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The Foundational Data Initiative for Parkinson Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinson disease (PD). FOUNDIN-PD generated a multi-layered molecular dataset in a cohort of induced pluripotent stem cell (iPSC) lines differentiated to dopaminergic (DA) neurons, a major affected cell type in PD. The lines were derived from the Parkinson's Progression Markers Initiative study, which included participants with PD carrying monogenic PD variants, variants with intermediate effects, and variants identified by genome-wide association studies and unaffected individuals. We generated genetic, epigenetic, regulatory, transcriptomic, and longitudinal cellular imaging data from iPSC-derived DA neurons to understand molecular relationships between disease-associated genetic variation and proximate molecular events. These data reveal that iPSC-derived DA neurons provide a valuable cellular context and foundational atlas for modeling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser as a resource for understanding the molecular pathogenesis of PD.

The extracellular RNA communication consortium (ERCC) is an NIH-funded program aiming to promote the development of new technologies, resources, and knowledge about exRNAs and their carriers. After Phase 1 (2013-2018), Phase 2 of the program (ERCC2, 2019-2023) aims to fill critical gaps in knowledge and technology to enable rigorous and reproducible methods for separation and characterization of both bulk populations of exRNA carriers and single EVs. ERCC2 investigators are also developing new bioinformatic pipelines to promote data integration through the exRNA atlas database. ERCC2 has established several Working Groups (Resource Sharing, Reagent Development, Data Analysis and Coordination, Technology Development, nomenclature, and Scientific Outreach) to promote collaboration between ERCC2 members and the broader scientific community. We expect that ERCC2's current and future achievements will significantly improve our understanding of exRNA biology and the development of accurate and efficient exRNA-based diagnostic, prognostic, and theranostic biomarker assays.

The cellular response to stress is an important determinant of disease pathogenesis. Uncovering the molecular fingerprints of distinct stress responses may identify novel biomarkers and key signaling pathways for different diseases. Emerging evidence shows that transfer RNA-derived small RNAs (tDRs) play pivotal roles in stress responses. However, RNA modifications present on tDRs are barriers to accurately quantifying tDRs using traditional small RNA sequencing. Here, AlkB-facilitated methylation sequencing is used to generate a comprehensive landscape of cellular and extracellular tDR abundances in various cell types during different stress responses. Extracellular tDRs are found to have distinct fragmentation signatures from intracellular tDRs and these tDR signatures are better indicators of different stress responses than miRNAs. These distinct extracellular tDR fragmentation patterns and signatures are also observed in plasma from patients on cardiopulmonary bypass. It is additionally demonstrated that angiogenin and RNASE1 are themselves regulated by stressors and contribute to the stress-modulated abundance of sub-populations of cellular and extracellular tDRs. Finally, a sub-population of extracellular tDRs is identified for which AGO2 appears to be required for their expression. Together, these findings provide a detailed profile of stress-responsive tDRs and provide insight about tDR biogenesis and stability in response to cellular stressors.

One promising goal for utilizing the molecular information circulating in biofluids is the discovery of clinically useful biomarkers. Extracellular RNAs (exRNAs) are one of the most diverse classes of molecular cargo, easily assayed by sequencing and with expressions that rapidly change in response to subject status. Despite diverse exRNA cargo, most evaluations from biofluids have focused on small RNA sequencing and analysis, specifically on microRNAs (miRNAs). Another goal of characterizing circulating molecular information, is to correlate expression to injuries associated with specific tissues of origin. Biomarker candidates are often described as being specific, enriched in a particular tissue or associated with a disease process. Likewise, miRNA data is often reported to be specific, enriched for a tissue, without rigorous testing to support the claim. Here we provide a tissue atlas of small RNAs from 30 different tissues and three different blood cell types. We analyzed the tissues for enrichment of small RNA sequences and assessed their expression in biofluids: plasma, cerebrospinal fluid, urine, and saliva. We employed published data sets representing physiological (resting vs. acute exercise) and pathologic states (early- vs. late-stage liver fibrosis, and differential subtypes of stroke) to determine differential tissue-enriched small RNAs. We also developed an online tool that provides information about exRNA sequences found in different biofluids and tissues. The data can be used to better understand the various types of small RNA sequences in different tissues as well as their potential release into biofluids, which should help in the validation or design of biomarker studies.

Extracellular vesicles (EVs) mediate intercellular signaling by transferring their cargo to recipient cells, but the functional consequences of signaling are not fully appreciated. RBC-derived EVs are abundant in circulation and have been implicated in regulating immune responses. Here, we use a transgenic mouse model for fluorescence-based mapping of RBC-EV recipient cells to assess the role of this intercellular signaling mechanism in heart disease. Using fluorescent-based mapping, we detected an increase in RBC-EV-targeted cardiomyocytes in a murine model of ischemic heart failure. Single cell nuclear RNA sequencing of the heart revealed a complex landscape of cardiac cells targeted by RBC-EVs, with enrichment of genes implicated in cell proliferation and stress signaling pathways compared with non-targeted cells. Correspondingly, cardiomyocytes targeted by RBC-EVs more frequently express cellular markers of DNA synthesis, suggesting the functional significance of EV-mediated signaling. In conclusion, our mouse model for mapping of EV-recipient cells reveals a complex cellular network of RBC-EV-mediated intercellular communication in ischemic heart failure and suggests a functional role for this mode of intercellular signaling.

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data.

Genes implicated in neuropsychiatric disorders are active in human fetal brain, yet difficult to study in a longitudinal fashion. We demonstrate that organoids from human pluripotent cells model cerebral cortical development on the molecular level before 16 weeks postconception. A multiomics analysis revealed differentially active genes and enhancers, with the greatest changes occurring at the transition from stem cells to progenitors. Networks of converging gene and enhancer modules were assembled into six and four global patterns of expression and activity across time. A pattern with progressive down-regulation was enriched with human-gained enhancers, suggesting their importance in early human brain development. A few convergent gene and enhancer modules were enriched in autism-associated genes and genomic variants in autistic children. The organoid model helps identify functional elements that may drive disease onset.