Annals of the rheumatic diseases · 2026
DNA methylation signatures distinguish gout from asymptomatic hyperuricaemia and converge with genetic risk at immune-metabolic loci.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Chen Ziyi, Ren Haofan, Ji Xiaopeng, Dong Bingzi, Ji Aichang
Аннотация
OBJECTIVES: Why only a minority of hyperuricaemic individuals develop gout remains unclear, and epigenetic differences between these states are poorly characterised. We aimed to define DNA methylation signatures distinguishing gout from asymptomatic hyperuricaemia and evaluate their utility for molecular stratification.
METHODS: We conducted a 2-stage case-control epigenetic study of gout (n = 124), asymptomatic hyperuricaemia (n = 121), and normouricaemic controls (n = 124). Peripheral-blood DNA methylation was profiled by genome-wide targeted bisulphite sequencing in a discovery cohort (n = 83), integrating differentially methylated regions (DMRs) and cytosines (DMCs) with genome-wide association study loci and transcription-factor binding sites (TFBSs). Candidate signatures were then tested by targeted amplicon methylation sequencing in an independent cohort (n = 286), and least absolute shrinkage and selection operator logistic regression constructed methylation-only and epigenetic-clinical classifiers.
RESULTS: DMRs were identified across all 3 pairwise comparisons of gout, hyperuricaemia, and normouricaemic controls, mapping to 84 genes that overlapped gout/serum urate risk loci-including HLA-DRB1, TAP2, and GNAS-and were enriched at TFBSs, with ZNF571 linked to IL27 and SAA2. One hundred thirteen DMCs were validated and used to build classifiers: a methylation-only model distinguished gout from normouricaemic controls (test-set area under the curve 0.96) and outperformed clinical variables in gout vs nongout controls (0.91 vs 0.78; DeLong P = 0.032), while integrating methylation with clinical variables improved the most challenging distinction-gout vs asymptomatic hyperuricaemia-from 0.67 to 0.87 (DeLong P = 0.018).
CONCLUSIONS: Peripheral-blood DNA methylation captures reproducible, stage-specific differences across gout, hyperuricaemia, and normouricaemic states converging with immune-metabolic genetic risk. These signatures support methylation-based molecular stratification, although prospective validation is needed before clinical deployment.
METHODS: We conducted a 2-stage case-control epigenetic study of gout (n = 124), asymptomatic hyperuricaemia (n = 121), and normouricaemic controls (n = 124). Peripheral-blood DNA methylation was profiled by genome-wide targeted bisulphite sequencing in a discovery cohort (n = 83), integrating differentially methylated regions (DMRs) and cytosines (DMCs) with genome-wide association study loci and transcription-factor binding sites (TFBSs). Candidate signatures were then tested by targeted amplicon methylation sequencing in an independent cohort (n = 286), and least absolute shrinkage and selection operator logistic regression constructed methylation-only and epigenetic-clinical classifiers.
RESULTS: DMRs were identified across all 3 pairwise comparisons of gout, hyperuricaemia, and normouricaemic controls, mapping to 84 genes that overlapped gout/serum urate risk loci-including HLA-DRB1, TAP2, and GNAS-and were enriched at TFBSs, with ZNF571 linked to IL27 and SAA2. One hundred thirteen DMCs were validated and used to build classifiers: a methylation-only model distinguished gout from normouricaemic controls (test-set area under the curve 0.96) and outperformed clinical variables in gout vs nongout controls (0.91 vs 0.78; DeLong P = 0.032), while integrating methylation with clinical variables improved the most challenging distinction-gout vs asymptomatic hyperuricaemia-from 0.67 to 0.87 (DeLong P = 0.018).
CONCLUSIONS: Peripheral-blood DNA methylation captures reproducible, stage-specific differences across gout, hyperuricaemia, and normouricaemic states converging with immune-metabolic genetic risk. These signatures support methylation-based molecular stratification, although prospective validation is needed before clinical deployment.