Biological basis of extensive pleiotropy between blood traits and cancer risk.

BACKGROUND: The immune system has a central role in preventing carcinogenesis. Alteration of systemic immune cell levels may increase cancer risk. However, the extent to which common genetic variation influences blood traits and cancer risk remains largely undetermined. Here, we identify pleiotropic variants and predict their underlying molecular and cellular alterations. METHODS: Multivariate Cox regression was used to evaluate associations between blood traits and cancer diagnosis in cases in the UK Biobank. Shared genetic variants were identified from the summary statistics of the genome-wide association studies of 27 blood traits and 27 cancer types and subtypes, applying the conditional/conjunctional false-discovery rate approach. Analysis of genomic positions, expression quantitative trait loci, enhancers, regulatory marks, functionally defined gene sets, and bulk- and single-cell expression profiles predicted the biological impact of pleiotropic variants. Plasma small RNAs were sequenced to assess association with cancer diagnosis. RESULTS: The study identified 4093 common genetic variants, involving 1248 gene loci, that contributed to blood-cancer pleiotropism. Genomic hotspots of pleiotropism include chromosomal regions 5p15-TERT and 6p21-HLA. Genes whose products are involved in regulating telomere length are found to be enriched in pleiotropic variants. Pleiotropic gene candidates are frequently linked to transcriptional programs that regulate hematopoiesis and define progenitor cell states of immune system development. Perturbation of the myeloid lineage is indicated by pleiotropic associations with defined master regulators and cell alterations. Eosinophil count is inversely associated with cancer risk. A high frequency of pleiotropic associations is also centered on the regulation of small noncoding Y-RNAs. Predicted pleiotropic Y-RNAs show specific regulatory marks and are overabundant in the normal tissue and blood of cancer patients. Analysis of plasma small RNAs in women who developed breast cancer indicates there is an overabundance of Y-RNA preceding neoplasm diagnosis. CONCLUSIONS: This study reveals extensive pleiotropism between blood traits and cancer risk. Pleiotropism is linked to factors and processes involved in hematopoietic development and immune system function, including components of the major histocompatibility complexes, and regulators of telomere length and myeloid lineage. Deregulation of Y-RNAs is also associated with pleiotropism. Overexpression of these elements might indicate increased cancer risk.

Small RNA Changes in Plasma Have Potential for Early Diagnosis of Alzheimer's Disease before Symptom Onset.

Alzheimer's disease (AD), due to its multifactorial nature and complex etiology, poses challenges for research, diagnosis, and treatment, and impacts millions worldwide. To address the need for minimally invasive, repeatable measures that aid in AD diagnosis and progression monitoring, studies leveraging RNAs associated with extracellular vesicles (EVs) in human biofluids have revealed AD-associated changes. However, the validation of AD biomarkers has suffered from the collection of samples from differing points in the disease time course or a lack of confirmed AD diagnoses. Here, we integrate clinical diagnosis and postmortem pathology data to form more accurate experimental groups and use small RNA sequencing to show that EVs from plasma can serve as a potential source of RNAs that reflect disease-related changes. Importantly, we demonstrated that these changes are identifiable in the EVs of preclinical patients, years before symptom manifestation, and that machine learning models based on differentially expressed RNAs can help predict disease conversion or progression. This research offers critical insight into early disease biomarkers and underscores the significance of accounting for disease progression and pathology in human AD studies.

Recommendations for reproducibility of cerebrospinal fluid extracellular vesicle studies.

