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Characterization of MRI-derived atrophy subtypes using post-mortem MRI and neuropathological markers in Alzheimer's disease 利用死后MRI和阿尔茨海默病的神经病理标记物表征MRI衍生的萎缩亚型
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106454
Ismael Luis Calandri, Laura E. Jonkman, Sophie E. Mastenbroek, Alex J. Wesseling, Colin Groot, Frederik Barkhof, Yolande A.L. Pijnenburg, Rik Ossenkoppele
<div> <section> <h3> Background</h3> <p>Alzheimer's disease (AD) exhibits diverse neurodegeneration patterns, highlighting the need for detailed atrophy mapping to improve early diagnosis and monitoring. Although MRI scans are commonly used for <i>in vivo</i> brain assessment, the interpretation of atrophy patterns in the context of neuropathological findings has been limited. This study aims to address this gap by combining structural MRI with postmortem pathological data to assess howdata-driven atrophy subtypes correlate with underlying AD pathology, axonal degeneration and myelin integrity.</p> </section> <section> <h3> Method</h3> <p>We analyzed 2,029 MRI scans from cognitively impaired individuals with positive AD biomarkers. Cortical volumes and thicknesses were computed using FreeSurfer and harmonized across MRI scanners with NeuroCombat. Measurements were normalized using data from 620 cognitively unimpaired individuals with negative AD biomarkers. A SuStaIn (Subtype and staging inference) model was trained with detection thresholds of 0.5, 1, and 2 SDs. To validate, the trained model was used to classify and stage a subset with available postmortem MRI and neuropathological data (<i>n</i> = 34 AD, <i>n</i> = 16 controls). We quantified amyloid (4G8), pTau (AT8), NfL, myelin (PLP), and microglia (IBA1) in the fusiform gyrus, superior parietal lobule, precuneus, middle temporal gyrus, middle frontal gyrus, posterior cingulate gyrus, parahippocampal gyrus, occipital cortex and right hippocampus. A linear mixed-effects model tested regional neuropathological differences across subtypes, adjusting for stage.</p> </section> <section> <h3> Result</h3> <p>We found three subtypes: Subtype-1,(limbic) initially hippocampal involvement, accounting for 55.8% of cases; subtype-2 (posterior), initial involvement of the parietal lobes, (29.4%); and subtype-3 (hippocampal sparing), relative preserved hippocampi until advanced stages (14.7%, Figures 1 and 2). Subtypes 1 and 2 showed significantly greater pTau deposition in middle frontal gyrus and temporal (fusiform gyrus, medial and parahippocampal) regions compared to subtype 3 (<i>p</i> <0.01, Figure 3). Subtype-2 exhibited higher Tau burden than subtype-1 in parietal regions (<i>p</i> <0.01). Additionally, subtype 1 had higher NfL levels in the superior parietal lobule (<i>p</i> = 0.02) than subtype-2. No significant differences were found in amyloid and microglia distribution.</p> </section> <section> <h3> Conclusion</h3> <p>We identified three subtypes of atrophy progression that resemble clini
阿尔茨海默病（AD）表现出多种神经退行性变模式，因此需要详细的萎缩图谱来改善早期诊断和监测。尽管MRI扫描通常用于体内脑评估，但在神经病理发现的背景下对萎缩模式的解释受到限制。本研究旨在通过结合结构MRI和死后病理数据来解决这一空白，以评估数据驱动的萎缩亚型如何与潜在的阿尔茨海默病病理、轴突变性和髓鞘完整性相关。方法分析2029例AD生物标志物阳性的认知障碍患者的MRI扫描结果。使用FreeSurfer计算皮质体积和厚度，并通过MRI扫描仪与NeuroCombat进行协调。使用620名AD生物标志物阴性的认知未受损个体的数据进行标准化测量。采用检测阈值为0.5、1和2 sd的SuStaIn（亚型和分期推断）模型进行训练。为了验证，训练后的模型使用可用的死后MRI和神经病理学数据对一个子集进行分类和分期（n = 34 AD, n = 16对照）。我们量化了梭状回、顶叶上小叶、楔前叶、颞中回、额叶中回、扣带回后回、海马旁回、枕皮质和右侧海马中的淀粉样蛋白（4G8）、pTau （AT8）、NfL、髓磷脂（PLP）和小胶质细胞（IBA1）。线性混合效应模型测试了不同亚型的区域神经病理差异，并根据阶段进行了调整。结果发现三种亚型：亚型- 1，（边缘）最初累及海马，占病例的55.8%；亚型‐2（后），最初累及顶叶，（29.4%）；亚型- 3（海马保留），相对保存的海马直到晚期（14.7%，图1和2）。与亚型3相比，亚型1和亚型2在额叶中回和颞叶（梭状回、内侧和海马旁）区域的pTau沉积显著增加（p <0.01，图3）。亚型2在顶叶区域的Tau负荷高于亚型1 （p <0.01）。此外，亚型1在顶叶上小叶中的NfL水平高于亚型2 （p = 0.02）。淀粉样蛋白和小胶质细胞分布无显著差异。结论：我们确定了三种与临床观察相似的萎缩进展亚型。死后标记物的分布通常反映了在不同亚型中观察到的萎缩模式，支持了所识别亚型的生物学合理性。
{"title":"Characterization of MRI-derived atrophy subtypes using post-mortem MRI and neuropathological markers in Alzheimer's disease","authors":"Ismael Luis Calandri,&nbsp;Laura E. Jonkman,&nbsp;Sophie E. Mastenbroek,&nbsp;Alex J. Wesseling,&nbsp;Colin Groot,&nbsp;Frederik Barkhof,&nbsp;Yolande A.L. Pijnenburg,&nbsp;Rik Ossenkoppele","doi":"10.1002/alz70856_106454","DOIUrl":"10.1002/alz70856_106454","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Alzheimer's disease (AD) exhibits diverse neurodegeneration patterns, highlighting the need for detailed atrophy mapping to improve early diagnosis and monitoring. Although MRI scans are commonly used for &lt;i&gt;in vivo&lt;/i&gt; brain assessment, the interpretation of atrophy patterns in the context of neuropathological findings has been limited. This study aims to address this gap by combining structural MRI with postmortem pathological data to assess howdata-driven atrophy subtypes correlate with underlying AD pathology, axonal degeneration and myelin integrity.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Method&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We analyzed 2,029 MRI scans from cognitively impaired individuals with positive AD biomarkers. Cortical volumes and thicknesses were computed using FreeSurfer and harmonized across MRI scanners with NeuroCombat. Measurements were normalized using data from 620 cognitively unimpaired individuals with negative AD biomarkers. A SuStaIn (Subtype and staging inference) model was trained with detection thresholds of 0.5, 1, and 2 SDs. To validate, the trained model was used to classify and stage a subset with available postmortem MRI and neuropathological data (&lt;i&gt;n&lt;/i&gt; = 34 AD, &lt;i&gt;n&lt;/i&gt; = 16 controls). We quantified amyloid (4G8), pTau (AT8), NfL, myelin (PLP), and microglia (IBA1) in the fusiform gyrus, superior parietal lobule, precuneus, middle temporal gyrus, middle frontal gyrus, posterior cingulate gyrus, parahippocampal gyrus, occipital cortex and right hippocampus. A linear mixed-effects model tested regional neuropathological differences across subtypes, adjusting for stage.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Result&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We found three subtypes: Subtype-1,(limbic) initially hippocampal involvement, accounting for 55.8% of cases; subtype-2 (posterior), initial involvement of the parietal lobes, (29.4%); and subtype-3 (hippocampal sparing), relative preserved hippocampi until advanced stages (14.7%, Figures 1 and 2). Subtypes 1 and 2 showed significantly greater pTau deposition in middle frontal gyrus and temporal (fusiform gyrus, medial and parahippocampal) regions compared to subtype 3 (&lt;i&gt;p&lt;/i&gt; &lt;0.01, Figure 3). Subtype-2 exhibited higher Tau burden than subtype-1 in parietal regions (&lt;i&gt;p&lt;/i&gt; &lt;0.01). Additionally, subtype 1 had higher NfL levels in the superior parietal lobule (&lt;i&gt;p&lt;/i&gt; = 0.02) than subtype-2. No significant differences were found in amyloid and microglia distribution.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We identified three subtypes of atrophy progression that resemble clini","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 S2","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz70856_106454","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Expert Evaluation of Deep Learning Approaches to White Matter Hyperintensity Segmentation in Older Adults 深度学习方法在老年人脑白质高强度分割中的专家评价
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106019
Adam Martersteck, Siobhan McDermott, Caleb VanDyke, Karthik Sreenivasan, Maria Kharitonova, Sophia Moore, Rhiana Schafer, Amanda Cook Maher, Elizabeth Finger, Felicia C. Goldstein, Ozioma C. Okonkwo, Angela C. Roberts, Emily J Rogalski, SuperAging Research Initiative
<div> <section> <h3> Background</h3> <p>White matter hyperintensities (WMHs) are critical markers of cerebrovascular health and neurodegenerative disease. Accurate and reproducible quantification of WMHs is essential for characterizing vascular contributions to aging, cognition, and Alzheimer disease and related dementias. Deep learning pipelines have emerged as powerful tools for WMH segmentation, yet limited research compares their performance using expert evaluation as the benchmark. Here, we assess the performance of five deep learning WMH segmentation pipelines by comparing their outputs through blinded neuroradiologist ratings.</p> </section> <section> <h3> Method</h3> <p>We processed FLAIR scans from 100 older adults (aged 80 and older) enrolled in the SuperAging Research Initiative. 3D T<sub>2</sub>-weighted FLAIR and T<sub>1</sub>-weighted MPRAGE sequences followed the ADNI-3 protocol, acquired across five sites, using 3T scanners from three vendors (GE, Siemens, Philips). Binary segmentation masks from five deep learning pipelines were utilized: sysu_media, ANTSx, DeepWMH, TrUE-Net, and HyperMapp3r. A neuroradiologist (C.V.) evaluated the per-participant level randomized segmentation masks, overlaid on the FLAIR and T<sub>1</sub>-weighted image, using a 7-point Likert-type scale, where 1 indicated “poor segmentation” and 7 indicated “excellent segmentation". Ratings were based on anatomical plausibility and alignment with WMH voxels visible on FLAIR. To compare scores, a Kruskal-Wallis test and post-hoc Mann-Whitney pairwise comparisons were used.</p> </section> <section> <h3> Result</h3> <p>The Kruskal-Wallis test revealed significant differences in segmentation quality across the five pipelines (<i>p</i> = 7.73 x 10<sup>-43</sup>). Post-hoc Mann-Whitney tests showed ANTSx (mean rating = 5.59 ± 1.17) performed significantly better than all other pipelines (all <i>p</i> < 0.00001), while HyperMapp3r (mean rating = 2.33 ± 1.22) consistently received significantly lower ratings (all <i>p</i> < 0.00001). DeepWMH (mean rating = 4.45 ± 1.34), sysu_media (mean rating = 4.18 ± 1.20), and TrUE-Net (mean rating = 4.49 ±1.18) had comparable ratings, with no significant differences between the three.</p> </section> <section> <h3> Conclusion</h3> <p>This study highlights significant variability in the quality of WMH segmentation across commonly used deep learning pipelines when benchmarked against expert evaluation. Among the evaluated pipelines, ANTSx demonstrated superior performance, producing clinically plausible segmentations with high anatomical fidelity. These findings underscore the importance of expert validation in s
背景白质高信号（WMHs）是脑血管健康和神经退行性疾病的重要标志。准确和可重复的量化wmh对于表征血管对衰老、认知、阿尔茨海默病和相关痴呆的贡献至关重要。深度学习管道已经成为WMH分割的强大工具，但很少有研究将其性能与专家评估作为基准进行比较。在这里，我们通过盲法神经放射学家评分来比较五种深度学习WMH分割管道的输出，从而评估它们的性能。方法：我们对100名参加超级衰老研究计划（SuperAging Research Initiative）的老年人（80岁及以上）的FLAIR扫描数据进行处理，使用来自三家供应商（GE、西门子、飞利浦）的3T扫描仪，按照ADNI-3协议，在五个地点获得3D t2加权FLAIR和t1加权MPRAGE序列。使用了来自五个深度学习管道的二进制分割掩码：sysu_media， ANTSx, DeepWMH， TrUE-Net和HyperMapp3r。神经放射学家（C.V.）评估每个参与者水平的随机分割面具，覆盖在FLAIR和t1加权图像上，使用7分likert型量表，其中1表示“分割差”，7表示“分割好”。评分基于解剖合理性和与FLAIR上可见的WMH体素的对齐。为了比较分数，使用了Kruskal-Wallis检验和事后曼-惠特尼两两比较。结果Kruskal-Wallis检验显示5条管道的分割质量存在显著差异（p = 7.73 x 10-43）。事后Mann-Whitney检验显示，ANTSx（平均评分= 5.59±1.17）显著优于其他所有管道（均p <； 0.00001），而HyperMapp3r（平均评分= 2.33±1.22）的评分始终显著低于其他管道（均p <； 0.00001）。DeepWMH（平均评分= 4.45±1.34）、sysu_media（平均评分= 4.18±1.20）和TrUE-Net（平均评分= 4.49±1.18）评分相当，三者之间无显著差异。本研究强调了在与专家评估进行基准比较时，跨常用深度学习管道的WMH分割质量的显著差异。在评估的管道中，ANTSx表现出优越的性能，产生具有高解剖保真度的临床合理的分割。这些发现强调了专家验证在选择和完善自动分割工具的重要性，用于衰老和神经退行性疾病的研究和临床应用。
