Inferring Multiple Sclerosis Stages from the Blood Transcriptome via Machine Learning.

Peripheral blood mononuclear cells (PBMCs) bear specific dysregulations in genes and pathways at distinct stages of multiple sclerosis (MS) that may help with classifying MS and non-MS subjects, specifying the early stage of disease, or discriminating among MS courses. Here we describe an unbiased machine learning workflow to build MS stage-specific classifiers based on PBMC transcriptomics profiles from more than 300 individuals, including healthy subjects and patients with clinically isolated syndromes, relapsing-remitting MS, primary or secondary progressive MS, or other neurological disorders. The pipeline, designed to optimize and compare the performance of distinct machine learning algorithms in the training cohort, generates predictive models not influenced by demographic features, such as age and gender, and displays high accuracy in the independent validation cohort. Proper application of machine learning to transcriptional profiles of circulating blood cells may allow identification of disease state and stage in MS.

Transcriptome analysis defines myocardium gene signatures in children with ToF and ASD and reveals disease-specific molecular reprogramming in response to surgery with cardiopulmonary bypass.

BACKGROUND: Tetralogy of Fallot (ToF) and Atrial Septal Defects (ASD) are the most common types of congenital heart diseases and a major cause of childhood morbidity and mortality. Cardiopulmonary bypass (CPB) is used during corrective cardiac surgery to support circulation and heart stabilization. However, this procedure triggers systemic inflammatory and stress response and consequent increased risk of postoperative complications. The aim of this study was to define the molecular bases of ToF and ASD pathogenesis and response to CPB and identify new potential biomarkers. METHODS: Comparative transcriptome analysis of right atrium specimens collected from 10 ToF and 10 ASD patients was conducted before (Pre-CPB) and after (Post-CPB) corrective surgery. Total RNA isolated from each sample was individually hybridized on Affymetrix HG-U133 Plus Array Strips containing 38,500 unique human genes. Differences in the gene expression profiles and functional enrichment/network analyses were assessed using bioinformatic tools. qRT-PCR analysis was used to validate gene modulation. RESULTS: Pre-CPB samples showed significant differential expression of a total of 72 genes, 28 of which were overexpressed in ToF and 44 in ASD. According to Gene Ontology annotation, the mostly enriched biological processes were represented by matrix organization and cell adhesion in ToF and by muscle development and contractility in ASD specimens. GSEA highlighted the specific enrichment of hypoxia gene sets in ToF samples, pointing to a role for hypoxia in disease pathogenesis. The post-CPB myocardium exhibited significant alterations in the expression profile of genes related to transcription regulation, growth/apoptosis, inflammation, adhesion/matrix organization, and oxidative stress. Among them, only 70 were common to the two disease groups, whereas 110 and 24 were unique in ToF and ASD, respectively. Multiple functional interactions among differentially expressed gene products were predicted by network analysis. Interestingly, gene expression changes in ASD samples followed a consensus hypoxia profile. CONCLUSION: Our results provide a comprehensive view of gene reprogramming in right atrium tissues of ToF and ASD patients before and after CPB, defining specific molecular pathways underlying disease pathophysiology and myocardium response to CPB. These findings have potential translational value because they identify new candidate prognostic markers and targets for tailored cardioprotective post-surgical therapies.

Convergence between Microglia and Peripheral Macrophages Phenotype during Development and Neuroinflammation.