Cerebrospinal fluid (CSF) is a clear, transparent fluid derived from blood plasma that protects the brain and spinal cord against mechanical shock, provides buoyancy, clears metabolic waste and transports extracellular components to remote sites in the brain. Given its contact with the brain and the spinal cord, CSF is the most informative biofluid for studies of the central nervous system (CNS). In addition to other components, CSF contains extracellular vesicles (EVs) that carry bioactive cargoes (e.g., lipids, nucleic acids, proteins), and that can have biological functions within and beyond the CNS. Thus, CSF EVs likely serve as both mediators of and contributors to communication in the CNS. Accordingly, their potential as biomarkers for CNS diseases has stimulated much excitement for and attention to CSF EV research. However, studies on CSF EVs present unique challenges relative to EV studies in other biofluids, including the invasive nature of CSF collection, limited CSF volumes and the low numbers of EVs in CSF as compared to plasma. Here, the objectives of the International Society for Extracellular Vesicles CSF Task Force are to promote the reproducibility of CSF EV studies by providing current reporting and best practices, and recommendations and reporting guidelines, for CSF EV studies. To accomplish this, we created and distributed a world-wide survey to ISEV members to assess methods considered 'best practices' for CSF EVs, then performed a detailed literature review for CSF EV publications that was used to curate methods and resources. Based on responses to the survey and curated information from publications, the CSF Task Force herein provides recommendations and reporting guidelines to promote the reproducibility of CSF EV studies in seven domains: (i) CSF Collection, Processing, and Storage; (ii) CSF EV Separation/Concentration; (iii) CSF EV Size and Number Measurements; (iv) CSF EV Protein Studies; (v) CSF EV RNA Studies; (vi) CSF EV Omics Studies and (vii) CSF EV Functional Studies.

Modelling TDP-43 proteinopathy in Drosophila uncovers shared and neuron-specific targets across ALS and FTD relevant circuits.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) comprise a spectrum of neurodegenerative diseases linked to TDP-43 proteinopathy, which at the cellular level, is characterized by loss of nuclear TDP-43 and accumulation of cytoplasmic TDP-43 inclusions that ultimately cause RNA processing defects including dysregulation of splicing, mRNA transport and translation. Complementing our previous work in motor neurons, here we report a novel model of TDP-43 proteinopathy based on overexpression of TDP-43 in a subset of Drosophila Kenyon cells of the mushroom body (MB), a circuit with structural characteristics reminiscent of vertebrate cortical networks. This model recapitulates several aspects of dementia-relevant pathological features including age-dependent neuronal loss, nuclear depletion and cytoplasmic accumulation of TDP-43, and behavioral deficits in working memory and sleep that occur prior to axonal degeneration. RNA immunoprecipitations identify several candidate mRNA targets of TDP-43 in MBs, some of which are unique to the MB circuit and others that are shared with motor neurons. Among the latter is the glypican Dally-like-protein (Dlp), which exhibits significant TDP-43 associated reduction in expression during aging. Using genetic interactions we show that overexpression of Dlp in MBs mitigates TDP-43 dependent working memory deficits, conistent with Dlp acting as a mediator of TDP-43 toxicity. Substantiating our findings in the fly model, we find that the expression of GPC6 mRNA, a human ortholog of dlp, is specifically altered in neurons exhibiting the molecular signature of TDP-43 pathology in FTD patient brains. These findings suggest that circuit-specific Drosophila models provide a platform for uncovering shared or disease-specific molecular mechanisms and vulnerabilities across the spectrum of TDP-43 proteinopathies.

Roadmap for C9ORF72 in Frontotemporal Dementia and Amyotrophic Lateral Sclerosis: Report on the C9ORF72 FTD/ALS Summit.

