Specificity

For DNA tests, two questions need to be distinguished:

• Analytical specificity: does the test indicate the variant being tested for only when it is actually present? For tests for a known mutation, it is usually close to 100 %.
• Clinical specificity: do animals carrying the variant actually become affected? In some hereditary diseases, not every animal with the corresponding genotype becomes affected (incomplete penetrance). A positive test then indicates a risk, but not certain future disease.

Clear-cut case: monogenic disease caused by one mutation. In Osteogenesis Imperfecta in the Dachshund, a single mutation in the SERPINH1 gene causes the disease. Every dog with two copies becomes affected; analytical and clinical specificity are close to 100 %.

Incomplete penetrance: PSSM1. In Polysaccharide Storage Myopathy type 1 (PSSM1) in horses, the test reliably detects the mutation in the GYS1 gene. Whether a carrier becomes affected, however, depends strongly on breed, feeding and exercise. In draft horses, the mutation is widespread and often tolerated; many carriers show no or only mild symptoms when fed appropriately. In relation to the disease, the clinical specificity is therefore lower than the analytical specificity.

Analytically specific, clinically not conclusive: PRA. A test for a particular form of PRA is 100 % specific for its mutation. A dog with the result n/n can nevertheless go blind from another form of PRA (see the example in the article Sensitivity).

In multifactorial diseases, several genes and environmental factors interact. A single genetic variant is a risk factor here: it increases the probability of becoming affected, but it is neither necessary nor sufficient. Animals with the variant may remain healthy, animals without it may become affected. Sensitivity and specificity can therefore not be read, as for monogenic diseases, as a measure of whether an animal will become affected.

For such tests, a different approach is taken:

• Assess analytical validity separately: whether the test detects the variants correctly is evaluated as for any DNA test.
• Report the result as a risk: what matters is how much a variant increases the risk of disease compared with animals without this variant. This is determined in studies of affected and healthy animals (relative risk, odds ratio).
• Evaluate variants together: several risk variants are considered jointly, for example via the number of risk alleles or a risk score.
• Take the environment into account: the result is interpreted together with breed, husbandry, feeding and workload. These factors in particular can often be influenced in a targeted way.
• Proceed gradually in breeding: the proportion of risk variants in the population is reduced over generations without jeopardising genetic diversity through strict exclusions from breeding.

Example horse: In Muscle Integrity Myopathy (MIM), variants in six genes are analysed as risk factors. Whether and how strongly a horse shows symptoms depends largely on feeding, training and husbandry. The test shows the genetic susceptibility, not certain disease.

Example human: In type 2 diabetes or hypertension, many gene variants, each with a small effect, contribute to the risk. Lifestyle, diet, physical activity and body weight have a major influence. Genetic tests provide a risk profile here, not a diagnosis.

Sensitivity and specificity are the key criteria used to measure the informative value of a test procedure. How reliable an individual positive or negative result is (predictive value) also depends on how common the disease is. Especially for rare diseases, even a small number of false positive results means that many positive findings are incorrect (see the example in the article Bayes Theorem).

Lexicon:

• Sensitivity
• Bayes Theorem

Literature:

• Trevethan, R.: Sensitivity, specificity, and predictive values: foundations, pliabilities, and pitfalls in research and practice.Front Public Health 5:307, 2017. DOI: 10.3389/fpubh.2017.00307