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Characterizing early symptomatic AD patients by visual and quantitative tau profiles 通过视觉和定量的tau谱来表征早期症状性AD患者
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106941
Amanda Morris, Min Jung Kim, Michael Pontecorvo, Sergey Shcherbinin, Leonardo Iaccarino, Samantha C. Burnham, John R. Sims, Dawn A. Brooks, Emily C. Collins, Mark A. Mintun, Ming Lu

Background

In the TRAILBLAZER-ALZ 2 study (NCT04437511), tau pathology at screening was evaluated with flortaucipir Positron Emission Tomography (PET) with a combination of visual read (V) and quantitative (Q) standardized uptake value ratio (SUVr) approaches. In most cases, participants had an advanced Alzheimer's disease (AD) tau visual pattern (AD++) with an AD-signature weighted neocortical SUVr>1.1 (V++/Q+). A minority of participants presented other V/Q profiles, namely an AD++ visual read with an SUVr1.1 (V++/Q-) and a moderate AD tau pattern (AD+) with an SUVr>1.1 (V+/Q+). The objective of these analyses was to characterise these populations.

Method

All available TRAILBLAZER-ALZ 2 placebo-treated early symptomatic AD participants were included. Baseline characteristics and progression on both clinical scales (Clinical Dementia Rating - Sum of Boxes [CDR-SB], integrated Alzheimer Disease Rating Scale [iADRS]) and biomarkers (p-tau217, glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL]) at Week 76 (using mixed model repeated measures methodology), of the V++/Q- and V+/Q+ groups were compared to each other and to the rest of the study population (V++/Q+).

Result

The V++/Q- group comprised 15.7% (126/802) and the V+/Q+ group 2.9% (23/802) of the placebo-treated study population with characteristics as shown in the Table. At Week 76, all groups were at risk of clinical progression, although changes from baseline in CDR-SB and iADRS for the V++/Q- and V+/Q+ groups were less compared to the rest of the population (significantly different between the V++/Q- and V++/Q+ groups; p <0.0001 for both CDR-SB and iADRS) (Figure). Progression for both AD-specific and non-AD specific biomarker progression was similar across all groups.

Conclusion

The observation of V++/Q- and V+/Q+ participants being older, milder in AD pathology while at a similar clinical stage at screening compared to V++/Q+ participants may suggest the effect of age-related comorbidities. Participants in the V++/Q- and the V+/Q+ groups showed clinical/pathological progression, although not at the level of those in the V++/Q+ group.

