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. 2025 May 1;64(5):2591-2600.
doi: 10.1093/rheumatology/keae492.

Genetic risk, lifestyle adherence, and risk of developing hyperuricaemia in a Japanese population

Masato Takase  1 , Naoki Nakaya  1   2 , Tomohiro Nakamura  2   3 , Mana Kogure  1   2 , Rieko Hatanaka  1   2 , Kumi Nakaya  1   2 , Ippei Chiba  1   2 , Sayuri Tokioka  1   2 , Ikumi Kanno  1   2 , Kotaro Nochioka  1   2   4 , Naho Tsuchiya  1   2 , Takumi Hirata  2   5 , Akira Narita  1   2 , Taku Obara  1   2 , Mami Ishikuro  1   2 , Hisashi Ohseto  1   2 , Akira Uruno  2 , Tomoko Kobayashi  1   2   4 , Eiichi N Kodama  2   6 , Yohei Hamanaka  2 , Masatsugu Orui  1   2 , Soichi Ogishima  1   2 , Satoshi Nagaie  1   2 , Nobuo Fuse  1   2 , Junichi Sugawara  1   2   4   7 , Shinichi Kuriyama  1   2   6 , Koichi Matsuda  8 , Yoko Izumi  1   2 , Kengo Kinoshita  1   2 , Gen Tamiya  1   2   9 , Atsushi Hozawa  1   2 , Masayuki Yamamoto  1   2 ; ToMMo Investigators
Collaborators, Affiliations

Genetic risk, lifestyle adherence, and risk of developing hyperuricaemia in a Japanese population

Masato Takase et al. Rheumatology (Oxford). .

Abstract

Objective: The objective of this study was to investigate the inter-relationships among genetic risk, adherence to a healthy lifestyle, and susceptibility to hyperuricaemia.

Methods: This prospective cohort study was conducted with 7241 hyperuricaemia-free individuals aged ≥20 years from the Tohoku Medical Megabank Community-based cohort study. A comprehensive lifestyle score included assessment of BMI, smoking, drinking, and physical activity, and a polygenic risk score (PRS) was constructed based on uric acid loci from a previous genome-wide association study meta-analysis. A multiple logistic regression model was used to estimate the association between genetic risk, adherence to a healthy lifestyle, and hyperuricaemia incidence and to calculate the area under the receiver operating characteristic curve (AUROC). Hyperuricaemia was defined as a uric acid level of ≥7.0 mg/dL or a self-reported history of hyperuricaemia.

Results: Of the 7241 adults [80.7% females; mean (±s.d.) age: 57.7 (12.6) years], 217 (3.0%) developed hyperuricaemia during 3.5 years of follow-up period. Genetic risk was correlated with hyperuricaemia development (P for interaction = 0.287), and lifestyle risks were independently associated. Participants with a high genetic risk and poor lifestyle had the highest risk (odds ratio: 5.34; 95% CI: 2.61-12.10). Although not statistically significant, adding the PRS in the model with lifestyle information improved predictive ability (AUROC = 0.771, 95% CI: 0.736-0.806 for lifestyle; AUROC = 0.785, 95% CI: 0.751-0.819 for lifestyle and PRS; P= 0.07).

Conclusion: A healthy lifestyle to prevent hyperuricaemia, irrespective of genetic risk, may mitigate the genetic risk. Genetic risk may complement lifestyle factors in identifying individuals at a heightened hyperuricaemia risk.

Keywords: epidemiology; genetic; hyperuricaemia; lifestyle; polygenic risk score.

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Figures

None
Graphical abstract
Figure 1.
Figure 1.
Flow chart of study participants. TMM: Tohoku Medical Megabank; SUA: serum uric acid; PRS: polygenic risk score
See this image and copyright information in PMC

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Supplementary concepts