If we consider the depleting ozone layer and the harmful UV rays responsible for all our skin troubles then it's time we rethink! A considerable number of genetic disorders too have dermatological manifestations and these are called Genetic dermatological disorders or Genodermatoses like Epidermolysis bullosa, Hailey Hailey disease etc. An article by Eve J. Lowenstein, published in The History of Dermatology Society Letter (2011) has provided evidences tracing the origin of genodermatoses, Basal cell nevus syndrome (BCNS), also known as Gorlin-Goltz syndrome back to the Egyptians dynasty (about 3000 years ago) . A recent study by Hamami et al. enlisted ichthyosis, epidermolysis bullosa (plakoglobin), neurofibromatosis, palmoplantar keratoderma (plakoglobin), darier's disease and xeroderma pigmentosa as the most common genodermatosis among Iraqi patients .
The phenotypic manifestations of dermatological disorders may be contributed by a single gene or multi-gene abnormalities. However, sometimes they are multifactorial in origin involving a complex interplay of various genetic and environmental factors. Due to the synergy of genetic and epigenetic factors, the incidence of skin disorders has increased tremendously and has led to a high economic burden. The past two decades have seen a linear growth in the number of known and described genodermatoses. From about 90 catalogued in 1991, the number increased to 580 in 2007[3-5]. Development of advanced treatments such as skin grafting, hair transplant, laser therapies etc. have diverted the focus of medical community from basic research of understanding the underlying causes of these manifestations to development of full-fledged techniques for directed personalized treatments. These in many cases have resulted in adverse side-effects as the available procedures were developed before completely understanding the underlying mechanism of disease occurrences. An organized study of the genotypic and environmental factors responsible for causing these diseases will probably elucidate common pathways and interlinks in their phenotypic expression.
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Several techniques used in a molecular biology/genetics have been extended for their application in understanding genodermatoses, with special focus on gene sequencing, polymerase chain reaction (PCR), DNA micro arrays and genotyping. Gene identification strategies such as Positional and Functional Cloning are being used to identify disease causing genes . To determine the genetic causes underlying various skin disorders, a number of Genome wide association studies (GWAS) and linkage analysis studies have been undertaken. The results of these studies have also revealed some unexpected associations. More than 80 different genes involved in various metabolic processes have been found to be associated with genodermatosis . The molecular basis of majority of the diseases has been explicated .
With their phenotypic manifestations ranging from minor to exceedingly severe and their increasing global distribution, dermatological diseases has become a major healthcare concern these days. Projects like The TAG (Together Against Genodermatoses) has been started to improve the health care and provide social support for patients and family affected by severe genodermatoses . It is hoped that DerMA will serve as a readily available resource for mutational information regarding every gene associated with risk of the various genodermatoses and would thus help minimize website hopping for mutational information regarding these diseases.
2. Construction and content
The Dermatological Mutation and Association database (DerMA) is developed keeping in mind the large number of mutations found in people diagnosed with dermatological diseases which might be associated with these diseases. This is a relational database that has been curated manually by the authors. Database developmental process was divided into three phases as described below:
2.1 Phase I:
An exhaustive literature survey was done and relevant data extracted from various literature sources [10-17] and a list of 296 genetic skin disorders was compiled [Figure 1]. For every mutation the information gathered in the database includes related disease, Disease classification, alternative names of the disease, observable phenotypic changes, HGNC gene symbols, chromosomal location of associated loci, types of mutation, SNP information such as ID (in the form of rs_ID), mutational Changes, variant/location of (exon, DNA, RNA and Protein), ethnic and geographic origins of patients studied, along with the Pubmed id of the reference reporting the mutation.
The primary disease information such as its classification, alternate Names and Common Symptoms reported were obtained from Genetic Skin Disorders by Virginia P. Sybert and Rook's Textbook of Dermatology [16-17]. The reliability of the information was confirmed from Online Mendelian Inheritance in Man (OMIM), which is online database containing vast information for various genetic human diseases. The list of vulnerable genes obtained from literature and OMIM was not exhaustive , therefore, databases such as Human Gene Mutation Database (HGMD), Human Genome Variation Database (HGVbase) and Genetic Association Database (GAD) were referred [12-14]. The gene specific information which includes Gene name and its Chromosomal location were retrieved from HUGO Gene Nomenclature Committee (HGNC) .