在TRAILBLAZER‐ALZ 2研究(NCT04437511)中,采用flortaucipir正电子发射断层扫描(PET)结合视觉读取(V)和定量(Q)标准化摄取值比(SUVr)方法评估筛查时的tau病理学。在大多数情况下,参与者患有晚期阿尔茨海默病(AD) tau视觉模式(AD++), AD‐特征加权新皮质suvr1.1 (v++ /Q+)。少数参与者呈现其他V/Q特征,即SUVr≤1.1 (v++ /Q‐)的AD++视觉阅读和SUVr>;1.1 (V+/Q‐)的中度AD tau模式(AD+)。这些分析的目的是描述这些人群的特征。方法纳入所有接受TRAILBLAZER - ALZ 2安慰剂治疗的早期症状性AD患者。在第76周(使用混合模型重复测量方法),将V++/Q+组和V+/Q+组的临床量表(临床痴呆评分-盒子总和[CDR‐SB],综合阿尔茨海默病评分量表[iADRS])和生物标志物(p‐tau217,胶质纤维酸性蛋白[GFAP],神经丝轻链[NfL])的基线特征和进展与其他研究人群(V++/Q+)进行比较。V++/Q +组占安慰剂治疗研究人群的15.7% (126/802),V+/Q+组占2.9%(23/802),其特征如表所示。在第76周,所有组都有临床进展的风险,尽管与其他人群相比,v++ /Q‐和V+/Q+组的CDR‐SB和iADRS的基线变化较小(v++ /Q‐和v++ /Q+组之间存在显著差异;CDR‐SB和iADRS的p <;0.0001)(图)。AD特异性和非AD特异性生物标志物的进展在所有组中相似。结论:与v++ /Q+受试者相比,v++ /Q+受试者年龄较大,AD病理较轻,且在筛查时处于相似临床阶段,这可能提示年龄相关合并症的影响。V++/Q+组和V+/Q+组的参与者表现出临床/病理进展,尽管没有达到V++/Q+组的水平。
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引用次数: 0
Cross-National Study to Operationalize Amyloid, Tau, Neurodegeneration, and Vascular Contributions to Dementia 淀粉样蛋白、Tau蛋白、神经变性和血管对痴呆的作用的跨国研究
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106635
Jeremy A. Tanner, Diefei Chen, Min Soo Byun, Evgeny J. Chumin, Ileana De Anda-Duran, Kacie D Deters, Martine Elbejjani, Evan Fletcher, A. Zarina Kraal, Dong Young Lee, Silvia Mejia-Arango, Stefanie Pina-Escudero, Kwangsik Nho, Talia L. Robinson, C. Elizabeth Shaaban, Adam M. Staffaroni, Andrew J. Saykin, Paul K Crane, Dahyun Yi, Shannon L Risacher, the Alzheimer's Disease Neuroimaging Initiative; the KBASE Research Group
<div> <section> <h3> Background</h3> <p>Recent diagnosis and staging criteria have been proposed for AD based on amyloid(“A”), tau(“T”), and neurodegeneration(“N”), with consideration of comorbid vascular(“V”) pathology. However, challenges remain in their application and interpretation for research and clinical use. Additionally, current criteria have been largely informed by data derived from samples of highly educated, non-Hispanic White cohorts in the US. We compared methods to operationalize multimodal ATNV measures across two cohorts to meaningfully inform future research and clinical practice.</p> </section> <section> <h3> Method</h3> <p>Participants with amyloid PET, tau PET, and brain MRI were included from two prospective cohort studies with similar study designs: ADNI3 in the US and KBASE in Korea. ATNV measures were operationalized as continuous (A=centiloid; T=meta-temporal ROI; <i>N</i> = AD signature region cortical thickness; V=white matter hyperintensity volume) and as binary (+/-) variables by replicating approaches applied in other cohorts. Clinical diagnoses of cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia were determined by experts at multidisciplinary consensus conferences. Parallel cross-sectional analyses were performed within each cohort. Multivariate logistic regressions with ATNV modeled as continuous or binary predictors (16 possible combinations) adjusting for age, sex, and education were performed to compare model fit and predictive power for distinguishing participants with dementia versus CU.</p> </section> <section> <h3> Result</h3> <p>A total of 508 participants in ADNI (mean age=71±7, female=55%, education(yrs)=16.5±2.3) and 165 in KBASE (<i>n</i> = 165; age=73±8, female=64%, education(yrs)=11.0±4.6) were included (Table 1). In ADNI, the continuous ATNV and continuous ATN+binary V explained the most variance in dementia diagnosis (highest pseudo-R<sup>2</sup>, lowest AIC/BIC; Table 2). In KBASE, models had higher overall predictive power for distinguishing dementia. The best-performing models included continuous A and T, binary N, and continuous V, or binary A, continuous T, binary N, and continuous V (Table 3).</p> </section> <section> <h3> Conclusion</h3> <p>Models including ATNV were highly predictive of dementia in both cohorts. Models with predominantly continuous variables explained more variability in dementia diagnosis, and are optimal for research use due to their simplicity. In Korea, binary N and binary A increased predictive power. Ongoing analyses will assess the relative
