Validating Alzheimer's disease micro RNAs using next‐generation sequencing

Transcriptome Analysis Identifies Oncogenic Tissue Remodeling during Progression from Common Nevi to Early Melanoma

Early detection and treatment of melanoma, the most aggressive skin cancer, improves the median 5-year survival rate of patients from 25% to 99%. Melanoma development involves a stepwise process during which genetic changes drive histologic alterations within nevi and surrounding tissue. Herein, a comprehensive analysis of publicly available gene expression data sets of melanoma, common or congenital nevi (CN), and dysplastic nevi (DN), assessed molecular and genetic pathways leading to early melanoma. The results demonstrate several pathways reflective of ongoing local structural tissue remodeling activity likely involved during the transition from benign to early-stage melanoma. These processes include the gene expression of cancer-associated fibroblasts, collagens, extracellular matrix, and integrins, which assist early melanoma development and the immune surveillance that plays a substantial role at this early stage. Furthermore, genes up-regulated in DN were also overexpressed in melanoma tissue, supporting the notion that DN may serve as a transitional phase toward oncogenesis. CN collected from healthy individuals exhibited different gene signatures compared with histologically benign nevi tissue located adjacent to melanoma (adjacent nevi). Finally, the expression profile of microdissected adjacent nevi tissue was more similar to melanoma compared with CN, revealing the melanoma influence on this annexed tissue.

GeneSelectML: a comprehensive way of gene selection for RNA-Seq data via machine learning algorithms

Selection of differentially expressed genes (DEGs) is a vital process to discover the causes of diseases. It has been shown that modelling of genomics data by considering relation among genes increases the predictive performance of methods compared to univariate analysis. However, there exist serious differences among most studies analyzing the same dataset for the reasons arising from the methods. Therefore, there is a strong need for easily accessible, user-friendly, and interactive tool to perform gene selection for RNA-seq data via machine learning algorithms simultaneously not to miss DEGs. We develop an open-source and freely available web-based tool for gene selection via machine learning algorithms that can deal with high performance computation. This tool includes six machine learning algorithms having different aspects. Moreover, the tool involves classical pre-processing steps; filtering, normalization, transformation, and univariate analysis. It also offers well-arranged graphical approaches; network plot, heatmap, venn diagram, and box-and-whisker plot. Gene ontology analysis is provided for both mRNA and miRNA DEGs. The implementation is carried out on Alzheimer RNA-seq data to demonstrate the use of this web-based tool. Eleven genes are suggested by at least two out of six methods. One of these genes, hsa-miR-148a-3p, might be considered as a new biomarker for Alzheimer's disease diagnosis. Kidney Chromophobe dataset is also analyzed to demonstrate the validity of GeneSelectML web tool on a different dataset. GeneSelectML is distinguished in that it simultaneously uses different machine learning algorithms for gene selection and can perform pre-processing, graphical representation, and gene ontology analyses on the same tool. This tool is freely available at www.softmed.hacettepe.edu.tr/GeneSelectML .

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer's Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ1-42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

Systematic Review: microRNAs as Potential Biomarkers in Mild Cognitive Impairment Diagnosis

The rate of progression from Mild Cognitive Impairment (MCI) to Alzheimer's disease (AD) is estimated at >10% per year, reaching up to 80-90% after 6 years. MCI is considered an indicator of early-stage AD. In this context, the diagnostic screening of MCI is crucial for detecting individuals at high risk of AD before they progress and manifest further severe symptoms. Typically, MCI has been determined using neuropsychological assessment tools such as the Montreal Cognitive Assessment (MoCA) or Mini-Mental Status Examination (MMSE). Unfortunately, other diagnostic methods are not available or are unable to identify MCI in its early stages. Therefore, identifying new biomarkers for MCI diagnosis and prognosis is a significant challenge. In this framework, miRNAs in serum, plasma, and other body fluids have emerged as a promising source of biomarkers for MCI and AD-related cognitive impairments. Interestingly, miRNAs can regulate several signaling pathways via multiple and diverse targets in response to pathophysiological stimuli. This systematic review aims to describe the current state of the art regarding AD-related target genes modulated by differentially expressed miRNAs in peripheral fluids samples in MCI subjects to identify potential miRNA biomarkers in the early stages of AD. We found 30 articles that described five miRNA expression profiles from peripheral fluid in MCI subjects, showing possible candidates for miRNA biomarkers that may be followed up as fluid biomarkers or therapeutic targets of early-stage AD. However, additional research is needed to validate these miRNAs and characterize the precise neuropathological mechanisms.

Prediction of P-tau/Aβ42 in the cerebrospinal fluid with blood microRNAs in Alzheimer's disease

BACKGROUND

The most common biomarkers of Alzheimer's disease (AD) are amyloid β (Aβ) and tau, detected in cerebrospinal fluid (CSF) or with positron emission tomography imaging. However, these procedures are invasive and expensive, which hamper their availability to the general population. Here, we report a panel of microRNAs (miRNAs) in serum that can predict P-tau/Aβ42 in CSF and readily differentiate AD from other dementias, including vascular dementia (VaD), Parkinson disease dementia (PDD), behavioral variant frontotemporal dementia (bvFTD), and dementia with Lewy body (DLB).

METHODS

RNA samples were extracted from the participant's blood. P-tau/Aβ42 of CSF was examined for diagnostic purposes. A pilot study (controls, 21; AD, 23), followed by second (controls, 216; AD, 190) and third groups (controls, 153; AD, 151), is used to establish and verify a predictive model of P-tau/Aβ42 in CSF. The test is then applied to a fourth group of patients with different dementias (controls, 139; AD,155; amnestic mild cognitive impairment [aMCI], 55; VaD, 51; PDD, 53; bvFTD, 53; DLB, 52) to assess its diagnostic capacity.

RESULTS

In the pilot study, 29 upregulated and 31 downregulated miRNAs in the AD group were found. In Dataset 2, these miRNAs were then included as independent variables in the linear regression model. A seven-microRNA panel (miR-139-3p, miR-143-3p, miR-146a-5p, miR-485-5p, miR-10a-5P, miR-26b-5p, and miR-451a-5p) accurately predicted values of P-tau/Aβ42 of CSF. In Datasets 3 and 4, by applying the predicted P-tau/Aβ42, the predictive model successfully differentiates AD from controls and VaD, PDD, bvFTD, and DLB.

CONCLUSIONS

This study suggests that the panel of microRNAs is a promising substitute for traditional measurement of P-tau/Aβ42 in CSF as an effective biomarker of AD.

