Assessment of salivary microRNA by RT-qPCR: Facing challenges in data interpretation for clinical diagnosis.

In the last few decades, human saliva has attracted a great attention in the medical diagnostic field as a bio-fluid that provides access to various biomarkers in a non-invasive manner. Similar to peripheral blood, saliva contains a high versatility of circulating molecules that allows early diagnosis of systemic disorders [ 1 , 2 ]. For clinical practice, saliva offers a number of advantages over blood sampling such as a remarkable stability [ 1 ], simple sample collection, possibility for auto-sampling, and practical transportation and storage condition. In addition, saliva has a high turnover rate exhibiting fast bidirectional exchange of biomarkers, which opens access to recent biological events. However, the high turnover rate is at the cost of harbouring large biochemical and physical dynamics among samples [ 2 ] and the presence of buccal mucosa and non-human derived ( i . e . oral bacteria) biomaterial that mask the low concentration of circulating biomarkers. Altogether, this makes the quantification of salivary biomarkers highly challenging, requiring exceedingly robust assays [ 3 ]. Nevertheless, the concentration levels of salivary biomarkers of different natures including DNA, RNA, protein and metabolite have been identified to be associated to a broad range of diseases [ 4 – 7 ] via numerous clinical studies, demonstrating the significant clinical interest of precisely quantifying these biomarkers. Recently, salivary miRNAs have been considered as the next generation of non-invasive biomarkers for the diagnostics of diverse diseases [ 8 , 9 ]. They are small non-coding RNAs that regulate gene expression at the post-transcriptional level, playing a crucial role in every fundamental aspect of cellular function [ 10 ]. The relationships of their regulation with the disease onsets [ 8 , 9 ] and their presence in the extracellular circulation [ 11 – 13 ] make them available for various liquid biopsies enabling non-invasive medical assessment [ 14 , 15 ]. For instance, signatures of salivary miRNAs have been recently associated with the diagnosis of mild traumatic brain injury (mTBI) [ 6 , 16 – 18 ], cancers [ 12 , 19 , 20 ], endometriosis [ 21 , 22 ], neurodegenerative [ 23 ], metabolic [ 24 ] or systemic diseases [ 7 ] along with many others [ 25 – 29 ]. However, due to their small size (19–25 nucleotides), their high sequence similarity and their complex gene regulation process [ 10 ], the correlation between their expression levels and disease stages is often non-linear, causing it an issue of constant debate [ 8 , 15 , 30 ]. The majority of the miRNA studies have been standardized by microarray or Next Generation of Sequencing (NGS) methods followed by subsequent validation using various customized RT-qPCR approaches [ 31 – 36 ]. Notwithstanding the practicality, rapidity and cost effectiveness(8) of the RT-qPCR technique, its application in the quantification of miRNAs faces methodological inconsistencies in both detection and data normalization [ 37 , 38 ], making data interpretation controversial [ 39 ] and study dependent [ 18 ]. These unsettled topics are the main issues that restrain the use of miRNAs in current clinical practice. Understanding technical issues of a given assay for quantification of salivary miRNA to navigate corresponding solutions would accelerate the clinical translation process for salivary miRNA biomarkers. To this aim, in this study we evaluated the use of a wildly used commercial RT-qPCR kit [ 31 ] for quantification of salivary miRNAs by determining its capacity to specifically discriminate miRNAs with various homologous degrees. A panel of six miRNAs, namely hsa-Let-7a-5p, hsa-Let-7f-5p, hsa-mir-148a-3p, hsa-miR-26b-5p, hsa-miR-107 and hsa-miR-103a-3p was chosen based on both their clinical values [ 16 , 40 , 41 ] and their sequence homology. RT-qPCR assays were performed on both miRNA targets extracted from saliva of healthy volunteers and synthetic ones. Fundamental technical parameters such as sensitivity, specificity, limit of detection (LOD), limit of quantification (LOQ) and cross-reactions of all assays were characterized and included in the data interpretation process. Additionally, a synthetic version of target miRNAs spiked-in extracted sample was investigated as a potential solution for more accurate quantification of low abundance miRNAs whose concentrations are close to or at the LOD.