A summit held March 2023 in Scottsdale, Arizona (USA) focused on the intronic hexanucleotide expansion in the C9ORF72 gene and its relevance in frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS; C9ORF72-FTD/ALS). The goal of this summit was to connect basic scientists, clinical researchers, drug developers, and individuals affected by C9ORF72-FTD/ALS to evaluate how collaborative efforts across the FTD-ALS disease spectrum might break down existing disease silos. Presentations and discussions covered recent discoveries in C9ORF72-FTD/ALS disease mechanisms, availability of disease biomarkers and recent advances in therapeutic development, and clinical trial design for prevention and treatment for individuals affected by C9ORF72-FTD/ALS and asymptomatic pathological expansion carriers. The C9ORF72-associated hexanucleotide repeat expansion is an important locus for both ALS and FTD. C9ORF72-FTD/ALS may be characterized by loss of function of the C9ORF72 protein and toxic gain of functions caused by both dipeptide repeat (DPR) proteins and hexanucleotide repeat RNA. C9ORF72-FTD/ALS therapeutic strategies discussed at the summit included the use of antisense oligonucleotides, adeno-associated virus (AAV)-mediated gene silencing and gene delivery, and engineered small molecules targeting RNA structures associated with the C9ORF72 expansion. Neurofilament light chain, DPR proteins, and transactive response (TAR) DNA-binding protein 43 (TDP-43)-associated molecular changes were presented as biomarker candidates. Similarly, brain imaging modalities (i.e., magnetic resonance imaging [MRI] and positron emission tomography [PET]) measuring structural, functional, and metabolic changes were discussed as important tools to monitor individuals affected with C9ORF72-FTD/ALS, at both pre-symptomatic and symptomatic disease stages. Finally, summit attendees evaluated current clinical trial designs available for FTD or ALS patients and concluded that therapeutics relevant to FTD/ALS patients, such as those specifically targeting C9ORF72, may need to be tested with composite endpoints covering clinical symptoms of both FTD and ALS. The latter will require novel clinical trial designs to be inclusive of all patient subgroups spanning the FTD/ALS spectrum.

The C9ORF72 Summit was held in March 2023 in Scottsdale, Arizona (USA). Some people who have the disease frontotemporal dementia or the disease amyotrophic lateral sclerosis have a change in one of their genes; the name of the gene is C9ORF72. People who carry this genetic difference usually inherited it from a parent. Researchers are improving their understanding of how the change in the C9ORF72 gene affects people, and efforts are being made to use this knowledge to develop treatments for amyotrophic lateral sclerosis and frontotemporal dementia. In addition to studying the cellular and molecular mechanisms of how the C9ORF72 mutation leads to cellular dysfunction and frontotemporal dementia and amyotrophic lateral sclerosis clinical symptoms, a large effort of the research community is aimed at developing measurements, called biomarkers, that could enhance therapy development efforts in multiple ways. Examples include monitoring of disease activity, identifying those at risk of developing amyotrophic lateral sclerosis or frontotemporal dementia, predicting which people might benefit from a particular treatment, and showing that a drug has had a biological effect. Markers that identify healthy people who are at risk of developing amyotrophic lateral sclerosis or frontotemporal dementia could be used to test treatments that would start before a person shows any symptoms and hopefully would delay or even prevent their onset.

Single Extracellular VEsicle Nanoscopy.

Extracellular vesicles (EVs) and their cargo constitute novel biomarkers. EV subpopulations have been defined not only by abundant tetraspanins (e.g., CD9, CD63 and CD81) but also by specific markers derived from their source cells. However, it remains a challenge to robustly isolate and characterize EV subpopulations. Here, we combined affinity isolation with super-resolution imaging to comprehensively assess EV subpopulations from human plasma. Our Single Extracellular VEsicle Nanoscopy (SEVEN) assay successfully quantified the number of affinity-isolated EVs, their size, shape, molecular tetraspanin content, and heterogeneity. The number of detected tetraspanin-enriched EVs positively correlated with sample dilution in a 64-fold range (for SEC-enriched plasma) and a 50-fold range (for crude plasma). Importantly, SEVEN robustly detected EVs from as little as ∼0.1 µL of crude plasma. We further characterized the size, shape and molecular tetraspanin content (with corresponding heterogeneities) for CD9-, CD63- and CD81-enriched EV subpopulations. Finally, we assessed EVs from the plasma of four pancreatic ductal adenocarcinoma patients with resectable disease. Compared to healthy plasma, CD9-enriched EVs from patients were smaller while IGF1R-enriched EVs from patients were larger, rounder and contained more tetraspanin molecules, suggestive of a unique pancreatic cancer-enriched EV subpopulation. This study provides the method validation and demonstrates that SEVEN could be advanced into a platform for characterizing both disease-associated and organ-associated EV subpopulations.