Histone lysine demethylase 4B regulates general and unique gene expression signatures in hypoxic cancer cells

The hypoxic tumor microenvironment promotes tumor survival by inducing the expression of genes involved in angiogenesis and metastasis. As a direct target of hypoxia-inducible factor, lysine demethylase 4B (KDM4B) is overexpressed in multiple cancers, suggesting that a general KDM4B regulatory mechanism may exist in these cancer types. In this study, we sought to further investigate the general and unique roles of KDM4B in ovarian, colon, and renal cancer cells. We first identified a set of potential KDM4B targets shared by SKOV3ip.1, HCT116, and RCC4 cell lines, as well as numerous genes specifically regulated in each cell line. Through Gene Ontology, KEGG, and Oncobox pathway analyses, we found that KDM4B primarily regulated biosynthetic and cell cycle pathways in normoxia, whereas in hypoxia, it regulated pathways associated with inflammatory response and migration. TCGA data analyses reveal high expression of KDM4B in multiple cancer types and differential expression across cancer stages. Kaplan-Meier plots suggest that elevated KDM4B expression may contribute to a better or worse prognosis in a manner specific to each cancer type. Overall, our findings suggest that KDM4B plays complex roles in regulating multiple cancer processes, providing a useful resource for the future development of cancer therapies that target KDM4B expression.

The promise of microRNA-based therapies in Alzheimer's disease: challenges and perspectives

Multi-pathway approaches for the treatment of complex polygenic disorders are emerging as alternatives to classical monotarget therapies and microRNAs are of particular interest in that regard. MicroRNA research has come a long way from their initial discovery to the cumulative appreciation of their regulatory potential in healthy and diseased brain. However, systematic interrogation of putative therapeutic or toxic effects of microRNAs in (models of) Alzheimer's disease is currently missing and fundamental research findings are yet to be translated into clinical applications. Here, we review the literature to summarize the knowledge on microRNA regulation in Alzheimer's pathophysiology and to critically discuss whether and to what extent these increasing insights can be exploited for the development of microRNA-based therapeutics in the clinic.

miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale

Analyzing all features of small non-coding RNA sequencing data can be demanding and challenging. To facilitate this process, we developed miRMaster. After the analysis of over 125 000 human samples and 1.5 trillion human small RNA reads over 4 years, we present miRMaster 2 with a wide range of updates and new features. We extended our reference data sets so that miRMaster 2 now supports the analysis of eight species (e.g. human, mouse, chicken, dog, cow) and 10 non-coding RNA classes (e.g. microRNAs, piRNAs, tRNAs, rRNAs, circRNAs). We also incorporated new downstream analysis modules such as batch effect analysis or sample embeddings using UMAP, and updated annotation data bases included by default (miRBase, Ensembl, GtRNAdb). To accommodate the increasing popularity of single cell small-RNA sequencing data, we incorporated a module for unique molecular identifier (UMI) processing. Further, the output tables and graphics have been improved based on user feedback and new output formats that emerged in the community are now supported (e.g. miRGFF3). Finally, we integrated differential expression analysis with the miRNA enrichment analysis tool miEAA. miRMaster is freely available at https://www.ccb.uni-saarland.de/mirmaster2.

Deep sequencing of sncRNAs reveals hallmarks and regulatory modules of the transcriptome during Parkinson’s disease progression

Noncoding RNAs have diagnostic and prognostic importance in Parkinson's disease (PD). We studied circulating small noncoding RNAs (sncRNAs) in two large-scale longitudinal PD cohorts (Parkinson's Progression Markers Initiative (PPMI) and Luxembourg Parkinson's Study (NCER-PD)) and modeled their impact on the transcriptome. Sequencing of sncRNAs in 5,450 blood samples of 1,614 individuals in PPMI yielded 323 billion reads, most of which mapped to microRNAs but covered also other RNA classes such as piwi-interacting RNAs, ribosomal RNAs and small nucleolar RNAs. Dysregulated microRNAs associated with disease and disease progression occur in two distinct waves in the third and seventh decade of life. Originating predominantly from immune cells, they resemble a systemic inflammation response and mitochondrial dysfunction, two hallmarks of PD. Profiling 1,553 samples from 1,024 individuals in the NCER-PD cohort validated biomarkers and main findings by an independent technology. Finally, network analysis of sncRNA and transcriptome sequencing from PPMI identified regulatory modules emerging in patients with progressing PD.

Neuronal Development-Related miRNAs as Biomarkers for Alzheimer's Disease, Depression, Schizophrenia and Ionizing Radiation Exposure

Radiation exposure may induce Alzheimer's disease (AD), depression or schizophrenia. A number of experimental and clinical studies suggest the involvement of miRNA in the development of these diseases, and also in the neuropathological changes after brain radiation exposure. The current literature review indicated the involvement of 65 miRNAs in neuronal development in the brain. In the brain tissue, blood, or cerebral spinal fluid (CSF), 11, 55, or 28 miRNAs are involved in the development of AD respectively, 89, 50, 19 miRNAs in depression, and 102, 35, 8 miRNAs in schizophrenia. We compared miRNAs regulating neuronal development to those involved in the genesis of AD, depression and schizophrenia and also those driving radiation-induced brain neuropathological changes by reviewing the available data. We found that 3, 11, or 8 neuronal developmentrelated miRNAs from the brain tissue, 13, 16 or 14 miRNAs from the blood of patient with AD, depression and schizophrenia respectively were also involved in radiation-induced brain pathological changes, suggesting a possibly specific involvement of these miRNAs in radiation-induced development of AD, depression and schizophrenia respectively. On the other hand, we noted that radiationinduced changes of two miRNAs, i.e., miR-132, miR-29 in the brain tissue, three miRNAs, i.e., miR- 29c-5p, miR-106b-5p, miR-34a-5p in the blood were also involved in the development of AD, depression and schizophrenia, thereby suggesting that these miRNAs may be involved in the common brain neuropathological changes, such as impairment of neurogenesis and reduced learning memory ability observed in these three diseases and also after radiation exposure.