Following each sampling, physical characteristics of individual saliva samples were visually inspected prior to small RNA extraction. Results revealed that saliva from a given participant (P) had a typical physical property harbouring a given level of cesia and viscosity, which remained unchanged throughout the 4 samplings of the study ( Fig 1A and 1B ). Concentrations of total extracted small RNA varied both among participants and sampling times ( Fig 1C ), although no significant difference among the average concentrations of the four samplings was observed ( S1 Fig ). We highlighted consistently low concentrations across the study for P5 and P6 samples ( S2 Fig ), whose saliva were both liquid and transparent. Efficiencies for every individual small RNA extraction were technically controlled by quantifying the retained amount of the UniSP6 miRNA that had been equally spiked-in preceding the extraction process. Consistent RT-qPCR results for the detection of UniSP6 (Average Ct = 21.7 ± 0.02) using 1 μL of extracted small RNA from all samples revealed a comparable extraction efficiency for all participants ( Fig 1D ), which was conserved throughout this study ( S3 Fig ). More precisely, upon standardizing the total RNA concentration with respect to 1 μL condition, UniSP6 detection remains linear demonstrating that the small RNA content of a given sample does not affect its extraction efficiency ( S4 Fig ). Subsequently, we validated that the addition of this spiked-in miRNA had no influence on the extraction efficiency for the six target miRNAs. To this aim, we chose three samples (P2, P6 and P7) whose small RNA contents are in different range ( Fig 1C ) to perform the RNA extraction procedure in the presence or absence of the spiking UniSP6 miRNA ( S5 Fig ). Results of RT-qPCR analysis using 50 ng of each extracted small RNA from these samples showed that spike-in UniSP6 had no differential effect on the six assessed miRNAs as the observed Ct values increased by less than 1% (Average ΔCt 0.2 ± 0.02), and ( S5C Fig ). ( A ) Cesia and ( B ) viscosity of the saliva samples prior RNA extraction. ( C ) Total small RNA extracted from 250 μL of saliva for each participant and for the 4 sampling points. Black points represent the mean value and error bars show the standard error of the mean. ( D ) Detection of spiked artificial UniSP6 miRNA prior to RNA extraction for sampling three. 1 μL of each extracted RNA sample was used as input. P1-10: Saliva sample from participants 1 to 10. A panel of six miRNAs was analysed on each saliva sample (10 participants and 4 temporal sampling points, n = 40). 50 ng of extracted small RNA was used as input for universal poly(A)-tailed RT reactions followed by target specific qPCR quantification (Qiagen). Fig 2A and S2 Table show the heterogeneous expression profiles obtained from detection signals of the six target miRNAs with averaged Ct values for the four samplings ranging from 22 to 29, which are within the acceptable detection ranges considered by the community [ 19 , 42 ]. However, the six miRNA targets shared a similar detection pattern among the four sampling points ( Fig 2B ). We observed a reduction in Ct value from the sampling 1 to sampling 3, followed by a restoration in the sampling 4 whose Ct values fell between the first two samplings. Even if we had previously observed no significant difference between the average of the extracted total RNA concentrations across temporal sampling ( S1 Fig ), Ct values on 50 ng samples revealed the contrary, showing a significant difference between sampling 1 and 3 for all miRNAs, and between sampling 3 and 4 for half of the miRNA assessed, namely hsa-Let-7a-5p, hsa-miR148a-3p and hsa-miR103a-3p ( S6A Fig ). Statistical analysis for individual miRNA targets revealed the apparition of two major groups, a lower Ct value group containing hsa-Let-7a-5p and hsa-Let-7f-5p, and a greater Ct value group containing hsa-miR148a-3p and hsa-miR107 (Figs 2C and S6B ). In between both groups, we found hsa-miR26b-5p and hsa-miR103-3p, which shared proximity with the lowest and the greatest Ct value group, respectively. However, the evaluation of the Ct values with respect to individual participants showed that the average miRNA signals ( Fig 2B ) partially masked the ones of individual participants ( Fig 2C ). Further analysis on these miRNA expression profiles revealed significant differences among participants, which can be clustered into three