{"title":"Expert Evaluation of Deep Learning Approaches to White Matter Hyperintensity Segmentation in Older Adults","authors":"Adam Martersteck,&nbsp;Siobhan McDermott,&nbsp;Caleb VanDyke,&nbsp;Karthik Sreenivasan,&nbsp;Maria Kharitonova,&nbsp;Sophia Moore,&nbsp;Rhiana Schafer,&nbsp;Amanda Cook Maher,&nbsp;Elizabeth Finger,&nbsp;Felicia C. Goldstein,&nbsp;Ozioma C. Okonkwo,&nbsp;Angela C. Roberts,&nbsp;Emily J Rogalski,&nbsp;SuperAging Research Initiative","doi":"10.1002/alz70856_106019","DOIUrl":"https://doi.org/10.1002/alz70856_106019","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;White matter hyperintensities (WMHs) are critical markers of cerebrovascular health and neurodegenerative disease. Accurate and reproducible quantification of WMHs is essential for characterizing vascular contributions to aging, cognition, and Alzheimer disease and related dementias. Deep learning pipelines have emerged as powerful tools for WMH segmentation, yet limited research compares their performance using expert evaluation as the benchmark. Here, we assess the performance of five deep learning WMH segmentation pipelines by comparing their outputs through blinded neuroradiologist ratings.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Method&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We processed FLAIR scans from 100 older adults (aged 80 and older) enrolled in the SuperAging Research Initiative. 3D T&lt;sub&gt;2&lt;/sub&gt;-weighted FLAIR and T&lt;sub&gt;1&lt;/sub&gt;-weighted MPRAGE sequences followed the ADNI-3 protocol, acquired across five sites, using 3T scanners from three vendors (GE, Siemens, Philips). Binary segmentation masks from five deep learning pipelines were utilized: sysu_media, ANTSx, DeepWMH, TrUE-Net, and HyperMapp3r. A neuroradiologist (C.V.) evaluated the per-participant level randomized segmentation masks, overlaid on the FLAIR and T&lt;sub&gt;1&lt;/sub&gt;-weighted image, using a 7-point Likert-type scale, where 1 indicated “poor segmentation” and 7 indicated “excellent segmentation\". Ratings were based on anatomical plausibility and alignment with WMH voxels visible on FLAIR. To compare scores, a Kruskal-Wallis test and post-hoc Mann-Whitney pairwise comparisons were used.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Result&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The Kruskal-Wallis test revealed significant differences in segmentation quality across the five pipelines (&lt;i&gt;p&lt;/i&gt; = 7.73 x 10&lt;sup&gt;-43&lt;/sup&gt;). Post-hoc Mann-Whitney tests showed ANTSx (mean rating = 5.59 ± 1.17) performed significantly better than all other pipelines (all &lt;i&gt;p&lt;/i&gt; &lt; 0.00001), while HyperMapp3r (mean rating = 2.33 ± 1.22) consistently received significantly lower ratings (all &lt;i&gt;p&lt;/i&gt; &lt; 0.00001). DeepWMH (mean rating = 4.45 ± 1.34), sysu_media (mean rating = 4.18 ± 1.20), and TrUE-Net (mean rating = 4.49 ±1.18) had comparable ratings, with no significant differences between the three.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;This study highlights significant variability in the quality of WMH segmentation across commonly used deep learning pipelines when benchmarked against expert evaluation. Among the evaluated pipelines, ANTSx demonstrated superior performance, producing clinically plausible segmentations with high anatomical fidelity. These findings underscore the importance of expert validation in s","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 S2","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz70856_106019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145964225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Large-scale cerebrospinal fluid proteomics identifies molecular signatures of disease progression across Alzheimer's disease and sporadic frontotemporal lobar degeneration 大规模脑脊液蛋白质组学鉴定了阿尔茨海默病和散发性额颞叶变性疾病进展的分子特征
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_107629
Rowan Saloner, Joshua Downer, Julia D Webb, Argentina Lario Lago, Peter A. Ljubenkov, Lawren VandeVrede, Adam M. Staffaroni, Emily W. Paolillo, Salvatore Spina, Lea T. Grinberg, Renaud La Joie, Gil D. Rabinovici, Joel H Kramer, Maria Luisa Gorno Tempini, Bruce L. Miller, Howard J. Rosen, Julio C. Rojas, Jennifer S. Yokoyama, William W. Seeley, Adam L. Boxer, Kaitlin B Casaletto
<div> <section> <h3> Background</h3> <p>Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), and other neurodegenerative diseases are characterized by pathological protein misfolding, yet postmortem neuropathological measures collectively explain less than half the variance in antemortem clinical progression. We leveraged large-scale cerebrospinal fluid (CSF) proteomics to identify overlapping and distinct molecular signatures that help explain clinical severity across patients with AD, FTLD-tau, and FTLD-TDP.</p> </section> <section> <h3> Method</h3> <p>CSF was assayed via aptamer-based proteomics (SomaScan v4.1 >7k proteins) in 132 symptomatic AD patients (positive CSF <i>p</i>-Tau181/Ab<sub>42</sub> ratios and/or amyloid PET), 64 sporadic FTLD-tau patients, 42 sporadic FTLD-TDP patients, and 72 AD biomarker-negative controls. FTLD cases screened negative for autosomal dominant FTLD mutations and were classified via either autopsy confirmation (65% of cases; FTLD-tau: progressive supranuclear palsy [PSP], corticobasal degeneration, Pick's; FTLD-TDP: types A-C) or clinical diagnosis with high etiologic specificity (35% of cases; FTLD-tau: PSP-RS; FTLD-TDP: semantic variant primary progressive aphasia). Clinical severity was measured via CDR®+NACC FTLD sum of boxes. Differential abundance and co-expression network analyses modeled proteomic differences across groups and in relation to clinical severity.</p> </section> <section> <h3> Result</h3> <p>We identified 1,026 differentially abundant proteins (DAPs) across diseases (omnibus ANOVA FDR-<i>p</i> <.05) that mapped onto 21 co-expression modules. Most modules harbored DAPs shared by >1 disease vs. control, suggesting common molecular signatures across diseases. Protein degradation modules exhibited overrepresentation of DAPs that were elevated in AD (module M14 phosphatase binding: 74% DAPs, M2 protein transport: 59% DAPs), neuronal modules had overrepresentation of DAPs that were reduced in FTLD-tau (M3 postsynapse: 73% DAPs, M1 axon guidance: 40% DAPs), and RNA metabolism modules had overrepresentation of DAPs that were reduced in FTLD-TDP (M19 ribonucleoprotein complex: 56% DAPs, M13 RNA splicing: 51% DAPs). Neuronal modules harbored the largest proportion of proteins negatively correlated with clinical severity across the full sample (M3: 79%, M1: 59%; <i>p</i>s<.05), including targets that outperformed CSF neurofilament light in predicting clinical severity across all three disease groups (e.g., NPTX2, IRF1, TMEM132B).</p> </section> <section> <h3> Conclusion</h3> <
阿尔茨海默病（AD）、额颞叶变性（FTLD）和其他神经退行性疾病的特征是病理性蛋白错误折叠，但死后神经病理学测量加起来只能解释不到一半的死前临床进展差异。我们利用大规模脑脊液（CSF）蛋白质组学来识别重叠和不同的分子特征，这些特征有助于解释AD、FTLD - tau和FTLD - TDP患者的临床严重程度。方法采用适体蛋白组学（SomaScan v4.1 >；7k蛋白）检测132例AD症状患者（CSF p - Tau181/Ab 42比值和/或淀粉样PET阳性）、64例散发性FTLD - tau患者、42例散发性FTLD - TDP患者和72例AD生物标志物阴性对照者的脑脊液。FTLD患者常染色体显性FTLD突变筛查阴性，通过尸检确认（65%的病例；FTLD‐tau：进行性核上性麻痹[PSP]，皮质基底变性，皮克氏症；FTLD‐TDP: A‐C型）或具有高病因特异性的临床诊断（35%的病例；FTLD‐tau: PSP‐RS； FTLD‐TDP：语义变异原发性进行性失语症）进行分类。临床严重程度通过CDR®+NACC FTLD总箱数来衡量。差异丰度和共表达网络分析模拟了各组之间的蛋白质组学差异以及与临床严重程度的关系。结果：我们鉴定出1026个不同疾病的差异丰富蛋白（DAPs）（综合方差分析FDR‐p <； 0.05），这些蛋白映射到21个共表达模块上。大多数模块都包含疾病与对照所共享的DAPs，这表明疾病之间存在共同的分子特征。蛋白质降解模块在AD中表现出高表达的DAPs（模块M14磷酸酶结合：74% DAPs， M2蛋白转运：59% DAPs），神经元模块在FTLD - tau中表现出高表达的DAPs (M3突触后：73% DAPs， M1轴突引导：40% DAPs)， RNA代谢模块在FTLD - TDP中表现出高表达的DAPs （M19核糖核蛋白复合物：56% DAPs， M13 RNA剪接：51% DAPs）。在整个样本中，神经元模块中与临床严重程度负相关的蛋白质比例最大（M3: 79%, M1: 59%; p s< 0.05），包括在预测所有三种疾病组的临床严重程度方面优于CSF神经丝光的靶标（例如，NPTX2, IRF1, TMEM132B）。结论：研究结果强调了AD和散发性FTLD中重叠的脑脊液蛋白质组改变。神经元富集蛋白群落强有力地跟踪了各种疾病的临床严重程度，强调了它们作为疾病进展的跨诊断生物标志物和所有衰老大脑的治疗靶点的潜力。
{"title":"Large-scale cerebrospinal fluid proteomics identifies molecular signatures of disease progression across Alzheimer's disease and sporadic frontotemporal lobar degeneration","authors":"Rowan Saloner,&nbsp;Joshua Downer,&nbsp;Julia D Webb,&nbsp;Argentina Lario Lago,&nbsp;Peter A. Ljubenkov,&nbsp;Lawren VandeVrede,&nbsp;Adam M. Staffaroni,&nbsp;Emily W. Paolillo,&nbsp;Salvatore Spina,&nbsp;Lea T. Grinberg,&nbsp;Renaud La Joie,&nbsp;Gil D. Rabinovici,&nbsp;Joel H Kramer,&nbsp;Maria Luisa Gorno Tempini,&nbsp;Bruce L. Miller,&nbsp;Howard J. Rosen,&nbsp;Julio C. Rojas,&nbsp;Jennifer S. Yokoyama,&nbsp;William W. Seeley,&nbsp;Adam L. Boxer,&nbsp;Kaitlin B Casaletto","doi":"10.1002/alz70856_107629","DOIUrl":"10.1002/alz70856_107629","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), and other neurodegenerative diseases are characterized by pathological protein misfolding, yet postmortem neuropathological measures collectively explain less than half the variance in antemortem clinical progression. We leveraged large-scale cerebrospinal fluid (CSF) proteomics to identify overlapping and distinct molecular signatures that help explain clinical severity across patients with AD, FTLD-tau, and FTLD-TDP.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Method&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;CSF was assayed via aptamer-based proteomics (SomaScan v4.1 &gt;7k proteins) in 132 symptomatic AD patients (positive CSF &lt;i&gt;p&lt;/i&gt;-Tau181/Ab&lt;sub&gt;42&lt;/sub&gt; ratios and/or amyloid PET), 64 sporadic FTLD-tau patients, 42 sporadic FTLD-TDP patients, and 72 AD biomarker-negative controls. FTLD cases screened negative for autosomal dominant FTLD mutations and were classified via either autopsy confirmation (65% of cases; FTLD-tau: progressive supranuclear palsy [PSP], corticobasal degeneration, Pick's; FTLD-TDP: types A-C) or clinical diagnosis with high etiologic specificity (35% of cases; FTLD-tau: PSP-RS; FTLD-TDP: semantic variant primary progressive aphasia). Clinical severity was measured via CDR®+NACC FTLD sum of boxes. Differential abundance and co-expression network analyses modeled proteomic differences across groups and in relation to clinical severity.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Result&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We identified 1,026 differentially abundant proteins (DAPs) across diseases (omnibus ANOVA FDR-&lt;i&gt;p&lt;/i&gt; &lt;.05) that mapped onto 21 co-expression modules. Most modules harbored DAPs shared by &gt;1 disease vs. control, suggesting common molecular signatures across diseases. Protein degradation modules exhibited overrepresentation of DAPs that were elevated in AD (module M14 phosphatase binding: 74% DAPs, M2 protein transport: 59% DAPs), neuronal modules had overrepresentation of DAPs that were reduced in FTLD-tau (M3 postsynapse: 73% DAPs, M1 axon guidance: 40% DAPs), and RNA metabolism modules had overrepresentation of DAPs that were reduced in FTLD-TDP (M19 ribonucleoprotein complex: 56% DAPs, M13 RNA splicing: 51% DAPs). Neuronal modules harbored the largest proportion of proteins negatively correlated with clinical severity across the full sample (M3: 79%, M1: 59%; &lt;i&gt;p&lt;/i&gt;s&lt;.05), including targets that outperformed CSF neurofilament light in predicting clinical severity across all three disease groups (e.g., NPTX2, IRF1, TMEM132B).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 S2","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz70856_107629","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Evaluation of Biomarkers in Active Alzheimer's Disease Intervention Clinical Trials – The Biomarker Observatory 活性阿尔茨海默病干预临床试验中生物标志物的评估-生物标志物观察站
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_105220
Amanda M. Leisgang Osse, Yadi Zhou, Andrew Hooyman, Ayan Sengupta, Jorge Fonseca, Jefferson W Kinney, Feixiong Cheng, Jeffrey L. Cummings

