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Background: Noninvasive biomarkers for the detection and monitoring of glioblastoma (GBM) are needed to improve clinical outcomes for patients. The objective of this pilot study was to evaluate the expression of a panel of 48 pre-selected microRNAs (miRNAs) in plasma specimens from GBM patients versus healthy controls to identify candidate miRNA biomarkers for noninvasive diagnosis of GBM. Methods: Selection of candidate miRNA biomarkers was based on a comprehensive literature review and data mining. RNA was extracted from plasma samples obtained prior to resection from patients with GBM (n = 30) and age- and sex-matched healthy controls (n = 30), as well as from matched FFPE GBM tissue samples when available (n = 3). Expression levels of 48 miRNAs were assessed in all samples, and expression data was processed using proprietary software to generate potential biomarkers and train linear classifiers. Results: Overall miRNA expression patterns were similar between matched plasma and FFPE tumor tissues in patients with GBM. miRNA levels were examined in pairs to determine the ratio between two miRNAs, which served to normalize the data. The top five miRNA pairs for distinguishing between GBM and healthy control plasma included miR-17-5p/miR-19b-3p (AUC 0.93, 95% CI = 0.870, 0.970), miR-20a-5p/miR-19b-3p (AUC 0.93, 95% CI = 0.870, 0.970), miR-93-5p/miR-92a-3p (AUC 0.92, 95% CI = 0.875, 0.965), miR-17-5p/miR-92a-3p (AUC 0.91, 95% CI = 0.865, 0.955), and miR-93-5p/miR-19b-3p (AUC 0.90, 95% CI = 0.850, 0.950). For the development of a multi-biomarker combination classifier consisting of up to three miRNA pair biomarkers, miRNA pairs with an AUC ≥ 0.8 were selected to build equal-weight linear classifiers. All possible combinations of three high-performing miRNA pairs were tested across the 60 samples. The top classifier (miR-20a-5p/miR-451a, miR-582-5p/miR-222-3p, and miR-17-5p/miR-222-3p) achieved an AUC value of 0.992, sensitivity of 0.93, specificity of 1, and accuracy of 0.97. Conclusions: These findings support the continued development of a plasma-based miRNA molecular diagnostic approach for the detection of GBM. The strong discriminatory performance observed in this study, including high AUC values, highlights the potential of circulating miRNA signatures as a minimally invasive diagnostic tool. As a pilot analysis, this work establishes a foundation for future prospective studies in larger, independent cohorts—including relevant disease control populations—to further define clinical performance, specificity, and utility in diagnostic and monitoring settings. Collectively, these results represent an important step toward the translation of plasma-based miRNA profiling into clinical application for GBM.

We have been developing a novel approach to identify cognitive impairment-related biomarkers by profiling brain-enriched and inflammation-associated microRNA (miRNA) in plasma specimens of cognitively unimpaired and cognitively impaired patients. Here, we present an analytical validation of the novel miRNA panel, CogniMIR®, using two competing quantitative PCR technologies for the expression analysis of 24 target miRNAs. Total RNA from the plasma specimens was isolated using the MagMAX mirVana Kit, and RT-qPCR was performed using stem-loop-based TaqMan and LNA-based qPCR assays. Evaluation of RNA dilution series for our target 24 miRNAs, performed by two operators on two different days, demonstrated that all CogniMIR® panel miRNAs can be reliably and consistently detected by both qPCR technologies, with sample input as low as 20 copies in a qPCR reaction. Intra-run and inter-run repeatability and reproducibility analyses using RNA specimens demonstrated that both operators generated repeatable and consistent Cts, with R2 values of 0.94 to 0.99 and 0.96 to 0.97, respectively. The study results clearly indicate the suitability of miRNA profiling of plasma specimens using either of the qPCR technologies. However, the LNA-based qPCR technology appears to be more operationally friendly and better suited for a CAP/CLIA-certified clinical laboratory.