major groups: A) high Ct values (P5 and P6), B) moderate Ct values (P8 and P9) and C) low Ct values (P1, P2, P3 and P4), with participant P7 and participant P10 between the later groups, being adjacent to group B&C and group C, respectively ( S7A Fig ). We noted that Ct values of these groups were in close relation to the dilution factor required to achieve the 50 ng of extracted small RNA for RT-qPCR experiments ( S3 Table ). More precisely, the first group presented small dilution factors (7x and 9x), the second group intermediate (25x and 23x, followed by P7 with 26.5x) and the third group highest (ranging from 30x to 42x, with the exception of the P3). Altogether, we observed that participants had higher variability (mean delta variability of 0.19) compared to sampling points for all the miRNA assays ( S8 Fig ). (A) Average Ct values of the four sampling points through which the six miRNAs were assessed on 10 participants. Expression profiles of the six analysed miRNAs across (B) time and (C) different participants. All analysis was perform with 50 ng of total extracted small RNA. All values represent the mean value and the error bars show the standard error of the mean. To fully evaluate the effect of the dilution factors on miRNA detection signals, we next performed dose dependent response experiments on three samples (P2, P6, P7). The six miRNA assays were performed using different extracted small RNA input concentrations for RT-qPCR, ranging from 1 ng up to 300 ng. Results demonstrated linear behaviour for all the six miRNAs for three participants ( S9 Fig ). However, while participants P2 and P7 showed high correlations coefficients (R 2 >0.99, except for hsa-Let-7f-5p in P7), participant P6 had lower coefficients, ranging from 0.94 to 0.99. Particularly, at the highest concentration (300ng), Ct values were lower than predicted by the linear fit ( S9B Fig ). Similarly, although the six tested qPCR assays had comparable efficiencies, overall higher efficiencies were observed for participants P2 and P7 compared to participant P6 ( S10 Fig ). Nevertheless, when averaging the three participants, we observed that the miRNA expression profile was conserved throughout the tested concentration range (from 1 ng up to 300 ng of extracted small RNA) ( S9D Fig ). Indeed, the detection of both UniSP6 ( S4 Fig ) and the six miRNA targets ( S11 Fig ) detected linearly at different working dilutions. To determine to what extent the variability observed in endogenous salivary miRNA quantification was associated to biological factors, we investigated the reliability of the assessed assays. To this aim, we investigated the sensitivity and specificity of the six miRNA assays using their corresponding synthetic targets. The limit of detection (LOD) for each miRNA assay was determined by signals obtained at the lowest target concentration in a serial dilution of concentration ranging from 1 to 10 12 copies/μL ( Fig 3A ). Results demonstrated very high sensitivities, allowing to detect down to at least 1 copies/μL of miRNA target from their negative controls (No detection or Ct Value = 35). However, we noted that under a given concentration, the detection signals was no longer linear, and hence we defined it as the limit of quantification (LOQ). The LOQ concentrations for hsa-Let-7a-5p, hsa-miR-148a-3p, hsa-miR26b-5p and hsa-miR-107 assays were higher (10 5 copies/μL) compared to that of hsa-Let-7f-5p and hsa-miR-103a-3p assays, which decreased down to 10 4 and 10 2 copies/μL, respectively. Calculation of the RT-qPCR efficiencies between the LOQ and the Ct saturation point ( i . e . Ct value = 5) revealed high efficiencies for all miRNA assays, ranging from 98.5 and 112.5% ( S12 and S13 Figs), which fall within reasonable limits for PCR exponential amplification. ( A ) Serial dilution from 1 to 10 12 copies/μL with synthetic miRNA target for each miRNA assay to determine their limit of detection (LOD) and their limit of quantification (LOQ). Values represent the mean value and the error bars depict the standard error of the mean. Cross reactions between miRNA assays and synthetic targets at ( B ) 10 9 copies/μL and ( C ) 10 5 copies/μL. ΔCt values are calculate from S14 Fig . Empty spaces represent no crosstalk (no detection or Ct Value = 35). Data obtained from a duplicate experiment. ΔCt values = CtOFF target–Ct ON target . Due to the short size, and hence high sequence similarity [ 15 ], miRNA detection is prone to