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Original Article : A Spotlight on Various and the Importance of Their Integration Erica Sequeira and Saraswathy Nagendran*

SVKM`s NMIMS Shobhaben Pratapbhai Patel School of Pharmacy and Technology , Vile Parle (W), Mumbai, India

ABSTRACT

Brain is one of the most complex organs of the body and thus the challenge in would seem the effort of understanding the complex structure, function, and development of the in healthy as well as diseased condition. Such understanding requires the integration of huge amounts of heterogeneous and complex collected at various levels of investigation. Neuroinformatics combines neuroscience with /technology and deals with the creation and maintenance of web accessible databases that will be required to achieve such integration. There is significant interest amongst in sharing neuroscience data and analytical tools which provides the opportunity to differently re- Address for analyze previously collected data and encourage new neuroscience Correspondence interpretations that facilitates further development. However, information is usually stored in various databases, managed by SVKM`s NMIMS heterogeneous management systems or files, spreadsheets Shobhaben Pratapbhai etc. which results into inaccuracy and inconsistencies in data Patel School of acquisition and processing, lack of coordination resulting in Pharmacy and duplication of efforts and of resources. Thus an integration of Technology databases is a vital solution to these problems. This article, analyses Management, Vile various databases in the field of neuroscience along with the Parle (W), Mumbai, importance of integration of databases. India. E-mail: saraswathy76 Keywords: Neuroscience, Databases, Nervous system, , @gmail.com .

INTRODUCTION Neuroinformatics as a field for decade witnessed a development which understanding the nervous system in healthy involved dealing with the complex types of as well as the diseased condition was data that is required during the . In initiated in the early 19001. The subsequent 2000, a paper had suggested that databases

American Journal of Phytomedicine and Clinical Therapeutics www.ajpct.org Nagendran et al______ISSN 2321 – 2748 were needed to organize the numerous Neuroinformatics databases databases and tools2. Around 2004, a database (SfN (Society for Neuroscience) Brain imaging database Neuroscience Database Gateway 2007)3 that Current techniques in brain imaging emerged to satisfy this need. Many are divided into mainly two different areas, investigators realized that the was firstly, structural imaging technique for a vital tool to keep a track of the series of studying the anatomy of the brain, for letters that represented the base sequence example, computerized tomography (CT) and that makes up the nucleic acids (e.g. GCAT) magnetic resonance imaging (MRI) and or the sequence of amino acids that makes secondly, functional imaging techniques for up the protein molecule4-7. European studying its functions or the connectivity of Molecular Biology laboratory’s EMBL- the brain, for example, functional magnetic Bank and the National Center for resonance imaging (fMRI), positron emission Biotechnology Information GenBank, were tomography (PET), and diffusion tensor launched in the early 1980s for databases of imaging (DTI). genes8,9. Neuroinformatics is a field that capitalizes on the potential synergies Brain-development.org between neuroscience and information It is a part of the research project in technology (IT) such as: deals with the the Imperial college London which contains application of advanced IT methods to deal datasets of over 600 MRI images of healthy with the flood of neuroscientific data by subjects which utilizes T1 T2 and PD developing and applying weighted images, MRA images, DTI images, methods for the study of the brain; by and Diffusion weighted images of normal and providing both analytical and numerical healthy human . It also gives the tools for theoretically modeling brain demographic information of each subject11. function; and by exploiting our insights into the principles underlying brain function to Brainmuseum.org develop new IT technologies. With the It is a public web site that provides the development of many methods of studying images and the information of well preserved, the brain, researchers have studied the brain sectioned and stained brains of over 100 using various technologies such as magnetic species of mammals including humans. resonance imaging (MRI), functional Stained sections of several species such as magnetic resonance imaging (fMRI), and humans, chimpanzees, monkeys, carnivores, computerized tomography (CT) to study rodents, California sea lion, Big brown bat, functions, connectivity, and structures of the American badger, American Racoon, yellow brain; microarray, in situ hybridization mongoose, zebra, cow and Atlantic Bottle (ISH) and next generation sequencing nose Dolphin is available and it explains how (NGS) to study the molecular of the the evolution of brain occurred12. brain; (EEG) and magnetoencephalography (MEG) to study Harvard whole brain atlas the electrophysiology of the brain10. Thus, It is a comprehensive and a well neuroscience has become essential to the designed site that contains a huge compilation neuroscience investigators and clinicians for of modern cross sectional signaling including conducting scientific inquiry, understanding CT, MRI and SPECT in health and diseased the cause and pathogenesis of a brain condition of brains such as cerebrovascular disorder and practicing . diseases, neoplastic diseases, degenerative

