Big data, big consortia, and pain: UK Biobank, PAINSTORM, and DOLORisk.
Big data, big consortia, and pain: UK Biobank, PAINSTORM, and DOLORisk.
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DOI:
10.1097/pr9.0000000000001086
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发表时间:
2023-09
期刊:
影响因子:
4.8
通讯作者:
中科院分区:
文献类型:
--
作者:
Current challenges in understanding chronic pain pathogenesis are being overcome by the creation of large consortia and biorepositories with a harmonised approach to phenotyping. Chronic pain (CP) is a common and often debilitating disorder that has major social and economic impacts. A subset of patients develop CP that significantly interferes with their activities of daily living and requires a high level of healthcare support. The challenge for treating physicians is in preventing the onset of refractory CP or effectively managing existing pain. To be able to do this, it is necessary to understand the risk factors, both genetic and environmental, for the onset of CP and response to treatment, as well as the pathogenesis of the disorder, which is highly heterogenous. However, studies of CP, particularly pain with neuropathic characteristics, have been hindered by a lack of consensus on phenotyping and data collection, making comparisons difficult. Furthermore, existing cohorts have suffered from small sample sizes meaning that analyses, especially genome-wide association studies, are insufficiently powered. The key to overcoming these issues is through the creation of large consortia such as DOLORisk and PAINSTORM and biorepositories, such as UK Biobank, where a common approach can be taken to CP phenotyping, which allows harmonisation across different cohorts and in turn increased study power. This review describes the approach that was used for studying neuropathic pain in DOLORisk and how this has informed current projects such as PAINSTORM, the rephenotyping of UK Biobank, and other endeavours. Moreover, an overview is provided of the outputs from these studies and the lessons learnt for future projects.
影响因子:
4.4
作者:
Patasova K;Khawaja AP;Tamraz B;Williams KM;Mahroo OA;Freidin M;Solebo AL;Vehof J;Falchi M;Rahi JS;Hammond CJ;Hysi PG
通讯作者:
Hysi PG
影响因子:
2.9
作者:
Hébert HL;Veluchamy A;Baskozos G;Fardo F;Van Ryckeghem DML;Pascal MMV;Jones C;Milburn K;Pearson ER;Crombez G;Bennett DLH;Meng W;Palmer CNA;Smith BH
通讯作者:
Smith BH