Genetics and prescription opioid use (GaPO): study design for consenting a cohort from an existing biobank to identify clinical and genetic factors influencing prescription opioid use and abuse.
Genetics and prescription opioid use (GaPO): study design for consenting a cohort from an existing biobank to identify clinical and genetic factors influencing prescription opioid use and abuse.
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DOI：
10.1186/s12920-021-01100-z
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发表时间：
2021-10-26
影响因子：
2.7
通讯作者：
Robishaw JD
中科院分区：
文献类型：
--
作者：
Troiani V;Crist RC;Doyle GA;Ferraro TN;Beiler D;Ranck S;McBryan K;Jarvis MA;Barbour JS;Han JJ;Ness RJ;Berrettini WH;Robishaw JD
处方阿片类药物(POS)通常用于治疗卫生系统中的中到重度慢性疼痛。尽管它们改善了许多患者的生活质量，但还需要更多的工作来确定临床和遗传因素，这些因素会使某些人在使用pos止痛后出现阿片类药物使用障碍(OUD)的高风险。随着对重要风险因素的更好理解，医生将能够更好地识别出患有OUD的风险最高的患者，这些患者应该考虑非阿片类药物的替代疗法和治疗。我们正在进行一项前瞻性的观察性研究，旨在确定与OUD最密切相关的临床和遗传因素。这项研究设计利用了现有的生物库，其中包括整个外显子组测序和阵列基因分型。生物库在一个综合卫生系统内维护，允许大规模捕获和整合遗传和非遗传数据。参与者通过知情同意加入卫生系统生物库，然后参加第二项侧重于阿片类药物使用的研究。数据捕获包括经过验证的自我报告调查，衡量成瘾严重程度、抑郁、焦虑和尼古丁使用情况，以及从电子健康记录中提取的其他临床、处方和脑成像数据。我们将利用这种多模式数据采集来建立有意义的患者表型，以了解OUD的遗传和非遗传贡献。网上版载有补充材料，可在10.1186/s12920-021-01100-z查阅。
Prescription opioids (POs) are commonly used to treat moderate to severe chronic pain in the health system setting. Although they improve quality of life for many patients, more work is needed to identify both the clinical and genetic factors that put certain individuals at high risk for developing opioid use disorder (OUD) following use of POs for pain relief. With a greater understanding of important risk factors, physicians will be better able to identify patients at highest risk for developing OUD for whom non-opioid alternative therapies and treatments should be considered. We are conducting a prospective observational study that aims to identify the clinical and genetic factors most stongly associated with OUD. The study design leverages an existing biobank that includes whole exome sequencing and array genotyping. The biobank is maintained within an integrated health system, allowing for the large-scale capture and integration of genetic and non-genetic data. Participants are enrolled into the health system biobank via informed consent and then into a second study that focuses on opioid medication use. Data capture includes validated self-report surveys measuring addiction severity, depression, anxiety, and nicotine use, as well as additional clinical, prescription, and brain imaging data extracted from electronic health records. We will harness this multimodal data capture to establish meaningful patient phenotypes in order to understand the genetic and non-genetic contributions to OUD. The online version contains supplementary material available at 10.1186/s12920-021-01100-z.
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影响因子：
11
作者：
Nelson EC;Agrawal A;Heath AC;Bogdan R;Sherva R;Zhang B;Al-Hasani R;Bruchas MR;Chou YL;Demers CH;Carey CE;Conley ED;Fakira AK;Farrer LA;Goate A;Gordon S;Henders AK;Hesselbrock V;Kapoor M;Lynskey MT;Madden PA;Moron JA;Rice JP;Saccone NL;Schwab SG;Shand FL;Todorov AA;Wallace L;Wang T;Wray NR;Zhou X;Degenhardt L;Martin NG;Hariri AR;Kranzler HR;Gelernter J;Bierut LJ;Clark DJ;Montgomery GW
通讯作者：
Montgomery GW
影响因子：
34.7
作者：
Alexander-Bloch, Aaron;Giedd, Jay N.;Bullmore, Edward T.
通讯作者：
Bullmore, Edward T.
影响因子：
0.5
作者：
Kroenke, K;Spitzer, RL
通讯作者：
Spitzer, RL
影响因子：
10.6
作者：
Bogdan R;Salmeron BJ;Carey CE;Agrawal A;Calhoun VD;Garavan H;Hariri AR;Heinz A;Hill MN;Holmes A;Kalin NH;Goldman D
通讯作者：
Goldman D
影响因子：
13.8
作者：
Appa A;Rodda LN;Cawley C;Zevin B;Coffin PO;Gandhi M;Imbert E
通讯作者：
Imbert E