A Novel Serum tsRNA for Diagnosis and Prediction of Nephritis in SLE.

Objective: Dysregulation of transfer RNA (tRNA)-derived small noncoding RNA (tsRNA) signatures in human serum has been found in various diseases. Here, we determine whether the signatures of tsRNAs in serum can serve as biomarkers for diagnosis or prognosis of systemic lupus erythematosus (SLE). Methods: Initially, small RNA sequencing was employed for the screening serum tsRNAs obtained from SLE patients, followed by validation with TaqMan probe-based quantitative reverse transcription-PCR (RT-PCR) assay. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic efficacy. The biological functions of tsRNAs were identified by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) assay. Results: We first analyzed tsRNA signatures in SLE serum and identified that tRF-His-GTG-1 was significantly upregulated in SLE serum. The combination of tRF-His-GTG-1 and anti-dsDNA could serve as biomarkers for diagnosing SLE with a high area under the curve (AUC) of 0.95 (95% CI = 0.92-0.99), sensitivity (83.72%), and specificity (94.19%). Importantly, the noninvasive serum tRF-His-GTG-1 could also be used to distinguish SLE with LN or SLE without LN with AUC of 0.81 (95% CI, 0.73-0.88) and performance (sensitivity 66.27%, specificity 96.15%). Moreover, the serum tsRNA is mainly secreted via exosome and can directly target signaling molecules that play crucial roles in regulating the immune system. Conclusion: In this study, it has been demonstrated for the first time that serum tsRNAs can be employed as noninvasive biomarkers for the efficient diagnosis and prediction of nephritis in SLE.

Comparative expression analysis of tRF-3001a and tRF-1003 with corresponding miRNAs (miR-1260a and miR-4521) and their network analysis with breast cancer biomarkers.

BACKGROUND: MicroRNAs and tRFs (tRNA-derived fragments) are small non-coding RNAs that are promising breast cancer (BC) biomarkers. miRNA sequences are found within tRFs. For example, miR-1260a and miR-4521 sequences are found within tRF-3001a and tRF-1003, respectively. No study has addressed the biomarker potential of these tRF-miRNA pairs in BC or their association with other BC miRNA biomarkers. METHODS AND RESULTS: Real-time PCR was performed to examine the expression of miR-1260a-tRF-3001a and miR-4521-tRF-1003 pairs in plasma of BC patients. miR-4521 and miR-1260a showed no change in plasma of breast cancer patients (n = 19). On the contrary, both the corresponding tRFs (tRF-1003 and tRF-3001a) were down-regulated. Also, we performed miRNA/mRNA network analysis for miR-1260a and miR-4521 with top degree BC biomarkers miR-16-5p and miR-93-5p. We found that they shared nine target genes. Moreover, miR-16-5p was down-regulated, and miR-93-5p was up-regulated in the same sample set. Survival analysis plotted using clinical data from Kaplan-Meier Plotter showed that all four miRNAs and 8/9 target gene expressions could predict the survival of BC patients. CONCLUSIONS: Our cohort analyses suggest that tRF-3001a and tRF-1003 serve as better biomarkers than their miRNA counterparts in addition to miR-93-5p and miR-16-5p. Also, they form a significant miRNA/mRNA biomarker cluster.

Circulating Non-Coding RNAs as a Signature of Autism Spectrum Disorder Symptomatology.

Autism spectrum disorder (ASD) is a multifaced neurodevelopmental disorder that becomes apparent during early childhood development. The complexity of ASD makes clinically diagnosing the condition difficult. Consequently, by identifying the biomarkers associated with ASD severity and combining them with clinical diagnosis, one may better factionalize within the spectrum and devise more targeted therapeutic strategies. Currently, there are no reliable biomarkers that can be used for precise ASD diagnosis. Consequently, our pilot experimental cohort was subdivided into three groups: healthy controls, individuals those that express severe symptoms of ASD, and individuals that exhibit mild symptoms of ASD. Using next-generation sequencing, we were able to identify several circulating non-coding RNAs (cir-ncRNAs) in plasma. To the best of our knowledge, this study is the first to show that miRNAs, piRNAs, snoRNAs, Y-RNAs, tRNAs, and lncRNAs are stably expressed in plasma. Our data identify cir-ncRNAs that are specific to ASD. Furthermore, several of the identified cir-ncRNAs were explicitly associated with either the severe or mild groups. Hence, our findings suggest that cir-ncRNAs have the potential to be utilized as objective diagnostic biomarkers and clinical targets.