Cryptic exon detection and transcriptomic changes revealed in single-nuclei RNA sequencing of C9ORF72 patients spanning the ALS-FTD spectrum.

The C9ORF72-linked diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are characterized by the nuclear depletion and cytoplasmic accumulation of TAR DNA-binding protein 43 (TDP-43). Recent studies have shown that the loss of TDP-43 function leads to the inclusion of cryptic exons (CE) in several RNA transcript targets of TDP-43. Here, we show for the first time the detection of CEs in a single-nuclei RNA sequencing (snRNA-seq) dataset obtained from frontal and occipital cortices of C9ORF72 patients that phenotypically span the ALS-FTD disease spectrum. We assessed each cellular cluster for detection of recently described TDP-43-induced CEs. Transcripts containing CEs in the genes STMN2 and KALRN were detected in the frontal cortex of all C9ORF72 disease groups with the highest frequency in excitatory neurons in the C9ORF72-FTD group. Within the excitatory neurons, the cluster with the highest proportion of cells containing a CE had transcriptomic similarities to von Economo neurons, which are known to be vulnerable to TDP-43 pathology and selectively lost in C9ORF72-FTD. Differential gene expression and pathway analysis of CE-containing neurons revealed multiple dysregulated metabolic processes. Our findings reveal novel insights into the transcriptomic changes of neurons vulnerable to TDP-43 pathology.

Moderate intrinsic phenotypic alterations in C9orf72 ALS/FTD iPSC-microglia despite the presence of C9orf72 pathological features.

While motor and cortical neurons are affected in C9orf72 amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD), it remains largely unknown if and how non-neuronal cells induce or exacerbate neuronal damage. We differentiated C9orf72 ALS/FTD patient-derived induced pluripotent stem cells into microglia (iPSC-MG) and examined their intrinsic phenotypes. Similar to iPSC motor neurons, C9orf72 ALS/FTD iPSC-MG mono-cultures form G4C2 repeat RNA foci, exhibit reduced C9orf72 protein levels, and generate dipeptide repeat proteins. Healthy control and C9orf72 ALS/FTD iPSC-MG equally express microglial specific genes and perform microglial functions, including inflammatory cytokine release and phagocytosis of extracellular cargos, such as synthetic amyloid beta peptides and healthy human brain synaptoneurosomes. RNA sequencing analysis revealed select transcriptional changes of genes associated with neuroinflammation or neurodegeneration in diseased microglia yet no significant differentially expressed microglial-enriched genes. Moderate molecular and functional differences were observed in C9orf72 iPSC-MG mono-cultures despite the presence of C9orf72 pathological features suggesting that a diseased microenvironment may be required to induce phenotypic changes in microglial cells and the associated neuronal dysfunction seen in C9orf72 ALS/FTD neurodegeneration.

exRNA-eCLIP intersection analysis reveals a map of extracellular RNA binding proteins and associated RNAs across major human biofluids and carriers.

Although the role of RNA binding proteins (RBPs) in extracellular RNA (exRNA) biology is well established, their exRNA cargo and distribution across biofluids are largely unknown. To address this gap, we extend the exRNA Atlas resource by mapping exRNAs carried by extracellular RBPs (exRBPs). This map was developed through an integrative analysis of ENCODE enhanced crosslinking and immunoprecipitation (eCLIP) data (150 RBPs) and human exRNA profiles (6,930 samples). Computational analysis and experimental validation identified exRBPs in plasma, serum, saliva, urine, cerebrospinal fluid, and cell-culture-conditioned medium. exRBPs carry exRNA transcripts from small non-coding RNA biotypes, including microRNA (miRNA), piRNA, tRNA, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), Y RNA, and lncRNA, as well as protein-coding mRNA fragments. Computational deconvolution of exRBP RNA cargo reveals associations of exRBPs with extracellular vesicles, lipoproteins, and ribonucleoproteins across human biofluids. Overall, we mapped the distribution of exRBPs across human biofluids, presenting a resource for the community.