Background

Biomarkers are critically important for Alzheimer's Disease (AD) drug development. They have a role in patient diagnosis and trial eligibility, pharmacodynamic changes, safety, monitoring, disease modification, and target engagement. In AD clinical trials, biomarkers are vital in determining the treatment efficacy, reliability, and safety.

Method

We created the Biomarker Observatory (BMO) to provide curated information on AD biomarkers for drug developers and clinical trialists. From the BMO, our aim is to explore and present the biomarkers that are currently being used in active AD intervention trials. We extract information from clinicaltrials.gov and annotate the eligibility, primary, secondary, and other biomarkers from each trial. Together with information from the Clinical Trial Observatory, we explore the imaging, fluid, and digital biomarkers being measured in active AD clinical trials, the trial characteristics, and influence of biomarkers on trials.

Result

For active trials in the year 2024 (January 1 to December 30, 2024), we found that 57% of the clinical trials used a biomarker as an eligibility criterion for patient participation. Imaging was the most common type of marker, with magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) most used as eligibility and primary outcome biomarkers. Fluid biomarkers (CSF, blood, plasma, or serum) were used in 28% of AD clinical trials as eligibility biomarkers and in 12% of trials as a primary outcome measure. Seventeen AD clinical trials measured amyloid beta protein (Aβ) in fluid samples as a criterion for eligibility and 17 evaluated hyperphosphorylated tau (p-tau). As a primary outcome measure, 2 trials measured Aβ in fluid samples and 7 investigated p-tau levels. Total tau and neurofilament light chain (NfL) were included as primary outcome measures in 2 and 3 trials, respectively.

Conclusion

Our data demonstrate how imaging, fluid, and digital biomarkers are used in current AD clinical trials and the impact they have on trial design and outcomes. We provide current biomarker information to advance AD drug development, aiming to increase trial success rates and reducing the time it takes for new AD therapeutics to reach patients.