The circulatory small non-coding RNA landscape in community-acquired pneumonia on intensive care unit admission.

Community-acquired pneumonia (CAP) is a major cause of sepsis. Despite several clinical trials targeting components of the inflammatory response, no specific treatment other than antimicrobial therapy has been approved. This argued for a deeper understanding of sepsis immunopathology, in particular factors that can modulate the host response. Small non-coding RNA, for example, micro (mi)RNA, have been established as important modifiers of cellular phenotypes. Notably, miRNAs are not exclusive to the intracellular milieu but have also been detected extracellular in the circulation with functional consequences. Here, we sought to determine shifts in circulatory small RNA levels of critically ill patients with CAP-associated sepsis and to determine the influence of clinical severity and causal pathogens on small RNA levels. Blood plasma was collected from 13 critically ill patients with sepsis caused by CAP on intensive care unit admission and from 5 non-infectious control participants. Plasma small RNA-sequencing identified significantly altered levels of primarily mature miRNAs in CAP relative to controls. Pathways analysis of high or low abundance miRNA identified various over-represented cellular biological pathways. Analysis of small RNA levels against common clinical severity and inflammatory parameters indices showed direct and indirect correlations. Additionally, variance of plasma small RNA levels in CAP patients may be explained, at least in part, by differences in causal pathogens. Small nuclear RNA levels were specifically altered in CAP due to Influenza infection in contrast to Streptococcus pneumoniae infection. Pathway analysis of plasma miRNA signatures unique to Influenza or Streptococcus pneumoniae infections showed enrichment for specific proteoglycan, cell cycle, and immunometabolic pathways.

Protocol to analyze circulating small non-coding RNAs by high-throughput RNA sequencing from human plasma samples.

The identification and validation of circulating small non-coding RNA (sncRNA) as biomarkers for disease diagnosis, staging, and response to novel therapies is still a compelling challenge. Pre-analytical variables, such as storage temperature or blood hemolysis, and different analytical approaches affect sncRNA stability, detection, and expression, resulting in discrepancies among studies. Here, we report a systematic standardized protocol to reproducibly analyze circulating sncRNAs, employing high-throughput sncRNA sequencing and qRT-PCR validation, from 200 µL of human plasma samples. For details on the use and execution of this protocol, please refer to Ventriglia et al. (2020), Sebastiani et al. (2017), and Dotta et al. (2018).

Small noncoding RNA profiling across cellular and biofluid compartments and their implications for multiple sclerosis immunopathology.

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease affecting the central nervous system (CNS). Small non-coding RNAs (sncRNAs) and, in particular, microRNAs (miRNAs) have frequently been associated with MS. Here, we performed a comprehensive analysis of all classes of sncRNAs in matching samples of peripheral blood mononuclear cells (PBMCs), plasma, cerebrospinal fluid (CSF) cells, and cell-free CSF from relapsing-remitting (RRMS, n = 12 in relapse and n = 11 in remission) patients, secondary progressive (SPMS, n = 6) MS patients, and noninflammatory and inflammatory neurological disease controls (NINDC, n = 11; INDC, n = 5). We show widespread changes in miRNAs and sncRNA-derived fragments of small nuclear, nucleolar, and transfer RNAs. In CSF cells, 133 out of 133 and 115 out of 117 differentially expressed sncRNAs were increased in RRMS relapse compared to remission and RRMS compared to NINDC, respectively. In contrast, 65 out of 67 differentially expressed PBMC sncRNAs were decreased in RRMS compared to NINDC. The striking contrast between the periphery and CNS suggests that sncRNA-mediated mechanisms, including alternative splicing, RNA degradation, and mRNA translation, regulate the transcriptome of pathogenic cells primarily in the CNS target organ.

The Predictive Value of miR-16, -29a and -134 for Early Identification of Gestational Diabetes: A Nested Analysis of the DALI Cohort.

