Cell Biochemistry Martinsried
Cytometry and Human Disease
G.Valet

Potential of Cytometry

1. Problem:

Diseases are caused by biochemical changes in cellular systems or organs. The analysis of such changes should provide information on individual patient's disease diagnosis, predictions on further disease course as well as on the efficiencey of therapy.
The prediction of patient's future disease course as well as the risk assessment for the occurrence of disease are of high clinical interest. Practically it is, however, in most instances impossible to make disease course predictions by the biochemical analysis of body fluids as well as by other clinical or histo- and cytopathological analyses. Statistical disease prognosis can be derived at the most from such data. This is useful e.g. for therapy development or healthcare planning but of little value for the individual patient.
Some reasons for this unsatisfactory situation derive from the fact that the mostly performed humoral biochemistry measurements e.g. in clinical chemistry, reflect cell biochemical disease processes only indirectly through changes in concentration or function of cell derived biomolecules. Disease relevant biomelecules may, however, not appear outside cells, they may be metabolically altered or remain undetectable due to high dilution in the body's fluid compartments or to fast turnover.
The results of biochemical measurements on organ tissue preparations of biopsy material as an alternative for humoral measurements are difficult to interpret because organs contain a variety of discrete cell types whith potentially different reactivities during disease processes.
The important advantage of flow and image cytometry for predictive medicine consists in the combination of microscopic single cell observation with simultaneous multiparameter biochemical cell analysis at the very spot of disease action.

2. Potential of Cytometry

Patterns of various biomolecules can be reliably quantitated by cytometric analysis of viable or fixed cells following staining with biochemically specific fluorescent dyes. The particular effort of this laboratory consists in the development of specific stains for cell functions in viable cells as sensitive indicators of the altered cellular metabolism in acute or chronic disease. The simultaneous multiparameter data collection by the cytometer provides high amounts of functional and structural information on heterogeneous i.e. essentially unprocessed ex-vivo cell suspensions shortly after removal from the human body.
The cellular heterogeneity of human samples offers important advantages for clinical and experimental system cytometry because cytometry takes advantage of the high information content of simultaneously collected multiparameter data from a great variety of different cell types. The cytometric strategy is explicitely to measure as much heterogeneity as possible to profit during evaluation from the high information content of biocomplexity. The cytometric approach is therefore quite different from the tissue biochemistry approach which appreciates as much homogeneity as possible for unambiguous result interpretation.

3. Individual Patient Disease Course Predictions by Standardized Multiparameter Data Classification (SMDC)

The exhaustive extraction of information from cytometric or clinical chemistry multiparameter measurements by a laboratory and instrument independent, self learning and standardized data classification algorithm, developed earlier (2), provides single patient predictive as well as diagnostic disease evaluation with unprecedented accuracy. Clinical examples from several different medical disciplines underline this point. Predictive Medicine by cytometry represents Evidence Based Medicine (EBM) at a cellular level.
The practical consequence of this approach is that complications in a number of common diseases like severe infections, shock, exacerbation of rheumatoid and asthmatic disease, thromboembolic complications in diabetes, myocardial infarction and stroke sensitive patients or survival in cancer patients may become predictable at the individual patient level by combined multiparameter cytometry and Standardized Multiparameter Data Classification (SMDC).
Minor interventions like cytometry supervised short term antiphlogistic therapy e.g. just prior to an imminent exacerbation of rheumatoid disease may prevent severe tissue destruction leading otherwise to the stepwise disabling of the patient by deficient repair processes. The cell biochemical approach has in this case the potential to significantly postpone the invalidization of patients. The higher quality of patients's life would be paralleled by shorter disease periods at substantially lower therapy costs and chances for the development of unwanted therapeutic side effects (Optimized Medicine).