生物标志物对阿尔茨海默病（AD）药物开发至关重要。他们在患者诊断和试验资格、药效学变化、安全性、监测、疾病改变和目标参与方面发挥作用。在阿尔茨海默病临床试验中，生物标志物在确定治疗疗效、可靠性和安全性方面至关重要。方法建立生物标志物观察站（BMO），为药物开发人员和临床试验人员提供有关AD生物标志物的信息。从BMO来看，我们的目标是探索和展示目前用于主动AD干预试验的生物标志物。我们从clinicaltrials.gov上提取信息，并注释每个试验的资格、主要、次要和其他生物标志物。结合临床试验观察站提供的信息，我们探讨了活动性阿尔茨海默病临床试验中测量的成像、流体和数字生物标志物、试验特征以及生物标志物对试验的影响。结果在2024年（2024年1月1日至12月30日）进行的临床试验中，我们发现57%的临床试验使用生物标志物作为患者参与的资格标准。成像是最常见的标志物类型，磁共振成像（MRI）和淀粉样正电子发射断层扫描（PET）是最常用的资格和主要结局生物标志物。28%的阿尔茨海默病临床试验使用液体生物标志物（脑脊液、血液、血浆或血清）作为合格性生物标志物，12%的试验使用液体生物标志物作为主要结局指标。17项阿尔茨海默病临床试验测量了液体样品中的β淀粉样蛋白（a β）作为合格标准，17项试验评估了过度磷酸化的tau蛋白（p‐tau）。作为主要结局指标，2项试验测量了液体样品中的a β， 7项研究了p - tau水平。总tau蛋白和神经丝轻链（NfL）分别在2项和3项试验中作为主要结局指标。我们的数据展示了成像、流体和数字生物标志物如何在当前的AD临床试验中使用，以及它们对试验设计和结果的影响。我们提供当前的生物标志物信息，以推进阿尔茨海默病药物的开发，旨在提高试验成功率，缩短新的阿尔茨海默病治疗药物到达患者手中所需的时间。
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引用次数: 0
Reduced Grid Cell-Like fMRI Activity relates to Synaptic Biomarkers in Predementia Alzheimer's Disease 网格细胞样fMRI活性降低与痴呆前阿尔茨海默病的突触生物标志物有关
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_107406
Jonas Alexander Jarholm, Marcia Bécu, Gøril Rolfseng Grøntvedt, Ivan Krasovec, Per Selnes, Sigrid Botne Sando, Ann Brinkmalm, Johanna Nilsson, Tobias Navarro Schröder, Atle Bjornerud, Tormod Fladby, Kaj Blennow, Tora Bonnevie, Christian F. Doeller
<div> <section> <h3> Background</h3> <p>The Entorhinal cortex (EC) is affected early by Alzheimer's disease (AD) pathology and is the main anatomical location of grid cells. Our aim was to determine whether grid-cell-like activity, and hippocampal task-related activity, as measured by blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI), was associated with AD disease progression and specific biomarkers.</p> </section> <section> <h3> Method</h3> <p>We invited participants to perform a virtual reality (VR) navigation task during fMRI. Participants were stratified as amyloid positive (+) or negative (-) by CSF amyloid-beta (Aß) 42/40-ratio, and classified as cognitively normal (CN) or mild cognitive impairment (MCI) based on a standardized cognitive test-battery. Controls were CN Aß- (<i>n</i> = 20), while cases were CN Aß+ (<i>n</i> = 21) and MCI Aß+(<i>n</i> = 14).«Gridness» was defined as the strength of the hexadirectional modulation of the BOLD signal in EC, observed during virtual environment navigation as participants memorized and retrieved 4 objects in a 3T scanner. We used a general linear model to test the relationship between the fMRI parameters (gridness and hippocampal task-related activity) and the following biomarkers: cerebrospinal fluid (CSF) phosphorylated tau (ptau) 181, plasma ptau217, and CSF 14-3-3 zetadelta, a novel biomarker of synaptic degradation.</p> </section> <section> <h3> Result</h3> <p>Significant gridness was only found in controls, not in cases. Compared to controls, there was significantly lower gridness in MCI Aß+ (<i>p</i> <0.01) but only trending towards lower gridness (<i>p</i> = 0.078) in CN Aß+. Hippocampal task-related activity was significantly higher in both CN Aß+ (<i>p</i> <0.05) and MCI Aß+ (<i>p</i> <0.001) compared to controls. The association between gridness and biomarkers was trending for CSF ptau181 (<i>p</i> = 0.064), significant for plasma ptau217 (<i>p</i> = 0.05), and highly significant for CSF 14-3-3 zetadelta (<i>p</i> <0.01). The association with hippocampal task-related activity was not significant for CSF ptau181, and trending for plasma ptau217 (<i>p</i> = 0.057) and CSF 14-3-3 zetadelta (<i>p</i> = 0.054).</p> </section> <section> <h3> Conclusion</h3> <p>Lower gridness and higher hippocampal task-related activity was associated with more advanced predementia AD, also before cognitive impairment or MTL atrophy. Lower gridness could be caused by altered neuronal activity and computation. Gridness had the strongest association to biomarkers, especially CSF 14-3-3 zetadelta, suggesting that synaptic degradation could be an important
背景内嗅皮层（EC）是阿尔茨海默病（AD）的早期病变，是网格细胞的主要解剖位置。我们的目的是通过血氧水平依赖（BOLD）功能磁共振成像（fMRI）测量网格细胞样活动和海马任务相关活动是否与AD疾病进展和特定生物标志物相关。方法邀请参与者在fMRI期间执行虚拟现实（VR）导航任务。根据脑脊液淀粉样蛋白- β (β) 42/40的比率，将参与者分为淀粉样蛋白阳性（+）或阴性（‐），并根据标准化的认知测试-组将参与者分为认知正常（CN）或轻度认知障碍（MCI）。对照组为CN asass‐（n = 20），病例为CN asass +(n = 21)和MCI asass +(n = 14)。“网格”被定义为EC中BOLD信号的六向调制强度，在虚拟环境导航期间，参与者在3T扫描仪中记忆和检索4个物体时观察到。我们使用一般线性模型来测试fMRI参数（网格度和海马任务相关活动）与以下生物标志物之间的关系：脑脊液（CSF）磷酸化tau (ptau) 181，血浆ptau217和CSF 14‐3‐3 zetadelta（一种新的突触降解生物标志物）。结果仅在对照组中发现明显的网格，而在病例中没有。与对照组相比，MCI asas +的网格度显著降低（p <0.01），而CN asas +的网格度趋于降低（p = 0.078）。与对照组相比，CN asas + (p <0.05)和MCI asas + (p <0.001)的海马任务相关活动显著升高。网格度与生物标志物之间的相关性在CSF ptau181中呈趋势（p = 0.064），在血浆ptau217中呈显著性（p = 0.05），在CSF 14‐3‐3 zetadelta中呈高度显著性（p <0.01）。脑脊液ptau181与海马任务相关活动的相关性不显著，血浆ptau217 （p = 0.057）和脑脊液14‐3‐3 zetadelta呈趋势（p = 0.054）。结论：较低的网格度和较高的海马任务相关活动与更严重的痴呆前期AD相关，也与认知障碍或颞叶萎缩相关。较低的网格度可能是由神经元活动和计算的改变引起的。网格性与生物标志物，特别是CSF 14‐3‐3 zetadelta的相关性最强，这表明突触降解可能是阿尔茨海默病网格细胞功能障碍的重要标志。
{"title":"Reduced Grid Cell-Like fMRI Activity relates to Synaptic Biomarkers in Predementia Alzheimer's Disease","authors":"Jonas Alexander Jarholm,&nbsp;Marcia Bécu,&nbsp;Gøril Rolfseng Grøntvedt,&nbsp;Ivan Krasovec,&nbsp;Per Selnes,&nbsp;Sigrid Botne Sando,&nbsp;Ann Brinkmalm,&nbsp;Johanna Nilsson,&nbsp;Tobias Navarro Schröder,&nbsp;Atle Bjornerud,&nbsp;Tormod Fladby,&nbsp;Kaj Blennow,&nbsp;Tora Bonnevie,&nbsp;Christian F. Doeller","doi":"10.1002/alz70856_107406","DOIUrl":"10.1002/alz70856_107406","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The Entorhinal cortex (EC) is affected early by Alzheimer's disease (AD) pathology and is the main anatomical location of grid cells. Our aim was to determine whether grid-cell-like activity, and hippocampal task-related activity, as measured by blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI), was associated with AD disease progression and specific biomarkers.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Method&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We invited participants to perform a virtual reality (VR) navigation task during fMRI. Participants were stratified as amyloid positive (+) or negative (-) by CSF amyloid-beta (Aß) 42/40-ratio, and classified as cognitively normal (CN) or mild cognitive impairment (MCI) based on a standardized cognitive test-battery. Controls were CN Aß- (&lt;i&gt;n&lt;/i&gt; = 20), while cases were CN Aß+ (&lt;i&gt;n&lt;/i&gt; = 21) and MCI Aß+(&lt;i&gt;n&lt;/i&gt; = 14).«Gridness» was defined as the strength of the hexadirectional modulation of the BOLD signal in EC, observed during virtual environment navigation as participants memorized and retrieved 4 objects in a 3T scanner. We used a general linear model to test the relationship between the fMRI parameters (gridness and hippocampal task-related activity) and the following biomarkers: cerebrospinal fluid (CSF) phosphorylated tau (ptau) 181, plasma ptau217, and CSF 14-3-3 zetadelta, a novel biomarker of synaptic degradation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Result&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Significant gridness was only found in controls, not in cases. Compared to controls, there was significantly lower gridness in MCI Aß+ (&lt;i&gt;p&lt;/i&gt; &lt;0.01) but only trending towards lower gridness (&lt;i&gt;p&lt;/i&gt; = 0.078) in CN Aß+. Hippocampal task-related activity was significantly higher in both CN Aß+ (&lt;i&gt;p&lt;/i&gt; &lt;0.05) and MCI Aß+ (&lt;i&gt;p&lt;/i&gt; &lt;0.001) compared to controls. The association between gridness and biomarkers was trending for CSF ptau181 (&lt;i&gt;p&lt;/i&gt; = 0.064), significant for plasma ptau217 (&lt;i&gt;p&lt;/i&gt; = 0.05), and highly significant for CSF 14-3-3 zetadelta (&lt;i&gt;p&lt;/i&gt; &lt;0.01). The association with hippocampal task-related activity was not significant for CSF ptau181, and trending for plasma ptau217 (&lt;i&gt;p&lt;/i&gt; = 0.057) and CSF 14-3-3 zetadelta (&lt;i&gt;p&lt;/i&gt; = 0.054).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Lower gridness and higher hippocampal task-related activity was associated with more advanced predementia AD, also before cognitive impairment or MTL atrophy. Lower gridness could be caused by altered neuronal activity and computation. Gridness had the strongest association to biomarkers, especially CSF 14-3-3 zetadelta, suggesting that synaptic degradation could be an important ","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 S2","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz70856_107406","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Associations of Estradiol and APOE4 Genotype with Hippocampal Connectivity during Verbal Encoding in Postmenopausal Women 绝经后妇女言语编码过程中雌二醇和APOE4基因型与海马连通性的关系
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_104927
Rachel A Schroeder, Rebecca C. Thurston, Minjie Wu, Howard J Aizenstein, Thomas K Karikari, M. Ilyas Kamboh, Ann D Cohen, Pauline M Maki
<div> <section> <h3> Background</h3> <p>High levels of endogenous estradiol in postmenopausal women are associated with beneficial effects on memory circuitry after menopause. Here we extend this work to examine 1) how estradiol and hippocampal functional connectivity (HippfConn) vary as a function of <i>APOE4</i> carrier status, and 2) whether estradiol-associated patterns of HippfConn relate to adverse AD biomarker profiles among <i>APOE4+</i> women.</p> </section> <section> <h3> Methods</h3> <p>Participants were enrolled in MsBrain, a cohort study of postmenopausal women, a subsample of whom completed 3T MRI neuroimaging, estradiol assessment, and plasma AD biomarker (pTau181, pTau231, amyloid-beta 42/40) measures (<i>n</i> = 172, mean age 59.3 ± 3.9 years, 83.1% white, 23.33% <i>APOE4</i> carriers). Interactive associations of estradiol levels and <i>APOE4</i> genotype (<i>APOE4+</i> versus <i>APOE4-</i>, excluding <i>APOE2</i>) with whole-brain left and right HippfConn during a word encoding fMRI task were analyzed via linear regression. Next, the magnitude of association between each estradiol-related HippfConn and AD biomarkers was examined, stratified by <i>APOE4</i> genotype. Models controlled for age, years of education, and body mass index, and were cluster-corrected at <i>p</i> <.05.</p> </section> <section> <h3> Results</h3> <p><i>APOE4</i>+ status modified the association of estradiol with both left and right HippfConn during encoding. Among <i>APOE4</i>+ women, higher estradiol was associated with lower connectivity between the left HippfConn to the left inferior temporal lobe, left superior parietal lobe, right middle frontal gyrus (MFG), right fusiform, left MFG, left amygdala and parahippocampal gyrus, left lingual gyrus, and right superior occipital lobe; in contrast, in <i>APOE4</i>- women, those associations were beneficial or neutral (Figure 1). Among <i>APOE4</i>+ women, higher estradiol was associated with increased right HippfConn to right cingulate gyrus, right MFG, right superior temporal gyrus (STG), left STG, and left amygdala; in contrast, associations in <i>APOE4</i>- women were neutral or negative, except for the amygdala (Figure 2). HippfConn was more strongly related to AD pathology in <i>APOE4+</i> than <i>APOE4</i>- individuals (Figure 3).</p> </section> <section> <h3> Conclusion</h3> <p>Among <i>APOE4</i>+ women, higher estradiol was associated with poorer patterns of HippfConn and increased AD pathology, as measured by plasma biomarkers. Among <i>APOE4-</i> women, higher estradiol levels appeared beneficial
背景：绝经后妇女体内高水平的内源性雌二醇与绝经后记忆回路的有益作用有关。在这里，我们扩展了这项工作，以研究1)雌二醇和海马功能连接（hipfconn）如何随着APOE4载体状态的变化而变化，以及2)在APOE4阳性女性中，雌二醇相关的hipfconn模式是否与不利的AD生物标志物谱有关。方法：MsBrain是一项针对绝经后妇女的队列研究，研究对象完成了3T MRI神经成像、雌二醇评估和血浆AD生物标志物（pTau181、pTau231、淀粉样蛋白42/40）检测（n = 172，平均年龄59.3±3.9岁，83.1%为白人，23.33%为APOE4携带者）。在单词编码fMRI任务中，通过线性回归分析雌二醇水平和APOE4基因型（APOE4+ vs APOE4‐，不包括APOE2）与全脑左、右hipfconn的交互关系。接下来，通过APOE4基因型对每个与雌二醇相关的hipfconn和AD生物标志物进行分层，并检测它们之间的关联程度。模型控制了年龄、受教育年限和体重指数，并在p <； 0.05进行聚类校正。结果在编码过程中，APOE4 +状态改变了雌二醇与左右侧hipfconn的关联。在APOE4阳性的女性中，雌二醇水平升高与左侧海马与左侧下颞叶、左侧顶叶、右侧额叶中回、右侧梭状回、左侧额叶中回、左侧杏仁核和海马旁回、左侧舌回和右侧枕上叶之间的连通性降低有关；相反，在APOE4‐女性中，这些关联是有益的或中性的（图1）。APOE4阳性女性中，雌二醇水平升高与右侧扣带回、右侧MFG、右侧颞上回、左侧STG和左侧杏仁核之间的海马传导增加有关；相比之下，APOE4‐女性的相关性为中性或阴性，杏仁核除外（图2）。与APOE4‐个体相比，APOE4+个体中hipfconn与AD病理的相关性更强（图3）。结论在APOE4阳性的女性中，高雌二醇与较差的hipfconn模式和AD病理增加相关，这是通过血浆生物标志物测量的。在APOE4‐女性中，较高的雌二醇水平似乎有利于记忆回路。这些发现挑战了之前的假设，即雌二醇对大脑普遍有益，特别是对绝经后APOE4+女性。
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引用次数: 0
Impact of Age and Sex on Extra-Brain, Off-Target Binding in Tau PET Scans (18F-FTP) 年龄和性别对Tau PET扫描外脑脱靶结合的影响（18F‐FTP）
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_107719
Sujala Ghatamaneni, Daneil Kim, Marin E Nycklemoe, Yurim Claire Choi, Christopher Apgar, Mahathi Kandimalla, David N Jacobson, Tiffany Kung, Vamika Sharma, Seokbeen Lim, Haakon Hol, Emily S. Lundt, Sabrina M. Albertson, Christopher G Schwarz, Jeffrey L. Gunter, Ronald Petersen, Clifford R. Jack Jr., Val J Lowe, Hoon-Ki Min