Early identification of gestational diabetes mellitus (GDM) aims to reduce the risk of adverse maternal and perinatal outcomes. Currently, no circulating biomarker has proven clinically useful for accurate prediction of GDM. In this study, we tested if a panel of small non-coding circulating RNAs could improve early prediction of GDM. We performed a nested case-control study of participants from the European multicenter 'Vitamin D and lifestyle intervention for GDM prevention (DALI)' trial using serum samples from obese pregnant women (BMI ≥ 29 kg/m2) entailing 82 GDM cases (early- and late- GDM), and 41 age- and BMI-matched women with normal glucose tolerance (NGT) throughout pregnancy (controls). Anthropometric, clinical and biochemical characteristics were obtained at baseline (<20 weeks of gestation) and throughout gestation. Baseline serum microRNAs (miRNAs) were measured using quantitative real time PCR (qPCR). Elevated miR-16-5p, -29a-3p, and -134-5p levels were observed in women, who were NGT at baseline and later developed GDM, compared with controls who remained NGT. A combination of the three miRNAs could distinguish later GDM from NGT cases (AUC 0.717, p = 0.001, compared with fasting plasma glucose (AUC 0.687, p = 0.004)) as evaluated by area under the curves (AUCs) using Receiver Operator Characteristics (ROC) analysis. Elevated levels of individual miRNAs or a combination hereof were associated with higher odds ratios of GDM. Conclusively, circulating miRNAs early in pregnancy could serve as valuable predictive biomarkers of GDM.

Peripheral blood non-canonical small non-coding RNAs as novel biomarkers in lung cancer.

One unmet challenge in lung cancer diagnosis is to accurately differentiate lung cancer from other lung diseases with similar clinical symptoms and radiological features, such as pulmonary tuberculosis (TB). To identify reliable biomarkers for lung cancer screening, we leverage the recently discovered non-canonical small non-coding RNAs (i.e., tRNA-derived small RNAs [tsRNAs], rRNA-derived small RNAs [rsRNAs], and YRNA-derived small RNAs [ysRNAs]) in human peripheral blood mononuclear cells and develop a molecular signature composed of distinct ts/rs/ysRNAs (TRY-RNA). Our TRY-RNA signature precisely discriminates between control, lung cancer, and pulmonary TB subjects in both the discovery and validation cohorts and outperforms microRNA-based biomarkers, which bears the diagnostic potential for lung cancer screening.

Circulating microbial small RNAs are altered in patients with rheumatoid arthritis.

OBJECTIVES: To determine if plasma microbial small RNAs (sRNAs) are altered in patients with rheumatoid arthritis (RA) compared with control subjects, associated with RA disease-related features, and altered by disease-modifying antirheumatic drugs (DMARDs). METHODS: sRNA sequencing was performed on plasma from 165 patients with RA and 90 matched controls and a separate cohort of 70 patients with RA before and after starting a DMARD. Genome alignments for RA-associated bacteria, representative bacterial and fungal human microbiome genomes and environmental bacteria were performed. Microbial genome counts and individual sRNAs were compared across groups and correlated with disease features. False discovery rate was set at 0.05. RESULTS: Genome counts of Lactobacillus salivarius, Anaerobaculum hydrogeniformans, Staphylococcus epidermidis, Staphylococcus aureus, Paenisporosarcina spp, Facklamia hominis, Sphingobacterium spiritivorum, Lentibacillus amyloliquefaciens, Geobacillus spp, and Pseudomonas fluorescens were significantly decreased in the plasma of RA compared with control subjects. Three microbial transfer RNA-derived sRNAs were increased in RA versus controls and inversely associated with disease activity. Higher total microbial sRNA reads were associated with lower disease activity in RA. Baseline total microbial sRNAs were threefold higher among patients who improved with DMARD versus those who did not but did not change significantly after 6 months of treatment. CONCLUSION: Plasma microbial sRNA composition is altered in RA versus control subjects and associated with some measures of RA disease activity. DMARD treatment does not alter microbial sRNA abundance or composition, but increased abundance of microbial sRNAs at baseline was associated with disease activity improvement at 6 months.

Circulating Small Noncoding RNAs Have Specific Expression Patterns in Plasma and Extracellular Vesicles in Myelodysplastic Syndromes and Are Predictive of Patient Outcome.