crosstalk. To undercover the potential crosstalk among assays and targets used in this study, we compared the detection signal of each assay reporting on its corresponding miRNA target (ON target) to that of the detection on the other targets (OFF target) of the panel. ΔCt values were calculated between the Ct value of the OFF target and the ON target as indicator of their cross-reactivity (crosstalk). Firstly, we assessed the crosstalk of the six miRNA assays at a single concentration of 10 9 copies/μL, which corresponds to the middle of the quantification zone (Figs 3B & S14A ). Out of the 30 possible crosstalk combinations, only 12 of them showed no crosstalk (No detection or Ct Value = 35) while the rest (60%) presented significant crosstalk. The most striking crosstalk was observed between hsa-miR-107 and hsa-miR-103a-3p assays with respective ΔCt of 0.21 and 0.84, making their discrimination impossible. In the same line, it is very unlikely to discriminate hsa-Let7a-5p from hsa-Let7f-5p as these assays also presented high crosstalk, exhibiting ΔCt values of 3.9 and 8.7, respectively. The rest of crosstalk combinations presented variable ΔCt, ranging from 6.5 up to 25.4. We next assessed crosstalk contribution at 10 5 copies/μL, which corresponds to the LOQ concentration for four out of the six miRNA assays. At this concentration, although the number of crosstalk reduced down to 40%, most of the retained OFF targets drastically increased their significance (the average ΔCt decreased from 13.14 down to 3.6) (Figs 3C and S14B ). As for the two pairs: hsa-miR-107 vs hsa-miR-103a-3p, and hsa-Let7a-5p vs hsa-Let7f-5p, their maximal crosstalk at 10 9 copies/μL remains unchanged when concentration was lowered to 10 5 copies/μL. Secondly, we assessed the crosstalk between the hsa-Let7a-5p and hsa-Let7f-5p assays throughout the whole dilution range (from 0.1 to 10 12 copies/μL). As shown in Fig 4 , throughout the whole dilution range, crosstalk between these two assays remained generally stable with an average ΔCt value of 3.78 ± 0.27 for hsa-Let7a-5p ( Fig 4A , red circle) and 10.29 ± 0.32 for hsa-Let7f-5p ( Fig 4B , red circle). However, we noticed erratic responses associated with higher error values when the concentration of the OFF target was lower or at the transition to the LOQ. Re-calculation of the average ΔCt within the LOQ zone didn’t considerably change, being 3.93 ± 0.34 for hsa-Let7a-5p and 10.02 ± 0.36 and for hsa-Let7f-5p. ΔCt values obtained when comparing a serial dilution from 10 −1 to 10 12 copies/μL of the corresponding synthetic miRNA (ON target) with its cross reaction (OFF target, red circles) for ( A ) hsa-Let-7a-5p assay and ( B ) hsa-Let-7f-5p assay. The ΔCt by the addition of 10 7 copies/μL of OFF target on the serial dilution of ON target was also calculated (blue triangles). Red circles = Ct OFF target –Ct ON target , blue triangles = Ct ON target + OFF target at 10^7 copies/μL –Ct ON target . All values represent the mean value and the error bars show the standard error of the mean (two independent experiments). Grey region delimits the quantification region. Lastly, we evaluated the influence of the OFF target at a LOQ concentration (10 7 copies/μL) on the LOD of each assay. To do so, we compared the detection signals of the ON target throughout the whole serial dilution in the absence and presence (spike-in) of 10 7 copies/μL of the OFF target ( Fig 4 , blue triangle). Obtained results revealed that, for both hsa-Let-7a-5p and hsa-Let-7f-5p assays, the detection of the ON target was not affected by the presence of 10 7 copies/μL of the OFF target. However, for the hsa-Let7a-5p assay, the greatest crosstalk influence of the OFF target was observed at 10 6 copies/μL of the ON target (1 log difference), and a partial crosstalk at its adjacent concentrations ( i . e . 