Differently from other myeloid cells, microglia derive exclusively from precursors originating within the yolk sac and migrate to the CNS under development, without any contribution from fetal liver or postnatal hematopoiesis. Consistent with their unique ontology, microglia may express specific physiological markers, which have been partly described in recent years. Here we wondered whether profiles distinguishing microglia from peripheral macrophages vary with age and under pathology. To this goal, we profiled transcriptomes of microglia throughout the lifespan and included a parallel comparison with peripheral macrophages under physiological and neuroinflammatory settings using age- and sex-matched wild-type and bone marrow chimera mouse models. This comprehensive approach demonstrated that the phenotypic differentiation between microglia and peripheral macrophages is age-dependent and that peripheral macrophages do express some of the most commonly described microglia-specific markers early during development, such as Fcrls, P2ry12, Tmem119, and Trem2. Further, during chronic neuroinflammation CNS-infiltrating macrophages and not peripheral myeloid cells acquire microglial markers, indicating that the CNS niche may instruct peripheral myeloid cells to gain the phenotype and, presumably, the function of the microglia cell. In conclusion, our data provide further evidence about the plasticity of the myeloid cell and suggest caution in the strict definition and application of microglia-specific markers.SIGNIFICANCE STATEMENT Understanding the respective role of microglia and infiltrating monocytes in neuroinflammatory conditions has recently seemed possible by the identification of a specific microglia signature. Here instead we provide evidence that peripheral macrophages may express some of the most commonly described microglia markers at some developmental stages or pathological conditions, in particular during chronic neuroinflammation. Further, our data support the hypothesis about phenotypic plasticity and convergence among distinct myeloid cells so that they may act as a functional unit rather than as different entities, boosting their mutual functions in different phases of disease. This holds relevant implications in the view of the growing use of myeloid cell therapies to treat brain disease in humans.

Loss of Circulating CD8+ CD161high T Cells in Primary Progressive Multiple Sclerosis.

Recent evidence suggests that the primary progressive form of multiple sclerosis (PP-MS) may present with specific immunological alterations. In this study we focused our attention on CD161, an NK and T cell marker upregulated in relapsing-remitting MS, and investigated its transcript and protein levels in blood cells from PP-MS and healthy individuals. We demonstrated transcriptional downregulation of CD161 in PP-MS and described concomitant mRNA reduction for RORgt, CCR6, CXCR6, KLRK1/NKG2D and many other markers typical of mucosa associated invariant T (MAIT) cells. Targeted multiparametric flow cytometry on fresh blood cells from an independent cohort of case-control subjects confirmed the selective loss of circulating CD8 CD161high T cells, which consist mainly of MAIT cells, and not of CD8 CD161int T cells in PP-MS. These data demonstrate alterations in a specific circulating immune cell subset in MS patients with progressive onset.

Assessment of copy number variations in 120 patients with Poland syndrome.

BACKGROUND: Poland Syndrome (PS) is a rare congenital disorder presenting with agenesis/hypoplasia of the pectoralis major muscle variably associated with thoracic and/or upper limb anomalies. Most cases are sporadic, but familial recurrence, with different inheritance patterns, has been observed. The genetic etiology of PS remains unknown. Karyotyping and array-comparative genomic hybridization (CGH) analyses can identify genomic imbalances that can clarify the genetic etiology of congenital and neurodevelopmental disorders. We previously reported a chromosome 11 deletion in twin girls with pectoralis muscle hypoplasia and skeletal anomalies, and a chromosome six deletion in a patient presenting a complex phenotype that included pectoralis muscle hypoplasia. However, the contribution of genomic imbalances to PS remains largely unknown. METHODS: To investigate the prevalence of chromosomal imbalances in PS, standard cytogenetic and array-CGH analyses were performed in 120 PS patients. RESULTS: Following the application of stringent filter criteria, 14 rare copy number variations (CNVs) were identified in 14 PS patients in different regions outside known common copy number variations: seven genomic duplications and seven genomic deletions, enclosing the two previously reported PS associated chromosomal deletions. These CNVs ranged from 0.04 to 4.71 Mb in size. Bioinformatic analysis of array-CGH data indicated gene enrichment in pathways involved in cell-cell adhesion, DNA binding and apoptosis processes. The analysis also provided a number of candidate genes possibly causing the developmental defects observed in PS patients, among others REV3L, a gene coding for an error-prone DNA polymerase previously associated with Möbius Syndrome with variable phenotypes including pectoralis muscle agenesis. CONCLUSIONS: A number of rare CNVs were identified in PS patients, and these involve genes that represent candidates for further evaluation. Rare inherited CNVs may contribute to, or represent risk factors of PS in a multifactorial mode of inheritance.