AJPCT[2][8][2014]976-984 Nagendran et al______ISSN 2321 – 2748 diseases, and infections and inflammatory and integrated due to the complexity and diseases13. diversity of it. In spite of all these difficulties some databases and tools are developed and Brainmap.org available now. It is a database of published functional and structural experiments with NeuroElectro coordinate-based results (x, y, z) in Talairach It is a database describing the or Montreal Neurological Institute (MNI) electrophysiology properties of different space. It involves the development of types so as to understand the role of and tools to share neuroimaging diversity across neuron types. Using a results and enable meta-analysis of studies of combination of manual and automated function and structure in healthy methods it describes a methodology to curate and diseased subjects14. the neuron electrophysiology information into a centralized database and facilitates the Brainmaps.org discovery of neuron-to-neuro relationships18. It is an interactive multiresolution next generation brain atlas that is based on Code Analysis, Modeling and Repository for over 20 million megapixels of submicron E-Neuroscience (CARMEN) Project resolution, annotated, scanned images of It provides a web based portal serial sections of both primates, e.g. Homo platform through which users can share and sapiens and non-primate brain, e.g. Carassius collaboratively exploit data such as the neural auratus. In addition, it also contains activity recording including and series connectivity maps, .org of some of images; analysis code and expertise in species such as Caenorhabditis elegans15,16. neuroscience19.

Neuromorpho.org Collaborative Research in Computational It is the largest public repository of 3- Neuroscience (CRNCS) D digital neuronal reconstruction and It provides a forum of discussion over associated metadata. It is an inventory that electrophysiological datasets as well as contains 7,986 digitally reconstructed involved in sharing data. Data sets of this and is associated with peer-reviewed forum include the , auditory publications, it can be used for analysis, cortex, , eye movements, lateral visualization and modelling of neuronal geniculate nucleus in the mouse. It gives data17. information about data collection, experimental conditions, identifying the Electrophysiological databases species, surgical procedures and the special Brains achieve efficient functioning recording techniques20. due to different neurons that serve distinct computational role. One striking way in Brain connectivity databases which the neuron types differ is their To transfer information between electrophysiological properties. Electro- anatomical structures of a brain, the brain is physiology of the brain is an important aspect wired with a dense network of electrical since the biological information is converted signals such as the axonal connections and into electrical signals for the brain to interpret. synapses. But there are many connections However there are no firm standards how between the brain components of various electrophysiological data is to be described scales to an entire brain regional scale, and