10 5 and 10 7 copies/μL). Similarly, for hsa-Let7f-5p assay, the greatest crosstalk contribution was observed at 10 4 copies/μL of the ON target (3 log difference), showing a greater resilience compared to the hsa-Let7a-5p assay. These results are in agreement with the average ΔCt value of 3.9 (~ 1 log) and 10.0 (~ 3 logs) for the OFF target of the hsa-Let7a-5p and hsa-Let7f-5p assays, respectively. Based on the quantification zone (LOQ) identified for each assay ( S12 Fig ), we reconsidered the term “good range of detection” stated previously in Fig 2 for the six miRNA assays. Indeed, upon taking into consideration of the LOQ ( S12 Fig ), we observed that out of the 240 quantified samples (10 participants x 4 samplings x 6 miRNA assays), only 29% of them were quantified in their respective LOQ zones. Consequently, up to 42% of these samples, which included all analysis for hsa-miR-107 assay, were obtained outside the quantification zone, and the remaining samples were analysed at the LOQ (particularly for hsa-Let7a-5p and hsa-miR-148a-3p). In particular, of the 29% obtained Ct values obtained within the linear quantification zone, all 40 analysis of the hsa-miR103 assay was included (as a result of its lower LOQ). These results indicated that endogenous salivary hsa-miR103-3p was present at concentrations between 3.8x10 3 and 5.4x10 4 copies/μL, and that only participant P6 showed partial significant differences with respect to the other participants ( S7B Fig ). Given the high Ct values obtained for endogenous salivary hsa-Let7a-5p analysis, we decided to spike-in the synthetic hsa-Let7a-5p to surpass the LOQ concentration in order to acquire detection signal in the LOQ zone. Four different concentrations including two that were significantly under the LOQ (10 −1 copies/μL and 10 2 copies/μL), one at the LOQ (10 5 copies/μL) and the last one at 10-fold higher than the LOQ (10 6 copies/μL) were respectively spiked in the 50 ng endogenous samples. We first compared signals of the endogenous spiked-in samples with that of their respective endogenous samples alone ( Fig 5A ). Obtained results show a “so-called” dose dependent response in all analysed samples, since the higher the concentration of spiked-in synthetic miRNA, the stronger the detection signal (lower Ct value hence higher ΔCt) (Figs 5A & S15 ). However, not all samples responded similarly to the different concentrations of spiked-in synthetic miRNA, where some presented only partial dose dependency. In particular, samples P1 and P3 had no signal alteration for spike-in concentrations below 10 5 copies/μL, while at higher spiked-in concentrations smaller alterations were observed (Average ΔCt = 1.81 ± 0.26) compared to other samples (average ΔCt = 3.5 ± 0.24). However, when we compared these signals with that of their respective synthetic samples alone ( Fig 5B ), an opposite scenario was observed. Overall, the presence of synthetic miRNA at lower concentrations induced more alterations in signal detection in all samples whilst very high concentration negatively affected the detection of endogenous miRNA (negative ΔCt). On the contrary, synthetic spiked-in miRNA at 10 6 copies/μL concentration decreased significantly the detection signal in all samples. In particular, P1 and P3 samples appeared to be those whose detection signals were the most altered displaying the most increase at the lowest concentration (average ΔCt = 3.22 ± 0.178, compared to 1.63 ± 0.38) and the least decrease (average ΔCt = -0.54 ± 0.027 compared to -1.04 ± 0.156) at the highest concentration. Moreover, the negative effect of high concentration of spiked-in synthetic miRNA was observed only from 10 6 copies/μL for these two samples, while for the remaining participants, this effect was observed at 10 5 copies/μL, allowing to discern the samples that are close to the LOQ from those that are significantly lower (semi-quantification). ( A ) ΔCt values of spike-in synthetic hsa-Let-7a-5p miRNA in 50 ng RNA extract with respect to the RNA extract alone in a range of spike-in concentrations. ΔCt were calculated as CtEndogenous—Ct Endogenous + synthetic . ( B ) ΔCt values of spike-in synthetic hsa-Let-7a-5p miRNA in 50 ng RNA extract with respect to the respective synthetic miRNA sample alone. ΔCt were calculated as Ctsynthetic—Ct endogenous + synthetic . Data determined from S15 Fig .

In this work we have shown that a commercially available RT-qPCR kit shows significant variabilities in expression profiles of the six salivary miRNA targets among the ten healthy participants. However, we demonstrate that the majority of these differences are associated to technical limitations rather than the biological contexts. Our data demonstrated that assessing the technical limitations of the kit coupled with a rigorous experimental design is crucial for interpreting biological relevance using RT-qPCR data. Regarding the high potential application of salivary miRNA in medical diagnosis, further technological breakthroughs for reliable tests are still required to overcome data inconsistencies and study dependent results.

