Computer-supported interpretation of protein profiles after capillary electrophoresis.
BACKGROUND
Electrophoretic patterns of proteins in serum/plasma are useful in the diagnosis and evaluation of many diseases. Capillary zone electrophoresis (CZE) allows rapid and automated protein separation and produces digital absorbance data, appropriate for mathematical analysis. We previously demonstrated success in detection of monoclonal immunoglobulins in such a system. This study tests new algorithms to produce rapid standardized computer-supported interpretation of the entire electropherogram.


METHODS
Data from Beckman Paragon CZE 2000 electropherograms were compared with quantitative protein data from >800 routine clinical samples. Algorithms were designed to produce semiquantitative analyses of major proteins and to define different patterns of inflammation based on the electropherogram.


RESULTS
The algorithms produced reliable semiquantitative evaluations of prealbumin, albumin, alpha1-antitrypsin, haptoglobin, and transferrin, but were less accurate for alpha1-acid glycoprotein. Some genetic variants of albumin and deficiency variants of alpha1-antitrypsin were easily recognized. Complex clinical traits such as degree and type of inflammation could be evaluated. When used together with previously developed algorithms addressing immunoglobulins, the new algorithms provide relevant clinical interpretation. Selected outputs indicate the need for reflex testing or evaluation by specialists.


CONCLUSIONS
Automation of both electrophoresis and interpretation can provide a rapid, inexpensive, standardized analysis that can hopefully improve the diagnostic information and clinical outcome for large groups of patients. It also provides objective criteria for clinical interpretations, to be validated or adjusted in future clinical studies.
Jonsson
Magnus
M
Department of Clinical Chemistry, University Hospital MAS, S-205 02 Malmö, Sweden.
Carlson
Joyce
J
D000328:Adult; D000465:Algorithms; D018798:Anemia, Iron-Deficiency / Q000175:diagnosis; D001322:Autoanalysis; D001798:Blood Proteins / Q000032:analysis*; D003201:Computers; D019075:Electrophoresis, Capillary; D006801:Humans; D007249:Inflammation / Q000175:diagnosis; D009716:Numerical Analysis, Computer-Assisted; D012372:ROC Curve
D001798:Blood Proteins