近年来,人们提出了基于淀粉样蛋白(“A”)、tau蛋白(“T”)和神经变性(“N”)的AD诊断和分期标准,并考虑了合并症血管(“V”)病理。然而,它们在研究和临床应用中的应用和解释仍然存在挑战。此外,目前的标准在很大程度上是由美国受过高等教育的非西班牙裔白人群体的样本数据提供的。我们比较了在两个队列中实施多模式ATNV措施的方法,以便为未来的研究和临床实践提供有意义的信息。方法:两项具有相似研究设计的前瞻性队列研究(美国的ADNI3和韩国的KBASE)纳入了淀粉样蛋白PET、tau PET和脑MRI的参与者。ATNV测量被操作为连续(A=centiloid; T=meta-temporal ROI; N = AD特征区皮质厚度;V=白质高强度体积)和二元(+/-)变量,通过复制应用于其他队列的方法。认知无损伤(CU)、轻度认知损伤(MCI)和痴呆的临床诊断由多学科共识会议上的专家确定。在每个队列中进行平行横断面分析。将ATNV建模为连续或二元预测因子(16种可能的组合),进行多变量logistic回归,调整年龄、性别和教育程度,比较模型拟合和预测能力,以区分痴呆和CU的参与者。结果共纳入ADNI患者508例(平均年龄71±7岁,女性=55%,学历(年龄)=16.5±2.3),KBASE患者165例(n = 165,年龄=73±8岁,女性=64%,学历(年龄)=11.0±4.6)(表1)。在ADNI中,连续ATNV和连续ATN+二元V解释了痴呆诊断的最大方差(伪r2最高,AIC/BIC最低;表2)。在KBASE中,模型在区分痴呆方面具有更高的总体预测能力。表现最好的模型包括连续A和T,二元N和连续V,或者二元A,连续T,二元N和连续V(表3)。结论包括ATNV在内的模型在两组患者中均可高度预测痴呆。以连续变量为主的模型解释了痴呆症诊断中更多的可变性,并且由于其简单性而最适合研究使用。在韩国,二进制N和二进制A提高了预测能力。正在进行的分析将评估ATNV对每个队列的认知表现和诊断的相对贡献,以便更好地为跨国队列的适当研究和临床应用提供信息。
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引用次数: 0
Head-to-Head evaluation of plasma p-tau217 associations with MK6240, Flortaucipir, PI2620, and RO948 tau PET tracers 血浆p - tau217与MK6240、Flortaucipir、PI2620和RO948 tau PET示踪剂相关性的头对头评估
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106115
Pamela C.L. Ferreira, Tevy Chan, Bruna Bellaver, Guilherme Povala, Guilherme Bauer-Negrini, Emma Ruppert, Carolina Soares, Cynthia Felix, Andreia Rocha, Marina Scop Madeiros, Livia Amaral, Juli Cehula, Firoza Z Lussier, Joseph C. Masdeu, Dana L Tudorascu, Thomas K Karikari, David N. Soleimani-Meigooni, Juan Fortea, Val J Lowe, Hwamee Oh, Belen Pascual, Brian A. Gordon, Pedro Rosa-Neto, Suzanne L. Baker, Tharick A Pascoal
<div> <section> <h3> Background</h3> <p>Tau phosphorylation and aggregation are hallmark features of Alzheimer's disease pathology(AD). Previous studies have shown that plasma phosphorylated tau(<i>p</i>-tau) at threonine 217 can detect AD-related tau tangle pathology. However, the head-to-head association between <i>p</i>-tau217 and different tau PET tracers remains unexplored. Here, we conducted a head-to-head comparison of the association between plasma <i>p</i>-tau217 and four distinct tau PET tracers[MK6240, Flortaucipir(FTP), PI2620, RO948].</p> </section> <section> <h3> Method</h3> <p>We studied 338 individuals across the AD continuum from the HEAD study[190 cognitively unimpaired elderly(CU), 109 with mild cognitive impairment(MCI), and 39 with dementia] with available FTP, MK6240, and plasma <i>p</i>-tau217 measured by ALZpath assay. A subset of 64 individuals(28 CU, 25 MCI, and 11 dementia) also had PI2620 and RO948, and <i>p</i>-tau217 measured by Lumipulse. The strength of the association was determined using t-value maps from regression models testing the association between each tau PET tracer and plasma <i>p</i>-tau217, and the extent was measured by the percentage of significant voxels(t-value>3.2). R-square metric was used to determine how much of the variance in tau PET tracer estimates was explained by plasma <i>p</i>-tau217 concentrations. Associations between <i>p</i>-tau217 with tau PET were evaluated using the Spearman test.</p> </section> <section> <h3> Result</h3> <p>We found that in CU, both the extent and magnitude of the association with plasma <i>p</i>-tau217 were higher for MK6240 compared to FTP (Figure 1A-D). Plasma <i>p</i>-tau217 explained a greater proportion of the variance in MK6240 than in FTP (Figure 1E-F). In CI, the extent and magnitude of the association were similar for MK6240 and FTP. Additionally, plasma <i>p</i>-tau217 explained a similar proportion of the variance in MK6240 and FTP. Using the subset of individuals who had all tau tracers, MK6240 showed a slightly higher extent of association with <i>p</i>-tau217, followed by FTP, PI2620, and RO948 (Figure 2A-B). The magnitude of association was stronger for MK6240, followed by PI2620, RO948, and FTP (Figure 2C-D). Plasma <i>p</i>-tau217 explained a greater proportion of the variance in MK6240, followed by FTP, RO948, and PI2620 (Figure 2E-F). We compared the associations between different <i>p</i>-tau217 assays, and both assays presented similar associations with all tau PET tracers (Figure 3).</p> </section> <section> <h3> Conclusion</h3> <p>In sum
Tau蛋白磷酸化和聚集是阿尔茨海默病病理(AD)的标志性特征。先前的研究表明,血浆中苏氨酸217位点磷酸化的tau蛋白(p‐tau)可以检测AD相关的tau缠结病理。然而,p - tau217和不同的tau PET示踪剂之间的头对头关联仍未被探索。在这里,我们对血浆p - tau217和四种不同的tau PET示踪剂[MK6240, Flortaucipir(FTP), PI2620, RO948]之间的关系进行了头对头的比较。方法:我们研究了来自HEAD研究的338名AD连续个体[190名认知未受损老年人(CU), 109名轻度认知障碍患者(MCI)和39名痴呆患者],使用可用的FTP, MK6240和血浆p‐tau217通过ALZpath测定。64名个体(28名CU, 25名MCI, 11名痴呆)也有PI2620和RO948,以及Lumipulse测量的p - tau217。使用回归模型的t值图来确定关联的强度,该模型测试了每种tau PET示踪剂与血浆p - tau217之间的关联,并通过显著体素的百分比来测量其程度(t - value>3.2)。使用R平方度量来确定血浆p - tau217浓度对tau PET示踪剂估计值方差的解释。使用Spearman试验评估p - tau217与tau PET之间的关联。结果我们发现,与FTP相比,在CU中,MK6240与血浆p - tau217的关联程度和强度都更高(图1A‐D)。血浆p - tau217对MK6240变异的解释比FTP更大(图1E - F)。在CI中,MK6240和FTP的关联程度和强度相似。此外,血浆p - tau217解释了MK6240和FTP中相似比例的变异。使用具有所有tau示踪剂的个体子集,MK6240显示与p‐tau217的关联程度略高,其次是FTP, PI2620和RO948(图2A‐B)。MK6240的关联程度更强,其次是PI2620、RO948和FTP(图2C‐D)。血浆p‐tau217解释了MK6240中较大比例的变异,其次是FTP、RO948和PI2620(图2E‐F)。我们比较了不同的p - tau217检测方法之间的相关性,两种检测方法都显示出与所有tau PET示踪剂相似的相关性(图3)。总之,我们的研究结果表明,在相似的地形区域,四种tau PET示踪剂与血浆p - tau217具有很强的相关性。
