IFA is one of the two most commonly used tests for ANAs. Typically, HEp-2 cells are used as a substrate to detect the antibodies in human serum. Microscope slides are coated with HEp-2 cells, and the serum is incubated with the cells. If antibodies are present, they will bind to the antigens on the cells, and, in the case of ANAs, the antibodies will typically bind to the nucleus. The binding is visualized by adding a fluorescent-tagged anti-human antibody that binds to the Fc portion of the patient's antibodies. Typically, fluorescein isothiocyanate (FITC) is employed as the fluorescent marker on the secondary antibody. The bound complex will fluoresce at a specific wavelength of light that can be seen under the microscope. Depending on the antibody present in the human serum and the localization of the antigen in the cell, distinct patterns of fluorescence will be seen on the HEp-2 cells.
In positive samples, the cell nuclei will show a bright apple-green fluorescence with a staining pattern characteristic of the particular nuclear antigen distribution within the cells. If the sample is negative for ANA, the nucleus will show no discernible pattern of nuclear fluorescence. The cytoplasm may demonstrate weak staining, while the non-chromosome region of mitotic cells demonstrates brighter staining.
The levels of antibodies are analyzed by performing dilutions on the serum sample and reported as a titer. This is the highest serum dilution at which autoantibodies are still detectable. Depending on the laboratory and specific method used, an ANA titer is typically considered negative when it is less than or equal to 1:40. A titer equal to or less than 1:80 is often considered borderline, while a titer greater than 1:80 is considered positive. Higher titers are more clinically significant, whereas low positives (≤1:160) may be found in up to 20% of healthy individuals (especially the elderly). Although positive titers of 1:160 or higher are strongly associated with autoimmune disorders, they are also found in 5% of healthy individuals.
It is important to stress that autoantibody screening is useful in diagnosing autoimmune disorders, and monitoring levels help predict the progression of the disease. However, a positive ANA test is seldom useful if other clinical or laboratory data supporting a diagnosis are not present.
Patterns of cellular fluorescence
In addition to the ANA titer, positive results on IFA will include a description of the type of fluorescent pattern seen. Different patterns have been associated with different autoimmune disorders, although some overlap may occur. Some of the more common patterns include:
- Homogenous (diffuse) pattern: Typically associated with SLE, mixed connective tissue disease, and drug-induced lupus.
- Speckled pattern: Associated with SLE, Sjögren's syndrome, scleroderma, polymyositis, RA, and mixed connective tissue disease.
- Nucleolar pattern: Associated with scleroderma and polymyositis.
- Centromere (peripheral) pattern: Associated with scleroderma and CREST (calcinosis, Raynaud syndrome, esophageal dysmotility, sclerodactyly, telangiectasia).
The typical results reported using the IFA method would have the ANA dilution titer and a description of the fluorescence pattern, such as "Positive at 1:320 dilution with a homogenous pattern." When assessing the test results, the clinician must consider the following:
- The ANA test results can be positive in people without any known autoimmune disease and thus need to be evaluated carefully in conjunction with an individual's signs and symptoms.
- An ANA test may become positive before signs and symptoms of an autoimmune disease develop; therefore, it may take time to interpret the significance of a positive ANA test in a person who does not have symptoms.
- Some medications can stimulate the production of ANAs, including procainamide, hydralazine, and phenytoin. ANAs that are stimulated by medication are referred to as drug-induced ANAs.
- Ultimately, the ANA result must be interpreted in the specific context of an individual patient's symptoms, underlying medical conditions, and other test results. It may or may not be significant, even if positive, in a given individual.
