Leveraging complementary big data methods and patient intervention designs to optimize neural markers of adolescent cannabis use

利用互补的大数据方法和患者干预设计来优化青少年大麻使用的神经标记

• 批准号: 10739527
• 负责人: Brenden Craig Tervo-Clemmens
• 金额: $ 19.55万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10739527
• 关键词: 14 year old; 16 year old; 18 year old; Abstinence; Address; Adolescence; Adolescent; Adult; Age; Award; Big Data; Big Data Methods; Biochemical; Biometry; Brain; Cannabis; Clinical; Clinical Trials Design; Cognitive; Corpus striatum structure; Data; Data Set; Development; Enrollment; Epidemiologic Methods; Epidemiology; Family history of; Frequencies; Functional Magnetic Resonance Imaging; Funding; Future; Goals; Image; Impulsivity; Incentives; Income; Intervention; Link; Machine Learning; Mentored Patient-Oriented Research Career Development Award; Mentors; Mentorship; Meta-Analysis; Methodology; Methods; Monitor; Multivariate Analysis; Neurosciences; Outcome; Patients; Pharmacological Treatment; Phenotype; Population; Population Study; Probability; Process; Protocols documentation; Psychiatry; Psychotic Disorders; Randomized; Recovery; Reproducibility; Research; Research Methodology; Rest; Rewards; Risk; Risk Factors; Role; Sampling; Scanning; Specificity; Substance Use Disorder; Testing; Time; Training; Translational Research; Translations; Validation; addiction; career development; clinical training; clinical translation; clinically relevant; cognitive development; contingency management; data integration; design; disorder prevention; expectation; improved; innovation; large scale data; magnetic resonance imaging biomarker; marijuana use; marijuana use disorder; multidisciplinary; neural; neurodevelopment; neuroimaging; patient oriented; pre-clinical; predictive modeling; prevent; programs; prolonged abstinence; psychosocial; research and development; response; reward circuitry; skills; social determinants; support vector machine; therapy design; trait

ABSTRACT/PROJECT SUMMARY Cannabis initiation during adolescence confers four-fold greater risk for cannabis use disorder (CUD) than initiation in adulthood and is associated with increased risk for negative psychiatric outcomes. No effective pharmacologic treatment exists for adolescent cannabis use or CUD, and most adolescents do not achieve sustained abstinence with psychosocial interventions. Functional MRI (fMRI) holds promise for identifying new intervention targets and/or clarifying mechanisms of existing treatments but has yet to lead to clinical translation. New, large-scale neuroimaging data and complementary patient intervention designs with precision neuroimaging can begin to address remaining questions on the cause vs. effect between neural markers and cannabis use, the extent to which putative neural markers of cannabis use instead reflect psychiatric, familial, and/or social determinants of substance use disorders (SUDs), and whether neural markers normalize with abstinence. Through this 4-year K23 award, I will build upon my existing skillset in developmental neuroscience and big data neuroimaging with new training in addiction phenotyping in population studies (e.g., Adolescent Brain Cognitive Development [ABCD] study) and mentored implementation of complementary precision neuroimaging approaches within patient intervention designs for adolescents with CUD. The proposed research aims will (1) utilize existing ABCD Study data to validate known and identify new functional MRI markers of cannabis use initiation and (2) leverage a precision neuroimaging study within a CUD patient intervention design to test the modifiability of functional MRI markers of cannabis use during the transition from regular use to abstinence. Matched neuroimaging protocols, out-of-sample validation, design approaches to increase reliability, and high frequency scanning in the precision neuroimaging study (3 scans over 6 weeks in adolescents with CUD randomized to cannabis abstinence (n=24) or cannabis monitoring (n=20), and matched controls (n=20)) provide key innovations towards rigor and reproducibility. With these methods, we will test the overarching hypothesis that hyperfunction of fronto-striatal reward circuitry is both a trait-level risk-factor and modifiable consequence of adolescent cannabis use. Recognizing the need for both neural and phenotypic specificity, we will compare hypothesis-driven, fronto-striatal circuit markers to data-driven, whole-brain effects and also examine the potential moderating role of psychiatric, environmental, and social determinants of SUD. Through these scientific aims, associated training goals, and guidance from an exceptional multidisciplinary mentorship team, I will gain the necessary skills to address the current methodological issues facing my field and contribute to improved translational research on the neurodevelopment of SUDs. Complementary skillsets in large-scale neuroimaging and clinically relevant, patient-oriented designs, together with my clinical training, will uniquely prepare me for an independent program of research and associated independent funding. .

摘要/项目总结 青少年时期开始吸食大麻，患大麻使用障碍（CUD）的风险是青少年时期的四倍。 在成年期开始，并与负面精神病结果的风险增加有关。没有有效 药物治疗存在青少年大麻使用或CUD，大多数青少年没有达到 通过社会心理干预持续禁欲。功能性磁共振成像（fMRI）有望识别新的 干预目标和/或澄清现有治疗的机制，但尚未导致临床转化。 新的大规模神经影像数据和精确的辅助患者干预设计 神经成像可以开始解决关于神经标记物之间的因果关系的剩余问题， 大麻使用，大麻使用的假定神经标志物在多大程度上反映了精神病，家庭， 和/或物质使用障碍（SUD）的社会决定因素，以及神经标志物是否正常化， 禁欲通过这个为期4年的K23奖，我将建立在我现有的技能在发展神经科学 和大数据神经成像与人口研究中成瘾表型的新培训（例如，青少年 大脑认知发展[ABCD]研究）和指导实施互补精度 青少年CUD患者干预设计中的神经影像学方法。拟议研究 目的是（1）利用现有的ABCD研究数据来验证已知的和识别新的功能性MRI标记物， 开始使用大麻和（2）在CUD患者干预设计中利用精确的神经成像研究 测试大麻使用的功能性MRI标记物在从常规使用过渡到 禁欲匹配的神经成像协议，样本外验证，提高可靠性的设计方法， 在精确神经成像研究中，高频扫描（在青少年中进行6周以上的3次扫描， CUD随机分为大麻戒断组（n=24）或大麻监测组（n=20），以及匹配对照组（n=20）） 为严谨性和可重复性提供关键创新。通过这些方法，我们将测试 假设额-纹状体奖赏回路功能亢进既是一个特质水平的危险因素， 青少年使用大麻的后果。认识到需要神经和表型特异性，我们 将比较假设驱动的额纹状体电路标记与数据驱动的全脑效应， 研究SUD的精神，环境和社会决定因素的潜在调节作用。通过 这些科学目标，相关的培训目标，并从一个特殊的多学科导师的指导， 我将获得必要的技能，以解决当前面临的方法问题，我的领域，并作出贡献 改善对SUD神经发育的转化研究。大规模的互补技能 神经影像学和临床相关的，以病人为导向的设计，加上我的临床培训，将独特的 为我准备一个独立的研究项目和相关的独立资金。 .