Myelodysplastic syndromes (MDS) are hematopoietic stem cell disorders with large heterogeneity at the clinical and molecular levels. As diagnostic procedures shift from bone marrow biopsies towards less invasive techniques, circulating small noncoding RNAs (sncRNAs) have become of particular interest as potential novel noninvasive biomarkers of the disease. We aimed to characterize the expression profiles of circulating sncRNAs of MDS patients and to search for specific RNAs applicable as potential biomarkers. We performed small RNA-seq in paired samples of total plasma and plasma-derived extracellular vesicles (EVs) obtained from 42 patients and 17 healthy controls and analyzed the data with respect to the stage of the disease, patient survival, response to azacitidine, mutational status, and RNA editing. Significantly higher amounts of RNA material and a striking imbalance in RNA content between plasma and EVs (more than 400 significantly deregulated sncRNAs) were found in MDS patients compared to healthy controls. Moreover, the RNA content of EV cargo was more homogeneous than that of total plasma, and different RNAs were deregulated in these two types of material. Differential expression analyses identified that many hematopoiesis-related miRNAs (e.g., miR-34a, miR-125a, and miR-150) were significantly increased in MDS and that miRNAs clustered on 14q32 were specifically increased in early MDS. Only low numbers of circulating sncRNAs were significantly associated with somatic mutations in the SF3B1 or DNMT3A genes. Survival analysis defined a signature of four sncRNAs (miR-1237-3p, U33, hsa_piR_019420, and miR-548av-5p measured in EVs) as the most significantly associated with overall survival (HR = 5.866, p < 0.001). In total plasma, we identified five circulating miRNAs (miR-423-5p, miR-126-3p, miR-151a-3p, miR-125a-5p, and miR-199a-3p) whose combined expression levels could predict the response to azacitidine treatment. In conclusion, our data demonstrate that circulating sncRNAs show specific patterns in MDS and that their expression changes during disease progression, providing a rationale for the potential clinical usefulness of circulating sncRNAs in MDS prognosis. However, monitoring sncRNA levels in total plasma or in the EV fraction does not reflect one another, instead, they seem to represent distinctive snapshots of the disease and the data should be interpreted circumspectly with respect to the type of material analyzed.

Comparability of the small RNA secretome across human biofluids concomitantly collected from healthy adults.

Small extracellular vesicles (sEV) are nano-sized (40-150 nm), membrane-encapsulated vesicles that are released by essentially all cells into the extracellular space and function as intercellular signaling vectors through the horizontal transfer of biologic molecules, including microRNA (miRNA) and other small non-coding RNA (ncRNA), that can alter the phenotype of recipient cells. sEV are present in essentially all extracellular biofluids, including serum, urine and saliva, and offer a new avenue for discovery and development of novel biomarkers of various disease states and exposures. The objective of this study was to systematically interrogate similarities and differences between sEV ncRNA derived from saliva, serum and urine, as well as cell-free small ncRNA (cf-ncRNA) from serum. Saliva, urine and serum were concomitantly collected from 4 healthy donors to mitigate potential bias that can stem from interpersonal and temporal variability. sEV were isolated from each respective biofluid, along with cf-RNA from serum. sEV were isolated from the respective biofluids via differential ultracentrifugation with a 30% sucrose cushion to minimize protein contamination. Small RNA-sequencing was performed on each sample, and cluster analysis was performed based on ncRNA profiles. While some similarities existed in terms of sEV ncRNA cargo across biofluids, there are also notable differences in ncRNA class and ncRNA secretion, with sEV in each biofluid bearing a unique ncRNA profile, including major differences in composition by ncRNA class. We conclude that sEV ncRNA cargo varies according to biofluid, so thus should be carefully selected and interpreted when designing or contrasting translational or epidemiological studies.

COMPSRA: a COMprehensive Platform for Small RNA-Seq data Analysis.

Small RNA-Seq is a common means to interrogate the small RNA'ome or the full spectrum of small RNAs (<200 nucleotide length) of a biological system. A pivotal problem in NGS based small RNA analysis is identifying and quantifying the small RNA'ome constituent components. For example, small RNAs in the circulatory system (circulating RNAs) are potential disease biomarkers and their function is being actively investigated. Most existing NGS data analysis tools focus on the microRNA component and a few other small RNA types like piRNA, snRNA and snoRNA. A comprehensive platform is needed to interrogate the full small RNA'ome, a prerequisite for down-stream data analysis. We present COMPSRA, a comprehensive modular stand-alone platform for identifying and quantifying small RNAs from small RNA sequencing data. COMPSRA contains prebuilt customizable standard RNA databases and sequence processing tools to enable turnkey basic small RNA analysis. We evaluated COMPSRA against comparable existing tools on small RNA sequencing data set from serum samples of 12 healthy human controls, and COMPSRA identified a greater diversity and abundance of small RNA molecules. COMPSRA is modular, stand-alone and integrates multiple customizable RNA databases and sequence processing tool and is distributed under the GNU General Public License free to non-commercial registered users at https://github.com/cougarlj/COMPSRA.