Design of a multi-signature ensemble classifier predicting neuroblastoma patients' outcome.

BACKGROUND: Neuroblastoma is the most common pediatric solid tumor of the sympathetic nervous system. Development of improved predictive tools for patients stratification is a crucial requirement for neuroblastoma therapy. Several studies utilized gene expression-based signatures to stratify neuroblastoma patients and demonstrated a clear advantage of adding genomic analysis to risk assessment. There is little overlapping among signatures and merging their prognostic potential would be advantageous. Here, we describe a new strategy to merge published neuroblastoma related gene signatures into a single, highly accurate, Multi-Signature Ensemble (MuSE)-classifier of neuroblastoma (NB) patients outcome. METHODS: Gene expression profiles of 182 neuroblastoma tumors, subdivided into three independent datasets, were used in the various phases of development and validation of neuroblastoma NB-MuSE-classifier. Thirty three signatures were evaluated for patients' outcome prediction using 22 classification algorithms each and generating 726 classifiers and prediction results. The best-performing algorithm for each signature was selected, validated on an independent dataset and the 20 signatures performing with an accuracy > = 80% were retained. RESULTS: We combined the 20 predictions associated to the corresponding signatures through the selection of the best performing algorithm into a single outcome predictor. The best performance was obtained by the Decision Table algorithm that produced the NB-MuSE-classifier characterized by an external validation accuracy of 94%. Kaplan-Meier curves and log-rank test demonstrated that patients with good and poor outcome prediction by the NB-MuSE-classifier have a significantly different survival (p < 0.0001). Survival curves constructed on subgroups of patients divided on the bases of known prognostic marker suggested an excellent stratification of localized and stage 4s tumors but more data are needed to prove this point. CONCLUSIONS: The NB-MuSE-classifier is based on an ensemble approach that merges twenty heterogeneous, neuroblastoma-related gene signatures to blend their discriminating power, rather than numeric values, into a single, highly accurate patients' outcome predictor. The novelty of our approach derives from the way to integrate the gene expression signatures, by optimally associating them with a single paradigm ultimately integrated into a single classifier. This model can be exported to other types of cancer and to diseases for which dedicated databases exist.

Identification of multiple hypoxia signatures in neuroblastoma cell lines by l1-l2 regularization and data reduction.

Hypoxia is a condition of low oxygen tension occurring in the tumor and negatively correlated with the progression of the disease. We studied the gene expression profiles of nine neuroblastoma cell lines grown under hypoxic conditions to define gene signatures that characterize hypoxic neuroblastoma. The l(1)-l(2) regularization applied to the entire transcriptome identified a single signature of 11 probesets discriminating the hypoxic state. We demonstrate that new hypoxia signatures, with similar discriminatory power, can be generated by a prior knowledge-based filtering in which a much smaller number of probesets, characterizing hypoxia-related biochemical pathways, are analyzed. l(1)-l(2) regularization identified novel and robust hypoxia signatures within apoptosis, glycolysis, and oxidative phosphorylation Gene Ontology classes. We conclude that the filtering approach overcomes the noisy nature of the microarray data and allows generating robust signatures suitable for biomarker discovery and patients risk assessment in a fraction of computer time.

Severe neuropathy after diphtheria-tetanus-pertussis vaccination in a child carrying a novel frame-shift mutation in the small heat-shock protein 27 gene.

