1Otto-von-Guericke-University Magdeburg,
Institute of Technical and Business Information Systems, Germany
2Childrenīs Hospital Reutlingen, Germany
To gain further knowledge about rare genetic diseases, a world wide method for data collection via the Internet has been established. This new approach will improve collecting valuable data from single case reports. RAMEDIS saves standardised patient data which will be usable for statistics, longitudinal examinations and co-operative studies in future time. Embedded in the scene of the German Human Genome Project, RAMEDIS directly will enable phenotype-genotype correlation's. Beside the better characterisation of clinical heterogeneity of rare metabolic diseases, there may be a great benefit for the treatment of these patients in whom prospective studies are otherwise expensive and difficult to perform.
A lot of papers, for example given in proceedings, present case reports especially of rare metabolic diseases. They represent valuable information for better understanding of rare conditions. However, most of these information may be "lost" using common publication forms.
RAMEDIS is another approach of publishing case reports via the Internet. In contrast to electronic journals we use a formal procedure for entering the data into RAMEDIS. As only standardised data are allowed (there are only few free text fields e.g. "Abstract") the data will be usable for studies and statistical evaluation.
A publishing committee will review each submitted case report. The aim is to collect high quality data on a central server, whereby the rights stay with the corresponding author. Furthermore, since molecular data are also included as far as available, RAMEDIS will be useful for genotype-phenotype investigations.
Inborn errors of metabolism are characterized by a block in a metabolic pathway, a deficiency of a transport protein or a defect in a storage mechanism caused by a gene defect. The defect gene leads up to an absent or wrong production of essential proteins, especially enzymes. But these enzymes are important components of the biochemical processes in cells and tissues. They enable, disable or catalyze the biochemical reactions of metabolic pathways. Thus, these disorders of the metabolism result in a threatening deficiency or accumulation of intermediate metabolites in the human organism and their following corresponding symptoms.
If a patient is suspected of having an inborn error of metabolism, specialized biochemical laboratories analyze enzyme activities in specimen of different tissues (skin, liver etc.) and investigate body liquids as blood, urine etc. for unusual metabolic pattern. With molecular methods it is also possible to confirm a diagnosis and to define the defect gene. In a screening procedure a number of inborn metabolic errors can be already examined prenatally or immediately after birth, e.g. Phenylketonuria (PKU).
For inborn errors of metabolism a lot of data is available in different databases accessible via Internet. A huge number of genes, enzymes and metabolic pathways have already been identified, isolated, sequenced and collected in these databases. For example, EMBL [1] and Genebank [1] contain DNA sequences and TRANSFAC [1] the knowledge about gene expression. Metabolic pathways and their single biochemical reactions are stored in the KEGG [1] system. Whereas BRENDA [2] provides the behavior of enzymatic driven processes. For medical data the databases MD-Cave [3] or Metagene [4] can be used. Most inborn errors of metabolism are also included in OMIM (Online Mendelian Inheritance in Man http://www3.ncbi.nlm.nih.gov/Omim).
The amount of this electronically available knowledge of genes, enzymes, metabolic pathways and metabolic diseases increases rapidly. But they give only highly specialized views of the biological systems. These lead up to the general task of integrating all this knowledge and make it biotechnologically and medically applicable. Within the scope of the German Human Genome Project a consortium of five partners has been founded to develop a bioinformatics system for representing, modeling and simulating genetic effects on gene regulation and metabolic processes in human cells. Thus, the correlation between the genotype and the clinically apparent phenotype will be established.
For the physician the user interface plays an important role for the acceptance of a system. This factor is often underestimated. An easy to handle system, oriented at common standards was developed. The use of RAMEDIS is free, but registration (user account) is recommended.
Clinical symptoms, laboratory finding results and data concerning molecular genetics are collected. Additionally, there is the possibility to store clinical findings in pictures (x-rays, MRI-scans, histopahological data etc.). The user could either analyse all data already present in the database in a anonymous manner, or he can commit "new" cases or edit his own case reports and modify them. Notice, that most fields are filled with selection lists and not by typing. Therefore, wrong spelling or the use of multiple synonyms is avoided.
The analysis tool offers the possibility to evaluate all data stored in RAMEDIS. The user can send different queries to the systen, e.g. to select all case reports with the same diagnosis or all metabolic patients of one centre. Last but not least the user may look for similar cases by entering a combination of laboratory findings and symptoms. If interested in a special case out of this list, the user may select this case report Notice, that the data is exposed anonymously without birth dates, initials etc. Thus confidentiality to the data is guaranteed.
All data of RAMEDIS are stored in one common database. For this persistent storage of the information an Oracle database management system in the version 8.0.5 is used. The system runs on a dual intel processor personal computer with a Red Hat Linux operating system. For the connection to the Internet an Apache webserver is installed. The internet domain of RAMEDIS is www.ramedis.de.
As mentioned before RAMEDIS is divided in an input/editing part and an analysis component. The data input and editing tool is implemented as Java application with Swing components. Java is a platform independent programming language from the Sun cooperation, which is mainly developed for Internet implementations. Swing is an extension of Java for the design of "nice" graphical user interfaces. For the connection between the tool and the RAMEDIS database JDBC is used. JDBC is an interface which is provided from database management system developers for an easy access to the databases by Java applications. The analysis tool is based on the Oracle WebDB system. WebDB includes a separate webserver and realizes a direct connection to the Oracle database.
Since November 2000, patient data is collected online. Up to now, 120 case reports of patients with rare metabolic diseases, some with more than hundreds of traits, have been committed. Further outside laboratories will be connected within 2001.
The final version of RAMEDIS will include data concerning therapy with diet regimes and given medicaments and some more detailed family history.
The vision is to implement a world wide used system to bring the data of the very seldom cases of inborn errors of metabolism together. Comparing the case reports of a special disease, a better characterisation of clinical heterogeneity of this disease could be obtained. As immediate aim for the Human Genome Project, the collected clinical data is used for the identification of genotype-phenotype correlation. The data may also be used for further characterisation of a genetic metabolic disease or for epidemiological investigations. As also data of therapy regimes will be stored, RAMEDIS will be very useful for longitudinal and/or co-operative therapy studies. Furthermore RAMEDIS will offer the basis for quality assurance between different metabolic centres concerning therapeutic outcomes.
Two examples of data collection via the Internet show the benefit which RAMEDIS will offer: The database for phenylketonuria (PHA-db) was created by the group of Charles Scriver in Montreal, who is the world leading expert for genetic metabolic disorders. This database (www.mcgill.ca/pahdb) became a very powerful tool for collecting molecular data, e.g. mutations as well as some clinical parameters for a genotype-phenotype correlation [5]. The aim of a project initiated by N. Blau at the University of Zurich is the collection of data from the specialised field of tetrahydrobiopterine deficiencies (www.bh4.org). Citation frequencies show that the information in these databases is highly valuable, contributing to a better understanding of genotype-phenotype correlation. Each of these two approaches covers only one single inborn error of metabolism. RAMEDIS offers the possibility to collect data of different rare metabolic diseases world-wide.
By this way new knowledge concerning the diseases could be gained and rules for therapeutic intervention could be developed. The special architecture of RAMEDIS enables users a worldwide and platform independent access onto the system.
This work is supported by the German Ministry of Education and Research in the German Human Genome Project (Project "Modeling of gene regulatory networks for linking genotype-phenotype information") grant 01KW9962/6 and 01KW9912.