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The main emphasis was on collecting disease related Single Nucleotide Polymorphisms. Disease related SNPs were found and their corresponding variant information for SNPs was retrieved from dbSNP . Locus Specific databases were reviewed to check for any overlooked information . The data was filtered to remove inconsistencies and compiled into a single, composite, non-redundant database. After an exhaustive survey, we identified 15573 polymorphisms in 341 genes and 296 diseases (65 of the total 296 were found not to have a gene mapped for them).
2.2 Phase II:
Develop a Relational database and data entry (Database Development):
A relational model was created to minimize redundancy and to enable the storage of raw data in an organized format. The relational model of the database is represented in [Figure 2]. The database was developed using MySQL workbench.
2.3 Phase III:
Web Interface development:
DerMA is a user friendly database that has been designed keeping in mind the user's perspective. It is easily accessible and can be used to retrieve the information of interest using disease name, gene or mutation ID (rs_ID or the DerMA ID) as keywords. Disease search can be carried out in 2 ways:
(a) The disease classification (class and subclass) which results in the display of a list of all the diseases based on that classification. The disease of interest can then be selected from this list.
(b) The disease name (if the user is unaware of the class and subclass of the disease) resulting in retrieval of the disease information and a list of associated genes.
The database can also be searched by gene name/HGNC symbol in order to obtain mutational information for specific genes. After the gene is selected, the user is presented with a list of associated diseases from which the disease of interest can be marked for further information. The search can further be refined by specifying the type of mutational information that the user wants to retrieve.
Users can also search directly for a SNP using its rsID and/or a unique DerMA id given to each mutation contained within the database. After the rsID/DerMA id is selected the user can view the associated gene and the disease associated with the mutation. A general scheme for the same has been shown in [Figure 3].
A separate page for mutation submission is provided for the user to expand and update the database with the most recently identified mutations.
3. Utility and Discussion
DerMA is designed to provide a readily available resource for identifying various genes responsible for dermatological manifestations of diseases. This database would enable categorization of various genes causing disorders of the skin based on similar phenotypic manifestations, thereby paving the way for pattern identification.
A compiled list of bio-markers would allow improved data analysis for determining the link between mutations at specific structural positions, their chances of causing diseases and the effect of silent mutations on disease phenotypes. The relationships between various mutations and polymorphisms in a population and its susceptibility of causing a disease in that population can be understood. Analysing the data could help us predict the probability of a particular disease with known affected chromosome and/or genes. The information can be used to create a genetic map that may reveal hotspots for genodermatoses. Creating a physical map will provide knowledge about the Disease-Gene associations giving insights into complex mechanism of multifactorial diseases. Drug targets for multiple diseases can also be predicted.
Knowledge of various mutations, especially SNPs linked with diseases and their correlation with protein structure would help in understanding the underlying mechanism of the disease and would facilitate its prediction and drug discovery. The field of pharmacogenomics is growing rapidly and the scope of personalized medicines is at its forefront. With very low pharmacogenomics and pharmacogenetics studies done on drugs used for dermatological disorders, DerMA can be a handy resource for identifying potential drug targets. The disease causing genes may be common to certain classes of diseases or those with similar phenotypic manifestations. Different genes may possibly interact in specific pathways and patterns giving rise to these disorders. Upon identification, such genes could be studied further to provide a better perceptive of the effects of mutations on diseases. A direct ramification of this would be the identification of individuals with high susceptibility to a disease as well as the prediction of undiscovered diseases causing mutations on the basis of the discovered patterns.
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DerMA is available at the URL http://dermaa.dce.edu/. It is a free-access database available online for academic research and non-commercial purpose only.
The author(s) declare that they have no competing interests
GK, MA, GS and PK collected and analysed data. GK, PK and YH prepared manuscript. MA and GS designed DerMA. YH conceived, designed and coordinated the study. All authors read and approve final manuscript.
Authors acknowledge Miss Deepika Jaggi for providing her inputs during the drafting of the manuscript.
List of abbreviations
DerMA Dermatological Mutational Association database
OMIM Online Mendelian Inheritance in Man
HGMD Human Genetic Mutation Database
HGVbase Human Genome Variation Database
GAD Genetic Association Database
SNP Single nucleotide polymorphism
dbSNP SNP database
HTML Hypertext Mark-up languages
CSS Cascading Style Sheets