Back

Somatic TET2 Mutations are Associated with Giant Cell Arteritis

Robinette, M. L.; Weeks, L. D.; Kramer, R. J.; Agrawal, M.; Gibson, C. J.; Yu, Z.; Sekar, A.; Mehta, A.; Niroula, A.; Brown, J. T.; McDermott, G. C.; Reshef, E. R.; Lu, J. E.; Liou, V. D.; Chiou, C. A.; Natarajan, P.; Freitag, S. K.; Rao, D. A.; Ebert, B. A.

2023-07-31 rheumatology
10.1101/2023.07.26.23292945 medRxiv
Show abstract

ObjectiveGiant cell arteritis (GCA) is an age-related vasculitis. Prior studies have identified an association between GCA and hematologic malignancies (HM). How the presence of somatic mutations which drive development of HM, or clonal hematopoiesis (CH), may influence clinical outcomes in GCA is not well understood. MethodsTo examine an association between CH and GCA, we analyzed sequenced exomes of 470960 UK Biobank participants for the presence of CH and used multivariable Cox regression. To examine the clinical phenotype of GCA in patients with and without somatic mutations across the spectrum of CH to HM, we performed targeted sequencing of blood samples and electronic health record review on 114 patients with GCA seen at our institution. We then examined associations between specific clonal mutations and GCA disease manifestations. ResultsUKB participants with CH had a 1.48-fold increased risk of incident GCA compared to UKB participants without CH. GCA risk was highest among individuals with cytopenia (HR 2.98, p =0.00178) and with TET2 mutation (HR 2.02, p =0.00116). Mutations were detected in 27.2% of our institutional GCA cohort, 3 of whom had HM at GCA diagnosis. TET2 mutations were associated with vision loss in patients with GCA (OR 4.33, p = 0.047). ConclusionsCH increases risk for development of GCA in a genotype-specific fashion, with greatest risk being conferred by the presence of mutations in TET2. Somatic TET2 mutations likewise increase the risk of GCA-associated vision loss. Integration of somatic genetic testing in GCA diagnostics may be warranted in the future.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.