CoolMPS: evaluation of antibody labeling based massively parallel non-coding RNA sequencing

Results of massive parallel sequencing-by-synthesis vary depending on the sequencing approach. CoolMPS™ is a new sequencing chemistry that incorporates bases by labeled antibodies. To evaluate the performance, we sequenced 240 human non-coding RNA samples (dementia patients and controls) with and without CoolMPS. The Q30 value as indicator of the per base sequencing quality increased from 91.8 to 94%. The higher quality was reached across the whole read length. Likewise, the percentage of reads mapping to the human genome increased from 84.9 to 86.2%. For both technologies, we computed similar distributions between different RNA classes (miRNA, piRNA, tRNA, snoRNA and yRNA) and within the classes. While standard sequencing-by-synthesis allowed to recover more annotated miRNAs, CoolMPS yielded more novel miRNAs. The correlation between the two methods was 0.97. Evaluating the diagnostic performance, we observed lower minimal P-values for CoolMPS (adjusted P-value of 0.0006 versus 0.0004) and larger effect sizes (Cohen's d of 0.878 versus 0.9). Validating 19 miRNAs resulted in a correlation of 0.852 between CoolMPS and reverse transcriptase-quantitative polymerase chain reaction. Comparison to data generated with Illumina technology confirmed a known shift in the overall RNA composition. With CoolMPS we evaluated a novel sequencing-by-synthesis technology showing high performance for the analysis of non-coding RNAs.

Molecular Changes in Circulating microRNAs' Expression and Oxidative Stress in Adults with Mild Cognitive Impairment: A Biochemical and Molecular Study

BACKGROUND

The release of miRNAs in tissue fluids significantly recommends its use as non-invasive diagnostic biomarkers for the progression and pathogenesis of mild cognitive impairment (MCI) in aged patients.

OBJECTIVE

The potential role of circulated miRNAs in the pathogenesis of MCI and its association with cellular oxidative stress, apoptosis, and circulated BDNF, Sirtuin 1 (SIRT1), and dipeptidyl peptidase-4 (DPP4) were evaluated in older adults with MCI.

METHODS

A total of 150 subjects aged 65.4±3.7 years were recruited in this study. The participants were classified into two groups: healthy normal (n=80) and MCI (n=70). Real-time PCR analysis was performed to estimate the relative expression of miRNAs; miR-124a, miR-483-5p, miR-142-3p, and miR-125b, and apoptotic-related genes Bax, Bcl-2, and caspase-3 in the sera of MCI and control subjects. In addition, oxidative stress parameters; MDA, NO, SOD, and CAT; as well as plasma DPP4 activity, BDNF, SIRT1 levels were colorimetrically estimated.

RESULTS

The levels of miR-124a and miR-483-5p significantly increased and miR-142-3p and miR-125b significantly reduced in the serum of MCI patients compared to controls. The expressed miRNAs significantly correlated with severe cognitive decline, measured by MMSE, MoCA, ADL, and memory scores. The expression of Bax, and caspase-3 apoptotic inducing genes significantly increased and Bcl-2 antiapoptotic gene significantly reduced in MCI subjects compared to controls. In addition, the plasma levels of MDA, NO, and DPP4 activity significantly increased, and the levels of SOD, CAT, BDNF, and SIRT1 significantly reduced in MCI subjects compared to controls. The expressed miRNAs correlated positively with NO, MDA, DPP4 activity, BDNF, and SIRT-1, and negatively with the levels of CAT, SOD, Bcl-2, Bax, and caspase-3 genes.

CONCLUSION

Circulating miR-124a, miR-483-5p, miR-142-3p, and miR-125b significantly associated with severe cognitive decline, cellular oxidative stress, and apoptosis in patients with MCI. Thus, it could be potential non-invasive biomarkers for the diagnosis of MCI with high diagnostic performance.

Encyclopedia of tools for the analysis of miRNA isoforms

RNA sequencing data sets rapidly increase in quantity. For microRNAs (miRNAs), frequently dozens to hundreds of billion reads are generated per study. The quantification of annotated miRNAs and the prediction of new miRNAs are leading computational tasks. Now, the increased depth of coverage allows to gain deeper insights into the variability of miRNAs. The analysis of isoforms of miRNAs (isomiRs) is a trending topic, and a range of computational tools for the analysis of isomiRs has been developed. We provide an overview on 27 available computational solutions for the analysis of isomiRs. These include both stand-alone programs (17 tools) and web-based solutions (10 tools) and span a publication time range from 2010 to 2020. Seven of the tools were published in 2019 and 2020, confirming the rising importance of the topic. While most of the analyzed tools work for a broad range of organisms or are completely independent of a reference organism, several tools have been tailored for the analysis of human miRNA data or for plants. While 14 of the tools are general analysis tools of miRNAs, and isomiR analysis is one of their features, the remaining 13 tools have specifically been developed for isomiR analysis. A direct comparison on 20 deep sequencing data sets for selected tools provides insights into the heterogeneity of results. With our work, we provide users a comprehensive overview on the landscape of isomiR analysis tools and in that support the selection of the most appropriate tool for their respective research task.

Common diseases alter the physiological age-related blood microRNA profile

Aging is a key risk factor for chronic diseases of the elderly. MicroRNAs regulate post-transcriptional gene silencing through base-pair binding on their target mRNAs. We identified nonlinear changes in age-related microRNAs by analyzing whole blood from 1334 healthy individuals. We observed a larger influence of the age as compared to the sex and provide evidence for a shift to the 5' mature form of miRNAs in healthy aging. The addition of 3059 diseased patients uncovered pan-disease and disease-specific alterations in aging profiles. Disease biomarker sets for all diseases were different between young and old patients. Computational deconvolution of whole-blood miRNAs into blood cell types suggests that cell intrinsic gene expression changes may impart greater significance than cell abundance changes to the whole blood miRNA profile. Altogether, these data provide a foundation for understanding the relationship between healthy aging and disease, and for the development of age-specific disease biomarkers.

miRSwitch: detecting microRNA arm shift and switch events

Arm selection, the preferential expression of a 3′ or 5′ mature microRNA (miRNA), is a highly dynamic and tissue-specific process. Time-dependent expression shifts or switches between the arms are also relevant for human diseases. We present miRSwitch, a web server to facilitate the analysis and interpretation of arm selection events. Our species-independent tool evaluates pre-processed small non-coding RNA sequencing (sncRNA-seq) data, i.e. expression matrices or output files from miRNA quantification tools (miRDeep2, miRMaster, sRNAbench). miRSwitch highlights potential changes in the distribution of mature miRNAs from the same precursor. Group comparisons from one or several user-provided annotations (e.g. disease states) are possible. Results can be dynamically adjusted by choosing from a continuous range of highly specific to very sensitive parameters. Users can compare potential arm shifts in the provided data to a human reference map of pre-computed arm shift frequencies. We created this map from 46 tissues and 30 521 samples. As case studies we present novel arm shift information in a Alzheimer’s disease biomarker data set and from a comparison of tissues in Homo sapiens and Mus musculus. In summary, miRSwitch offers a broad range of customized arm switch analyses along with comprehensive visualizations, and is freely available at: https://www.ccb.uni-saarland.de/mirswitch/.

