The genomic research community has recognized the need for community data-reporting and analysis standards in genetic disease association studies.
For example, the Human Genome Epidemiology Network (HuGENet) was established in
1998 by the Office of Public Health Genomics to advance the synthesis and interpretation of data on human genetic variation in disease association.
The publications of the
'Strengthening the Reporting of Observational Studies in Epidemiology' (STROBE) and
'Strengthening the Reporting of Genetic Association studies' (STREGA) statements represent further advances in these efforts,
enumerating specific areas in which adoption of community-based reporting guidelines can improve the consistent interpretation of genetic studies,
particularly for genome-wide association studies (GWAS) and meta-analyses of GWAS data.
The STROBE and STREGA statements represent significant progress toward the widespread adoption of such reporting standards in the field of genetic epidemiology,
and can be applied to gene-based population and evolutionary studies as well.
Many of the data-reporting issues described in these statements are pertinent to histocompatibility and immunogenetic studies.
However, these statements pertain primarily to large cohorts and single nucleotide polymorphism (SNP) based studies.
The high level of polymorphism associated with the HLA and KIR loci, the variety of HLA and KIR genotyping systems in use, the complexities of transplantation studies,
and the unique role played by the MHC region in predisposition to disease (in both the strength and complexity of associations)
require specific consideration for the development of reporting standards and recommendations that go beyond those defined in the STROBE and STREGA statements.
The goal of the immunogenomics data-analysis working group (IDAWG) is to develop consensus-based community data standards for the HLA and KIR gene systems.
The integration of standards for both immunogenetic systems will allow for consistent, reproducible, and easily combined analyses for each system,
and will facilitate the immunogenomic analysis of KIR and HLA interactions.
The first step in achieving this approach is to build on the principles outlined in the STREGA statement
and develop a set of community-based documentation guidelines intended to strengthen the reporting of immunogenomic studies.
Consistent reporting of the manner in which the data in immunogenomic studies are managed and analyzed will facilitate the reproducibility of studies,
enhance data-sharing and meta-analyses and make immunogenomic research more accessible to the larger genomics community.
While the guidelines described in the STROBE and STREGA statements need to be applied to immunogenomic studies, a STREIS statement
is also needed to extend these guidelines as described in the table below.
If you are interested in participating in the development of the STREIS statement, please complete the
IDAWG survey of HLA and KIR data-management practices, and
send us an email describing your interest.