Rett syndrome (RTT) is a severe neurodevelopmental disorder caused by mutations in the X-linked gene MECP2 (methyl-CpG-binding protein 2). Minimally invasive and accurate biomarkers of disease progression and treatment response could facilitate screening of therapeutic compounds in animal models, enrollment of better-defined participants into clinical trials, and treatment monitoring. In this study, we used a targeted approach based on analysis of brain-enriched microRNAs (miRNAs) circulating in plasma to identify miRNA biomarkers of RTT using Mecp2-mutant mice as a model system and human plasma samples. An “miRNA pair” approach, i.e. the ratio between two miRNAs, was used for data normalization. Specific miRNA pairs and their combinations (classifiers) analyzed in plasma differentiated wild-type from Mecp2 male and female mice with >90% accuracy. Individual miRNA pairs were more effective in distinguishing male (homozygous) animals than female (heterozygous) animals, suggesting that disease severity correlated with the levels of the miRNA biomarkers. In the human study, 30 RTT patients were compared with age-matched controls. The results of this study showed that miRNA classifiers were able to differentiate RTT patients from controls with 85–100% sensitivity. In addition, a comparison of various age groups demonstrated that the dynamics in levels of miRNAs appear to be associated with disease development (involvement of liver, muscle and lipid metabolism in the pathology). Importantly, certain miRNA biomarker pairs were common to both the animal models and human subjects, indicating the similarity between the underlying pathological processes. The data generated in this feasibility study suggest that circulating miRNAs have the potential to be developed as markers of RTT progression and treatment response. Larger clinical studies are needed to further evaluate the findings presented here.

Although there are numerous hypotheses explaining the nature of aging and associated processes, two concepts are dominant: (i) aging is a result of cell-autonomous processes, such as the accumulation of DNA mutations, aberrant methylations, protein defects, and shortening of telomeres, leading to either inhibition of cellular proliferation and death of non-dividing terminally differentiated cells or tumor development; (ii) aging is a result of a central program that is switched on at a specific stage of organismic development. The microRNA-based endocrine regulation hypothesis combines the two above concepts by proposing central regulation of cell death occurrences via hypothalamus-pituitary gland (PG)-secreted miRNA hormones, the expression and/or secretion of which are regulated by sex hormones. This hypothesis explains such well-known phenomena as inverse comorbidity of either cancer or Alzheimer’s (AD) and other neurodegenerative diseases; higher AD morbidity and lower frequency of many common types of cancer in women vs. men; higher risk of early AD and lower risk of cancer in subjects with Down syndrome; longer life expectancy in women vs. men and much lower sex-dependent differences, if any, in other mammals; increased lifespans due to hypophysectomy or PG hypofunction; and parabiotic effects of blood or plasma transfusions between young and old animals.

Aging is a major risk factor for many common and life-threatening pathologies. The development of reliable biomarkers of aging should lead to a better understanding of aging-associated processes and facilitate the development of therapeutic regimens that delay aging. Levels of 38 brain-enriched microRNAs (miRNA) circulating in plasma were measured by quantitative RT-PCR in two age groups: 26-35 and 56-65 years old. An miRNA-pair approach was used for data normalization and determination of effective miRNA biomarker ratios. Nineteen miRNAs, comprising miRNA pairs and pair combinations (classifiers) that effectively differentiated the age and sex (individual pairs: 74-95% and 68-95%, respectively; classifiers: up to 100% accuracy) groups, were selected for further analysis of plasma samples from 5 donor age groups: 26-35, 36-45, 46-55, 56-65 and 66-75 years old. Dynamic changes in the plasma concentrations of certain miRNAs occurred at different ages in females and males, with peaks in the 46-55-year-old and 56-65-year-old groups, respectively. This finding suggests that the changes in miRNA levels can reflect centrally regulated processes, including changes in hormone levels during menopause. Certain miRNAs and miRNA pairs correlated with age in the sex-stratified groups at different ages and should be investigated further as potentially promising biomarkers of brain aging.