The Foundational Data Initiative for Parkinson Disease: Enabling efficient translation from genetic maps to mechanism.

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.

Dynamic transcriptomic responses to divergent acute exercise stimuli in young adults.

Acute exercise elicits dynamic transcriptional changes that, when repeated, form the fundamental basis of health, resilience, and performance adaptations. While moderate-intensity endurance training combined with conventional resistance training (traditional, TRAD) is often prescribed and recommended by public health guidance, high-intensity training combining maximal-effort intervals with intensive, limited-rest resistance training is a time-efficient alternative that may be used tactically (HITT) to confer similar benefits. Mechanisms of action of these distinct stimuli are incompletely characterized and have not been directly compared. We assessed transcriptome-wide responses in skeletal muscle and circulating extracellular vesicles (EVs) to a single exercise bout in young adults randomized to TRAD (n = 21, 12 M/9 F, 22 ± 3 yr) or HITT (n = 19, 11 M/8 F, 22 ± 2 yr). Next-generation sequencing captured small, long, and circular RNA in muscle and EVs. Analysis identified differentially expressed transcripts (|log2FC|>1, FDR ≤ 0.05) immediately (h0, EVs only), h3, and h24 postexercise within and between exercise protocols. In aaddition, all apparently responsive transcripts (FDR < 0.2) underwent singular value decomposition to summarize data structures into latent variables (LVs) to deconvolve molecular expression circuits and interregulatory relationships. LVs were compared across time and exercise protocol. TRAD, a longer but less intense stimulus, generally elicited a stronger transcriptional response than HITT, but considerable overlap and key differences existed. Findings reveal shared and unique molecular responses to the exercise stimuli and lay groundwork toward establishing relationships between protein-coding genes and lesser-understood transcripts that serve regulatory roles following exercise. Future work should advance the understanding of these circuits and whether they repeat in other populations or following other types of exercise/stress.NEW & NOTEWORTHY We examined small and long transcriptomics in skeletal muscle and serum-derived extracellular vesicles before and after a single exposure to traditional combined exercise (TRAD) and high-intensity tactical training (HITT). Across 40 young adults, we found more consistent protein-coding gene responses to TRAD, whereas HITT elicited differential expression of microRNA enriched in brain regions. Follow-up analysis revealed relationships and temporal dynamics across transcript networks, highlighting potential avenues for research into mechanisms of exercise response and adaptation.

Plasma extracellular vesicle transcriptome as a dynamic liquid biopsy in acute heart failure.

