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Diagnostic assay development: why does bias occur?
It may sound scandalous, but it is a fact – bias and interference are everyday factors in diagnostic immunoassay development, but there is no scandal here. Diagnostic assay results must be accurate if they are going to be used by clinicians when deciding on appropriate patient treatments, so during assay development potential sources of error, such as bias, must be checked for and if possible, eliminated. I will try and explain how assays based on antibody-antigen interactions are susceptible to bias due to the nature of the biological interactions they are based on.
Antibodies and antigens
Diagnostic immunoassays use a class of proteins called antibodies. Antibodies are produced in the body as part of the immune response to the invasion of the body by foreign molecules. The foreign molecules that elicit this immune response are called antigens as they generate the production of antibodies.
Antibodies are capable of very selective binding (high specificity binding) with the antigen that triggered their production. What this means in practice is that in a complicated mixture of biomolecules, such as blood, the antibodies can bind to their specific antigen and stick to it. This property makes antibodies a genuine life saver as part of the body’s immune response by detecting foreign molecules. Specific binding also makes antibodies the cornerstone of diagnostic immunoassays.
So, for your immunoassay you will need an antibody that recognises your analyte of interest with high specificity.
Bias – or why all immunoassays don’t give the same answer?
Bias (or deviation from the true value) occurs when immunoassays, for the same analyte measuring the same sample, give consistently different results. As an immunoassay developer, bias is something you must quantify (and minimise if possible). Quantifying bias for your assay of interest is done by testing the same set of samples with a gold standard assay, for example a market leading assay. The next step is to plot one set of results against the other and fit a straight line to the data. If the straight line doesn’t go through the origin or the slope is not 1.0, then your assay is showing bias. Put more simply, there is a consistent difference (bias) between the results of the two assays.
Why does bias occur in diagnostics assay development?
Assay bias is a difficult concept to grasp, especially if you are a chemist or an engineer and used to dealing with absolute values. To understand how immunoassay bias might occur, you need to understand the nature of antibody-antigen interactions and what factors might influence these. The specific association of antigens and antibodies is dependent on noncovalent bonds (which are easily reversible) such as charge interactions. For example, a positive charge on the antibody is attracted to a negative charge on the antigen. Factors such as pH, ionic strength and temperature will affect these noncovalent interactions and reduce or increase the strength of the binding reaction. Different antibody-antigen interactions and therefore different immunoassays are affected differently by temperature, pH and ionic strength. Immunoassay results will therefore differ if these variables are not controlled.
Understanding your whole system and where errors can occur is key.
Matrix effects in diagnostics tests
In a lab setting, pH and ionic strength can be controlled by using standard solutions (with a known pH and ionic strength) containing known amounts of analyte. These standard solutions are important for immunoassay development and Quality Control. However, your diagnostic immunoassay needs to work with biological samples such as blood or urine and for these samples, the pH and ionic strength are not as well controlled and will differ between samples.
If we take blood as an example, it contains a huge number of different cells, proteins, carbohydrates and salts as well as your analyte of interest. This soup of biomolecules is referred to as the matrix. It is this matrix which gives rise to differences between your immunoassay results for a standard solution and those in a biological sample such as blood. The matrix of human blood is broadly the same for the population but different antibody-antigen interactions and therefore different immunoassays are affected differently by the matrix. This is why bias is observed between immunoassays.
Diagnostic assay systems are required to give reliable and accurate results. Assay bias is just one of the factors contributing to the overall error. Understanding your whole system and where errors can occur is key to a successful diagnostic system development. Taking a system view and understanding the contribution of factors such as bias will increase your team’s chances of success.