW.APP/PS1 (n=9; n=10; n=3), NZO.APP/PS1 (n=0; n=0; n=2), B6 (n=0; n=0; n=3), and B6.APP/PS1 (n=0; n=0; n=4). We assessed several key outcome measures. Elevated fibrin levels in both plasma and vascular walls indicated increased BBB permeability and vascular leakage. COL IV immunoreactivity was used to assess vascular integrity and endothelial cell function. Amyloid burden was quantified through X34 staining, and the plasma Aβ42/40 ratio was monitored to infer changes in amyloid metabolism and deposition. Neurofilament levels were measured as markers of neuroaxonal damage and neurodegeneration. Preliminary results indicate that BXW.APP/PS1.Angpt2+/- mice exhibit significantly reduced vascular leakage and fewer amyloid plaques compared to BXW.APP/PS1 controls. These findings suggest that Angpt2 heterozygosity enhances BBB integrity and mitigates CAA pathology, highlighting the therapeutic potential of modulating the Angpt2-TIE2 signaling pathway. The implications of this research are profound, as it emphasizes the importance of maintaining vascular health in developing effective AD interventions. Future studies will integrate advanced histological techniques, such as H&E staining to evaluate cortical superficial siderosis (cSS) and Prussian blue staining for cerebral microbleeds (CMBs). Additionally, cognitive assessments and endothelial cell-specific RNA sequencing will explore downstream mechanisms by which TIE2 activation prevents both BBB breakdown and CAA/AD. These efforts aim to complement existing methods, providing deeper insights into Angpt2\u27s role in cerebrovascular health while identifying additional therapeutic targets for improving AD patient outcomes by focusing on vascular health and integrity
Characterizing SVs associated with striatum eQTLs and addiction phenotypes in diverse mouse genomes
No full textBehavioral phenotypes, substance use disorders, and addiction are heritable traits which can be attributed with complex neurological presentations. Despite these associations, many genetic loci which directly contribute to addiction phenotypes remain unclear, and identification of causal genetic variants found within natural populations remains a difficult task. To identify molecular phenotypes responsible for addiction traits, comprehensive profiling of the associated brain regions is required. To investigate genomic regions responsible for changes in brain gene expression, we performed expression quantitative trait mapping of loci responsible for changes in striatum gene expression in the diversity outbred mouse panel. Regions responsible for differential striatum gene expression were profiled for structural variation (SV, genetic variants ≥ 50bp), a variant type historically underrepresented in next generation sequencing experiments and addiction studies. From these data, we investigated specific gene sets which contained striatum eQTLs associated with SVs of unique sequencing characteristics, including tandem repeat and transposable element variants. By coupling these data with publicly available single cell RNA sequencing data derived from the developing striatum, we identify cell type specific expression of gene sets correlated with unique SV type signatures, including those that facilitate dopaminergic responses
Determining the Mechanisms Responsible for Infertility in Homozygous Males of the 5XE Mutant Mouse Model
No full textA Chromosome (Ch) 13 quantitative trait locus (QTL) phenotypically influences numerous biological processes ranging from dactylaplasia to cleft lip and palate in mice (Byers et al., 2021). The Baker Lab created the 5XE mouse model – a DBA/2J (D2) background with a C57BL/6J (B6) congenic region on Ch 13 containing thirteen KRAB zinc finger proteins (KZFPs) – to study this QTL, and discovered homozygous (hom) males were completely infertile. In an attempt to locate the stage of spermatogenic failure, we immunostained 5XE spermatocyte spreads for double-strand breaks (yH2AX) and chromosome synapsis (SYCP3). Primary interpretations concluded DNA damage was restricted solely to the sex body during early meiosis yet, upon experimental replication, I discovered hom 5XE sex chromosomes fail to transition from mid- to late-pachytene during meiotic prophase I. The presence of an early meiotic block was also supported by testis seminiferous tubule counts, as week-ten homozygous 5XE testis cross sections were smaller in diameter and contained significantly less spermatozoa by sexual maturity compared to their fertile, heterozygous (het) counterparts. Therefore, 5XE infertility most likely results from a mid-pachytene meiotic block, manifested by inadequate KZFP regulation of local transposable elements (TEs) that disrupt specific fertility development genes of the D2 genome
