Scholarlink

<p>Preventing Alzheimer’s disease (AD) requires early-warning biomarkers. We developed a Regional Vulnerability Index (RVI) that quantifies individual brain similarity to AD patients’ expected brain deficit patterns. We calculated regional effect sizes to establish brain deficit patterns in amyloid-positive AD cases compared to amyloid-negative healthy controls. RVI-AD was calculated as a linear index of individual similarity to this established brain pattern in AD. We demonstrated RVI-AD elevation associated with risk factors in 335 participants (mean age: 49 ± 13 years) in the Amish Connectome Project, followed by an independent sample consisting of 26,010 participants (mean age: 64 ± 7 years) from the UK Biobank. Genetic and cardiovascular risks were evaluated using APOE-e4 genotype and Framingham Cardiovascular Risk Scores (FCVRS), respectively. Additionally, we assessed the risk of converting from MCI to dementia in <i>N</i> = 1932 participants (mean age: ~74) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Healthy participants with the APOE-e4 allele had significantly elevated RVI-AD indices (<i>p</i> = 0.03 and 2·10<sup>−5</sup>, for ACP and UKBB samples respectively). FCVRS significantly contributed to higher RVI-AD in an interaction with APOE-e4-specific manner (<i>p</i> = 2·10<sup>−4</sup> and 7·10<sup>−6</sup> for ACP and UKBB samples respectively). In ADNI cohort, RVI-AD significantly predicted conversion from MCI to dementia in the next decade, particularly in the first three years (AUC = 70–74%, OR = 2.16, 95% CI = 1.8–2.6, <i>p</i> &lt; 10<sup>−16</sup>). In healthy individuals, the RVI-AD detected the insidious impact of APOE-ε4 and cardiovascular risks in otherwise normally aging cohorts. Elevated RVI-AD also predicted conversion to dementia within ten years in the older, high-risk cohort. Further development of this brain-pattern similarity-based approach may yield a noninvasive, clinically accessible biomarker to aid early detection of the subtle to more imminent effects of AD risks.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Alzheimer’s disease-like brain pattern biomarker: capturing risks and predicting disease onset

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月27日

查看全文
  • Peter Kochunov,
  • Si Gao,
  • Lauren E. Salminen,
  • Neda Jahanshad,
  • Talia M. Nir,
  • Paul M. Thompson,
  • Xiaoming Du,
  • Bhim M. Adhikari,
  • Alice Kochunov,
  • Ryan Cassidy,
  • Yizhou Ma,
  • Joshua Chiappelli,
  • Seth Ament,
  • Yezhi Pan,
  • Shuo Chen,
  • Alan R. Shuldiner,
  • Braxton D. Mitchell,
  • L. Jair Soares,
  • L. Elliot Hong

摘要

Preventing Alzheimer’s disease (AD) requires early-warning biomarkers. We developed a Regional Vulnerability Index (RVI) that quantifies individual brain similarity to AD patients’ expected brain deficit patterns. We calculated regional effect sizes to establish brain deficit patterns in amyloid-positive AD cases compared to amyloid-negative healthy controls. RVI-AD was calculated as a linear index of individual similarity to this established brain pattern in AD. We demonstrated RVI-AD elevation associated with risk factors in 335 participants (mean age: 49 ± 13 years) in the Amish Connectome Project, followed by an independent sample consisting of 26,010 participants (mean age: 64 ± 7 years) from the UK Biobank. Genetic and cardiovascular risks were evaluated using APOE-e4 genotype and Framingham Cardiovascular Risk Scores (FCVRS), respectively. Additionally, we assessed the risk of converting from MCI to dementia in N = 1932 participants (mean age: ~74) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Healthy participants with the APOE-e4 allele had significantly elevated RVI-AD indices (p = 0.03 and 2·10−5, for ACP and UKBB samples respectively). FCVRS significantly contributed to higher RVI-AD in an interaction with APOE-e4-specific manner (p = 2·10−4 and 7·10−6 for ACP and UKBB samples respectively). In ADNI cohort, RVI-AD significantly predicted conversion from MCI to dementia in the next decade, particularly in the first three years (AUC = 70–74%, OR = 2.16, 95% CI = 1.8–2.6, p < 10−16). In healthy individuals, the RVI-AD detected the insidious impact of APOE-ε4 and cardiovascular risks in otherwise normally aging cohorts. Elevated RVI-AD also predicted conversion to dementia within ten years in the older, high-risk cohort. Further development of this brain-pattern similarity-based approach may yield a noninvasive, clinically accessible biomarker to aid early detection of the subtle to more imminent effects of AD risks.