Project Abstracts - HPAC

Klaus Kaestner, PhD, Investigator, University of Pennsylvania
Alvin Powers, MD, Investigator, Vanderbilt University
Mark Atkinson, PhD, Investigator, University of Florida
Michael Feldman, MD, PhD, co-Investigator, University of Pennsylvania
Jason Moore, PhD, co-Investigator, University of Pennsylvania (10/2016-11/2021)
Michael Betts, PhD, co-Investigator, University of Pennsylvania
Doris Stoffers, MD, PhD, co-Investigator, University of Pennsylvania
Marcela Brissova, PhD, co-Investigator, Vanderbilt University
Mingder Yang, PhD, co-Investigator, University of Florida
Irina Kusmartseva, PhD, co-Investigator, University of Florida
Babak Faryabi, PhD, co-Investigator, University of Pennsylvania (11/2021-present)

Start Date: September 20, 2016

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Abstract

In 2016, the NIH NIDDK selected a multi-disciplinary team of investigators from three institutions (UPENN, Vanderbilt, University of Florida) to establish the pilot phase of the Human Pancreas Analysis Program (HPAP). Over the past three years, type 1 diabetes (T1D)-relevant tissues from more than 50 organ donors were profiled at the anatomic, physiologic, metabolic, immunologic, genomic and epigenomic levels. The resulting data were compiled and organized into the publicly accessible PANC-DB database and website. Here, we propose not only to continue, but to expand our efforts to apply and develop state-of-the-art technologies designed to phenotype and molecularly profile human tissues relevant to the etiology of T1D through a series of innovative efforts by six Cores. Core A (Pancreas Procurement and Islet Isolation) will procure/process pancreatic islets, pancreas and lymphoid organs, expand donor outreach (in collaboration with the well-established nPOD program) and increase the collection of non-pancreatic tissues. Core B (Physiological Phenotyping)will provide a comprehensive metabolic profile and probe the key regulatory steps that govern hormone secretion from the major pancreatic endocrine cell types. Core C (Immunobiology) will develop an immune atlas of peripancreatic lymphoid populations, obtain transcriptomic profiles of the T1D- specific T cells, and perform immune repertoire profiling of B and T cells in association with single cell and antigen-specific cell approaches. Core D (Advanced Molecular Profiling) will perform RNAseq, ATACseq and DNA methylome analysis on sorted alpha-cell, beta-cell and exocrine cell population as well as scRNAseq and scATACseq and carry out whole genome sequencing. In addition, islet endocrine and major lymphocyte populations will be quantified precisely using flow CyTOF. Core E (Tissue Analysis & Biobanking) will analyze pancreatic tissue architecture and immune cell/epithelial cell interactions using multiple modalities including imaging mass cytometry, multi-spectral imaging and CODEX. Complete image data will be made available via PancreatlasTM and PANC-DB. Finally, Core F (PANC-DB, Data Analysis and Integration) will expand the PANC-DB resource by adding new features that will make the public web page even more useful, as well as add a Computational Biology and Data Science Unit for applying state-of-the-art analytical tools, allowing for the integration and visualization of generated datasets using different experimental modalities such as multi-spectral imaging and omics technologies. In addition, Core F will continue to expand its outreach activities, exemplified via the deposition of transcriptome and epigenome data into the Diabetes Epigenome Atlas (DGA). HPAP-T1D will be directed by an experienced, collaborative multi-PI team that confers weekly and will meet in-person on a biannual basis in coordination with NIDDK leadership to review the progress of the entire program.

 