AJPCT[2][8][2014]976-984 Nagendran et al______ISSN 2321 – 2748 different technologies are required for the BAMS is that it has atlas and parsing engine. analysis of each scale of connection. The parsing engine makes connectivity map Connectomes are divided to micro containing brain regions and connection and macro connectome on the strength. Since it has 5 atlases so it can easily basis of data scale of connections. be related to the other neuroscience Micro connectome is a matrix of all databases24. axonal connection between all individual neurons. Open connectome project is open to Databases for genetic information anybody to view, manipulate, analyze and Gene expressions in various brain contribute. It is interested in all levels, from regions and various cell types are important nano (using electron microscopy) to macro information for understanding a relationship (using magnetic resonance imaging). It between regulation of molecular level and provides the neuroanatomical images and the physiological level of brains. The volume of ultimate aim is to reconstruct the 3D model of genetic data has grown exponentially and brain. Meso connectomes is a matrix of all have studied gene expression of axonal connections between all neuron types. brains. Macro connectomes (connectivity matrices at brain regions level), focuses on the strength of SigCS base connections and the number of neurons It is an integrated genetic information between two brain regions21. Macro resource for human cerebral stroke. SigCS connectome data is usually obtained from base is an effective tool that can assist fMRI (functional Magnetic Resonance researchers in the identification of the genetic Imaging), Diffusion MRI, and DTI (Diffusion factors associated with stroke by utilizing Tensor Imaging)22. existing literature information, selecting candidate genes and variants for experimental CoCoMac studies, and examining the pathways that It is the main database and contains contribute to the pathophysiological data from tracing studies on anatomical mechanisms of stroke. The current version of connectivity in the macaque . SigCS base documents 1943 non-redundant The combined results are used for genes with 11472 genetic variants and 165 constructing the macaque macro connectome. non-redundant pathways25. It provides connectivity matrix data of primate brains. Since connectivity matrix is Gene expression omnibus (GEO) well-quantized such as each cell of matrix has It was a project initiated in response to a number of neurons composing each the growing demand for public repository for connection, its data can be easily interpreted high-throughput gene expression data. It and its use is facilitated by data provides a flexible and an open design that technique. CoCoMac also provides large facilitate submission, storage and retrieval of amount of data and 3D graphics23. heterogeneous data sets from gene expression and genomic hybridization experiments26. BAMS (Brain architecture management system) ArrayExpress It is an online database having the It is a new public database of information about the neural circuitry, brain microarray gene expression data which is a connectivity database and an ontology of generic gene expression database designed to brain regions. One of the special features of hold data from all microarray platforms.

AJPCT[2][8][2014]976-984 Nagendran et al______ISSN 2321 – 2748

ArrayExpress uses the annotation standard Databases related to brain disorders minimum information about a Microarray The various brain disorders such as Experiment (MIAME) and the associated Alzheimer’s disease, Parkinson’s disease, XML data exchange format Microarray Gene Huntington’s disease, depression, bipolar Expression Markup Language (MAGE-ML) disorder, schizophrenia, and so on are treated and it is designed to store well annotated data by various therapies and drugs. Due to the in a well organized way. Both, the GEO and complexity involved in the mechanism and ArrayExpress are representative repositories treatment strategies, it is of interest to collate of publicly available gene expression data the different brain disorders in the form of a from National Center for Biotechnology database. Information (NCBI) and European Institute (EBI). They stored Alzheimer’s disease neuroimaging initiative vast amount of gene expression profiles from (ADNI) brains of various species, various brain Unites the researchers with study data regions, including the brains with some as they work to prevent and treat the disorders27. progression of Alzheimer’s disease. ANDI researchers collect, validate and utilize data Allen brain atlas such as MRI and PET images, genetics, A growing collection of public cognitive tests, CSF and blood biomarkers as resources integrating gene expression and predictors for the disease. Using this database, neuroanatomical data. Interestingly, in researchers can validate their biomarkers addition, it also has launched Allen obtained from MRI / PET imaging, blood Developing Mouse Brain Atlas, Allen Human tests and tests of cerebrospinal fluid for Brain Atlas. Allen Developing Mouse Brain Alzheimer's disease (AD) clinical trials and Atlas is gene expression data in the mouse diagnosis29. brain beginning with mid-gestation through to juvenile / young adult. The Allen Developing Major depressive disorder neuroimaging Mouse Brain Atlas shows temporal and database (MaND) spatial regulation of gene expression of Provides an Excel spreadsheet file mouse brain. Allen Human Brain Atlas containing database and meta-analysis. The provides gene expression from human whole database contains information of 225 studies brain regions which is the first and unique which have investigated brain structure (using multi-modal gene expression atlas of the MRI and CT scans) in patients with major human brain. The interesting features include depressive disorder compared to a control both simple and sophisticated methods for group. 143 studies and 63 brain structures are gene searches, colorimetric and fluorescent included in the meta-analysis30. ISH image viewers, graphical displays of ISH, microarray and RNA sequencing data, The open access series of imaging studies Brain Explorer software for 3D navigation of A series of magnetic resonance anatomy and gene expression, and an imaging data sets that is publicly available for interactive reference atlas viewer. In addition, study and analysis. The cross sectional MRI cross data set searches enable users to query data contains images of 416 subjects aged 18 multiple Allen Brain Atlas data sets to 96 and longitudinal MRI data in non simultaneously28. demented and demented older adults. Longitudinal MRI data contains longitudinal collection of 150 subjects aged 60 to 96. In