Determining the Effect of Mitochondrial Respiration-Targeted Drugs on Leukemia Stem Cells in a Mouse Model of Acute Myeloid Leukemia
No full textAcute myeloid leukemia (AML) is a blood cancer that results in an abundance of abnormal blood cells. Within AML, a population of cells termed leukemia stem cells (LSCs) propagate malignancy and are largely resistant to chemotherapy, highlighting the need for a better understanding of these cells’ biology to improve treatment of AML. LSCs are known to rely on oxidative phosphorylation (OXPHOS), making mitochondrial activity a potential target for AML therapy that is also effective at depleting LSCs. By utilizing a Dmnt3aR878H/+ Npm1cA/+ mouse AML model developed by the Trowbridge lab, we aim to determine if drugs that target mitochondrial respiration can suppress the growth of AML LSCs. Therefore, we hypothesize that three mitochondrially-targeted molecules that reduce OXPHOS (MitoQ, metformin, and venetoclax) will reduce the growth of LSCs in a mouse model of Dnmt3aR878H/+ Npm1cA/+ AML. To test this, spleen and/or bone marrow samples were attained from Dnmt3aR878H/+ Npm1cA/+ non-disease and AML mice to determine in vitro cell viability after drug treatment. Our preliminary data suggests mitochondrial respiration-targeted drugs decrease cell viability in the context of AML but are less effective in the non-disease state. Further experimentation is necessary to understand the true impacts of these drugs to treat AML
Proteomic Profiles of Human Arterioles Isolated From Fresh Adipose Tissue or Following Overnight Storage.
No full textArterioles are key determinants of the total peripheral vascular resistance, which, in turn, is a key determinant of arterial blood pressure. However, the amount of protein available from one isolated human arteriole may be less than 5 mg, making proteomic analysis challenging. In addition, obtaining human arterioles requires manual dissection of unfrozen clinical specimens. This limits its feasibility, especially for powerful multicenter clinical studies in which clinical specimens need to be shipped overnight to a research laboratory for arteriole isolation. We performed a study to address low-input, test overnight tissue storage and develop a reference human arteriolar prote- omic profile. In tandem mass tag proteomics, use of a booster channel consisting of human induced pluripotent stem cellederived endothelial and vascular smooth muscle cells (1:5 ratio) increased the number of proteins detected in a human arteriole segment with a false discovery rate of \u3c0.01 from 1051 to more than 3000. The correlation coefficient of proteomic profile was similar between replicate arterioles isolated freshly, following cold storage, or before and after the cold storage (1-way analysis of variance; P ¼ .60). We built a human arteriolar proteomic profile consisting of 3832 proteins based on the analysis of 12 arteriole samples from 3 subjects. Of 1945 blood pressureerelevant proteins that we curated, 476 (12.5%) were detected in the arteriolar proteome, which was a significant overrepresentation (c2 test; P \u3c .05). These findings demon- strate that proteomic analysis is feasible with arterioles isolated from human adipose tissue following cold overnight storage and provide a reference human arteriolar proteome profile highly valuable for studies of arteriole-related traits
Expression of ALS-PFN1 impairs vesicular degradation in iPSC-derived microglia.
Get PDFMicroglia play a pivotal role in neurodegenerative disease pathogenesis, but the mechanisms underlying microglia dysfunction and toxicity remain to be elucidated. To investigate the effect of neurodegenerative disease-linked genes on the intrinsic properties of microglia, we studied microglia-like cells derived from human induced pluripotent stem cells (iPSCs), termed iMGs, harboring mutations in profilin-1 (PFN1) that are causative for amyotrophic lateral sclerosis (ALS). ALS-PFN1 iMGs exhibited evidence of lipid dysmetabolism, autophagy dysregulation and deficient phagocytosis, a canonical microglia function. Mutant PFN1 also displayed enhanced binding affinity for PI3P, a critical signaling molecule involved in autophagic and endocytic processing. Our cumulative data implicate a gain-of-toxic function for mutant PFN1 within the autophagic and endo-lysosomal pathways, as administration of rapamycin rescued phagocytic dysfunction in ALS-PFN1 iMGs. These outcomes demonstrate the utility of iMGs for neurodegenerative disease research and implicate microglial vesicular degradation pathways in the pathogenesis of these disorders