Osteoarthritis and cartilage · 2026
Genetics of osteoarthritis: Insights from GWAS to therapeutic opportunities.
СтатьяОбзорПоддержка исследования: вне правительства СШАНазвание 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.
Hatzikotoulas Konstantinos, Southam Lorraine, Zeggini Eleftheria
Аннотация
OBJECTIVE: Osteoarthritis is the most common joint disease and a leading cause of pain and disability worldwide, affecting both weight-bearing and non-weight-bearing joints. Osteoarthritis is a complex polygenic disease shaped by genetic, molecular, and environmental factors.
DESIGN AND RESULTS: Large-scale genome-wide association studies, enabled by global biobanks and international collaboration, have identified hundreds of risk variants implicating pathways involved in skeletal development, extracellular matrix organization, inflammation, metabolism, and neuronal signalling. Integration of genetic findings with multi-omics data in primary tissues has resolved many non-coding risk loci to likely effector genes and core biological processes, such as TGF-β, WNT, and BMP signalling. Emerging approaches linking genetics with imaging phenotypes through artificial intelligence have further refined disease subtypes and mechanisms.
CONCLUSIONS: Together, these advances in genetics highlight osteoarthritis as a molecularly heterogeneous disease and provide a foundation for improved patient stratification and therapeutic development.
DESIGN AND RESULTS: Large-scale genome-wide association studies, enabled by global biobanks and international collaboration, have identified hundreds of risk variants implicating pathways involved in skeletal development, extracellular matrix organization, inflammation, metabolism, and neuronal signalling. Integration of genetic findings with multi-omics data in primary tissues has resolved many non-coding risk loci to likely effector genes and core biological processes, such as TGF-β, WNT, and BMP signalling. Emerging approaches linking genetics with imaging phenotypes through artificial intelligence have further refined disease subtypes and mechanisms.
CONCLUSIONS: Together, these advances in genetics highlight osteoarthritis as a molecularly heterogeneous disease and provide a foundation for improved patient stratification and therapeutic development.