MicroRNAs in Alzheimer's Disease: Function and Potential Applications as Diagnostic Biomarkers

Alzheimer’s disease (AD) is the most common form of dementia. Although the incidence of AD is high, the rates of diagnosis and treatment are relatively low. Moreover, effective means for the diagnosis and treatment of AD are still lacking. MicroRNAs (miRNAs, miRs) are non-coding RNAs that play regulatory roles by targeting mRNAs. The expression of miRNAs is conserved, temporal, and tissue-specific. Impairment of microRNA function is closely related to AD pathogenesis, including the beta-amyloid and tau hallmarks of AD, and there is evidence that the expression of some microRNAs differs significantly between healthy people and AD patients. These properties of miRNAs endow them with potential diagnostic and therapeutic value in the treatment of this debilitating disease. This review provides comprehensive information about the regulatory function of miRNAs in AD, as well as potential applications as diagnostic biomarkers.

DynaVenn: web-based computation of the most significant overlap between ordered sets

BACKGROUND

In many research disciplines, ordered lists are compared. One example is to compare a subset of all significant genes or proteins in a primary study to those in a replication study. Often, the top of the lists are compared using Venn diagrams, ore more precisely Euler diagrams (set diagrams showing logical relations between a finite collection of different sets). If different cohort sizes, different techniques or algorithms for evaluation were applied, a direct comparison of significant genes with a fixed threshold can however be misleading and approaches comparing lists would be more appropriate.

RESULTS

We developed DynaVenn, a web-based tool that incrementally creates all possible subsets from two or three ordered lists and computes for each combination a p-value for the overlap. Respectively, dynamic Venn diagrams are generated as graphical representations. Additionally an animation is generated showing how the most significant overlap is reached by backtracking. We demonstrate the improved performance of DynaVenn over an arbitrary cut-off approach on an Alzheimer's Disease biomarker set.

CONCLUSION

DynaVenn combines the calculation of the most significant overlap of different cohorts with an intuitive visualization of the results. It is freely available as a web service at http://www.ccb.uni-saarland.de/dynavenn.

Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs

Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by adequate statistical learning approaches. Previously, we published high-throughput sequencing based microRNA (miRNA) signatures in Alzheimer’s disease (AD) patients in the United States (US) and Germany. Here, we determined abundance levels of 21 known circulating miRNAs in 465 individuals encompassing AD patients and controls by RT-qPCR. We computed models to assess the relation between miRNA expression and phenotypes, gender, age, or disease severity (Mini-Mental State Examination; MMSE). Of the 21 miRNAs, expression levels of 20 miRNAs were consistently de-regulated in the US and German cohorts. 18 miRNAs were significantly correlated with neurodegeneration (Benjamini-Hochberg adjusted P < 0.05) with highest significance for miR-532-5p (Benjamini-Hochberg adjusted P = 4.8 × 10⁻³⁰). Machine learning models reached an area under the curve (AUC) value of 87.6% in differentiating AD patients from controls. Further, ten miRNAs were significantly correlated with MMSE, in particular miR-26a/26b-5p (adjusted P = 0.0002). Interestingly, the miRNAs with lower abundance in AD were enriched in monocytes and T-helper cells, while those up-regulated in AD were enriched in serum, exosomes, cytotoxic t-cells, and B-cells. Our study represents the next important step in translational research for a miRNA-based AD test.

The sncRNA Zoo: a repository for circulating small noncoding RNAs in animals

The repertoire of small noncoding RNAs (sncRNAs), particularly miRNAs, in animals is considered to be evolutionarily conserved. Studies on sncRNAs are often largely based on homology-based information, relying on genomic sequence similarity and excluding actual expression data. To obtain information on sncRNA expression (including miRNAs, snoRNAs, YRNAs and tRNAs), we performed low-input-volume next-generation sequencing of 500 pg of RNA from 21 animals at two German zoological gardens. Notably, none of the species under investigation were previously annotated in any miRNA reference database. Sequencing was performed on blood cells as they are amongst the most accessible, stable and abundant sources of the different sncRNA classes. We evaluated and compared the composition and nature of sncRNAs across the different species by computational approaches. While the distribution of sncRNAs in the different RNA classes varied significantly, general evolutionary patterns were maintained. In particular, miRNA sequences and expression were found to be even more conserved than previously assumed. To make the results available for other researchers, all data, including expression profiles at the species and family levels, and different tools for viewing, filtering and searching the data are freely available in the online resource ASRA (Animal sncRNA Atlas) at https://www.ccb.uni-saarland.de/asra/.

An estimate of the total number of true human miRNAs

While the number of human miRNA candidates continuously increases, only a few of them are completely characterized and experimentally validated. Toward determining the total number of true miRNAs, we employed a combined in silico high- and experimental low-throughput validation strategy. We collected 28 866 human small RNA sequencing data sets containing 363.7 billion sequencing reads and excluded falsely annotated and low quality data. Our high-throughput analysis identified 65% of 24 127 mature miRNA candidates as likely false-positives. Using northern blotting, we experimentally validated miRBase entries and novel miRNA candidates. By exogenous overexpression of 108 precursors that encode 205 mature miRNAs, we confirmed 68.5% of the miRBase entries with the confirmation rate going up to 94.4% for the high-confidence entries and 18.3% of the novel miRNA candidates. Analyzing endogenous miRNAs, we verified the expression of 8 miRNAs in 12 different human cell lines. In total, we extrapolated 2300 true human mature miRNAs, 1115 of which are currently annotated in miRBase V22. The experimentally validated miRNAs will contribute to revising targetomes hypothesized by utilizing falsely annotated miRNAs.

miRCarta: a central repository for collecting miRNA candidates

The continuous increase of available biological data as consequence of modern high-throughput technologies poses new challenges for analysis techniques and database applications. Especially for miRNAs, one class of small non-coding RNAs, many algorithms have been developed to predict new candidates from next-generation sequencing data. While the amount of publications describing novel miRNA candidates keeps steadily increasing, the current gold standard database for miRNAs - miRBase - has not been updated since June 2014. As a result, publications describing new miRNA candidates in the last three to five years might have a substantial overlap of candidates without noticing. With miRCarta we implemented a database to collect novel miRNA candidates and augment the information provided by miRBase. In the first stage, miRCarta is thought to be a highly sensitive collection of potential miRNA candidates with a high degree of analysis functionality, annotations and details on each miRNA. We added-besides the full content of the miRBase-12,857 human miRNA precursors to miRCarta. Users can match their own predictions to the entries of miRCarta to reduce potential redundancies in their studies. miRCarta provides the most comprehensive collection of human miRNAs and miRNA candidates to form a basis for further refinement and validation studies. The database is freely accessible at https://mircarta.cs.uni-saarland.de/.