Background

The tau PET imaging with 18F-flortacipir (18F-FTP) has focused interest in accurately tracking longitudinal tau changes in Alzheimer's disease [1]. Thus, minimizing variability is critical. Off-target signal has the potential to complicate interpretation of tau-PET imaging due to potential spillover or bleed-in effects, with increased effects seen in later stages of Alzheimer's due to cerebral atrophy and proximity of off-target areas to relevant cortical areas[2]. Previously, we demonstrated the effect of uptake period activity on 18F-FTP signal. With increasing recent interest in demographic factors that may affect off-target binding, we investigated the effect of age in extra-cerebral off-target signal in 18F-FTP PET imaging.

Method

Standard 18F-FTP PET protocol was performed in 330 participants. Two independent readers measured tau uptake in predetermined off-target regions, including extraocular muscle, meninges, and occipital bone among others. Linear regression models assessed the relationship between participants’ age, sex, and tau uptake values (SUV and SUVr) (SUV = (Tissue radioactivity concentration / Injected dose) / Body weight & SUVr = SUV of target region/ SUV of reference region.)

Result

Sex had a significant effect on off-target signal in most brain regions, with variable positive or negative correlation based on area. Notably, SUV in the eyeball-retina, occipital bone, upper skull meninges all showed significant positive correlation with sex, with ‘male’ status generally associated with lower SUV. The greatest effect of sex was observed in superior skull meninges, occipital bone, and internal carotid artery (p <0.001). Age showed minimally affected SUV and SUVr in off-target regions. SUVr values show a significant correlation with SUV values of upper skull meninges in sex. Cognitive status did not significantly affect off-target SUV.

Conclusion

We observed that sex significantly affected extra-brain off-target signal in 18F-FTP PET imaging, while age has minimal effect, adding to previous evidence of off-target binding within brain regions. Further evaluation is necessary to understand the age-related effects on off-target regions. As a result, the variability introduced by sex may pose challenges to studying tau accumulation.