Publications

• A beta cell subset with enhanced insulin secretion and glucose metabolism is reduced in type 2 diabetes
• Benchmarking algorithms for joint integration of unpaired and paired single-cell RNA-seq and ATAC-seq data
• An integrated map of cell type-specific gene expression in pancreatic islets
• Autoantibodies are highly prevalent in non-SARS-CoV-2 respiratory infections and critical illness
• Human pancreatic capillaries and nerve fibers persist in type 1 diabetes despite beta cell loss
• AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics
• Computational workflow and interactive analysis of single-cell expression profiling of islets generated by the Human Pancreas Analysis Program
• Integration of single-cell multiomic measurements across disease states with genetics identifies mechanisms of beta cell dysfunction in type 2 diabetes
• Understanding islet dysfunction in type 2 diabetes through multidimensional pancreatic phenotyping: The Human Pancreas Analysis Program
• Aging compromises human islet beta cell function and identity by decreasing transcription factor activity and inducing ER stress
• d-Amino Acids and Classical Neurotransmitters in Healthy and Type 2 Diabetes-Affected Human Pancreatic Islets of Langerhans
• 3D chromatin maps of the human pancreas reveal lineage-specific regulatory architecture of T2D risk
• Every islet matters: improving the impact of human islet research
• Adaptation to chronic ER stress enforces pancreatic β-cell plasticity
• TCF-1 promotes chromatin interactions across topologically associating domains in T cell progenitors
• α Cell dysfunction in islets from nondiabetic, glutamic acid decarboxylase autoantibody-positive individuals
• Variant-to-gene-mapping analyses reveal a role for pancreatic islet cells in conferring genetic susceptibility to sleep-related traits
• Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes
• Heterogenous impairment of α cell function in type 2 diabetes is linked to cell maturation state
• Autoantibodies targeting cytokines and connective tissue disease autoantigens are common in acute non-SARS-CoV-2 infections
• Islet Lymphocytes Maintain a Stable Regulatory Phenotype Under Homeostatic Conditions and Metabolic Stress
• Transcription factors combine to paint the methylation landscape
• Cellular and humoral immune responses following SARS-CoV-2 mRNA vaccination in patients with multiple sclerosis on anti-CD20 therapy
• New-onset IgG autoantibodies in hospitalized patients with COVID-19
• What is a β cell? – Chapter I in the Human Islet Research Network (HIRN) Review Series
• From type 1 diabetes biology to therapy: The Human Islet Research Network
• A New Hypothesis for Type 1 Diabetes Risk: The At-Risk Allele at rs3842753 Associates With Increased Beta-cell INS Messenger RNA in a Meta-Analysis of Single-Cell RNA-Sequencing Data
• Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling
• Deep immune profiling of MIS-C demonstrates marked but transient immune activation compared to adult and pediatric COVID-19
• Pancreatic islet reserve in type 1 diabetes
• TCR(+)/BCR(+) dual-expressing cells and their associated public BCR clonotype are not enriched in type 1 diabetes
• Remodeling the chromatin landscape in T lymphocytes by a division of labor among transcription factors
• Norovirus-Specific CD8(+) T Cell Responses in Human Blood and Tissues
• The Identity of Human Tissue-Emigrant CD8(+) T Cells
• SARS-CoV-2 Cell Entry Factors ACE2 and TMPRSS2 Are Expressed in the Microvasculature and Ducts of Human Pancreas but Are Not Enriched in β Cells
• Ten simple rules for writing a paper about scientific software
• Mining the Antibody Repertoire for Solutions to SARS-CoV-2
• Organisation of the human pancreas in health and in diabetes
• Embedding covariate adjustments in tree-based automated machine learning for biomedical big data analyses
• Islet transplantation in the subcutaneous space achieves long-term euglycaemia in preclinical models of type 1 diabetes
• Genetic Variation in Type 1 Diabetes Reconfigures the 3D Chromatin Organization of T Cells and Alters Gene Expression.
• Exploration of a diversity of computational and statistical measures of association for genome-wide genetic studies
• Integration of genetic and clinical information to improve imputation of data missing from electronic health records
• ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites
• Automated discovery of test statistics using genetic programming
• Multiplexed In Situ Imaging Mass Cytometry Analysis of the Human Endocrine Pancreas and Immune System in Type 1 Diabetes
• ImmuneDB, a Novel Tool for the Analysis, Storage, and Dissemination of Immune Repertoire Sequencing Data
• Benchmarking Relief-Based Feature Selection Methods for Bioinformatics Data Mining
• Leveraging epigenomics and contactomics data to investigate SNP pairs in GWAS
• Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV)
• Investigating the parameter space of evolutionary algorithms
• Data-driven advice for applying machine learning to bioinformatics problems
• A miRNA181a/NFAT5 axis links impaired T cell tolerance induction with autoimmune type 1 diabetes
• A Heuristic Method for Simulating Open-data of Arbitrary Complexity that can be used to Compare and Evaluate Machine Learning Methods
• Leveraging putative enhancer-promoter interactions to investigate two-way epistasis in Type 2 Diabetes GWAS
• PMLB: a Large Benchmark Suite for Machine Learning Evaluation and Comparison
• Evolutionarily derived networks to inform disease pathways