Mutations in small heat-shock protein 27 and small heat-shock protein 22 genes were found in association with Charcot-Marie-Tooth disease type 2 and distal hereditary motor neuropathy. We searched for mutations in small heat-shock protein 27 gene in an Italian family with peripheral neuropathy and intrafamilial phenotypic variability. A novel heterozygous frame-shift mutation c.476_477delCT was found while point mutations in most genes associated with hereditary neuropathies were ruled out. In the proband, who showed a severe early onset peripheral neuropathy, an independent pathogenetic effect on the peripheral nervous system secondary to the tetanus toxoid injection may be supposed. This is the first truncating nonsense mutation in the small heat-shock protein 27 gene identified so far and the clinical, neurophysiologic, and neuropathological findings are discussed.

Clinical features and molecular modelling of novel MPZ mutations in demyelinating and axonal neuropathies.

Mutations in the myelin protein zero (MPZ) gene have been associated with different Charcot-Marie-Tooth disease (CMT) phenotypes, including classical demyelinating CMT1B and the axonal form of the disease (CMT2). The MPZ role in the pathogenesis of both demyelinating and axonal inherited neuropathies was evaluated in the Italian population by screening a cohort of 214 patients with CMT1 or CMT2. A MPZ mutation frequency of 7.9% in demyelinating cases and of 4.8% in axonal cases was observed. In the total cohort (264 patients), including those with mutations in other genes, a mutation frequency of 5.8% (7/121) in demyelinating cases and 4.2% (6/143) in axonal cases was found. Three novel MPZ mutations, two missense (p.Ser111Cys, p.Thr124Ala) and one frameshift (p.Tyr145fs) were found, and a molecular modelling approach was used to test the effects of these mutations on the protein structure. Electrostatic distribution changes within the protein, caused by the amino acid substitution, fit in with phenotypes presented by patients herein described. Our findings suggest that the clinical features associated with MPZ mutations depend partly on the nature of amino acid change and that molecular modelling may provide useful support, based on effects on secondary and tertiary protein structure, to predict the phenotype associated with MPZ mutations.

Gap junction beta 1 (GJB1) gene mutations in Italian patients with X-linked Charcot-Marie-Tooth disease.

X-linked Charcot-Marie-Tooth disease (CMT1X) is a peripheral neuropathy transmitted in a dominant manner and caused by mutations in the Connexin 32 (Cx32) gene (GJB1, gap junction beta 1). Here we report the mutation analysis of the GJB1 gene in 76 subjects with possible CMT1 and absence of 17p11.2 duplication, and in 38 CMT2 patients without mutations in CMT2-associated-genes, selected from a cohort of 684 patients with peripheral sensory-motor neuropathy. The analysis was performed by direct sequencing of the coding sequence and exon/intron boundaries of the GJB1 gene. The mutation screening identified 22 mutations in GJB1, eight of which have not been previously published: six point mutations (c.50C > G, c.107T > A, c.545C > T, c.545C > G, c.548G > C, c.791G > T) and two deletions (c.84delC, c.573_581delCGTCTTCAT). The GJB1 mutation frequency (19.3%) and the clinical heterogeneity of our patients suggest searching for GJB1 mutations in all CMT cases without the 17p11.2 duplication, regardless of the gender of the proband, as well as in CMT2 patients with possible X-linked inheritance.

Nanocomposite polymeric electrolytes to record electrophysiological brain signals in prolonged, unconventional or extreme conditions.

Chemically stable nanocomposite iono-conducting polymeric membranes (based on lithium salts and nanocrystalline oxide powders dispersed in a polymethyl methacrylate matrix) performed successfully in the recording of human brain responses to visual stimulation. Impedance was higher than that of conventional electrodes. However, the electrophysiological signals recorded by acid Al(2)O(3) and neutral Al(2)O(3) 5 wt.% and 10 wt.% nanocomposite gel electrolytes were comparable to those obtained with standard electrodes, even without preliminary skin cleaning and in the absence of gel electrolytes allowing better contact with and skin-electrode ionic conductance. The electrochemical and mechanical characteristics of these membranes make them fit for human and animal research, for clinical application (specifically in emergencies, prolonged electrophysiological recordings), or in unconventional or extreme conditions when fluid electrolytes are unsuitable (e.g., biomedical space research).