使用18F‐flortacipir （18F‐FTP）进行tau PET成像的重点是准确跟踪阿尔茨海默病bbb的纵向tau变化。因此，最小化可变性是至关重要的。由于潜在的溢出效应或出血效应，脱靶信号有可能使tau - PET成像的解释复杂化，在阿尔茨海默氏症晚期，由于脑萎缩和脱靶区靠近相关皮层区域[2]，脱靶信号的影响会增加。先前，我们证明了摄取周期活动对18F - FTP信号的影响。随着最近对可能影响脱靶结合的人口统计学因素的兴趣日益增加，我们研究了年龄对18F - FTP PET成像中脑外脱靶信号的影响。方法采用标准18F‐FTP PET协议对330例受试者进行检测。两个独立的阅读器测量了预定的靶外区域的tau摄取，包括眼外肌、脑膜和枕骨等。线性回归模型评估了参与者的年龄、性别和tau摄取值（SUV和SUVr）之间的关系（SUV =（组织放射性浓度/注射剂量）/体重&； SUVr =目标区域SUV /参考区域SUV）。结果性别对大多数脑区脱靶信号有显著的影响，并根据脑区呈现不同的正相关或负相关。值得注意的是，眼球视网膜、枕骨、上颅骨脑膜的SUV均与性别呈显著正相关，“男性”身份通常与较低的SUV相关。性别对上颅脑膜、枕骨和颈内动脉的影响最大（p <0.001）。年龄对非靶区SUV和SUVr的影响最小。两性上颅脑膜的SUV值与SUV值有显著相关性。认知状态对偏离目标的SUV没有显著影响。我们观察到，在18F - FTP PET成像中，性别显著影响脑外脱靶信号，而年龄影响最小，这进一步证实了先前脑区域内脱靶结合的证据。进一步的评估是必要的，以了解年龄对非靶区相关的影响。因此，性别引入的变异可能对研究tau积累构成挑战。
{"title":"Impact of Age and Sex on Extra-Brain, Off-Target Binding in Tau PET Scans (18F-FTP)","authors":"Sujala Ghatamaneni,&nbsp;Daneil Kim,&nbsp;Marin E Nycklemoe,&nbsp;Yurim Claire Choi,&nbsp;Christopher Apgar,&nbsp;Mahathi Kandimalla,&nbsp;David N Jacobson,&nbsp;Tiffany Kung,&nbsp;Vamika Sharma,&nbsp;Seokbeen Lim,&nbsp;Haakon Hol,&nbsp;Emily S. Lundt,&nbsp;Sabrina M. Albertson,&nbsp;Christopher G Schwarz,&nbsp;Jeffrey L. Gunter,&nbsp;Ronald Petersen,&nbsp;Clifford R. Jack Jr.,&nbsp;Val J Lowe,&nbsp;Hoon-Ki Min","doi":"10.1002/alz70856_107719","DOIUrl":"10.1002/alz70856_107719","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>The tau PET imaging with 18F-flortacipir (18F-FTP) has focused interest in accurately tracking longitudinal tau changes in Alzheimer's disease [1]. Thus, minimizing variability is critical. Off-target signal has the potential to complicate interpretation of tau-PET imaging due to potential spillover or bleed-in effects, with increased effects seen in later stages of Alzheimer's due to cerebral atrophy and proximity of off-target areas to relevant cortical areas[2]. Previously, we demonstrated the effect of uptake period activity on 18F-FTP signal. With increasing recent interest in demographic factors that may affect off-target binding, we investigated the effect of age in extra-cerebral off-target signal in 18F-FTP PET imaging.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>Standard 18F-FTP PET protocol was performed in 330 participants. Two independent readers measured tau uptake in predetermined off-target regions, including extraocular muscle, meninges, and occipital bone among others. Linear regression models assessed the relationship between participants’ age, sex, and tau uptake values (SUV and SUVr) (SUV = (Tissue radioactivity concentration / Injected dose) / Body weight &amp; SUVr = SUV of target region/ SUV of reference region.)</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Result</h3>\u0000 \u0000 <p>Sex had a significant effect on off-target signal in most brain regions, with variable positive or negative correlation based on area. Notably, SUV in the eyeball-retina, occipital bone, upper skull meninges all showed significant positive correlation with sex, with ‘male’ status generally associated with lower SUV. The greatest effect of sex was observed in superior skull meninges, occipital bone, and internal carotid artery (<i>p</i> &lt;0.001). Age showed minimally affected SUV and SUVr in off-target regions. SUVr values show a significant correlation with SUV values of upper skull meninges in sex. Cognitive status did not significantly affect off-target SUV.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>We observed that sex significantly affected extra-brain off-target signal in 18F-FTP PET imaging, while age has minimal effect, adding to previous evidence of off-target binding within brain regions. Further evaluation is necessary to understand the age-related effects on off-target regions. As a result, the variability introduced by sex may pose challenges to studying tau accumulation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 S2","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz70856_107719","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Lower CD8+ T-cell Senescence Partially Mediates the Neuroprotection of Higher Aerobic Fitness 低CD8+ T细胞衰老部分介导高有氧适应性的神经保护
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_107391
Bernadette A. Fausto, Elizabeth Akbulut, Mustafa Sheikh, Stephanie Ghaly, Alicia Codrington, Andrew Gamil, Imran Arshad, Darian A. Napoleon, Robert Perna, Wiktoria Piaszczynska, Mark A. Gluck, Patricia Fitzgerald-Bocarsly
<div> <section> <h3> Background</h3> <p>Immunosenescence––age-related changes in immunity––may exacerbate the pathologic processes of Alzheimer's disease. Compartments of the <i>adaptive</i> immune system (e.g., cytotoxic CD8+ T-cells) show the most significant decline in later life. Fortunately, a higher level of aerobic fitness is linked to both lower age-related accumulation of senescent T-cells and reduced Alzheimer's risk. However, it remains unclear whether this association between higher aerobic fitness and decreased Alzheimer's risk is mediated by lower proportions of T-cell senescence. In a cohort of older African Americans, this study aimed to: 1) examine the relationship between aerobic fitness and generalization (a sensitive cognitive marker of Alzheimer's risk) and 2) investigate whether CD8+ T-cell senescence mediates this relationship.</p> </section> <section> <h3> Method</h3> <p>231 older African American participants from the <i>Pathways to Healthy Aging in African Americans</i> cohort study (<i>M</i><sub>age</sub>=70.74 years, <i>SD</i> = 6.40; <i>M</i><sub>education</sub>=14.02 years, <i>SD</i> = 2.25) responded to demographic, health, and lifestyle questionnaires; completed a cognitive battery including a generalization task (Concurrent Discrimination and Transfer Task); underwent an anthropometric and physical performance battery; and provided a blood sample for T-cell senescence characterization. Using the blood specimens, peripheral blood mononuclear cells were isolated and analyzed for senescence-associated ß-Galactosidase activity as a measure of proportions of cytotoxic CD8+ T-cell senescence. Aerobic fitness (VO<sub>2</sub>peak) was estimated from the Six-Minute Walk Test. Covariates included age, sex, education, and waist-to-hip ratio.</p> </section> <section> <h3> Result</h3> <p>Higher aerobic fitness was significantly associated with fewer generalization errors. The direction of the paths indicated that higher aerobic fitness was associated with lower CD8+ T-cell senescence ( = -0.29, <i>p</i> = .03), which was subsequently associated with a decrease in generalization errors ( = 0.15, <i>p</i> = .01). Overall, reduced T-cell senescence may explain 15% of the neuroprotective benefits of exercise.</p> </section> <section> <h3> Conclusion</h3> <p>One pathway by which higher aerobic fitness is associated with lower Alzheimer's risk in older African Americans is through lower proportions of CD8+ T-cell senescence. The remaining 85% of the effect could include other immune, inflammatory, or other cellular phenotypes associat
免疫衰老——与年龄相关的免疫变化——可能加剧阿尔茨海默病的病理过程。适应性免疫系统的区室（如细胞毒性CD8+ T细胞）在晚年表现出最显著的衰退。幸运的是，较高的有氧健康水平与较低的衰老T细胞积累和降低阿尔茨海默病的风险有关。然而，目前尚不清楚高有氧适应性和降低阿尔茨海默病风险之间的联系是否由较低比例的T细胞衰老介导。在一个年长的非裔美国人队列中，本研究旨在：1)检查有氧健身和泛化（阿尔茨海默病风险的敏感认知标志物）之间的关系，2)调查CD8+ T细胞衰老是否介导了这种关系。方法来自非裔美国人健康老龄化途径队列研究的231名老年非裔美国人（M年龄=70.74岁，SD = 6.40； M教育=14.02岁，SD = 2.25）填写了人口统计学、健康和生活方式问卷；完成一个认知电池，包括一个概括任务（并发歧视和迁移任务）；接受人体测量和体能测试；并为T细胞衰老鉴定提供了血液样本。使用血液标本，分离外周血单个核细胞并分析衰老相关的β -半乳糖苷酶活性，作为细胞毒性CD8+ T细胞衰老比例的衡量标准。有氧适能（vo2峰值）由6分钟步行测试估计。协变量包括年龄、性别、教育程度和腰臀比。结果有氧适应度越高，泛化误差越小。这些路径的方向表明，较高的有氧适应性与较低的CD8+ T细胞衰老相关（= 0.29,p = 0.03），这随后与泛化误差的降低相关（= 0.15,p = 0.01）。总的来说，减少T细胞衰老可以解释15%的运动对神经保护的好处。结论：在老年非裔美国人中，较高的有氧适能与较低的阿尔茨海默病风险相关的一个途径是CD8+ T细胞衰老比例较低。其余85%的影响可能包括与年龄和身体功能相关的其他免疫、炎症或其他细胞表型。这些结果强调了积极运动的生活方式对免疫和认知功能的好处。
{"title":"Lower CD8+ T-cell Senescence Partially Mediates the Neuroprotection of Higher Aerobic Fitness","authors":"Bernadette A. Fausto,&nbsp;Elizabeth Akbulut,&nbsp;Mustafa Sheikh,&nbsp;Stephanie Ghaly,&nbsp;Alicia Codrington,&nbsp;Andrew Gamil,&nbsp;Imran Arshad,&nbsp;Darian A. Napoleon,&nbsp;Robert Perna,&nbsp;Wiktoria Piaszczynska,&nbsp;Mark A. Gluck,&nbsp;Patricia Fitzgerald-Bocarsly","doi":"10.1002/alz70856_107391","DOIUrl":"10.1002/alz70856_107391","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Immunosenescence––age-related changes in immunity––may exacerbate the pathologic processes of Alzheimer's disease. Compartments of the &lt;i&gt;adaptive&lt;/i&gt; immune system (e.g., cytotoxic CD8+ T-cells) show the most significant decline in later life. Fortunately, a higher level of aerobic fitness is linked to both lower age-related accumulation of senescent T-cells and reduced Alzheimer's risk. However, it remains unclear whether this association between higher aerobic fitness and decreased Alzheimer's risk is mediated by lower proportions of T-cell senescence. In a cohort of older African Americans, this study aimed to: 1) examine the relationship between aerobic fitness and generalization (a sensitive cognitive marker of Alzheimer's risk) and 2) investigate whether CD8+ T-cell senescence mediates this relationship.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Method&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;231 older African American participants from the &lt;i&gt;Pathways to Healthy Aging in African Americans&lt;/i&gt; cohort study (&lt;i&gt;M&lt;/i&gt;&lt;sub&gt;age&lt;/sub&gt;=70.74 years, &lt;i&gt;SD&lt;/i&gt; = 6.40; &lt;i&gt;M&lt;/i&gt;&lt;sub&gt;education&lt;/sub&gt;=14.02 years, &lt;i&gt;SD&lt;/i&gt; = 2.25) responded to demographic, health, and lifestyle questionnaires; completed a cognitive battery including a generalization task (Concurrent Discrimination and Transfer Task); underwent an anthropometric and physical performance battery; and provided a blood sample for T-cell senescence characterization. Using the blood specimens, peripheral blood mononuclear cells were isolated and analyzed for senescence-associated ß-Galactosidase activity as a measure of proportions of cytotoxic CD8+ T-cell senescence. Aerobic fitness (VO&lt;sub&gt;2&lt;/sub&gt;peak) was estimated from the Six-Minute Walk Test. Covariates included age, sex, education, and waist-to-hip ratio.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Result&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Higher aerobic fitness was significantly associated with fewer generalization errors. The direction of the paths indicated that higher aerobic fitness was associated with lower CD8+ T-cell senescence ( = -0.29, &lt;i&gt;p&lt;/i&gt; = .03), which was subsequently associated with a decrease in generalization errors ( = 0.15, &lt;i&gt;p&lt;/i&gt; = .01). Overall, reduced T-cell senescence may explain 15% of the neuroprotective benefits of exercise.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusion&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;One pathway by which higher aerobic fitness is associated with lower Alzheimer's risk in older African Americans is through lower proportions of CD8+ T-cell senescence. The remaining 85% of the effect could include other immune, inflammatory, or other cellular phenotypes associat","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 S2","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz70856_107391","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Alzheimer's disease plasma biomarkers are differentially affected by Type II Diabetes Mellitus based on those with Alzheimer's disease 2型糖尿病对阿尔茨海默病血浆生物标志物的影响是不同的
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106863
John Grizzanti, Xuemei Zeng, Rebecca A Deek, Michel N Nafash, Jeremy M. Gu, Lamia Choity, Tara K Lafferty, Marissa F Farinas, Margaret A Bedison, Rocco B Mercurio, Cristy Matan, Alexandra Gogola, Julia K. Kofler, Dana L Tudorascu, C. Elizabeth Shaaban, Jennifer H Lingler, Tharick A Pascoal, William E Klunk, Victor L. Villemagne, Milos D. Ikonomovic, Sarah B Berman, Robert Sweet, Beth E. Snitz, Ann D Cohen, M. Ilyas Kamboh, Oscar L Lopez, Thomas K Karikari

Background

Type II Diabetes Mellitus (T2DM) remains one of the strongest comorbidities associated with the development of AD. Use of fluid-based biomarker assays allows for quick, inexpensive, and accurate identification of those at high risk for developing AD or likely already have the disease. While AD and related dementias (ADRD) fluid biomarkers are well characterized during aging and cognitive impairment, little is known about the effects of T2DM on ADRD fluid biomarkers, especially those related to tau.