The current status of blood epigenetic biomarkers for dementia

Dementia is an overarching term which describes a group of symptoms that result in long-term decline in cognitive functioning that is significant enough to affect daily function. It is caused by a number of different diseases, the most common of which is Alzheimer's disease. Currently, there are no definitive biomarkers for preclinical or diagnostic use, or which differentiate between underlying disease types. The purpose of this review is to highlight several important areas of research on blood-based biomarkers of dementia, with a specific focus on epigenetic biomarkers. A systematic search of the literature identified 77 studies that compared blood DNA methylation between individuals with dementia and controls and 45 studies that measured microRNA. Very few studies were identified that focused on histone modifications. There were many promising findings from studies in the field of blood-based epigenetic biomarkers of dementia, however, a lack of consistency in study design, technologies, and platforms used for the biomarker measurement, as well as statistical analysis methods, have hampered progress. To date, there are very few findings that have been independently replicated across more than one study, indicating a preponderance of false-positive findings and the field has likely been plagued by positive publication bias. Here, we highlight and discuss several of the limitations of existing studies and provide recommendations for how these could be overcome in future research. A robust framework should be followed to enable development of the most valid and reproducible biomarkers with the strongest clinical utility. Defining a series of biomarkers that may be complimentary to each other could permit a stronger multifactorial biomarker to be developed that would allow for not only accurate dementia diagnosis but preclinical detection.

Neuroepigenetics and Alzheimer's Disease: An Update

Epigenetics is the study of changes in gene expression which may be triggered by both genetic and environmental factors, and independent from changes to the underlying DNA sequence-a change in phenotype without a change in genotype-which in turn affects how cells read genes. Epigenetic changes represent a regular and natural occurrence but can be influenced also by factors such as age, environment, and disease state. Epigenetic modifications can manifest themselves not only as the manner in which cells terminally differentiate, but can have also deleterious effects, resulting in diseases such as cancer. At least three systems including DNA methylation, histone modification, and non-coding RNA (ncRNA)-associated gene silencing are thought to initiate and sustain epigenetic change. For example, in Alzheimer's disease (AD), both genetic and non-genetic factors contribute to disease etiopathology. While over 250 gene mutations have been related to familial AD, less than 5% of AD cases are explained by known disease genes. More than likely, non-genetic factors, probably triggered by environmental factors, are causative factors of late-onset AD. AD is associated with dysregulation of DNA methylation, histone modifications, and ncRNAs. Among the classes of ncRNA, microRNAs (miRNAs) have a well-established regulatory relevance. MicroRNAs are highly expressed in CNS neurons, where they play a major role in neuron differentiation, synaptogenesis, and plasticity. MicroRNAs impact higher cognitive functions, as their functional impairment is involved in the etiology of neurological diseases, including AD. Alterations in the miRNA network contribute to AD disease processes, e.g., in the regulation of amyloid peptides, tau, lipid metabolism, and neuroinflammation. MicroRNAs, both as biomarkers for AD and therapeutic targets, are in the early stages of exploration. In addition, emerging data suggest that altered transcription of long ncRNAs, endogenous, ncRNAs longer than 200 nucleotides, may be involved in an elevated risk for AD.

A Systematic Review of MicroRNA Expression as Biomarker of Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease (LOAD) is a high-occurrence neurological disorder but the difficulty in identifying precise and early biomarkers has complicated the understanding of the disease and the development of new treatments. In this sense, important knowledge is emerging regarding novel molecular and biological candidates with diagnostic potential, including microRNAs (miRNAs), which have a key role in gene repression. The aim of this systematic review was to define the role of miRNAs' expression as biomarkers for LOAD both in brain tissues, which could help understand the biology of the disease, and circulating tissues, which could serve as non-invasive markers of the pathology. A systematic search was performed in Web of Science and PubMed using the keywords ((Alzheimer or Alzheimer's) and (microRNA or microRNAs or miRNA or miRNAs or miR)) until August 2018 to retrieve all articles that presented independent original data evaluating the impact of miRNA expression on the development of LOAD in human population. A total of 90 studies investigating the role of miRNAs' expression in the development of LOAD were identified. While other widely studied miRNAs such as hsa-miR-146a presented contradictory results among studies, deregulation in brain tissue of seven miRNAs, hsa-miR-16-5p, hsa-miR-34a-5p, hsa-miR-107, hsa-miR-125-5p, hsa-miR-132-3p, hsa-miR-181-3p, and hsa-miR-212-3p, was consistently identified in LOAD patients. Their role in the disease could be mediated through the regulation of key pathways, such as axon guidance, longevity, insulin, and MAPK signaling pathway. However, regarding their role as non-invasive biomarkers of LOAD in fluids, although the limited results available are promising, further studies are required.

Spring is in the air: seasonal profiles indicate vernal change of miRNA activity

The envisioned application of miRNAs as diagnostic or prognostic biomarkers calls for an in-depth understanding of their distribution and variability in different physiological states. While effects with respect to ethnic origin, age, or gender are known, the inter-individual variability of miRNAs across the four seasons remained largely hidden. We sequentially profiled the complete repertoire of blood-borne miRNAs for 25 physiologically normal individuals in spring, summer, fall, and winter (altogether 95 samples) and validated the results on 292 individuals (919 samples collected with the Mitra home sampling device) by RT-qPCR. Principal variance component analysis suggests that the largest variability observed in miRNA expression is due to individual variability and the individuals' gender. But the results also highlight a deviation of miRNA activity in samples collected during spring time. Following adjustment for multiple testing, remarkable differences are observed between spring and fall (77 miRNAs). The two most dys-regulated miRNAs were miR-181c-5p and miR-106b-5p (adjusted p-value of 0.007). Other significant miRNAs include miR-140-3p, miR-21-3p, and let-7c-5p. The dys-regulation was validated by RT-qPCR. Systems biology analysis further provides strong evidence for the immunological origin of the signals: dys-regulated miRNAs are enriched in CD56 cells and belong to various signalling and immune-system-related pathways. Our data suggest that besides known confounding factors such as age and sex, also the season in which a test is conducted might have a considerable influence on the expression of blood-borne miRNAs and subsequently might interfere with diagnosis based on such signatures.