AJPCT[2][8][2014]976-984 Nagendran et al______ISSN 2321 – 2748

Longitudinal MRI datasets, 72 subjects were status of mental illness (e.g. depression) and not demented throughout the study, 64 that information can be used for surveying the subjects were characterized as demented at brain disorders. Thus it gives the information initial image, and 14 subjects were not about the prevalence of the major diseases demented at initial image and subsequently and the risk factors for the diseases40. characterized as demented through a longitudinal study31. Integration of databases PDGene, SZGene, ALSGene, With the increasing amount of data of MSGene and Alzgene are examples of brain generated from technologies there has databases for providing Parkinson’s disease, been an increasing need of integration of schizophrenia, amyotrophic lateral sclerosis, databases as well as codifying them in multiple sclerosis, and Alzheimer’s disease standard formats. genetic association studies with sufficient Neuroscience Information Framework data32-36. (NIF) is one such example which provides the information network and has integrated over MDPD (Mutation database for parkinson’s 174 datasets and databases. It is meant for disease) researchers to discover and access to a large Provides not only an integrated amount of public neuroscience data and tools genetic information resource for Parkinson’s easily, thus serves as a single hub for disease but also each genetic substitution and neuroscience information41. the resulting impact with its reference37. Neuronames is a comprehensive hierarchical nomenclature for structures of the DND (Database of Neurodegenerative primate (human and macaque) brain used as Disorders) an indexing structure for computer systems. It An on-line web based database that defines the brain using 550 primary structures contains more than 100 neuro related disease and includes other related structures, names, concepts and provides with a covering of all and synonyms. Neuronames contains 15,000 related genes, proteins, pathways and drug neuroanatomical terms, and shows information. The interface offers different hierarchical relationship between each options to learn about the disease causing structures and neuroanatomical terms42. molecular factors38. Combination of databases have their own advantages, for example, different gene Environment Wide Association Study expressions from postmortem brain studies of (EWAS) mental illness can be caused by not only Using environmental factors with effects of mental illness but also by treatments brain disorders can be conducted for brain of the brain disorder. Leon French et al., disorders39. 2011, studied relationship between gene expression and neuroanatomical connectivity National Health and Nutrition Examination in the adult rodent brain43 by utilizing a large Survey (NHANES) data set of the rat brain “connectome” from Provides studies designed to assess the Brain Architecture Management System the health and nutritional status of adults and and used statistical approaches to relate the children in the United States, carried out by data to the gene expression signatures of interviews and physical examinations. It 17,530 genes in 142 anatomical regions from contains information of samples about not the Allen Brain Atlas. Their results showed only environmental factors but also clinical that gene expression signature of mouse brain

AJPCT[2][8][2014]976-984 Nagendran et al______ISSN 2321 – 2748 regions are significantly related to CONCLUSION connectivity of mouse brain regions and also found a set of genes that are closely correlated Through this survey, various with neuroanatomical connectivity. Lior Wolf databases of different information types has et al., 2011, also studied the link between been represented. Various databases are gene expressions of mouse brain regions and already available for the researchers so as to neural connectivity patterns of mouse brain understand the brain in every aspect and more regions44 by using Allen Brain Atlas and information would be available in future to Brain Architecture Management System. the researchers. Thus, the researchers have They found that through the gene expression increased opportunities to study the brain levels of mouse brain regions it is possible to from new perspectives using these databases. predict the connectivity of mouse brain Integrating the databases is a novel approach regions. Byungkyu Part et al., combined towards understanding the brain which genome-wide microarray- based gene decreases the chances of errors and helps in expression profiles and diffusion tesnsor better understanding of the brain. Despite the images of human brain to study Alzheimer’s research being very active in the past 20 disease45. They modelled the interactions of years, integration of databases has to be Alzheimer related genes from the fiber achieved at all levels and the effort to solve pathway by using microarray data of Allen the integration issues should be continued so Human Brain Atlas and diffusion tensor that the proposed methodologies are images of Allen Brain Atlas. evaluated through experiments.

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