Neuronal Apoptosis Revealed by Genomic Analysis: Integrating Gene Expression Profiles with Functional Information

Apoptosis is a key physiological response that occurs during development of the nervous system, resulting in the death of nearly half of the embryonic neuronal population. Aberrant apoptotic mechanisms are thought to contribute significantly to many neurological disorders including Alzheimer’s disease. Although many experiments in the past have demonstrated the requirement of de novo gene expression during neuronal apoptosis, the complete spectrum of genes involved in distinct temporal domains is mostly unknown. To begin a comprehensive survey of the gene-based molecular mechanisms that underlie neuronal apoptosis, we have used the unprecedented experimental opportunities that genome sequences and the development of DNA microarray technology now provide to perform genome-wide expression analysis in different paradigms of neuronal apoptosis. In order to extract knowledge from gene expression information we have developed new informatics applications that enable clustering methods based on semantic characteristics, such as gene ontologies. This review will highlight the use of a genomic approach to identify the molecular program underlying neuronal apoptosis and illustrate how a semantic clustering method can be useful to extract more knowledge from microarray data.     

A genetic approach to ischemic stroke therapy

Stroke therapy will undergo a great revolution in the present decade. The knowledge of the human genome, gene interactions and proteomics will permit a new concept of drug development for stroke. Gene therapy by modification of gene expression will be useful to treat atherosclerosis and hypertensive microangiopathy, or in the acute phase, we will manipulate the acute gene expression induced by ischemia or the apoptotic gene program. However, a single abnormal gene, as in monogenic diseases, is easier to replace than several genes in complex multigenic disorders. Gene therapy, stem cell therapy and neurological grafts for stroke are still in the experimental phase, and many hurdles will have to be jumped before the introduction of these therapies into human clinical stroke trials. A more immediate clinical application of genetics to stroke therapy is the development of pharmacogenetics that analyzes the influence of genetic variability of individuals on drug response. A new era of personalized therapy is dawning where specific DNA biochips will help stroke clinicians to decide on the better use of thrombolytics, neuroprotectants, antithrombotics, statins or antihypertensives.     

DNA microarrays: translation of the genome from laboratory to clinic

As the complete sequences of human and other mammalian genomes become available we are faced with the challenge of understanding how variation in sequence and gene expression contributes to neurological and psychiatric disorders. DNA microarrays, or DNA chips, provide the means to measure simultaneously where and when thousands of genes are expressed. Microarrays are changing the way that researchers approach work at the bench and have already yielded new insights into brain tumours, multiple sclerosis, acute neurological insults such as stroke and seizures, and schizophrenia. The study of disease-related changes in gene expression is the first step in the long process in translation of genome research to the clinic. Eventually, the changes observed in microarray studies will need to be independently confirmed and we wil need to understand how gene expression changes translate into functional effects at the cellular level in the nervous system. Progress in these studies will translate into array-based disease classification schemes and help optimise therapy for individual patients based on gene expression patterns or their genetic background.     

Utility of correlation measures in analysis of gene expression

The role of the correlation structure of gene expression data are two-fold: It is a source of complications and useful information at the same time. Ignoring the strong stochastic dependence between gene expression levels in statistical methodologies for microarray data analysis may deteriorate their performance. However, there is a host of valuable information in the correlation structure that deserves a closer look. A proper use of correlation measures can remedy deficiencies of currently practiced methods that are focused too heavily on strong effects in terms of differential expression of genes. The present paper discusses the utility of correlation measures in microarray data analysis and gene regulatory network reconstruction, along with various pitfalls in both research areas that have been uncovered in methodological studies. These issues have broad applicability to all genomic studies examining the biology, diagnosis, and treatment of neurological disorders.     

Gene Editing and Modulation: the Holy Grail for the Genetic Epilepsies?

Epilepsy is a complex neurological disorder for which there are a large number of monogenic subtypes. Monogenic epilepsies are often severe and disabling, featuring drug-resistant seizures and significant developmental comorbidities. These disorders are potentially amenable to a precision medicine approach, of which genome editing using CRISPR/Cas represents the holy grail. Here we consider mutations in some of the most ‘common’ rare epilepsy genes and discuss the different CRISPR/Cas approaches that could be taken to cure these disorders. We consider scenarios where CRISPR-mediated gene modulation could serve as an effective therapeutic strategy and discuss whether a single gene corrective approach could hold therapeutic potential in the context of homeostatic compensation in the developing, highly dynamic brain. Despite an incomplete understanding of the mechanisms of the genetic epilepsies and current limitations of gene editing tools, CRISPR-mediated approaches have game-changing potential in the treatment of genetic epilepsy over the next decade.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13311-021-01081-y.     