Extracellular Vesicle as a Source of Alzheimer's Biomarkers: Opportunities and Challenges

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease characterized by memory decline and cognitive dysfunction. Although the primary causes of AD are not clear, it is widely accepted that the accumulation of amyloid beta (Aβ) and consecutive hyper-phosphorylation of tau, synaptic loss, oxidative stress and neuronal death might play a vital role in AD pathogenesis. Recently, it has been widely suggested that extracellular vesicles (EVs), which are released from virtually all cell types, are a mediator in regulating AD pathogenesis. Clinical evidence for the diagnostic performance of EV-associated biomarkers, particularly exosome biomarkers in the blood, is also emerging. In this review, we briefly introduce the biological function of EVs in the central nervous system and discuss the roles of EVs in AD pathogenesis. In particular, the roles of EVs associated with autophagy and lysosomal degradation systems in AD proteinopathy and in disease propagation are discussed. Next, we summarize candidates for biochemical AD biomarkers in EVs, including proteins and miRNAs. The accumulating data brings hope that the application of EVs will be helpful for early diagnostics and the identification of new therapeutic targets for AD. However, at the same time, there are several challenges in developing valid EV biomarkers. We highlight considerations for the development of AD biomarkers from circulating EVs, which includes the standardization of pre-analytical sources of variability, yield and purity of isolated EVs and quantification of EV biomarkers. The development of valid EV AD biomarkers may be facilitated by collaboration between investigators and the industry.

MicroRNAs and mild cognitive impairment: A systematic review

BACKGROUND

Mild cognitive impairment (MCI) is usually described as an intermediate phase between normal cognition and dementia. Identifying the subjects at a higher risk of progressing from MCI to AD is essential to manage this condition. The diagnosis of MCI is mainly clinical. Several biomarkers have been proposed, but mostly for research purposes, as they are based on an invasive procedure to obtain the sample, such as cerebrospinal fluid (CSF). As a consequence, rapid and non-invasive biomarkers are needed to improve diagnosis. The objective of this systematic review is to summarize available evidence on the use of miRNAs as biomarkers in subjects with MCI.

METHODS

Relevant literature published up to June 2018 was retrieved searching the databases PubMed, ISI Web of Knowledge and the Cochrane Database. Only studies considering microRNAs (miRNAs) and a diagnosis of MCI were included. Data were extracted using a specifically-designed standardized form, and their methodological quality was assessed using QUADAS-2 and QUIPS.

RESULTS

Twenty-one studies of 153 retrieved articles met the predefined inclusion/exclusion criteria. Studies included participants ranging from 6 to 330. More than 40 miRNAs resulted as dysregulated, and miR-206 was the only miRNA that was found as differentially expressed in patients with MCI by more than two studies. However, these results have either not yet been confirmed in other independent cohorts, or data are still inconsistent. Inconsistencies among included studies could be due to several issues including the selection of participants, pre-analytical and analytical procedures, and statistical analyses.

Omics-based Biomarkers for the Early Alzheimer Disease Diagnosis and Reliable Therapeutic Targets Development

BACKGROUND

Alzheimer's disease (AD), the most common cause of dementia in adulthood, has great medical, social, and economic impact worldwide. Available treatments result in symptomatic relief, and most of them are indicated from the early stages of the disease. Therefore, there is an increasing body of research developing accurate and early diagnoses, as well as diseasemodifying therapies.

OBJECTIVE

Advancing the knowledge of AD physiopathological mechanisms, improving early diagnosis and developing effective treatments from omics-based biomarkers.

METHODS

Studies using omics technologies to detect early AD, were reviewed with a particular focus on the metabolites/lipids, micro-RNAs and proteins, which are identified as potential biomarkers in non-invasive samples.

RESULTS

This review summarizes recent research on metabolomics/lipidomics, epigenomics and proteomics, applied to early AD detection. Main research lines are the study of metabolites from pathways, such as lipid, amino acid and neurotransmitter metabolisms, cholesterol biosynthesis, and Krebs and urea cycles. In addition, some microRNAs and proteins (microglobulins, interleukins), related to a common network with amyloid precursor protein and tau, have been also identified as potential biomarkers. Nevertheless, the reproducibility of results among studies is not good enough and a standard methodological approach is needed in order to obtain accurate information.

CONCLUSION

The assessment of metabolomic/lipidomic, epigenomic and proteomic changes associated with AD to identify early biomarkers in non-invasive samples from well-defined participants groups will potentially allow the advancement in the early diagnosis and improvement of therapeutic interventions.

MicroRNAs as diagnostic and therapeutic tools for Alzheimer's disease: advances and limitations

Alzheimer’s disease (AD) is the most common age-related, progressive neurodegenerative disease. It is characterized by memory loss and cognitive decline and responsible for most cases of dementia in the elderly. Late-onset or sporadic AD accounts for > 95% of cases, with age at onset > 65 years. Currently there are no drugs or other therapeutic agents available to prevent or delay the progression of AD. The cellular and molecular changes occurring in the brains of individuals with AD include accumulation of β-amyloid peptide and hyperphosphorylated tau protein, decrease of acetylcholine neurotransmitter, inflammation, and oxidative stress. Aggregation of β-amyloid peptide in extracellular plaques and the hyperphosphorylated tau protein in intracellular neurofibrillary tangles are characteristic of AD. A major challenge is identifying molecular biomarkers of the early-stage AD in patients as most studies have been performed with blood or brain tissue samples (postmortem) at late-stage AD. Subjects with mild cognitive impairment almost always have the neuropathologic features of AD with about 50% of mild cognitive impairment patients progressing to AD. They could provide important information about AD pathomechanism and potentially also highlight minimally or noninvasive, easy-to-access biomarkers. MicroRNAs are dysregulated in AD, and may facilitate the early detection of the disease and potentially the continual monitoring of disease progression and allow therapeutic interventions to be evaluated. Four recent reviews have been published of microRNAs in AD, each of which identified areas of weakness or limitations in the reported studies. Importantly, studies in the last three years have shown considerable progress in overcoming some of these limitations and identifying specific microRNAs as biomarkers for AD and mild cognitive impairment. Further large-scale human studies are warranted with less disparity in the study populations, and using an appropriate method to validate the findings.