{"title":"Head-to-Head evaluation of plasma p-tau217 associations with MK6240, Flortaucipir, PI2620, and RO948 tau PET tracers","authors":"Pamela C.L. Ferreira,&nbsp;Tevy Chan,&nbsp;Bruna Bellaver,&nbsp;Guilherme Povala,&nbsp;Guilherme Bauer-Negrini,&nbsp;Emma Ruppert,&nbsp;Carolina Soares,&nbsp;Cynthia Felix,&nbsp;Andreia Rocha,&nbsp;Marina Scop Madeiros,&nbsp;Livia Amaral,&nbsp;Juli Cehula,&nbsp;Firoza Z Lussier,&nbsp;Joseph C. Masdeu,&nbsp;Dana L Tudorascu,&nbsp;Thomas K Karikari,&nbsp;David N. Soleimani-Meigooni,&nbsp;Juan Fortea,&nbsp;Val J Lowe,&nbsp;Hwamee Oh,&nbsp;Belen Pascual,&nbsp;Brian A. Gordon,&nbsp;Pedro Rosa-Neto,&nbsp;Suzanne L. Baker,&nbsp;Tharick A Pascoal","doi":"10.1002/alz70856_106115","DOIUrl":"10.1002/alz70856_106115","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;Tau phosphorylation and aggregation are hallmark features of Alzheimer's disease pathology(AD). Previous studies have shown that plasma phosphorylated tau(&lt;i&gt;p&lt;/i&gt;-tau) at threonine 217 can detect AD-related tau tangle pathology. However, the head-to-head association between &lt;i&gt;p&lt;/i&gt;-tau217 and different tau PET tracers remains unexplored. Here, we conducted a head-to-head comparison of the association between plasma &lt;i&gt;p&lt;/i&gt;-tau217 and four distinct tau PET tracers[MK6240, Flortaucipir(FTP), PI2620, RO948].&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 studied 338 individuals across the AD continuum from the HEAD study[190 cognitively unimpaired elderly(CU), 109 with mild cognitive impairment(MCI), and 39 with dementia] with available FTP, MK6240, and plasma &lt;i&gt;p&lt;/i&gt;-tau217 measured by ALZpath assay. A subset of 64 individuals(28 CU, 25 MCI, and 11 dementia) also had PI2620 and RO948, and &lt;i&gt;p&lt;/i&gt;-tau217 measured by Lumipulse. The strength of the association was determined using t-value maps from regression models testing the association between each tau PET tracer and plasma &lt;i&gt;p&lt;/i&gt;-tau217, and the extent was measured by the percentage of significant voxels(t-value&gt;3.2). R-square metric was used to determine how much of the variance in tau PET tracer estimates was explained by plasma &lt;i&gt;p&lt;/i&gt;-tau217 concentrations. Associations between &lt;i&gt;p&lt;/i&gt;-tau217 with tau PET were evaluated using the Spearman test.&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 that in CU, both the extent and magnitude of the association with plasma &lt;i&gt;p&lt;/i&gt;-tau217 were higher for MK6240 compared to FTP (Figure 1A-D). Plasma &lt;i&gt;p&lt;/i&gt;-tau217 explained a greater proportion of the variance in MK6240 than in FTP (Figure 1E-F). In CI, the extent and magnitude of the association were similar for MK6240 and FTP. Additionally, plasma &lt;i&gt;p&lt;/i&gt;-tau217 explained a similar proportion of the variance in MK6240 and FTP. Using the subset of individuals who had all tau tracers, MK6240 showed a slightly higher extent of association with &lt;i&gt;p&lt;/i&gt;-tau217, followed by FTP, PI2620, and RO948 (Figure 2A-B). The magnitude of association was stronger for MK6240, followed by PI2620, RO948, and FTP (Figure 2C-D). Plasma &lt;i&gt;p&lt;/i&gt;-tau217 explained a greater proportion of the variance in MK6240, followed by FTP, RO948, and PI2620 (Figure 2E-F). We compared the associations between different &lt;i&gt;p&lt;/i&gt;-tau217 assays, and both assays presented similar associations with all tau PET tracers (Figure 3).&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;In sum","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_106115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955337","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
Analysis of the relationship between volumetry and visual classification of hippocampal atrophy on magnetic ressonance image 磁共振成像海马萎缩的体积测量与视觉分类关系分析
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106082
Fabricio Nery Garrafiel, Ricardo Benardi Soder, Ricardo Pessini Paganin, Maria Rosa Alves da Silva, Andrei Bieger Sr., Vitor Verlindo Vidaletti, Cristiano Aguzzoli, Lucas Porcello Schilling

