From the Department of Neurology (C.M.A., B.B.W.), University of Virginia, Charlottesville; Department of Neurology (R.B., J.W.C.), University of Maryland, Baltimore; Program in Physical Therapy (K.L.), Washington University; Department of Neurology (K.L.), Washington University, St. Louis, MO; Department of Neurology (A.H.), Center for Brain and Mind Health, Yale University, New Haven, CT; Department of Neurology (S.C.C.), University of California Los Angeles; California Rehabilitation Institute (S.C.C.), Los Angeles; Department of Clinical Sciences Lund, Neurology (A.G.L.), Lund University; Department of Neurology (A.G.L.), Skane University Hospital, Sweden; Department of Public Health Sciences (K.L.K., B.B.W.); Center for Health Equity and Precision Public Health (K.L.K.), University of Virginia, Charlottesville; and Department of Biostatistics (F.-C.H.), School of Medicine, Wake Forest University, Winston-Salem, NC.
Neurology. 2024 Feb 13;102(3):e208011. doi: 10.1212/WNL.0000000000208011. Epub 2024 Jan 5.
Stroke genetic research has made substantial progress in the past decade. Its recovery application, however, remains behind, in part due to its reliance on the modified Rankin Scale (mRS) score as a measure of poststroke outcome. The mRS does not map well to biological processes because numerous psychosocial factors drive much of what the mRS captures. Second, the mRS contains multiple disparate biological events into a single measure further limiting its use for biological discovery. This led us to investigate the effect of distinct stroke recovery phenotypes on genetic variation associations with Genome-Wide Association Studies (GWASs) by repurposing the NIH Stroke Scale (NIHSS) and its subscores.
In the Vitamin Intervention for Stroke Prevention cohort, we estimated changes in cognition, motor, and global impairments over 2 years using specific measures. We included genotyped participants with a total NIHSS score greater than zero at randomization and excluded those with recurrent stroke during the trial. A GWAS linear mixed-effects model predicted score changes, with participant as a random effect, and included initial score, age, sex, treatment group, and the first 5 ancestry principal components.
In total, 1,270 participants (64% male) were included with a median NIHSS score of 2 (interquartile range [IQR] 1-3) and median age 68 (IQR 59-75) years. At randomization, 20% had cognitive deficits (NIHSS Cog-4 score >0) and 70% had ≥1 motor deficits (impairment score >1). At 2 years, these percentages improved to 7.2% with cognitive deficits and 30% with motor deficits. GWAS identified novel suggestive gene-impairment associations ( < 5e) for cognition (, , , , , and ), motor (, , , , , and ), and global ( and ) impairments.
Defining domain-specific stroke recovery phenotypes and using longitudinal clinical trial designs can help detect novel genes associated with chronic recovery. These data support the use of granular endpoints to identify genetic associations related to stroke recovery.
在过去十年中,中风遗传学研究取得了重大进展。然而,其恢复应用仍落后于其他领域,部分原因是它依赖于改良 Rankin 量表(mRS)评分作为中风后结果的衡量标准。mRS 与生物过程并不吻合,因为许多社会心理因素驱动了 mRS 所捕捉到的大部分内容。其次,mRS 将多个不同的生物事件纳入一个单一的测量标准,进一步限制了它在生物发现中的应用。这促使我们通过重新利用 NIH 中风量表(NIHSS)及其子评分来研究不同的中风恢复表型对与全基因组关联研究(GWAS)相关的遗传变异的影响。
在维生素干预预防中风队列中,我们使用特定的措施估计了认知、运动和整体障碍在 2 年内的变化。我们纳入了在随机分组时 NIHSS 总分大于零的基因分型参与者,并排除了在试验期间再次中风的参与者。GWAS 线性混合效应模型预测了评分变化,参与者作为随机效应,包括初始评分、年龄、性别、治疗组和前 5 个祖先主成分。
总共纳入了 1270 名参与者(64%为男性),其 NIHSS 评分中位数为 2(四分位间距 [IQR] 1-3),年龄中位数为 68(IQR 59-75)岁。在随机分组时,20%的人存在认知缺陷(NIHSS Cog-4 评分>0),70%的人存在≥1 个运动缺陷(损伤评分>1)。2 年后,认知缺陷的百分比改善到 7.2%,运动缺陷的百分比改善到 30%。GWAS 确定了认知(、、、、、和)、运动(、、、、、和)和整体(和)损伤的新的提示性基因-损伤关联(<5e)。
定义特定于领域的中风恢复表型并使用纵向临床试验设计可以帮助检测与慢性恢复相关的新基因。这些数据支持使用粒度终点来识别与中风恢复相关的遗传关联。