Background: Acute decompensation is associated with increased mortality in heart failure (HF) patients, though the underlying etiology remains unclear. Extracellular vesicles (EVs) and their cargo may mark specific cardiovascular physiologic states. We hypothesized that EV transcriptomic cargo, including long non-coding RNAs (lncRNAs) and mRNAs, is dynamic from the decompensated to recompensated HF state, reflecting molecular pathways relevant to adverse remodeling. Methods: We examined differential RNA expression from circulating plasma extracellular RNA in acute HF patients at hospital admission and discharge alongside healthy controls. We leveraged different exRNA carrier isolation methods, publicly available tissue banks, and single nuclear deconvolution of human cardiac tissue to identify cell and compartment specificity of the topmost significantly differentially expressed targets. EV-derived transcript fragments were prioritized by fold change (-1.5 to + 1.5) and significance (<5% false discovery rate), and their expression in EVs was subsequently validated in 182 additional patients (24 control; 86 HFpEF; 72 HFrEF) by qRT-PCR. We finally examined the regulation of EV-derived lncRNA transcripts in human cardiac cellular stress models. Results: We identified 138 lncRNAs and 147 mRNAs (present mostly as fragments in EVs) differentially expressed between HF and control. Differentially expressed transcripts between HFrEF vs. control were primarily cardiomyocyte derived, while those between HFpEF vs. control originated from multiple organs and different (non-cardiomyocyte) cell types within the myocardium. We validated 5 lncRNAs and 6 mRNAs to differentiate between HF and control. Of those, 4 lncRNAs (AC092656.1, lnc-CALML5-7, LINC00989, RMRP) were altered by decongestion, with their levels independent of weight changes during hospitalization. Further, these 4 lncRNAs dynamically responded to stress in cardiomyocytes and pericytes in vitro , with a directionality mirroring the acute congested state. Conclusion: Circulating EV transcriptome is significantly altered during acute HF, with distinct cell and organ specificity in HFpEF vs. HFrEF consistent with a multi-organ vs. cardiac origin, respectively. Plasma EV-derived lncRNA fragments were more dynamically regulated with acute HF therapy independent of weight change (relative to mRNAs). This dynamicity was further demonstrated with cellular stress in vitro . Prioritizing transcriptional changes in plasma circulating EVs with HF therapy may be a fruitful approach to HF subtype-specific mechanistic discovery. CLINICAL PERSPECTIVE: What is new?: We performed extracellular transcriptomic analysis on the plasma of patients with acute decompensated heart failure (HFrEF and HFpEF) before and after decongestive efforts.Long non-coding RNAs (lncRNAs) within extracellular vesicles (EVs) changed dynamically upon decongestion in concordance with changes within human iPSC-derived cardiomyocytes under stress.In acute decompensated HFrEF, EV RNAs are mainly derived from cardiomyocytes, whereas in HFpEF, EV RNAs appear to have broader, non-cardiomyocyte origins.What are the clinical implications?: Given their concordance between human expression profiles and dynamic in vitro responses, lncRNAs within EVs during acute HF may provide insight into potential therapeutic targets and mechanistically relevant pathways. These findings provide a "liquid biopsy" support for the burgeoning concept of HFpEF as a systemic disorder extending beyond the heart, as opposed to a more cardiac-focused physiology in HFrEF.

MATR3 P154S knock-in mice do not exhibit motor, muscle or neuropathologic features of ALS.

Matrin 3 is a nuclear matrix protein that has many roles in RNA processing including splicing and transport of mRNA. Many missense mutations in the Matrin 3 gene (MATR3) have been linked to familial forms of amyotrophic lateral sclerosis (ALS) and distal myopathy. However, the exact role of MATR3 mutations in ALS and myopathy pathogenesis is not understood. To demonstrate a role of MATR3 mutations in vivo, we generated a novel CRISPR/Cas9 mediated knock-in mouse model harboring the MATR3 P154S mutation expressed under the control of the endogenous promoter. The P154S variant of the MATR3 gene has been linked to familial forms of ALS. Heterozygous and homozygous MATR3 P154S knock-in mice did not develop progressive motor deficits compared to wild-type mice. In addition, ALS-like pathology did not develop in nervous or muscle tissue in either heterozygous or homozygous mice. Our results suggest that the MATR3 P154S variant is not sufficient to produce ALS-like pathology in vivo.

The Texas Immuno-Oncology Biorepository, a statewide biospecimen collection and clinical informatics system to enable longitudinal tumor and immune profiling.