Background

Magnetic resonance imaging (MRI) is a tool used in the evaluation of patients with cognitive deficits, capable of identifying characteristic changes of neurodegenerative processes, such as hippocampal atrophy. The most common assessment methods include scoring systems using the Fazekas and MTA scales. The present study aims to evaluate the relationship between the classification data from the MTA scale, obtained through the analysis of MRI images by two experienced neuroradiologists, and the data obtained from hippocampal volumetry of the same image sample.

Method

677 MRI images were collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and the hippocampal volume quantification values were extracted using Freesurfer. The degree of atrophy, according to the MTA scale, on both sides of the hippocampus were classified by two independent specialized radiologists.

Result

The correlation between MTA classifications was 0.85, and a negative correlation (-0.64) was found between volumetry and atrophy grade (fgure 1). Despite these results correlating the MTA grade with automatic volumetry, approximately 10% of the individuals were classified as outliers, being determined to be outside 2 standard deviations from the mean volume of each atrophy grade (Figure 2).

Conclusion

The results showed a strong correlation between the MTA scale and volumetry, as well as a consistent correlation between the radiologists' MTA classification. Albeit we identified 10% of individuals classified as outliers, highlighting the existence of specific cases that should be better investigated in order to understand the efficiency of the qualitative method and the accuracy of its classifications.

磁共振成像(MRI)是一种用于评估认知缺陷患者的工具,能够识别神经退行性过程的特征性变化,如海马萎缩。最常见的评估方法包括使用Fazekas和MTA量表的评分系统。本研究旨在评价两名经验丰富的神经放射学家通过分析MRI图像获得的MTA分级数据与同一图像样本的海马体积测量数据之间的关系。方法从阿尔茨海默病神经影像学倡议(ADNI)数据库中收集677张MRI图像,使用Freesurfer提取海马体积量化值。根据MTA量表,由两名独立的专业放射科医生对两侧海马的萎缩程度进行分类。MTA分类之间的相关性为0.85,体积学和萎缩等级之间的相关性为负0.64(图1)。尽管这些结果将MTA分级与自动容量测定相关联,但大约10%的个体被归类为异常值,被确定为在每个萎缩分级的平均体积2个标准差之外(图2)。结论MTA分级与体积有较强的相关性,放射科医师的MTA分级也有较强的相关性。虽然我们确定了10%的个体被归类为异常值,但强调了应该更好地调查特定案例的存在,以了解定性方法的效率及其分类的准确性。
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引用次数: 0
Microstructural White Matter Alterations in Alzheimer's Disease: A Diffusion Tensor Imaging Study 阿尔茨海默病微结构白质改变:弥散张量成像研究
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_105992
Rufeyda Yagci, Tatjana Schmidt, Marcella Montagnese, Timothy Rittman

Background

White matter (WM) degeneration has been proposed as an early indicator of Alzheimer's disease (AD). Alterations in WM integrity, such as reductions in fractional anisotropy (FA) and increases in mean diffusivity (MD), may reflect the underlying pathological processes associated with AD. This study aims to investigate microstructural changes in AD utilizing Diffusion Tensor Imaging (DTI) and its applicability to a real world setting.

Method

A total of 30 participants diagnosed with AD with a mean age of 68.5 ± 8.4 and 42 control participants with a mean age of 58.7 ± 7.7 were included, from the Quantitative MRI in NHS Memory Clinics (QMIN-MC) study, recruited from NHS Memory Assessment Services. Diffusion-weighted imaging (DWI) data were preprocessed using the Micapipe preprocessing pipeline to generate fractional anisotropy (FA) and mean diffusivity (MD) values. Twenty-five regions of interest (ROIs) were selected from the JHU ICBM DTI-81 Atlas and analyzed using FMRIB Software Library (FSL) tools.

Results

We analyzed 25 ROIs to identify differences in FA and MD between AD and control groups. FA values showed significant differences in 17 regions (Figure 1), including the hippocampus, fornix, and cingulate gyrus, while MD values revealed significant differences in 18 regions (Figure 2). Normalization was performed using reference tracts considered least affected by age-related changes: the superior longitudinal fasciculus (SLF) for FA and the superior fronto-occipital fasciculus (SFO) for MD. After normalization, 6 regions showed significant differences for FA, and 18 regions for MD (Figure 3).

Conclusion

Our findings support DTI measures as potential diagnostic tools for evaluation of AD patients as part of routine clinical practice. The involvement of key structures of the limbic system (hippocampus, fornix, and cingulate gyrus) along with white matter pathways such as the tapetum and stria terminalis provide evidence for the disruption of memory and executive processing, alongside inter-hemispheric communication in Alzheimer's disease. Such insights provide a basis for further research into the microstructural changes underlying AD pathology and their real world diagnostic application.