Background: Minimally invasive specific biomarkers of neurodegenerative diseases (NDs) would facilitate patient selection and disease progression monitoring. We describe the assessment of circulating brain-enriched microRNAs as potential biomarkers for Alzheimer’s disease (AD), frontotemporal dementia (FTD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS).
Methods: In this case-control study, the plasma samples were collected from 250 research participants with a clinical diagnosis of AD, FTD, PD, and ALS, as well as from age- and sex-matched control subjects (n = 50 for each group), recruited from 2003 to 2015 at the University of Pennsylvania Health System, including the Alzheimer’s Disease Center, the Parkinson’s Disease and Movement Disorders Center, the Frontotemporal Degeneration Center, and the Amyotrophic Lateral Sclerosis Clinic. Each group was randomly divided into training and confirmation sets of equal size. To evaluate the potential of circulating microRNAs enriched in specific brain regions affected by NDs and present in synapses as biomarkers of NDs, the levels of 37 brain-enriched and inflammation-associated microRNAs in the plasma of all participants were measured using individual qRT-PCR. A “microRNA pair” approach was used for data normalization.
Results: MicroRNA pairs and their combinations (classifiers) capable of differentiating NDs from control and from each other were defined using independently and jointly analyzed training and confirmation datasets. AD, PD, FTD, and ALS are differentiated from control with accuracy of 0.89, 0.90, 0.88, and 0.83 (AUCs, 0.96, 0.96, 0.94, and 0.93), respectively; NDs are differentiated from each other with accuracy ranging from 0.77 (AUC, 0.87) for AD vs. FTD to 0.93 (AUC, 0.98) for AD vs. ALS. The data further indicate sex dependence of some microRNA markers. The average increase in accuracy in distinguishing ND from control for all and male/female groups is 0.06; the largest increase is for ALS, from 0.83 for all participants to 0.92/0.98 for male/female participants.
Conclusions: The work presented here suggests the possibility of developing microRNA-based diagnostics for detection and differentiation of NDs. Larger multicenter clinical studies are needed to further evaluate circulating brain-enriched microRNAs as biomarkers for NDs and to investigate their association with other ND biomarkers in clinical trial settings.

Early disease detection leads to more effective and cost-efficient treatment. It is especially important for cancer and neurodegenerative diseases, because progression of these pathologies leads to significant and frequently irreversible changes in underlying pathophysiological processes. At the same time, the development of specific screening tests for detection of each of the hundreds of human pathologies in asymptomatic stage may be impractical. Here, we discuss a recently proposed concept: the development of minimally invasive Universal Screening Test (UST) based on analysis of organ-enriched microRNAs in plasma and other bodily fluids. The UST is designed to detect the presence of a pathology in particular organ systems, organs, tissues or cell types without diagnosing a specific disease. Once the pathology is detected, more specific, and if necessary invasive and expensive, tests can be administered to precisely define the nature of the disease. Here, we discuss recent studies and analyze the data supporting the UST approach.

Background: Early disease detection with a minimally invasive screening test will significantly increase effectiveness and decrease the cost of treatment. Here we propose a framework of a novel approach – Universal Screening Test (UST) for the detection of pathological processes in a particular organ system, organ, or tissue by RT-qPCR analysis of circulating cell-free miRNAs in plasma. As the first step towards assessing the feasibility of this concept, the present study was designed to analyze whether the same microRNAs (miRNAs) can detect various diseases of a particular organ system.
Methods: RNA was extracted from plasma using Trizol treatment and silica binding. Levels of miRNAs were measured by single target RT-qPCR. The following innovations have been tested and proven effective: (i) the use of organ system/organ/tissue-enriched miRNAs; (ii) the use of miRNAs associated with broad disease categories, such as cancer and inflammation, in combination with the organ-enriched miRNAs; and (iii) the use of “miRNA pairs” for selecting miRNA combinations with the highest sensitivity and specificity.
Results: Here we report biomarker miRNA pairs effectively differentiating (i) patients with pulmonary system diseases (asthma, pneumonia and non-small cell lung cancer) and gastrointestinal (GI) system diseases (Crohn’s disease, stages I/II esophageal, gastric and colon cancers) from controls, each with 95% accuracy; (ii) patients with a pathology of the pulmonary system from patients with a pathology of the GI system with 94% accuracy; and (iii) cancer patients (stages I/II esophageal, gastric, colon cancers, or non-small cell lung cancer) from patients with inflammatory diseases (asthma, pneumonia, or Crohn’s disease) with 93%-95% accuracy.
Conclusions: The results obtained in the present study, along with the data reported by us and others previously, are encouraging and lay the ground for further investigation of the described approach for UST development.

