New evidence suggests the rheumatoid factor–positive polyarticular subtype of juvenile idiopathic arthritis bears a close genetic resemblance to adult rheumatoid arthritis, lending support to the growing suspicion that in arthritis, biological underpinnings are more important than age of onset when it comes to characterizing and, potentially, choosing treatments.

Previous work had shown that rheumatoid factor (RF)–negative patients have genetic risks similar to those of adults with RF-negative disease. “If the RF-negative patients in adult and childhood are similar, then maybe the RF-positive patients are similar in their genetic background as well. That’s what this study was testing,” study coauthor Anne M. Stevens, MD, PhD , division chief of rheumatology at the University of Washington, Seattle, said in an interview. The study was published online Feb. 9 in Arthritis & Rheumatology .

There are seven recognized categories of juvenile idiopathic arthritis (JIA), and all are believed to have genetic risk factors. Previously, the researchers used the Immunochip custom microarray to map 186 autoimmune disease-associated loci from 11 autoimmune phenotypes, including adult rheumatoid arthritis (RA). In the current work, the researchers analyzed 340 RF-positive polyarticular JIA cases (292 females) and 14,412 controls (8,002 females) from the United States, United Kingdom, Germany, Canada, and Norway. RF-positive polyarticular disease accounts for about 5% of JIA cases, and its symptoms and presentations resemble adult RA.

The researchers found associations in the human leukocyte antigen (HLA) region. The most significant was found at rs3129769, near HLA-DRB1 (P = 5.51 x 10-31). This single nucleotide polymorphism (SNP) was in strong linkage disequilibrium (LD, r2 = 0.88) with the rs660895 HLA-DRB1 SNP that has been reported in adult RA (P = 2.14 x 10-29).

The researchers examined links between RF-positive polyarticular JIA and the 27 SNPs that had been identified in the previous study of oligoarticular/RF-negative polyarticular JIA. Just 6 of those 27 SNPs were significantly associated with RF-positive polyarticular JIA (P less than .05). On the other hand, of 44 SNPs most strongly associated with RA, 19 were associated with RF-positive polyarticular JIA (P less than .05).

That suggests that RF-positive polyarticular JIA cases are different from other JIA cases. “They’re more like adult patients than they’re like child patients,” said Dr. Stevens.

The researchers also compared the weighted genetic risk scores (wGRS) produced from the top RA loci to wGRS produced from the top oligoarticular/RF-negative polyarticular JIA loci. The wGRS from the top RA loci was a better predictor of RF-positive polyarticular JIA cases (area under the curve [AUC] = 0.71 versus AUC = 0.58; P = 8.26 x 10-33).

The wGRS from RA had similar success in predicting RF-positive polyarticular JIA and early-onset RA cases (AUC = 0.75; P = .25), but it fared worse in predicting late-onset RA (at 70 years or older, AUC = 0.62), compared with the wGRS from RF-positive polyarticular JIA (P = 1.65 x 10-5).

Those results suggest that RF-positive polyarticular JIA more closely resembles younger RA cases than older RA cases.

“If you consider early-onset RA patients, less than 29 years old when they develop RA, they look like JIA patients. But older RA patients, who are over 70 when they develop RA, they look like they totally have a different genetic background,” Dr. Stevens said.

The study could have clinical implications. The lead author, Anne Hinks, PhD , is a research fellow at the University of Manchester (England) and has led the charge to characterize JIA. The wGRS score she developed has the potential to help physicians diagnose classify and treat JIA patients. Currently, they must rely on the International League of Associations for Rheumatology criteria, which can take months to work through and may lead to misclassification diagnoses.

And in any case, the emerging genetic research suggests that the underlying genetics of JIA may be a better way to classify patients. “There’s a lot of overlap and risk of misclassifying patients with the current system. This weighted genetic risk score that Dr. Hinks developed could be used to classify patients with one DNA sample. This is the kind of clinical test we need,” Dr. Stevens said.

The study received funding from a range of government and private sources. Dr. Stevens has a patent licensed to Quest Diagnostics, is conducting research collaborations with Seattle Genetics and Kineta, and has received fellowship support from Pfizer.

SOURCE: Hinks A et al. Arthritis Rheumatol. 2018 Feb 9. doi: 10.1002/art.40443


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