背景白质(WM)变性被认为是阿尔茨海默病(AD)的早期指标。WM完整性的改变,如分数各向异性(FA)的降低和平均扩散率(MD)的增加,可能反映了与AD相关的潜在病理过程。本研究旨在利用扩散张量成像(DTI)研究AD的微观结构变化及其在现实世界中的适用性。方法共纳入30名平均年龄为68.5±8.4岁的AD患者和42名平均年龄为58.7±7.7岁的对照患者,这些患者来自NHS记忆诊所定量MRI (QMIN‐MC)研究,来自NHS记忆评估服务。使用Micapipe预处理管道对扩散加权成像(DWI)数据进行预处理,生成分数各向异性(FA)和平均扩散系数(MD)值。从JHU ICBM DTI - 81图谱中选择25个感兴趣区域(roi),并使用FMRIB软件库(FSL)工具进行分析。结果我们分析了25个roi,以确定AD组与对照组之间FA和MD的差异。FA值在海马、穹窿、扣带回等17个区域存在显著差异(图1),MD值在18个区域存在显著差异(图2)。使用被认为受年龄相关变化影响最小的参考束进行归一化:FA的上纵束(SLF)和MD的额枕上束(SFO)。归一化后,FA的6个区域和MD的18个区域显示显著差异(图3)。结论:我们的研究结果支持DTI测量作为评估AD患者的潜在诊断工具作为常规临床实践的一部分。边缘系统的关键结构(海马体、穹窿和扣带回)以及白质通路(如绒毡层和终纹)的参与,为阿尔茨海默病的记忆和执行过程以及半球间交流的中断提供了证据。这些见解为进一步研究阿尔茨海默病病理的微观结构变化及其在现实世界中的诊断应用提供了基础。
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引用次数: 0
Distinct risk factors drive white matter hyperintensity progression which relates to cognitive performance in individuals at risk of Alzheimer's disease 不同的风险因素驱动白质高强度进展,这与阿尔茨海默病风险个体的认知表现有关
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106766
Patricia Genius, Blanca Rodríguez-Fernández, Mahnaz Shekari, Gonzalo Sánchez-Benavides, Gwendlyn Kollmorgen, Clara Quijano Rubio, Carole H Sudre, Marta Cirach, Mark Nieuwenhuijsen, Marc Suárez-Calvet, Arcadi Navarro, Juan Domingo Gispert, Natalia Vilor-Tejedor
<div> <section> <h3> Background</h3> <p>White matter hyperintensities (WMHs) are a hallmark of cerebral small vessel disease (CSVD) linked to cognitive impairment and risk of dementia. Several risk factors are associated with WMH, but their contribution to WMH progression remains unclear. This study aimed to identify risk factors driving WMHs changes in middle-aged individuals and to examine their impact on cognitive decline.</p> </section> <section> <h3> Method</h3> <p>Global WMHs and cognitive composites were evaluated at baseline and after three years on 75 cognitively unimpaired individuals at risk of Alzheimer's disease (AD) whose WMH volumes increased (Progressors: ΔWMHv2-v1 > 10+Percentile ΔWMHv2-v1=0). CSF biomarkers, exposure to air pollutants, AD pathway-specific polygenic risk scores (PRS) and cardiovascular risk factors were evaluated as predictors of the annual rate of change of global WMH, which was assessed as a predictor of cognitive performance. Partial least squares regression identified latent factors describing predictor-outcome covariance. Latent factors and WMH change were used in independent linear regression models to predict cognitive performance.</p> </section> <section> <h3> Result</h3> <p>Global WMHs increased by 9.5%, while cognitive composites declined annually by 1–11% [Table 1]. Five latent factors explained 56% of the variance in risk factors, though their stability was limited, with only a few significant loadings after bootstrapping (CI 95%) [Figure 1A]. Key predictors of WMH progression included higher genetic risks for WMH and AD (via the stimulus signaling pathway) and notably lower educational attainment, even when paired with low levels of other risk factors [Figure 1B]. Component 3, linked to baseline risk factors (e.g. Centiloid, CSF Aβ42/40)[Figure 1C], predicted lower language and PACC scores after 3 years [Figure 2A]. While WMH change did not mediate this association, it correlated with worse PACC (<i>p</i> = 0.057) and memory performance (ꞵ= -0.1 [-0.188, -0.011], <i>p</i> = 0.028) [Figure 2B].</p> </section> <section> <h3> Conclusion</h3> <p>WMHs progression is linked to subclinical cognitive decline in cognitively unimpaired individuals, for which low educational attainment and risk of AD via signaling pathways drive WMH progression. Remarkably, when combined with other risk factors, these variables predict worse PACC outcomes. These findings highlight the need to work with larger sample sizes to identify covariance patterns in modifiable and non-modifiable risk factors related to cerebrovascular d
背景白质高信号(WMHs)是与认知障碍和痴呆风险相关的脑血管疾病(CSVD)的标志。几种与WMH相关的危险因素,但它们对WMH进展的影响尚不清楚。本研究旨在确定导致中年个体WMHs变化的危险因素,并检查其对认知能力下降的影响。方法在基线和三年后,对75名认知功能未受损的阿尔茨海默病(AD)风险患者进行总体WMH和认知复合评估(进展:ΔWMHv2‐v1 >; 10+百分位数ΔWMHv2‐v1=0)。CSF生物标志物、空气污染物暴露、AD通路特异性多基因风险评分(PRS)和心血管危险因素被评估为全球WMH年变化率的预测因子,这被评估为认知表现的预测因子。偏最小二乘回归确定了描述预测结果协方差的潜在因素。潜在因素和WMH变化在独立线性回归模型中预测认知表现。结果全球wmh增加9.5%,而认知复合指数每年下降1 - 11%[表1]。五个潜在因素解释了56%的风险因素方差,尽管它们的稳定性有限,在启动后只有少数显著的负荷(CI 95%)[图1A]。WMH进展的关键预测因素包括WMH和AD的较高遗传风险(通过刺激信号通路)和显著较低的受教育程度,即使与低水平的其他风险因素配对[图1B]。成分3与基线危险因素(如Centiloid, CSF a - β42/40)相关[图1C],预测3年后较低的语言和PACC评分[图2A]。虽然WMH的改变并没有介导这种关联,但它与更差的PACC (p = 0.057)和记忆表现(ꞵ=‐0.1[‐0.188,‐0.011],p = 0.028)相关[图2B]。结论认知功能未受损个体的WMH进展与亚临床认知能力下降有关,低受教育程度和AD风险通过信号通路驱动WMH进展。值得注意的是,当与其他风险因素结合时,这些变量预测更差的PACC结果。这些发现强调需要更大的样本量来确定与脑血管损伤和认知能力下降相关的可改变和不可改变危险因素的协方差模式。
{"title":"Distinct risk factors drive white matter hyperintensity progression which relates to cognitive performance in individuals at risk of Alzheimer's disease","authors":"Patricia Genius,&nbsp;Blanca Rodríguez-Fernández,&nbsp;Mahnaz Shekari,&nbsp;Gonzalo Sánchez-Benavides,&nbsp;Gwendlyn Kollmorgen,&nbsp;Clara Quijano Rubio,&nbsp;Carole H Sudre,&nbsp;Marta Cirach,&nbsp;Mark Nieuwenhuijsen,&nbsp;Marc Suárez-Calvet,&nbsp;Arcadi Navarro,&nbsp;Juan Domingo Gispert,&nbsp;Natalia Vilor-Tejedor","doi":"10.1002/alz70856_106766","DOIUrl":"10.1002/alz70856_106766","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 a hallmark of cerebral small vessel disease (CSVD) linked to cognitive impairment and risk of dementia. Several risk factors are associated with WMH, but their contribution to WMH progression remains unclear. This study aimed to identify risk factors driving WMHs changes in middle-aged individuals and to examine their impact on cognitive decline.&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;Global WMHs and cognitive composites were evaluated at baseline and after three years on 75 cognitively unimpaired individuals at risk of Alzheimer's disease (AD) whose WMH volumes increased (Progressors: ΔWMHv2-v1 &gt; 10+Percentile ΔWMHv2-v1=0). CSF biomarkers, exposure to air pollutants, AD pathway-specific polygenic risk scores (PRS) and cardiovascular risk factors were evaluated as predictors of the annual rate of change of global WMH, which was assessed as a predictor of cognitive performance. Partial least squares regression identified latent factors describing predictor-outcome covariance. Latent factors and WMH change were used in independent linear regression models to predict cognitive performance.&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;Global WMHs increased by 9.5%, while cognitive composites declined annually by 1–11% [Table 1]. Five latent factors explained 56% of the variance in risk factors, though their stability was limited, with only a few significant loadings after bootstrapping (CI 95%) [Figure 1A]. Key predictors of WMH progression included higher genetic risks for WMH and AD (via the stimulus signaling pathway) and notably lower educational attainment, even when paired with low levels of other risk factors [Figure 1B]. Component 3, linked to baseline risk factors (e.g. Centiloid, CSF Aβ42/40)[Figure 1C], predicted lower language and PACC scores after 3 years [Figure 2A]. While WMH change did not mediate this association, it correlated with worse PACC (&lt;i&gt;p&lt;/i&gt; = 0.057) and memory performance (ꞵ= -0.1 [-0.188, -0.011], &lt;i&gt;p&lt;/i&gt; = 0.028) [Figure 2B].&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;WMHs progression is linked to subclinical cognitive decline in cognitively unimpaired individuals, for which low educational attainment and risk of AD via signaling pathways drive WMH progression. Remarkably, when combined with other risk factors, these variables predict worse PACC outcomes. These findings highlight the need to work with larger sample sizes to identify covariance patterns in modifiable and non-modifiable risk factors related to cerebrovascular d","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_106766","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145947319","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
The relevance of MRI-based AI Predictive Modelling for Treatment's response sand personalized Clinical Trials design 基于MRI的人工智能预测模型与治疗反应和个性化临床试验设计的相关性
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106596
Luca Villa, Nicolas Guizard, Mathilde Borrot, Ayoub Gueddou, Audrey Gabelle, Elizabeth Gordon, Olivier Courreges