Global Characterization of Circulating Nucleic Acids.

Circulating nucleic acids (CNAs) include genomic and mitochondrial DNA fragments, small RNAs, and bacterial and viral DNA/RNA. Different mechanisms such as cell apoptosis, necrosis, and active CNA release from cells have been proposed to result in nucleic acids in the circulation. Application of next generation sequencing technology demonstrated that CNAs contain specific mutations, indels, microsatellite alterations, and epigenetic changes (DNA methylation) associated with various diseases. Their clinical implications have been demonstrated for diseases such as cancer, stroke, trauma, myocardial infarction, autoimmune disorders, and pregnancy-associated complications. Thus, CNAs in blood represent an attractive family of molecules that can serve as biomarkers and the analysis of CNAs can be alternative for immunohistochemical analyses of conventional biopsies. The methods described in this chapter provides details for circulating DNA and small RNA isolation, CNA(-derived cDNA) library preparation, and sequencing data analysis.

A 10-year prediagnostic follow-up study shows that serum RNA signals are highly dynamic in lung carcinogenesis.

The majority of lung cancer (LC) patients are diagnosed at a late stage, and survival is poor. Circulating RNA molecules are known to have a role in cancer; however, their involvement before diagnosis remains an open question. In this study, we investigated circulating RNA dynamics in prediagnostic LC samples, focusing on smokers, to identify if and when disease-related signals can be detected in serum. We sequenced small RNAs in 542 serum LC samples donated up to 10 years before diagnosis and 519 matched cancer-free controls coming from 905 individuals in the Janus Serum Bank. This sample size provided sufficient statistical power to independently analyze time to diagnosis, stage, and histology. The results showed dynamic changes in differentially expressed circulating RNAs specific to LC histology and stage. The greatest number of differentially expressed RNAs was identified around 7 years before diagnosis for early-stage LC and 1-4 years prior to diagnosis for locally advanced and advanced-stage LC, regardless of LC histology. Furthermore, NSCLC and SCLC histologies have distinct prediagnostic signals. The majority of differentially expressed RNAs were associated with cancer-related pathways. The dynamic RNA signals pinpointed different phases of tumor development over time. Stage-specific RNA profiles may be associated with tumor aggressiveness. Our results improve the molecular understanding of carcinogenesis. They indicate substantial opportunity for screening and improved treatment and will guide further research on early detection of LC. However, the dynamic nature of the RNA signals also suggests challenges for prediagnostic biomarker discovery.

Comparative analysis of small RNAs released by the filarial nematode Litomosoides sigmodontis in vitro and in vivo.

BACKGROUND: The release of small non-coding RNAs (sRNAs) has been reported in parasitic nematodes, trematodes and cestodes of medical and veterinary importance. However, little is known regarding the diversity and composition of sRNAs released by different lifecycle stages and the portion of sRNAs that persist in host tissues during filarial infection. This information is relevant to understanding potential roles of sRNAs in parasite-to-host communication, as well as to inform on the location within the host and time point at which they can be detected. METHODOLOGY AND PRINCIPAL FINDINGS: We have used small RNA (sRNA) sequencing analysis to identify sRNAs in replicate samples of the excretory-secretory (ES) products of developmental stages of the filarial nematode Litomosoides sigmodontis in vitro and compare this to the parasite-derived sRNA detected in host tissues. We show that all L. sigmodontis developmental stages release RNAs in vitro, including ribosomal RNA fragments, 5'-derived tRNA fragments (5'-tRFs) and, to a lesser extent, microRNAs (miRNAs). The gravid adult females (gAF) produce the largest diversity and abundance of miRNAs in the ES compared to the adult males or microfilariae. Analysis of sRNAs detected in serum and macrophages from infected animals reveals that parasite miRNAs are preferentially detected in vivo, compared to their low levels in the ES products, and identifies miR-92-3p and miR-71-5p as L. sigmodontis miRNAs that are stably detected in host cells in vivo. CONCLUSIONS: Our results suggest that gravid adult female worms secrete the largest diversity of extracellular sRNAs compared to adult males or microfilariae. We further show differences in the parasite sRNA biotype distribution detected in vitro versus in vivo. We identify macrophages as one reservoir for parasite sRNA during infection, and confirm the presence of parasite miRNAs and tRNAs in host serum during patent infection.

Large-scale analysis of small RNAs derived from traditional Chinese herbs in human tissues.

