Multivariate statistical analysis of large-scale IgE antibody measurements reveals allergen extract relationships in sensitized individuals
Received 2 April 2007; received in revised form 28 June 2007; accepted 16 July 2007. published online 10 September 2007.
Background
Many allergenic sources are reportedly cross-reactive because of protein structural similarities. Although several aggregations are well characterized, no holistic mapping of IgE reactivity has hitherto been reported.
Objective
The aim of this study was to disclose relevant associations within a large set of allergen preparations, as revealed by specific IgE antibody levels in blood sera of multireactive human donors.
Methods
A dataset of recorded IgE antibody serum concentrations of 1011 nonidentifiable multireactive individuals (devoid of clinical records) to 89 allergen extracts was compiled for in silico analysis. Various algorithms were used to identify specific multivariate dependencies between the IgE antibody levels.
Results
Exhaustive cluster analysis demonstrates that IgE antibody responses to the 89 extracts can be aggregated into 12 stable formations. These clusters hold both well-known relationships, unexpected patterns, and unknown patterns, the latter categories being exemplified by the coclustering of wasp and certain seafood and a clear differentiation among pollen allergens.
Conclusion
Identified relationships within several well-known groups of cross-reactive allergen extracts confirm the applicability of dedicated multivariate data analysis within the allergology field. Moreover, some of the unexpected IgE reactivity associations in sensitized human subjects might help in identifying new relationships with potential importance to allergy.
Clinical implications
Although clinical implications from this study should be validated in subsequent investigations with documentation on symptoms included, we believe this seminal approach is a key step toward the development of new analysis tools for interpretation of allergy data generated by using high-throughput recording systems.
aDivision of Toxicology, National Food Administration, Uppsala, Sweden
bResearch and Development, Phadia AB, Uppsala, Sweden
cDepartment of Engineering Sciences, Uppsala University, Uppsala, Sweden
dDepartment of Medical Sciences, Uppsala University Hospital, Uppsala, Sweden
Reprint requests: Ulf Hammerling, Division of Toxicology, National Food Administration, PO Box 622, SE-751 26 Uppsala, Sweden.
Mats G. Gustafsson, Department of Engineering Science, Uppsala University, PO Box 534, SE-751 21, Uppsala, Sweden.
Supported by the Swedish Governmental Agency for Innovation Systems (VINNOVA).
Disclosure of potential conflict of interest: A. Önell and A. Kober are employed by Phadia AB. P. Matsson owns stock in, has patent licensing arrangements with, and is employed by Phadia AB. The rest of the authors have declared that they have no conflict of interest.
ABSTRACT