microRNA diagnostic panel for Alzheimer's disease and epigenetic trade-off between neurodegeneration and cancer

microRNAs (miRNAs) have been extensively studied as potential biomarkers for Alzheimer's disease (AD). Their profiles have been analyzed in blood, cerebrospinal fluid (CSF) and brain tissue. However, due to the high variability between the reported data, stemming from the lack of methodological standardization and the heterogeneity of AD, the most promising miRNA biomarker candidates have not been selected. Our literature review shows that out of 137 miRNAs found to be altered in AD blood, 36 have been replicated in at least one independent study, and out of 166 miRNAs reported as differential in AD CSF, 13 have been repeatedly found. Only 3 miRNAs have been consistently reported as altered in three analyzed specimens: blood, CSF and the brain (hsa-miR-146a, hsa-miR-125b, hsa-miR-135a). Nonetheless, all 36 repeatedly differential miRNAs in AD blood are promising as components of the diagnostic panel. Given their predicted functions, such miRNA panel may report multiple pathways contributing to AD pathology, enabling the design of personalized therapies. In addition, the analysis revealed that the miRNAs dysregulated in AD overlap highly with miRNAs implicated in cancer. However, the directions of the miRNA changes are usually opposite in cancer and AD, indicative of an epigenetic trade-off between the two diseases.

Blood-based biomarkers for Alzheimer disease: mapping the road to the clinic

Biomarker discovery and development for clinical research, diagnostics and therapy monitoring in clinical trials have advanced rapidly in key areas of medicine - most notably, oncology and cardiovascular diseases - allowing rapid early detection and supporting the evolution of biomarker-guided, precision-medicine-based targeted therapies. In Alzheimer disease (AD), breakthroughs in biomarker identification and validation include cerebrospinal fluid and PET markers of amyloid-β and tau proteins, which are highly accurate in detecting the presence of AD-associated pathophysiological and neuropathological changes. However, the high cost, insufficient accessibility and/or invasiveness of these assays limit their use as viable first-line tools for detecting patterns of pathophysiology. Therefore, a multistage, tiered approach is needed, prioritizing development of an initial screen to exclude from these tests the high numbers of people with cognitive deficits who do not demonstrate evidence of underlying AD pathophysiology. This Review summarizes the efforts of an international working group that aimed to survey the current landscape of blood-based AD biomarkers and outlines operational steps for an effective academic-industry co-development pathway from identification and assay development to validation for clinical use.

Genome-wide MicroRNA Expression Profiles in COPD: Early Predictors for Cancer Development

Chronic obstructive pulmonary disease (COPD) significantly increases the risk of developing cancer. Biomarker studies frequently follow a case-control set-up in which patients diagnosed with a disease are compared to controls. Longitudinal cohort studies such as the COPD-centered German COPD and SYstemic consequences-COmorbidities NETwork (COSYCONET) study provide the patient and biomaterial base for discovering predictive molecular markers. We asked whether microRNA (miRNA) profiles in blood collected from COPD patients prior to a tumor diagnosis could support an early diagnosis of tumor development independent of the tumor type. From 2741 participants of COSYCONET diagnosed with COPD, we selected 534 individuals including 33 patients who developed cancer during the follow-up period of 54 months and 501 patients who did not develop cancer, but had similar age, gender and smoking history. Genome-wide miRNA profiles were generated and evaluated using machine learning techniques. For patients developing cancer we identified nine miRNAs with significantly decreased abundance (two-tailed unpaired t-test adjusted for multiple testing P < 0.05), including members of the miR-320 family. The identified miRNAs regulate different cancer-related pathways including the MAPK pathway (P = 2.3 × 10⁻⁵). We also observed the impact of confounding factors on the generated miRNA profiles, underlining the value of our matched analysis. For selected miRNAs, qRT-PCR analysis was applied to validate the results. In conclusion, we identified several miRNAs in blood of COPD patients, which could serve as candidates for biomarkers to help identify COPD patients at risk of developing cancer.

Small ncRNA-Seq Results of Human Tissues: Variations Depending on Sample Integrity

BACKGROUND

Although mature miRNAs are relatively stable in vivo, RNA degradation can have a substantial influence on small noncoding RNA (sncRNA) profiles.

METHODS

Using different tissue storage conditions and RNA isolation procedures, we analyzed the integrity and quality of RNA isolates from human lung and heart tissues. We sequenced a total of 64 RNA samples and quantified the effect of RNA degradation, DNA contamination, and other confounding factors on the sncRNA-seq data. Besides microRNAs, other noncoding RNA species (piRNAs, tRNAs, snoRNAs, rRNAs) were investigated.

RESULTS

Consistent with previous results, we found that the tissue specificity of microRNAs is generally well preserved. The distribution of microRNA isoforms was similar to the distribution of canonical forms. New miRNAs were more frequently discovered in degraded samples. sncRNA Reads generated from degraded samples mapped frequently to piRNAs, tRNAs, snoRNAs, or scaRNAs. Sequencing reads that were depleted of sncRNAs showed an increased mapping frequency to bacterial species.

CONCLUSIONS

Our data emphasize the importance of sample integrity, especially for next-generation sequencing (NGS)-based high-throughput sncRNA profiles. For the prediction of novel miRNAs in particular, only samples with the highest RNA integrity should be used in order to avoid identification of false "miRNAs."

MicroRNA Profile in Patients with Alzheimer's Disease: Analysis of miR-9-5p and miR-598 in Raw and Exosome Enriched Cerebrospinal Fluid Samples

BACKGROUND

MicroRNAs have been postulated as potential biomarkers for Alzheimer's disease (AD). Exosomes are nanovesicles which transport microRNAs, proteins, and other cargos. It has been hypothesized that the exosome traffic might be increased in neurodegenerative disorders.

OBJECTIVE

i) To assess the cerebrospinal fluid (CSF) microRNA profile in a group of AD patients and control subjects and to validate a group of microRNAs previously reported by other authors. ii) To compare microRNA levels in whole CSF and in the exosome-enriched fraction in AD patients.

METHODS

A panel of 760 microRNAs was analyzed in the CSF of 10 AD patients and 10 healthy subjects. Among microRNAs differently expressed, we selected those that had been previously reported by other authors. Candidates were validated in a larger group by individual qPCR assays. MicroRNA expression was also evaluated in exosome-enriched CSF samples of patients with AD and controls.

