“Brain-predicted age” estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology. We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid-β-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament-light-chain [NfL]), and cognition (global neuropsychological composite and CDR-sum of boxes). We compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of ADAD mutation variants, APOE ε4 carrier status, sex, and education. Advanced brain aging was observed in mutation-carriers approximately 7 years before expected symptom onset, in line with other established structural indicators of atrophy. BAG was moderately associated with amyloid PET and strongly associated with pTau-181, NfL, and cognition in mutation-carriers. Mutation variants, sex, and years of education contributed to variability in BAG. We extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG associates well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, BAG offers unique benefits in simplicity of data processing and interpretation. Thus, results in this unique ADAD cohort with few age-related confounds suggest that brain aging attributable to AD neuropathology can be accurately quantified from minimally-processed MRI.

中文翻译：

---

临床前常染色体显性阿尔茨海默病的高级结构性脑老化

“大脑预测年龄”根据神经影像扫描中复杂的非线性特征来估计生物年龄。在散发性阿尔茨海默病 (AD) 中，预测年龄与实足年龄之间的大脑年龄差距 (BAG) 较高，但在常染色体显性 AD (ADAD) 中尚未得到充分研究，其中 AD 进展是高度可预测的，与年龄相关的共同病理学混杂程度极低。我们使用经过最少处理的结构 MRI 扫描，在显性遗传性阿尔茨海默病网络的 257 名深度表型 ADAD 突变携带者和 179 名非携带者中建立了 BAG 模型。然后，我们测试了 BAG 是否因突变和认知状态或症状出现的估计年数而有所不同，以及它是否与已建立的淀粉样蛋白标志物（PiB PET、CSF 淀粉样蛋白-β-42/40）、磷酸化 tau 蛋白（CSF）相关。和血浆 pTau-181）、神经变性（CSF 和血浆神经丝轻链 [NfL]）和认知（整体神经心理复合和 CDR 框总和）。我们将 BAG 与其他 MRI 测量结果进行了比较，并检查了 BAG 的异质性与 ADAD 突变变异、APOE ε4 携带者状态、性别和教育程度的函数关系。在预期症状出现前大约 7 年，在突变携带者中观察到大脑提前老化，这与其他已确定的萎缩结构指标一致。 BAG 与淀粉样蛋白 PET 中度相关，与 pTau-181、NfL 和突变携带者认知密切相关。突变变异、性别和教育年限会导致 BAG 的变异。我们将之前使用 BAG 的工作从零星的 AD 扩展到 ADAD，并注意到一致的结果。 BAG 与 ADAD 中的 pTau、神经退行性变和认知标志物密切相关，但与淀粉样蛋白的关联程度较小。 BAG 可以捕获与已建立的 MRI 测量类似的信号。然而，BAG 在数据处理和解释简单性方面具有独特的优势。因此，这个独特的 ADAD 队列的结果几乎没有与年龄相关的混杂因素，这表明 AD 神经病理学引起的大脑衰老可以通过最少处理的 MRI 准确量化。