A minimally invasive test for early detection and monitoring of Alzheimer’s and other neurodegenerative diseases is a highly unmet need for drug development and planning of patient care. Mild Cognitive Impairment (MCI) is a syndrome characteristic of early stages of many neurodegenerative diseases. Recently, we have identified two sets of circulating brain-enriched miRNAs, the miR-132 family (miR-128, miR-132, miR-874) normalized per miR-491-5p and the miR-134 family (miR-134, miR-323-3p, miR-382) normalized per miR-370, capable of differentiating MCI from age-matched control (AMC) with high accuracy. Here we report a biomarker validation study of the identified miRNA pairs using larger independent sets of age- and gender- matched plasma samples. The biomarker pairs detected MCI with sensitivity, specificity and overall accuracy similar to those obtained in the first study. The miR-132 family biomarkers differentiated MCI from AMC with 84%-94% sensitivity and 96%-98% specificity, and the miR-134 family biomarkers demonstrated 74%-88% sensitivity and 80-92% specificity. When miRNAs of the same family were combined, miR-132 and miR-134 family biomarkers demonstrated 96% and 87% overall accuracy, respectively. No statistically significant differences in the biomarker concentrations in samples obtained from male and female subjects were observed for either MCI or AMC. The present study also demonstrated that the highest sensitivity and specificity are achieved with pairs of miRNAs whose concentrations in plasma are highly correlated.

Many neurodegenerative diseases, such as Alzheimer’s disease, Parkinson disease, vascular and frontotemporal dementias, as well as other chronic neurological pathologies, are characterized by slow development with a long asymptomatic period followed by a stage with mild clinical symptoms. As a consequence, these serious pathologies are diagnosed late in the course of a disease, when massive death of neurons has already occurred and effective therapeutic intervention is problematic. Thus, the development of screening tests capable of detecting neurodegenerative diseases during early, preferably asymptomatic, stages is a high unmet need. Since such tests are to be used for screening of large populations, they should be non-invasive and relatively inexpensive. Further, while subjects identified by screening tests can be further tested with more invasive and expensive methods, e.g., analysis of cerebrospinal fluid or imaging techniques, to be of practical utility screening tests should have high sensitivity and specificity. In this review, we discuss advantages and disadvantages of various approaches to developing screening tests based on analysis of circulating cell-free microRNA (miRNA). Applications of circulating miRNA-based tests for diagnosis of acute and chronic brain pathologies, for research of normal brain aging, and for disease and treatment monitoring are also discussed.

Comment on: Sheinerman KS, Tsivinsky VG, Crawford F, Mullan MJ, Abdullah L, Umansky SR. Plasma microRNA biomarkers for detection of mild cognitive impairment. Aging (Albany NY). 2012; 4:590-605.

Comment on: Sheinerman KS, Tsivinsky VG, Crawford F, Mullan MJ, Abdullah L, Umansky SR. Plasma microRNA biomarkers for detection of mild cognitive impairment. Aging (Albany NY). 2012; 4:590-605.

Early stages of many neurodegenerative diseases, such as Alzheimer’s disease, vascular and frontotemporal dementia, and Parkinson’s disease, are frequently associated with Mild Cognitive Impairment (MCI). A minimally invasive screening test for early detection of MCI may be used to select optimal patient groups in clinical trials, to monitor disease progression and response to treatment, and to better plan patient clinical care. Here, we examined the feasibility of using pairs of brain‐enriched plasma microRNA (miRNA), at least one of which is enriched in synapses and neurites, as biomarkers that could differentiate patients with MCI from age‐matched controls. The identified biomarker pairs fall into two sets: the “miR‐132 family” (miR‐128/miR‐491‐5p, miR‐132/miR‐491‐5p and mir‐874/miR‐491‐5p) and the “miR‐134 family” (miR‐134/miR‐370, miR‐323‐3p/miR‐370 and miR‐382/miR‐370). The area under the Receiver‐Operating Characteristic curve for the differentiation of MCI from controls using these biomarker pairs is 0.91‐0.95, with sensitivity and specificity at 79%‐100% (miR‐132 family) and 79%‐95% (miR‐134 family), and p < 0.001. In a separate longitudinal study, the identified miRNA biomarker pairs successfully detected MCI in majority of patients at asymptomatic stage 1‐5 years prior to clinical diagnosis. The reported biomarker pairs also appear useful for detecting age‐related brain changes. Further testing in a larger study is necessary for validation of these results.