Background

The heterogeneity of patient clinical progression is a key challenge in Alzheimer's disease (AD). This is especially the case when conducting disease-modifying clinical trials in patients with mild cognitive impairment (MCI) and early AD where, historically, large proportions of patients in placebo groups show subtle cognitive decline within the period of the trials, hindering the ability to detect treatment effects. Recent advances in Artificial Intelligence (AI) have allowed rapid progress to be made in the field of predictive modeling, enabling the integration of clinical, demographic, genetic, and neuroimaging data to provide accurate personalized predictions of prognosis at an individual level. So far, these methods have remained in the domain of academic research but have huge potential if applied to the enrichment of real-world clinical trials in AD, as well as in the prioritization of medication prescription for newly approved treatments.

Method

We have developed QyScore®, an advanced fully-automated CE-Marked and FDA-cleared medical imaging platform that is certified for grey and white matter segmentation, and was used to identify a reduction in grey matter atrophy associated with treatment in a recent AD clinical trial. Moreover, we have developed QyPredict®, an AI-based predictive modelling platform designed to predict clinical progression in central nervous system diseases.

Result

By integrating the neuroimaging quantifications generated by QyScore® into QyPredict®, alongside key demographic, clinical, and genetic data from a wide variety of patients and healthy controls, we have achieved high prediction accuracies when predicting clinical decline – with the following range of performance metrics, depending on clinical population and prediction target: Balanced Accuracy: 0.70-0.81, Sensitivity: 0.73-0.80, Specificity: 0.60-0.88, Precision: 0.77-0.81, Negative Predictive Value: 0.59-0.87, F1: 0.74-0.81.

