The enlargement and species-specific elaboration of the cerebral neocortex during evolution holds the secret to the mental abilities of humans; however, the genetic origin and cellular mechanisms that generated the distinct evolutionary advancements are not well understood. This article describes how novelties that make us human may have been introduced during evolution, based on findings in the embryonic cerebral cortex in different mammalian species. The data on the differences in gene expression, new molecular pathways and novel cellular interactions that have led to these evolutionary advances may also provide insight into the pathogenesis and therapies for human-specific neuropsychiatric disorders.

/pdf/evolution-of-the-neocortex-a-perspective-from-developmental-j3mn8rfbcd.pdf

Evolution of the neocortex: a perspective from developmental biology

The introduction of in vitro nucleic acid amplification techniques, led by real-time PCR, into the clinical microbiology laboratory has transformed the laboratory detection of viruses and select bacterial pathogens. However, the progression of the molecular diagnostic revolution currently relies on the ability to efficiently and accurately offer multiplex detection and characterization for a variety of infectious disease pathogens. Microarray analysis has the capability to offer robust multiplex detection but has just started to enter the diagnostic microbiology laboratory. Multiple microarray platforms exist, including printed double-stranded DNA and oligonucleotide arrays, in situ-synthesized arrays, high-density bead arrays, electronic microarrays, and suspension bead arrays. One aim of this paper is to review microarray technology, highlighting technical differences between them and each platform's advantages and disadvantages. Although the use of microarrays to generate gene expression data has become routine, applications pertinent to clinical microbiology continue to rapidly expand. This review highlights uses of microarray technology that impact diagnostic microbiology, including the detection and identification of pathogens, determination of antimicrobial resistance, epidemiological strain typing, and analysis of microbial infections using host genomic expression and polymorphism profiles.

Basic Concepts of Microarrays and Potential Applications in Clinical Microbiology

Septic syndromes represent a major although largely underrecognized healthcare problem worldwide, accounting for thousands of deaths every year. It is now agreed that sepsis deeply perturbs immune homeostasis by inducing an initial tremendous systemic inflammatory response which is accompanied by an anti-inflammatory process, acting as negative feedback. This compensatory inhibitory response secondly becomes deleterious as nearly all immune functions are compromised. These alterations might be directly responsible for worsening outcome, as they may play a major role in the decreased resistance to nosocomial infections in patients who survived initial resuscitation. Consequently, immunostimulatory therapies may now be assessed for the treatment of sepsis. This review focuses on immune dysfunctions described in septic patients and on their potential use as markers on a routine standardized basis for prediction of adverse outcome or of occurrence of secondary nosocomial infections. This constitutes a prerequisite to a staging system for individualized treatment for these hitherto deadly syndromes.

Monitoring immune dysfunctions in the septic patient: a new skin for the old ceremony.

Although several dozen studies of gene expression in sepsis have been published, distinguishing sepsis from a sterile systemic inflammatory response syndrome (SIRS) is still largely up to clinical suspicion. We hypothesized that a multicohort analysis of the publicly available sepsis gene expression data sets would yield a robust set of genes for distinguishing patients with sepsis from patients with sterile inflammation. A comprehensive search for gene expression data sets in sepsis identified 27 data sets matching our inclusion criteria. Five data sets (n = 663 samples) compared patients with sterile inflammation (SIRS/trauma) to time-matched patients with infections. We applied our multicohort analysis framework that uses both effect sizes and P values in a leave-one-data set-out fashion to these data sets. We identified 11 genes that were differentially expressed (false discovery rate ≤1%, inter–data set heterogeneity P > 0.01, summary effect size >1.5-fold) across all discovery cohorts with excellent diagnostic power [mean area under the receiver operating characteristic curve (AUC), 0.87; range, 0.7 to 0.98]. We then validated these 11 genes in 15 independent cohorts comparing (i) time-matched infected versus noninfected trauma patients (4 cohorts), (ii) ICU/trauma patients with infections over the clinical time course (3 cohorts), and (iii) healthy subjects versus sepsis patients (8 cohorts). In the discovery Glue Grant cohort, SIRS plus the 11-gene set improved prediction of infection (compared to SIRS alone) with a continuous net reclassification index of 0.90. Overall, multicohort analysis of time-matched cohorts yielded 11 genes that robustly distinguish sterile inflammation from infectious inflammation.

