Genetic data may up diagnostic efficiency for rheumatic disease

Genetic data may up diagnostic efficiency for rheumatic disease

(HealthDay)—Converting genotype information into an interpretable probability value for five different inflammatory arthritis-causing diseases could potentially improve the diagnostic efficiency of rheumatic disease, according to a study published in the May 27 issue of Science Translational Medicine.

Rachel Knevel, M.D., Ph.D., from Harvard Medical School in Boston, and colleagues developed a Genetic Probability tool (G-PROB) to calculate the probability of different diseases for a patient based on genetic risk scores. The G-PROB was tested for inflammatory arthritis-causing diseases (, , spondyloarthropathy, psoriatic arthritis, and gout). After validation on simulated data, G-PROB was tested in three cohorts with 1,211, 245, and 243 patients.

The researchers found that calibration of G-probabilities with disease status was high, with regression coefficients varying from 0.90 to 1.08. Across the three cohorts, G-probabilities discriminated true diagnoses, with pooled areas under the curve of 0.69, 0.81, and 0.84, respectively. At least one disease could be ruled out for all patients; in 45 percent of patients, a likely diagnosis was identified with a of 64 percent. The clinician's initial diagnosis was incorrect in 35 percent of cases. Thirty-nine percent of the variance in final disease was explained by initial clinical diagnosis; after adding G-probabilities, this improved to 51 percent.

"Preexisting could be considered part of a patient's given its potential to improve precision medicine in the modern outpatient clinic," the authors write.

One author disclosed financial ties to the biopharmaceutical industry; a second author disclosed consulting for a nutrition company.

More information: Abstract/Full Text (subscription or payment may be required)
Journal information: Science Translational Medicine

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Citation: Genetic data may up diagnostic efficiency for rheumatic disease (2020, May 29) retrieved 28 November 2022 from
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