Method

Participants with relevant demographic, diagnostic, and ADRD plasma biomarker data from the University of Pittsburgh's Alzheimer's disease Research Center were utilized for this study (N = 1,140). Participants were stratified by cognitive diagnosis [CogDx] (Cognitively unimpaired [CU], MCI, or AD) and diabetes (non-diabetic [ND] or T2DM). ADRD plasma biomarkers were analyzed using single molecule array (Simoa): Brain-derived (BD) tau, p-tau181, p-tau217, NfL, and GFAP. After a log2-transformation, ADRD plasma biomarkers were analyzed via 2-way ANCOVA with a Bonferroni correction while controlling for age.

Result

Of the 1,140 included participants 150 (13.2%) were diagnosed with T2DM. Most participants were classified as AD (523, 45.9%) or MCI (305, 26.8%). There was no mean age difference between participants ± T2DM. There was a stepwise difference in age between CU<MCI<AD participants (p <0.001). 2-way ANCOVA analysis of plasma biomarkers: p-tau181, BDtau, NfL, and GFAP all increased stepwise from CU<MCI<AD, (p <0.001). GFAP (p <0.001) and NfL (p = 0.036) levels were also separately affected by diabetes and were lower in those with T2DM compared to NDs. Lastly, p-tau217 showed an interaction between CogDx and T2DM (p = 0.05), with a stepwise increase from CU to MCI to AD in ND, but similar levels between T2DM+CU and T2DM+MCI and a higher level in T2DM+AD than both groups.

Conclusion

All ADRD plasma biomarkers showed a clear, stepwise increase based on CogDx (CU<MCI<AD), recapitulating previous works. Novel data demonstrated an unanticipated decrease in plasma GFAP and NfL in those with T2DM. Lastly, p-tau217 was preferentially increased in participants with AD+T2DM vs. T2DM participants that were CU or with MCI. These novel findings require further scrutiny within this cohort and others.