Plant-derived microRNAs have recently been reported to function in human blood and tissues. Controversy was immediately raised due to possible contamination and the lack of large sample sizes. Here, we report thousands of unique small RNAs derived from traditional Chinese medicine (TCM) herbs found in human blood cells and mouse lung tissues using a large-scale analysis. We extracted small RNAs from decoctions of 10 TCM plants (Ban Zhi Lian, Chai Hu, Chuan Xin Lian, Di Ding Zi Jin, Huang Qin, Jin Yin Hua, Lian Qiao, Pu Gong Ying, Xia Ku Cao, and Yu Xing Cao) and obtained millions of RNA sequences from each herb. We also obtained RNA-Seq data from the blood cells of humans who consumed herbal decoctions and from the lung tissues of mice administered RNAs from herbal decoctions via oral gavage. We identified thousands of unique small RNA sequences in human blood cells and mouse lung tissues. Some of these identified small RNAs from Chuan Xin Lian and Hong Jing Tian could be mapped to the genomes of the herbs, confirming their TCM plant origin. Small RNAs derived from herbs regulate mammalian gene expression in a sequence-specific manner, and thus are a superior novel class of herbal drug components that hold great potential as oral gene-targeted therapeutics, highlighting the important role of herbgenomics in their development.

Circulating small non-coding RNAs associated with age, sex, smoking, body mass and physical activity.

Small non-coding RNAs (sncRNA) are regulators of cell functions and circulating sncRNAs from the majority of RNA classes are potential non-invasive biomarkers. Understanding how common traits influence ncRNA expression is essential for assessing their biomarker potential. In this study, we identify associations between sncRNA expression and common traits (sex, age, self-reported smoking, body mass, self-reported physical activity). We used RNAseq data from 526 serum samples from the Janus Serum Bank and traits from health examination surveys. Ageing showed the strongest association with sncRNA expression, both in terms of statistical significance and number of RNAs, regardless of RNA class. piRNAs were abundant in the serum samples and they were associated to sex. Interestingly, smoking cessation generally restored RNA expression to non-smoking levels, although for some sncRNAs smoking-related expression levels persisted. Pathway analysis suggests that smoking-related sncRNAs target the cholinergic synapses and may therefore potentially play a role in smoking addiction. Our results show that common traits influence circulating sncRNA expression. It is clear that sncRNA biomarker analyses should be adjusted for age and sex. In addition, for specific sncRNAs, analyses should also be adjusted for body mass, smoking, physical activity and technical factors.

Cancer cells exploit an orphan RNA to drive metastatic progression.

Here we performed a systematic search to identify breast-cancer-specific small noncoding RNAs, which we have collectively termed orphan noncoding RNAs (oncRNAs). We subsequently discovered that one of these oncRNAs, which originates from the 3' end of TERC, acts as a regulator of gene expression and is a robust promoter of breast cancer metastasis. This oncRNA, which we have named T3p, exerts its prometastatic effects by acting as an inhibitor of RISC complex activity and increasing the expression of the prometastatic genes NUPR1 and PANX2. Furthermore, we have shown that oncRNAs are present in cancer-cell-derived extracellular vesicles, raising the possibility that these circulating oncRNAs may also have a role in non-cell autonomous disease pathogenesis. Additionally, these circulating oncRNAs present a novel avenue for cancer fingerprinting using liquid biopsies.

Next Generation Sequencing Analysis of Total Small Noncoding RNAs from Low Input RNA from Dried Blood Sampling.

Circulating miRNAs are favored for biomarker candidates as they can reflect tissue specific miRNA dysregulation in disease contexts. Moreover, they have the additional advantage that they can be monitored in a minimally invasive manner. Blood-borne miRNAs are therefore currently characterized to identify, describe, and validate their potential suitability as biomarkers; however, sampling and as well miRNA detection methods limit these studies in terms of sensitivity but also practicability in clinical, at-home, or low-resource sampling of high-quality circulating RNA samples. We describe here a novel and innovative method of circulating RNA microsampling from minimal volume dried blood samples with direct enrichment for small RNA fractions in combination with ligation free library preparation. We evaluated crucial parameters for efficient library preparation from low RNA inputs of 50 pg for efficient dissection not only of miRNAs but also isomiRs, piRNAs, and lincRNAs. We compared these data to classical microarrays and characterize the technical reproducibility and its sensitivity. We demonstrate and evaluate a method for easy low resource sampling and NGS analysis of circulating RNAs providing a powerful tool for massive cohort and remote patient monitoring.