A detailed understanding of the molecular and immunological changes that occur longitudinally across tumors exposed to immune checkpoint inhibitors is a significant knowledge gap in oncology. To address this unmet need, we created a statewide biospecimen collection and clinical informatics system to enable longitudinal tumor and immune profiling and to enhance translational research. The Texas Immuno-Oncology Biorepository (TIOB) consents patients to collect, process, store, and analyze serial biospecimens of tissue, blood, urine, and stool from a diverse population of over 100,000 cancer patients treated each year across the Baylor Scott & White Health system. Here we sought to demonstrate that these samples were fit for purpose with regard to downstream multi-omic assays. Plasma, urine, peripheral blood mononuclear cells, and stool samples from 11 enrolled patients were collected from various cancer types. RNA isolated from extracellular vesicles derived from plasma and urine was sufficient for transcriptomics. Peripheral blood mononuclear cells demonstrated excellent yield and viability. Ten of 11 stool samples produced RNA quality to enable microbiome characterization. Sample acquisition and processing methods are known to impact sample quality and performance. We demonstrate that consistent acquisition methodology, sample preparation, and sample storage employed by the TIOB can produce high-quality specimens, suited for employment in a wide array of multi-omic platforms, enabling comprehensive immune and molecular profiling.

Muscle transcriptomic circuits linked to periarticular physiology in end-stage osteoarthritis.

The ability of individuals with end-stage osteoarthritis (OA) to functionally recover from total joint arthroplasty is highly inconsistent. The molecular mechanisms driving this heterogeneity have yet to be elucidated. Furthermore, OA disproportionately impacts females, suggesting a need for identifying female-specific therapeutic targets. We profiled the skeletal muscle transcriptome in females with end-stage OA (n = 20) undergoing total knee or hip arthroplasty using RNA-Seq. Single-gene differential expression (DE) analyses tested for DE genes between skeletal muscle overlaying the surgical (SX) joint and muscle from the contralateral (CTRL) leg. Network analyses were performed using Pathway-Level Information ExtractoR (PLIER) to summarize genes into latent variables (LVs), i.e., gene circuits, and link them to biological pathways. LV differences in SX versus CTRL muscle and across sources of muscle tissue (vastus medialis, vastus lateralis, or tensor fascia latae) were determined with ANOVA. Linear models tested for associations between LVs and muscle phenotype on the SX side (inflammation, function, and integrity). DE analysis revealed 360 DE genes (|Log2 fold-difference| ≥ 1, FDR ≤ 0.05) between the SX and CTRL limbs, many associated with inflammation and lipid metabolism. PLIER analyses revealed circuits associated with protein degradation and fibro-adipogenic cell gene expression. Muscle inflammation and function were linked to an LV associated with endothelial cell gene expression highlighting a potential regulatory role of endothelial cells within skeletal muscle. These findings may provide insight into potential therapeutic targets to improve OA rehabilitation before and/or following total joint replacement.

Multi-modality machine learning predicting Parkinson's disease.

Personalized medicine promises individualized disease prediction and treatment. The convergence of machine learning (ML) and available multimodal data is key moving forward. We build upon previous work to deliver multimodal predictions of Parkinson's disease (PD) risk and systematically develop a model using GenoML, an automated ML package, to make improved multi-omic predictions of PD, validated in an external cohort. We investigated top features, constructed hypothesis-free disease-relevant networks, and investigated drug-gene interactions. We performed automated ML on multimodal data from the Parkinson's progression marker initiative (PPMI). After selecting the best performing algorithm, all PPMI data was used to tune the selected model. The model was validated in the Parkinson's Disease Biomarker Program (PDBP) dataset. Our initial model showed an area under the curve (AUC) of 89.72% for the diagnosis of PD. The tuned model was then tested for validation on external data (PDBP, AUC 85.03%). Optimizing thresholds for classification increased the diagnosis prediction accuracy and other metrics. Finally, networks were built to identify gene communities specific to PD. Combining data modalities outperforms the single biomarker paradigm. UPSIT and PRS contributed most to the predictive power of the model, but the accuracy of these are supplemented by many smaller effect transcripts and risk SNPs. Our model is best suited to identifying large groups of individuals to monitor within a health registry or biobank to prioritize for further testing. This approach allows complex predictive models to be reproducible and accessible to the community, with the package, code, and results publicly available.

Distinct Stress-Dependent Signatures of Cellular and Extracellular tRNA-Derived Small RNAs.

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.