Immunoassays are the versatile workhorses of clinical laboratories, aiding in fast, easy, and inexpensive diagnosis of various diseases by measuring analytes ranging from hormones and antibodies to proteins and drugs in matrices as diverse as whole blood, sweat, meconium, and cerebrospinal fluid. With continuous advancements, these tests, which utilize the antigen-antibody immune reaction, are sensitive—detecting up to picomolar concentrations—and specific, measuring a wide range of analyte concentrations.

Immunoassays also flex their detective muscles in different ways: by competition and sandwich, as homogeneous or heterogeneous, or by using colorimetric, fluorometric, or chemiluminescent signals. They use antibodies or antibody fragments generated against the target analyte in different species of animals—mouse, rat, rabbit, goat, and pig being most common. The antibodies can be monoclonal or polyclonal.

Despite all their versatility, immunoassays have some challenges in that they are subject to interferences, thereby generating false increase (positive interference) or false decrease (negative interference) in reported results. Such results could lead to misdiagnosis or missed diagnosis, causing unnecessary and expensive additional laboratory and clinical investigations, not to mention significant morbidity and even mortality in the affected patients. So it is important to detect interferences and take steps to generate correct results. This article summarizes the five most common sources of immunoassay interference along with strategies for resolving them.

An important source of immunoassay interference is human endogenous antibodies, which may react with immunoassay reagents, causing either positive or negative interferences, depending on assay antibodies and architecture. These interfering antibodies are of four types:

Heterophilic antibodies. These nonspecific antibodies interact poorly with immunoassay antibodies (mostly at the Fc region).

Anti-animal antibodies. These are specific and interact strongly with assay antibodies. Patients develop them because of either treatment with therapeutic (animal) antibodies or close association with those animals. Human anti-mouse antibodies are most common and they are used most often in assay reagents.

Autoantibodies. These are found mostly in individuals with autoimmune disorders. For example, patients with thyroid disease have anti-thyroid antibodies.

Therapeutic antibodies. These are therapeutically administered antibodies or their fragments, like Digibind, which detoxifies digitalis toxicity. Therapeutic antibodies will interfere in immunoassays until excreted by the kidneys. 

Serial dilution should resolve antibody interference. When the interference is sufficiently diluted out, the analyte concentration, adjusted for dilution, will provide the correct result. Precipitation or ultrafiltration also will remove interfering antibodies, after which the reanalyzed sample should yield the correct result.

Since the immunoreaction involves interaction between epitope of the analyte and the binding site of the antibody, any compound presenting a similar epitope may cross-react with the assay antibodies. The extent of interference from a cross reactant will depend on how similar its structure is to the analyte epitope. Competition assays, which use single-assay antibodies, suffer more from cross-reactivity interference than immunometric or sandwich assays, which use two antibodies. Bidirectional interference—positive with certain analyte and interferent concentrations, and negative with other concentrations—has been observed in some immunoassays. Use of monoclonal antibodies in modern immunoassays has improved assay specificity, reducing cross reactivity. Furthermore, serial dilutions of samples can resolve interference from cross reactants.

Prozone is a specific type of interference found only in one-step sandwich assays with very high analyte concentrations. The analyte molecules, under this condition, saturate out all reagent antibodies, thus producing negative interference only. The best way to resolve prozone interference is to dilute the samples and rerun the assay.

Elevated endogenous serum components, such as bilirubin (icterus), hemoglobin (hemolysis), lipids (turbidity), and proteins interfere more in homogeneous than heterogeneous assays. Automated analyzers can flag results in which such interference may be present. Sample dilution is a common way to resolve these interferences.

Matrix effect—nonspecific inter­action between the specimen and the assay reagents—is another type of immunoassay interference. Labs use various proteins and surfactants and optimize their assay buffers and ionic strength to minimize the matrix effect. Samples that contain enzymes or substrates similar to those used in immunoassays may generate incorrect results. For example, a sample with elevated alkaline phosphatase may give incorrect results in assays that employ alkaline phosphatase as labels. Or, samples containing biotin will interfere in assays employing avidin biotin as reagents. Samples may also contain molecules that inhibit or modulate assay enzymes, thus causing interference. Automated random access analyzers are normally tested for sample or reagent carryover, but unless properly addressed with extra washes, carryover may give incorrect results.

In summary, laboratorians must work closely with physicians to identify incorrect immunoassay results, identify the root causes, solve the interferences, and report correct results. These efforts will be well worth it in aiding with faster and ­correct diagnosis and avoiding ­unnecessary costs.

Pradip Datta, PhD, DABCC, is a senior staff scientist with Siemens Healthcare Diagnostics in Newark, Delaware and the author of AACC’s Quick Guide to Immunoassay Interferences. +Email: pradip.datta@siemens.com