Ten healthy males with ages ranging from 18 to 40 were recruited in the Sys2diag laboratory based in Montpellier, France, according to the personal protection committee (CPP) with registered number 23.00930.000169 ( NCT06149351 on www.clinicaltrials.gov ). All subjects were informed, signed and consented in accordance with the CPP prior to the recruitment. Saliva collection and analyses were performed with approved protocols. Participants were asked to refrain from eating, drinking or smoking for at least 30 min prior to saliva collection. During the 3 months of the study, a total of four collections (one collection every 2–3 weeks) were performed at the same time of the day. Approximately 2 mL of unstimulated saliva was collected from each participant and stored at 4°C for a maximum of 2 hours prior small RNA extraction. The appearance of each individual saliva was visually inspected while its viscosity was estimated via its flow resistance using a combitip®. Total small RNA was extracted from 250 μL of whole saliva using miRNeasy Serum/Plasma Kit (Qiagen) according to the manufacture instructions (except for the elution step, where the extracted salivary small RNA was collected in 20 μL nuclease free water). In brief, 250 μL of whole saliva from each participant was homogenized in 1 mL of Qiazol solution, and was followed by the addition of 5.6 x 10 8 copies of UniSP6 miRNA as a technical control for the extraction process, unless mentioned otherwise. Chloroform purification was followed by RNA precipitation by isopropanol, which was then loaded into a miRNeasy column, where only small RNA fragments (<200 bp fragments) are retained following multiple washes. All samples were handled and processed by the same manner with an equally respected delay between sampling and extraction time. Total small RNA concentration was quantified by Nanodrop One (Thermo Scientific, Wilmington USA). Small fragments of eluted RNA was confirmed by Labchip using small RNA assay (PerkinElmer), which are similar to those extracted by conventional trizol-based RNA precipitation method ( S1 Fig ). Six miRNAs, including hsa-Let7a-5p, hsa-Let7f-5p, hsa-miR-148a-3p, hsa-miR-26b-5p, hsa-miR-107 and hsa-miR-103a-3p, were selected according to their sequence similarity and clinical relevance. All the six synthetic miRNAs were purchased from Integrated DNA technologies (IDT, Europe). All sequences and annotations are available in the supplementary data section ( S1 Table ). miRCURY LNA RT Kit employing poly (A) polymerase for tailing RNA prior to an universal reverse transcription (RT) using poly T primer was purchased from Qiagen. 10 μL RT reactions were prepared in 96 well plates containing 2 μL of 5X reaction buffer, 1 μL 10X reverse transcriptase and 1 μL of synthetic or extracted small RNA at desired concentrations. The reactions were incubated in a peqSTAR 96X thermocycler (Ozyme, Montigny-le-Bretonneux France) at 42°C for 60 min, followed by a denaturation step at 85°C for 5 min and stored at -20°C until used. No template and no reverse transcriptase enzyme negative controls were included in each run. UniSp6 miRNA was included when needed as plate calibrator. All samples and control conditions were run in duplicate. For the analysis using 50 ng of extracted small RNA as input, all extracted samples were normalized to 50 ng/μL and then 1 μL was added to the RT-qPCR reaction, except for P5 and P6 samples whose concentration were inferior to 50 ng/μL, and hence higher volumes were required. miRCURY LNA SYBR Green PCR Kit and target specific primers (miRCURY LNA miRNA PCR assays) were purchased from Qiagen. 10 μl qPCR reactions were prepared in 384 multi-well plates containing 5 μL of qPCR master mix; 1 μL of corresponding primers (miRCURYLNA miRNA PCR Assay) and 3 μL of 10X diluted RT product. QPCR negative controls (No-template reactions) were included for each assay. All samples and control conditions were run in duplicate. Real-time qPCR thermal cycling reactions were performed by the LightCycler 480 (Roche, Meylan France) directed by the LightCycler 480 Software (version 1.5.1.62). Thermal cycling conditions were: Pre-incubation for 2 minutes at 95°C, 40 cycles of amplification (95°C for 10s, 56°C for 60s). Ct values were analysed by Abs Quant/2nd Derivative Max of the same software. Ct values of UniSP6 was verified prior to all analysis when plate calibrator was needed. All Ct value at 35 was considered as noise. Scipy version 1.11.2 was used on python 3.10.4 to do statistical analysis. All statistical test were done using Mann-Whitney U (scipy.stats.mannwhitneyu) with asymptotic method ( i . e . p-value calculated by comparing to normal distribution and hence correcting for ties). All statistical calculations show the mean values ± standard error of the mean.