A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set

Aneuploidy, or an aberrant karyotype, results in developmental disabilities and has been implicated in tumorigenesis. However, the causes of aneuploidy-induced phenotypes and the consequences of aneuploidy on cell physiology remain poorly understood. We have performed a metaanalysis on gene expression data from aneuploid cells in diverse organisms, including yeast, plants, mice, and humans. We found highly related gene expression patterns that are conserved between species: genes that were involved in the response to stress were consistently upregulated, and genes associated with the cell cycle and cell proliferation were downregulated in aneuploid cells. Within species, different aneuploidies induced similar changes in gene expression, independent of the specific chromosomal aberrations. Taken together, our results demonstrate that aneuploidies of different chromosomes and in different organisms impact similar cellular pathways and cause a stereotypical antiproliferative response that must be overcome before transformation.

/pdf/transcriptional-consequences-of-aneuploidy-vrk5j4hkpc.pdf

Transcriptional consequences of aneuploidy

Down syndrome, caused by trisomic chromosome 21, is the leading genetic cause of mental retardation. Recent studies demonstrated that dosage-dependent increases in chromosome 21 gene expression occur in trisomy 21. However, it is unclear whether the entire transcriptome is disrupted, or whether there is a more restricted increase in the expression of those genes assigned to chromosome 21. Also, the statistical significance of differentially expressed genes in human Down syndrome tissues has not been reported. We measured levels of transcripts in human fetal cerebellum and heart tissues using DNA microarrays and demonstrated a dosage-dependent increase in transcription across different tissue/cell types as a result of trisomy 21. Moreover, by having a larger sample size, combining the data from four different tissue and cell types, and using an ANOVA approach, we identified individual genes with significantly altered expression in trisomy 21, some of which showed this dysregulation in a tissue-specific manner. We validated our microarray data by over 5,600 quantitative real-time PCRs on 28 genes assigned to chromosome 21 and other chromosomes. Gene expression values from chromosome 21, but not from other chromosomes, accurately classified trisomy 21 from euploid samples. Our data also indicated functional groups that might be perturbed in trisomy 21. In Down syndrome, there is a primary transcriptional effect of disruption of chromosome 21 gene expression, without a pervasive secondary effect on the remaining transcriptome. The identification of dysregulated genes and pathways suggests molecular changes that may underlie the Down syndrome phenotypes.

/pdf/primary-and-secondary-transcriptional-effects-in-the-hdtv22l4v9.pdf

Primary and secondary transcriptional effects in the developing human Down syndrome brain and heart

Background Based on recent in vitro data, we tested the hypothesis that microarray expression profiles can be used to diagnose sepsis, distinguishing in vivo between sterile and infectious causes of systemic inflammation. Study design Exploratory studies were conducted using spleens from septic patients and from mice with abdominal sepsis. Seven patients with sepsis after injury were identified retrospectively and compared with six injured patients. C57BL/6 male mice were subjected to cecal ligation and puncture, or to IP lipopolysaccharide. Control mice had sham laparotomy or injection of IP saline, respectively. A sepsis classification model was created and tested on blood samples from septic mice. Results Accuracy of sepsis prediction was obtained using cross-validation of gene expression data from 12 human spleen samples and from 16 mouse spleen samples. For blood studies, classifiers were constructed using data from a training data set of 26 microarrays. The error rate of the classifiers was estimated on seven de-identified microarrays, and then on a subsequent cross-validation for all 33 blood microarrays. Estimates of classification accuracy of sepsis in human spleen were 67.1%; in mouse spleen, 96%; and in mouse blood, 94.4% (all estimates were based on nested cross-validation). Lists of genes with substantial changes in expression between study and control groups were used to identify nine mouse common inflammatory response genes, six of which were mapped into a single pathway using contemporary pathway analysis tools. Conclusions Sepsis induces changes in mouse leukocyte gene expression that can be used to diagnose sepsis apart from systemic inflammation.

https://www.journalacs.org/article/S1072-7515(06)01082-9/pdf

Molecular diagnostics in sepsis : From bedside to bench

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Primary and secondary transcriptional effects in the developing human Down syndrome brain and heart

Molecular diagnostics in sepsis : From bedside to bench