Gene expression profiling in multiple sclerosis brain

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system and the leading cause of non-traumatic neurological disability in young adults in the United States and Europe. The clinical disease course is variable and starts with reversible episodes of neurological disability in the third or fourth decade of life. Microarray-based comparative gene profiling provides a snapshot of genes underlying a particular condition. Several large scale microarray studies have been conducted using brain tissue from MS patients. In this review, we summarize existing data from different gene expression profiling studies and how they relate to understand the pathogenesis of MS.     

Homozygous contiguous gene deletion of 13q12 causing LGMD2C and ARSACS in the same patient

We describe a 10‐year‐old girl with limb‐girdle muscular dystrophy type 2C (LGMD2C, gamma‐sarcoglycan deficiency) with additional features that include progressive lower limb spasticity, peripheral neuropathy, and ataxia. The gene for LGMD2C lies in close approximation to the gene for autosomal recessive spastic ataxia of Charlevoix–Saguenay (ARSACS) on chromosome 13q12. The clinical presentation was suspicious for a genomic rearrangement affecting the expression of both genes. Using chromosomal microarray analysis, a homozygous deletion that encompassed the genes for both disorders was identified. This is the first report of a patient with both neurological diseases, and this case illustrates the clinical utility of microarray technology in the investigation of patients with unusual presentations. Muscle Nerve 39: 396–400, 2009     

Use of microarrays in the search of gene expression patterns: application to the study of complex phenotypes

Sequencing the human genome has prompted the development of new technologies, which have emerged as promising methodological and scientific tools for advancing the current knowledge about the causes and mechanisms involved in various complex disorders. Among those, the high-throughput technique known as microarray is particularly powerful in providing a global view of gene expression patterns in biological samples. By the simultaneous determination of the expression levels of thousands of genes, microarrays allow researchers to compare the molecular behaviour of different types of cells lines or specific tissues that have been exposed to pathological or experimental conditions. The method may provide insights into physiological processes and facilitate the identification of novel biological markers for diagnostic, prognostic and pharmacological treatments for a number of diseases. In this article, we present theoretical and methodological concepts underlying the microarray technology, as well as an overview of its advantages, perspectives and future scientific directions. In an attempt to demonstrate the applicability and efficiency of the method in the study of complex phenotypes, initial results on gene expression studies in post mortem brain samples of psychiatric patients and on the molecular and functional consequences of sleep disturbances, which is strongly associated with psychiatric illness, will be described and discussed.     

Making yeast tremble

Genetic experiments in mice, which are indispensable for studying the molecular basis of neurological disorders, have certain limitations that include slow pace and high costs. It is therefore not surprising that in recent years numerous neurological diseases have been modeled in genetically tractable organisms, including Drosophila, Caenorhabditis elegans, and yeast. Yeast models in particular have a special advantage with respect to genome-wide experimental approaches as a result of the completed sequencing of the genome, the availability of a collection of precise deletion mutants of every gene in the genome, and the rapidly evolving databases of yeast protein-protein interactions and gene expression patterns. These large and easily accessible bodies of information, coupled with the ease with which yeast can be manipulated genetically, have led to dissection of novel mechanisms of neurodegenerative disorders. In this review, we discuss how studies in yeast models have already resulted in significant insights into the understanding of neurodegenerative disorders that include prion disease, Parkinson's disease, polyglutamine expansion disorders, Friedreich's ataxia, and Batten disease.     

The genomic profile of the cerebral cortex after closed head injury in mice: effects of minocycline

Microarray analysis was used to delineate gene expression patterns and profile changes following traumatic brain injury (TBI) in mice. A parallel microarray analysis was carried out in mice with TBI that were subsequently treated with minocycline, a drug proposed as a neuroprotectant in other neurological disorders. The aim of this comparison was to identify pathways that may be involved in secondary injury processes following TBI and potential specific pathways that could be targeted with second generation therapeutics for the treatment of neurotrauma patients. Gene expression profiles were measured with the compugen long oligo chip and real-time PCR was used to validate microarray findings. A pilot study of effect of minocycline on gene expression following TBI was also carried out. Gene ontology comparison analysis of sham TBI and minocycline treated brains revealed biological pathways with more genes differentially expressed than predicted by chance. Among 495 gene ontology categories, the significantly different gene ontology groups included chemokines, genes involved in cell surface receptor-linked signal transduction and pro-inflammatory cytokines. Expression levels of some key genes were validated by real-time quantitative PCR. This study confirms that multiple regulatory pathways are affected following brain injury and demonstrates for the first time that specific genes and molecular networks are affected by minocycline following brain injury. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.