(A) Distribution of the total extracted small RNA concentrations among 10 participants throughout four sampling points. Black points represent the mean value and error bars show the standard error of the mean. (B) Mann-Whitney U results of statistical tests performed on panel A. (C) Gel and (D) electropherogram Labchip data show similar small RNA profiles by two different extraction methods, RNA precipitation or filter column (used in this study). (TIF) (TIF) (A) RT-qPCR quantification values of spike-in UniSP6 miRNA using 50 ng of the total extracted salivary small RNAs for the different sampling points. Points represent the mean value and error bars depict the standard error of the mean. (B) Mann-Whitney U results performed on panel A. (TIF) All samples were analysed in two conditions: Using 1μL (circle) or 50 ng (cross) of the total extracted small RNAs as input. Since the same concentration of UniSp6 miRNA is present at 1 μL for all participants, all 50 ng values have been normalized with respect to the RNA concentration at 1 μL (dilution factor), and all Ct values have been shifted with respect to the 1 μL value (causing the overlapping of all 1 μL values). ΔCt values = Ct 50ng –Ct 1μL . (TIF) Small RNAs were extracted from three saliva samples (P2, P6 and P7) in the presence and absence of spiked-in artificial UniSP6 miRNA. (A) RT-qPCR quantification for the six miRNAs using 50 ng of small RNAs. Mann-Whitney U results for panel A of ΔCt between with and without spiking with respect to (B) individual participants and (C) miRNA assay. (TIF) Mann-Whitney U results for data presented in Fig 2B of the manuscript showing differences within (A) samplings for each miRNA assay and (B) within miRNA assays. (TIF) Statistical analysis for data in Fig 2C showing statistical differences within participants (A) when averaging the six miRNAs and (B) within hsa-miR-103a-3p. We note that in panel A, participant P7 and participant P10 do not clearly belong to a group but rather are adjacent to a group, sharing partial significance. (TIF) (TIF) Ct values for participant P2 (A) , P6 (B) and P7 (C). (D) Average Ct values of the 3 participants with respect to the miRNA assay at different concentrations of total extracted small RNA. Error bars show the standard error of the mean. (TIF) (A) RT-qPCR efficiencies calculated from the dose dependent data presented in S5 Fig . Mann-Whitney U results for panel A with respect to participants (B) and miRNA assay (C) . (TIF) As for S4 Fig , two inputs concentrations where used, 1μL (circle) or 50 ng (cross). Again, all 50 ng values have been normalized with respect to the RNA concentration at 1 μL (dilution factor) and all Ct values have been shifted with respect to the 1 μL value. Although in this case the miRNA concentration may or not be heterogeneous, a linear behaviour is still obtained because we are observing the linear behaviour on the Ct value (ΔCt) due to the dilution effect (log dilution factor). ΔCt values = Ct 50ng –Ct 1μL . (TIF) Individual plots for data shown in Fig 3A of the manuscript, demonstrating high sensitivity (LOD of 1 copy/μL) for all six assays. Regression line calculated within LOQ and Ct saturation point ( i . e . Ct value = 5). Points represent the mean value and error bars depict the standard error of the mean. The grey region delimits the quantification region. (TIF) Data from S12 Fig was used to calculate efficiencies. (TIF) Cross detections among miRNA assays when using (A) 10 9 copies/μL and (B) 10 5 copies/μL of synthetic targets. The absence of circles indicate no detection or Ct values = 35. This data was used to calculate the ΔCt values in Fig 4B & 4C of the manuscript. (TIF) Data used to calculate the ΔCt values in Fig 5 of the manuscript. (TIF) Sequence homology calculated by (A) number of homologous nucleotides and (B) percentage homology. (TIF) Two similar pairs of miRNAs were included in this study, where they only differentiated by a single nucleotide (red font for the first pair and blue for the second pair). (DOCX) (DOCX) (DOCX) (DOCX) (XLSX)