RESULTS

Fifteen microRNAs were differently expressed in AD. MiR-9-5p, miR-134, and miR-598 were selected as candidates for further analysis. MiR-9-5p and miR-598 were detected in 50 and 75% of control CSF samples, respectively, while they were not detected in any AD CSF samples. We observed an opposite pattern when we evaluated the microRNA expression in the exosome-enriched CSF AD samples. No pattern variations were noted among healthy subjects.

CONCLUSION

These data propose miR-9-5p and miR-598 as potential biomarkers for AD. Further studies in plasma and other body fluids will confirm their potential role as easily accessible biomarkers. In addition, our data suggest that exosome trafficking is different between AD and control subjects raising the need to take this phenomenon into consideration in future studies of AD biomarkers.

Quantifying miRNA Deregulation in Alzheimer's Disease

Analysis of miRNA expression in circulating immune cells, such as monocytes, using qRT-PCR arrays, allows the quantification of a wide range of miRNAs in easily accessible biosamples from Alzheimer's disease patients. This technique enables the identification of differentially expressed miRNAs and provides important clues for the discovery of new miRNA-based biomarkers. Here we describe how to isolate a specific lymphocyte population from human blood samples, CD14⁺ monocytes, and how to extract total RNA, containing short RNAs, from these cells, transcribe the RNA into cDNA and quantify a pre-set of specific miRNAs using customizable PCR plates of 96 or 384 wells.

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs

The analysis of small RNA NGS data together with the discovery of new small RNAs is among the foremost challenges in life science. For the analysis of raw high-throughput sequencing data we implemented the fast, accurate and comprehensive web-based tool miRMaster. Our toolbox provides a wide range of modules for quantification of miRNAs and other non-coding RNAs, discovering new miRNAs, isomiRs, mutations, exogenous RNAs and motifs. Use-cases comprising hundreds of samples are processed in less than 5 h with an accuracy of 99.4%. An integrative analysis of small RNAs from 1836 data sets (20 billion reads) indicated that context-specific miRNAs (e.g. miRNAs present only in one or few different tissues / cell types) still remain to be discovered while broadly expressed miRNAs appear to be largely known. In total, our analysis of known and novel miRNAs indicated nearly 22 000 candidates of precursors with one or two mature forms. Based on these, we designed a custom microarray comprising 11 872 potential mature miRNAs to assess the quality of our prediction. MiRMaster is a convenient-to-use tool for the comprehensive and fast analysis of miRNA NGS data. In addition, our predicted miRNA candidates provided as custom array will allow researchers to perform in depth validation of candidates interesting to them.

Profile of 6 microRNA in blood plasma distinguish early stage Alzheimer's disease patients from non-demented subjects

Alzheimer's disease (AD) is the most common age-related dementia. Among its major challenges is identifying molecular signatures characteristic for the early AD stage in patients with Mild Cognitive Impairment (MCI-AD), which could serve for deciphering the AD pathomechanism and also as non-invasive, easy-to-access biomarkers. Using qRT-PCR we compared the microRNA (miRNA) profiles in blood plasma of 15 MCI-AD patients, whose diagnoses were confirmed by cerebrospinal fluid (CSF) biomarkers, with 20 AD patients and 15 non-demented, age-matched individuals (CTR).To minimize methodological variability, we adhered to standardization of blood and CSF assays recommended by the international Joint Programming for Neurodegenerative Diseases (JPND) BIOMARKAPD consortium, and we employed commercially available Exiqon qRT-PCR-assays. In the first screening, we assessed 179 miRNAs of plasma. We confirmed 23 miRNAs reported earlier as AD biomarker candidates in blood and found 26 novel differential miRNAs between AD and control subjects. For representative 15 differential miRNAs, the TargetScan, MirTarBase and KEGG database analysis indicated putative protein targets among such AD hallmarks as MAPT (Tau), proteins involved in amyloidogenic proteolysis, and in apoptosis. These 15 miRNAs were verified in separate, subsequent subject groups. Finally, 6 miRNAs (3 not yet reported in AD context and 3 reported in AD blood) were selected as the most promising biomarker candidates differentiating early AD from controls with the highest fold changes (from 1.32 to 14.72), consistent significance, specificities from 0.78 to 1 and sensitivities from 0.75 to 1. (patent pending, PCT/IB2016/052440).

Advances in the Care of Primary Immunodeficiencies (PIDs): from Birth to Adulthood

Primary immunodeficiencies (PIDs) are a widely heterogeneous group of inherited defects of the immune system consisting of many clinical phenotypes with at least 300 underlying genetic deficits currently known. Patients with PIDs can present with, or develop during the course of their life, a susceptibility to recurrent and chronic infection along with autoimmune, allergic, inflammatory, and/or proliferative disorders, all potentially leading to end-organ damage. In recent years, a combination of basic and clinical research has greatly improved understanding of the underlying immunological and genetic defects in PIDs, leading to improved diagnosis, classification, and treatment approaches. In this review, we consider some of the key understandings that should direct diagnostic and treatment approaches in PID and offer insights into current and emerging management approaches and the lifelong care of patients from childhood through to adulthood.

cPAS-based sequencing on the BGISEQ-500 to explore small non-coding RNAs

Background

We present the first sequencing data using the combinatorial probe-anchor synthesis (cPAS)-based BGISEQ-500 sequencer. Applying cPAS, we investigated the repertoire of human small non-coding RNAs and compared it to other techniques.

Results

Starting with repeated measurements of different specimens including solid tissues (brain and heart) and blood, we generated a median of 30.1 million reads per sample. 24.1 million mapped to the human genome and 23.3 million to the miRBase. Among six technical replicates of brain samples, we observed a median correlation of 0.98. Comparing BGISEQ-500 to HiSeq, we calculated a correlation of 0.75. The comparability to microarrays was similar for both BGISEQ-500 and HiSeq with the first one showing a correlation of 0.58 and the latter one correlation of 0.6. As for a potential bias in the detected expression distribution in blood cells, 98.6% of HiSeq reads versus 93.1% of BGISEQ-500 reads match to the 10 miRNAs with highest read count. After using miRDeep2 and employing stringent selection criteria for predicting new miRNAs, we detected 74 high-likely candidates in the cPAS sequencing reads prevalent in solid tissues and 36 candidates prevalent in blood.

Conclusions

While there is apparently no ideal platform for all challenges of miRNome analyses, cPAS shows high technical reproducibility and supplements the hitherto available platforms.

Electronic supplementary material

The online version of this article (doi:10.1186/s13148-016-0287-1) contains supplementary material, which is available to authorized users.