背景2型糖尿病（T2DM）仍然是与AD发展相关的最强合并症之一。使用基于液体的生物标志物检测，可以快速、廉价、准确地识别出阿尔茨海默病的高风险人群或可能已经患有该疾病的人群。虽然AD和相关痴呆（ADRD）液体生物标志物在衰老和认知障碍期间得到了很好的表征，但对T2DM对ADRD液体生物标志物的影响知之甚少，特别是与tau相关的生物标志物。方法采用来自匹兹堡大学阿尔茨海默病研究中心的具有相关人口统计学、诊断和ADRD血浆生物标志物数据的参与者（N = 1,140）。参与者根据认知诊断[CogDx]（认知未受损[CU]、MCI或AD）和糖尿病（非糖尿病[ND]或2型糖尿病）进行分层。使用单分子阵列（Simoa）分析ADRD血浆生物标志物：脑源性（BD） tau, p - tau181, p - tau217， NfL和GFAP。log2转化后，在控制年龄的情况下，通过Bonferroni校正的2 - way ANCOVA分析ADRD血浆生物标志物。结果在1140名参与者中，150名（13.2%）被诊断为T2DM。大多数参与者被归类为AD（523人，45.9%）或MCI（305人，26.8%）。受试者±T2DM之间没有平均年龄差异。CU<MCI<；AD参与者的年龄存在逐步差异（p <0.001）。2 - way ANCOVA分析血浆生物标志物：p - tau181、BDtau、NfL和GFAP均从CU<；MCI<；AD逐渐升高（p <0.001）。GFAP （p <0.001）和NfL （p = 0.036）水平也分别受到糖尿病的影响，与非糖尿病患者相比，T2DM患者GFAP水平较低。最后，p - tau217显示了CogDx与T2DM之间的相互作用（p = 0.05）， ND中从CU到MCI再到AD的水平逐渐增加，但T2DM+CU和T2DM+MCI之间的水平相似，T2DM+AD的水平高于两组。结论基于CogDx (CU<MCI<；AD)，所有ADRD血浆生物标志物均呈明显的逐步升高，总结了前人的研究成果。新数据显示，T2DM患者血浆GFAP和NfL出乎意料地下降。最后，p - tau217在AD+T2DM患者与CU或MCI T2DM患者中优先增加。这些新发现需要在这个群体和其他群体中进行进一步的审查。
{"title":"Alzheimer's disease plasma biomarkers are differentially affected by Type II Diabetes Mellitus based on those with Alzheimer's disease","authors":"John Grizzanti,&nbsp;Xuemei Zeng,&nbsp;Rebecca A Deek,&nbsp;Michel N Nafash,&nbsp;Jeremy M. Gu,&nbsp;Lamia Choity,&nbsp;Tara K Lafferty,&nbsp;Marissa F Farinas,&nbsp;Margaret A Bedison,&nbsp;Rocco B Mercurio,&nbsp;Cristy Matan,&nbsp;Alexandra Gogola,&nbsp;Julia K. Kofler,&nbsp;Dana L Tudorascu,&nbsp;C. Elizabeth Shaaban,&nbsp;Jennifer H Lingler,&nbsp;Tharick A Pascoal,&nbsp;William E Klunk,&nbsp;Victor L. Villemagne,&nbsp;Milos D. Ikonomovic,&nbsp;Sarah B Berman,&nbsp;Robert Sweet,&nbsp;Beth E. Snitz,&nbsp;Ann D Cohen,&nbsp;M. Ilyas Kamboh,&nbsp;Oscar L Lopez,&nbsp;Thomas K Karikari","doi":"10.1002/alz70856_106863","DOIUrl":"10.1002/alz70856_106863","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Type II Diabetes Mellitus (T2DM) remains one of the strongest comorbidities associated with the development of AD. Use of fluid-based biomarker assays allows for quick, inexpensive, and accurate identification of those at high risk for developing AD or likely already have the disease. While AD and related dementias (ADRD) fluid biomarkers are well characterized during aging and cognitive impairment, little is known about the effects of T2DM on ADRD fluid biomarkers, especially those related to tau.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>Participants with relevant demographic, diagnostic, and ADRD plasma biomarker data from the University of Pittsburgh's Alzheimer's disease Research Center were utilized for this study (<i>N</i> = 1,140). Participants were stratified by cognitive diagnosis [CogDx] (Cognitively unimpaired [CU], MCI, or AD) and diabetes (non-diabetic [ND] or T2DM). ADRD plasma biomarkers were analyzed using single molecule array (Simoa): Brain-derived (BD) tau, <i>p</i>-tau181, <i>p</i>-tau217, NfL, and GFAP. After a log2-transformation, ADRD plasma biomarkers were analyzed via 2-way ANCOVA with a Bonferroni correction while controlling for age.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Result</h3>\u0000 \u0000 <p>Of the 1,140 included participants 150 (13.2%) were diagnosed with T2DM. Most participants were classified as AD (523, 45.9%) or MCI (305, 26.8%). There was no mean age difference between participants ± T2DM. There was a stepwise difference in age between CU&lt;MCI&lt;AD participants (<i>p</i> &lt;0.001). 2-way ANCOVA analysis of plasma biomarkers: <i>p</i>-tau181, BDtau, NfL, and GFAP all increased stepwise from CU&lt;MCI&lt;AD, (<i>p</i> &lt;0.001). GFAP (<i>p</i> &lt;0.001) and NfL (<i>p</i> = 0.036) levels were also separately affected by diabetes and were lower in those with T2DM compared to NDs. Lastly, <i>p</i>-tau217 showed an interaction between CogDx and T2DM (<i>p</i> = 0.05), with a stepwise increase from CU to MCI to AD in ND, but similar levels between T2DM+CU and T2DM+MCI and a higher level in T2DM+AD than both groups.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>All ADRD plasma biomarkers showed a clear, stepwise increase based on CogDx (CU&lt;MCI&lt;AD), recapitulating previous works. Novel data demonstrated an unanticipated decrease in plasma GFAP and NfL in those with T2DM. Lastly, <i>p</i>-tau217 was preferentially increased in participants with AD+T2DM vs. T2DM participants that were CU or with MCI. These novel findings require further scrutiny within this cohort and others.</p>\u0000 </section>\u0000 </div>","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 S2","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz70856_106863","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Genetic variants associated with Alzheimer's disease and telomere length 与阿尔茨海默病和端粒长度相关的遗传变异
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY
Alzheimer's & Dementia
Pub Date : 2026-01-11 DOI: 10.1002/alz70856_107105
Zainab Khurshid, Tong Tong, Oluwatosin A Olayinka, Congcong Zhu, John J. Farrell, Alzheimer's Disease Sequencing Project (ADSP), Eden R. Martin, William S Bush, Margaret Pericak-Vance, Li-San Wang, Gerald D. Schellenberg, Jonathan L Haines, Kathryn L. Lunetta, Xiaoling Zhang, Lindsay A. Farrer
<div> <section> <h3> Background</h3> <p>Telomere length (TL), a marker of biological aging, has been implicated in multiple age-related diseases, but its association with Alzheimer's disease (AD) remains unclear. We analyzed whole genome sequence data from the Alzheimer's Disease Sequencing Project (release 4) to identify genetic variants associated with both AD and TL.</p> </section> <section> <h3> Method</h3> <p>We estimated TL for 35,014 participants using TelSeq, which after quality control yielded a dataset including 6,973 persons of European ancestry (EA; 3,701 AD cases, 3,273 controls), 4,188 African Americans (AA; 1,329 AD cases, 2,859 controls), 4,008 Caribbean Hispanics (CH; 1,588 AD cases, 2,420 controls), and 4,170 Native American Hispanics (NAH; 754 AD cases, 3,416 controls). The association of AD with TL was tested using a linear regression model including covariates for age, sex, and dosage of the <i>APOE</i> e2 and e4 alleles. The interaction of TL with SNPs having a minor allele count >20 was evaluated for its association with AD in each ancestry group by logistic regression models using GENESIS including SNP, TL, an interaction term for SNPxTL, and covariates for age, sex, sequencing center, genetic relationship matrix, and principal components of ancestry. Results were combined across groups using METASOFT.</p> </section> <section> <h3> Result</h3> <p>AD (<i>p</i> = 5.32x10<sup>-12</sup>), age (<i>p</i> = 2.00x10<sup>-16</sup>), sex (<i>p</i> = 2.00x10<sup>-16</sup>), and <i>APOE</i> e2 (<i>p</i> = 5.35x10<sup>-6</sup>) were significantly associated with TL. In the EA sample, interaction of TL with <i>CRTC3-AS1</i> intronic SNP rs533691286 was associated with AD at the genome-wide significance (GWS) level (<i>p</i> = 1.13x10<sup>-8</sup>). Suggestive associations were found with rs537146885 located between <i>RP5-884C9.2</i> and <i>LINC01343</i> (<i>p</i> = 8.95x10<sup>-8</sup>). In the NAH group, GWS associations were observed for interactions of TL with <i>MIR548XHG</i> intronic variants rs117856971 (<i>p</i> = 2.06x10<sup>-9</sup>) and rs18578882 (<i>p</i> = 3.70x10<sup>-8</sup>). No TLxSNP interactions were GWS in the CH and AA groups. In the total sample, GWS associations were identified for interactions of TL with intronic variants in <i>SLC23A2 (</i>rs184956772, <i>p</i> = 3.19x10<sup>-9</sup>) and <i>CFAP61</i> (rs769676169, <i>p</i> = 3.64x10<sup>-9</sup>), rs1037982496 upstream of <i>DEFB123</i> (<i>p</i> = 2.96x10<sup>-9</sup>), and several intergenic variants including <i>DEFB115-DKKL1P1</i> (rs968020553, <i>p</i> = 2.96X10<sup>-9</sup>), <i>RP5-884C9.2-LINC01343</i> (rs537146885, <i>p</i> = 4.98x10<sup>-9</sup>), <i>MIR3193-COX4I2</i> (rs921951239, <i>p</i> = 2.70x10<sup>-9</
端粒长度（TL）是生物衰老的标志，与多种年龄相关疾病有关，但其与阿尔茨海默病（AD）的关系尚不清楚。我们分析了来自阿尔茨海默病测序项目（第4版）的全基因组序列数据，以确定与AD和TL相关的遗传变异。方法我们使用TelSeq估计了35,014名参与者的TL，经过质量控制后产生的数据集包括6,973名欧洲血统（EA）， 3,701名AD病例，3,273名对照),4,188名非洲裔美国人(AA；1329例AD病例，2859例对照)，4008名加勒比西班牙裔（CH； 1588例AD病例，2420例对照），4170名美洲原住民西班牙裔（NAH； 754例AD病例，3416例对照）。采用线性回归模型，包括年龄、性别和apoee2和e4等位基因剂量等协变量，检验AD与TL的相关性。利用GENESIS的逻辑回归模型，包括SNP、TL （SNPxTL的相互作用项）以及年龄、性别、测序中心、亲缘关系矩阵和祖先主成分等协变量，评估了TL与每个祖先组中具有较小等位基因计数>；20的SNP的相互作用与AD的关联。使用METASOFT对各组结果进行综合分析。结果AD （p = 5.32x10-12）、年龄（p = 2.00x10-16）、性别（p = 2.00x10-16）、APOE e2 （p = 5.35x10-6）与AD有显著相关性，在EA样本中，TL与CRTC3-AS1内含子SNP rs533691286的相互作用在GWS水平上与AD有显著相关性（p = 1.13x10-8）。rs537146885位于RP5-884C9.2和LINC01343之间（p = 8.95x10-8）。在NAH组中，TL与MIR548XHG内含子变异rs117856971 （p = 2.06x10-9）和rs18578882 （p = 3.70x10-8）的相互作用存在GWS关联。在CH和AA组中没有TLxSNP相互作用。在总样本中，TL与SLC23A2 （rs184956772, p = 3.19x10-9）、CFAP61 （rs769676169, p = 3.64x10-9）、DEFB123上游rs1037982496 （p = 2.96x10-9）、DEFB115-DKKL1P1 （rs968020553, p = 2.96x10-9）、RP5-884C9.2-LINC01343 （rss537146885, p = 4.98x10-9）、MIR3193-COX4I2 （rs921951239, p = 2.70x10-9）、AC010091.1 （rs552422184, p = 5.86x10-9）的内含子变异相互作用存在GWS关联。CTA-109P11.1-RP11-328K15.1 （rs77699417, p = 6.51x10-9）。结论：我们发现了通过与TL相互作用显著影响AD风险的变异，表明TL维持途径可能是AD发病的核心。
{"title":"Genetic variants associated with Alzheimer's disease and telomere length","authors":"Zainab Khurshid,&nbsp;Tong Tong,&nbsp;Oluwatosin A Olayinka,&nbsp;Congcong Zhu,&nbsp;John J. Farrell,&nbsp;Alzheimer's Disease Sequencing Project (ADSP),&nbsp;Eden R. Martin,&nbsp;William S Bush,&nbsp;Margaret Pericak-Vance,&nbsp;Li-San Wang,&nbsp;Gerald D. Schellenberg,&nbsp;Jonathan L Haines,&nbsp;Kathryn L. Lunetta,&nbsp;Xiaoling Zhang,&nbsp;Lindsay A. Farrer","doi":"10.1002/alz70856_107105","DOIUrl":"https://doi.org/10.1002/alz70856_107105","url":null,"abstract":"&lt;div&gt;\u0000 \u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Background&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Telomere length (TL), a marker of biological aging, has been implicated in multiple age-related diseases, but its association with Alzheimer's disease (AD) remains unclear. We analyzed whole genome sequence data from the Alzheimer's Disease Sequencing Project (release 4) to identify genetic variants associated with both AD and TL.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Method&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We estimated TL for 35,014 participants using TelSeq, which after quality control yielded a dataset including 6,973 persons of European ancestry (EA; 3,701 AD cases, 3,273 controls), 4,188 African Americans (AA; 1,329 AD cases, 2,859 controls), 4,008 Caribbean Hispanics (CH; 1,588 AD cases, 2,420 controls), and 4,170 Native American Hispanics (NAH; 754 AD cases, 3,416 controls). The association of AD with TL was tested using a linear regression model including covariates for age, sex, and dosage of the &lt;i&gt;APOE&lt;/i&gt; e2 and e4 alleles. The interaction of TL with SNPs having a minor allele count &gt;20 was evaluated for its association with AD in each ancestry group by logistic regression models using GENESIS including SNP, TL, an interaction term for SNPxTL, and covariates for age, sex, sequencing center, genetic relationship matrix, and principal components of ancestry. Results were combined across groups using METASOFT.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Result&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;AD (&lt;i&gt;p&lt;/i&gt; = 5.32x10&lt;sup&gt;-12&lt;/sup&gt;), age (&lt;i&gt;p&lt;/i&gt; = 2.00x10&lt;sup&gt;-16&lt;/sup&gt;), sex (&lt;i&gt;p&lt;/i&gt; = 2.00x10&lt;sup&gt;-16&lt;/sup&gt;), and &lt;i&gt;APOE&lt;/i&gt; e2 (&lt;i&gt;p&lt;/i&gt; = 5.35x10&lt;sup&gt;-6&lt;/sup&gt;) were significantly associated with TL. In the EA sample, interaction of TL with &lt;i&gt;CRTC3-AS1&lt;/i&gt; intronic SNP rs533691286 was associated with AD at the genome-wide significance (GWS) level (&lt;i&gt;p&lt;/i&gt; = 1.13x10&lt;sup&gt;-8&lt;/sup&gt;). Suggestive associations were found with rs537146885 located between &lt;i&gt;RP5-884C9.2&lt;/i&gt; and &lt;i&gt;LINC01343&lt;/i&gt; (&lt;i&gt;p&lt;/i&gt; = 8.95x10&lt;sup&gt;-8&lt;/sup&gt;). In the NAH group, GWS associations were observed for interactions of TL with &lt;i&gt;MIR548XHG&lt;/i&gt; intronic variants rs117856971 (&lt;i&gt;p&lt;/i&gt; = 2.06x10&lt;sup&gt;-9&lt;/sup&gt;) and rs18578882 (&lt;i&gt;p&lt;/i&gt; = 3.70x10&lt;sup&gt;-8&lt;/sup&gt;). No TLxSNP interactions were GWS in the CH and AA groups. In the total sample, GWS associations were identified for interactions of TL with intronic variants in &lt;i&gt;SLC23A2 (&lt;/i&gt;rs184956772, &lt;i&gt;p&lt;/i&gt; = 3.19x10&lt;sup&gt;-9&lt;/sup&gt;) and &lt;i&gt;CFAP61&lt;/i&gt; (rs769676169, &lt;i&gt;p&lt;/i&gt; = 3.64x10&lt;sup&gt;-9&lt;/sup&gt;), rs1037982496 upstream of &lt;i&gt;DEFB123&lt;/i&gt; (&lt;i&gt;p&lt;/i&gt; = 2.96x10&lt;sup&gt;-9&lt;/sup&gt;), and several intergenic variants including &lt;i&gt;DEFB115-DKKL1P1&lt;/i&gt; (rs968020553, &lt;i&gt;p&lt;/i&gt; = 2.96X10&lt;sup&gt;-9&lt;/sup&gt;), &lt;i&gt;RP5-884C9.2-LINC01343&lt;/i&gt; (rs537146885, &lt;i&gt;p&lt;/i&gt; = 4.98x10&lt;sup&gt;-9&lt;/sup&gt;), &lt;i&gt;MIR3193-COX4I2&lt;/i&gt; (rs921951239, &lt;i&gt;p&lt;/i&gt; = 2.70x10&lt;sup&gt;-9&lt;/","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 S2","pages":""},"PeriodicalIF":11.1,"publicationDate":"2026-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz70856_107105","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145963889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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