Conclusion

Given the ability of this predictive modelling platform to identify patients at the highest risk of clinical decline, it could be invaluable for the stratification of the right patient’ target. Moreover, its ability to predict patients with the greatest likelihood for remaining clinically stable could be invaluable for the identification and exclusion of patients in future clinical trials that are unlikely to show clinical decline – therefore improving the ability of future trials to detect treatment effects.

患者临床进展的异质性是阿尔茨海默病(AD)的一个关键挑战。在对轻度认知障碍(MCI)和早期AD患者进行疾病改善临床试验时尤其如此,从历史上看,安慰剂组中大部分患者在试验期间表现出轻微的认知能力下降,阻碍了检测治疗效果的能力。人工智能(AI)的最新进展使预测建模领域取得了快速进展,使临床、人口统计学、遗传和神经影像学数据得以整合,从而在个体层面上提供准确的个性化预后预测。到目前为止,这些方法仍停留在学术研究领域,但如果应用于丰富阿尔茨海默病的现实世界临床试验,以及新批准治疗的药物处方优先排序,则具有巨大的潜力。方法:我们开发了QyScore®,一种先进的全自动CE认证和FDA认证的医学成像平台,用于灰质和白质分割,并在最近的一项阿尔茨海默病临床试验中用于识别与治疗相关的灰质萎缩的减少。此外,我们还开发了QyPredict®,这是一个基于人工智能的预测建模平台,旨在预测中枢神经系统疾病的临床进展。通过将QyScore®生成的神经影像学定量数据整合到QyPredict®中,以及来自各种患者和健康对照的关键人口统计学、临床和遗传数据,我们在预测临床衰退时取得了很高的预测准确性——根据临床人群和预测目标,我们具有以下性能指标范围:平衡精度:0.70‐0.81,灵敏度:0.73‐0.80,特异性:0.60‐0.88,精度:0.77‐0.81,阴性预测值:0.59‐0.87,F1: 0.74‐0.81。鉴于该预测建模平台识别临床衰退风险最高的患者的能力,它对于正确患者目标的分层可能是非常宝贵的。此外,它预测最有可能保持临床稳定的患者的能力对于在未来的临床试验中识别和排除不太可能出现临床衰退的患者是非常宝贵的,从而提高了未来试验检测治疗效果的能力。
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引用次数: 0
Plasma NfL Levels Across Cognitive Stages and the Impact of Comorbidities in a Thai Cohort 一个泰国队列中认知阶段血浆NfL水平和合并症的影响
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_106886
Chatchawan Rattanabannakit, Kristsana Khuranae, Natthamon Wongkom, Pathitta Dujada, Paphawadee Phoyoo, Leatchai Wachirutmanggur, Vorapun Senanarong
<div> <section> <h3> Background</h3> <p>Elevated plasma neurofilament light chain (NfL) is a promising biomarker for dementia diagnosis. However, it has also been reported to be associated with age, body mass index (BMI), and comorbidities such as diabetes, hypertension, chronic kidney disease (CKD), stroke, and cardiovascular diseases. This study aimed to investigate the relationship between plasma NfL levels, cognitive performance, and activities of daily living (ADL) in a Thai population, as well as the comorbidities influencing NfL levels.</p> </section> <section> <h3> Method</h3> <p>A pilot study was conducted with 48 participants categorized into normal cognition (<i>n</i> = 4), mild cognitive impairment (MCI)(<i>n</i> = 18), and dementia (<i>n</i> = 26) groups. Plasma NfL levels were analyzed using Single Molecule Arrays (SiMoA) technology. Statistical analyses, including Mann-Whitney U Test and Spearman's rho correlations, were used to examine associations between NfL levels and other variables.</p> </section> <section> <h3> Result</h3> <p>The mean age of participants was 70.8±12.0 years, and 58.3% were female. Median plasma NFL levels were significantly higher (<i>p</i> <0.05) in the dementia group (44.3, IQR45.9) compared to the MCI (18.7, IQR13.9) and normal cognition groups (8.6, IQR15.8). Higher NFL levels were significantly associated with lower cognitive scores, including Thai Mental State Examination scores (r=-0.58, <i>p</i> <0.001) and Montreal Cognitive Assessment scores (r=-0.55, <i>p</i> <0.001). They also correlated with poorer function, as measured by the sum of basic and instrumental ADL scores, and Clinical Dementia Rating scale-sum of boxes (r=0.61 and 0.64, respectively, <i>p</i> <0.001). Plasma NFL levels were significantly correlated with serum albumin (r=-0.37, <i>p</i> = 0.028) and BMI (<i>r</i> =-0.37, <i>p</i> = 0.023). Age and comorbidities, including diabetes, hypertension, dyslipidemia, CKD, cardiovascular and cerebrovascular disease, levels of blood urea nitrogen, creatinine, liver enzymes, lipid profiles, and thyroid functions, did not significantly influence NfL concentrations. However, higher creatinine (r=0.31, <i>p</i> = 0.051) and a history of CKD (<i>p</i> = 0.054) showed a trend toward an associate with elevated plasma NfL levels.</p> </section> <section> <h3> Conclusion</h3> <p>In our pilot study, plasma NfL levels are significantly associated with dementia stages, ADL, serum albumin, and BMI and showed a trend toward an associated with renal dysfunction. The interplay between systemic health and NfL levels underscores the need for comorbidity assessments in dementia resear
血浆神经丝轻链(NfL)升高是一种很有前景的痴呆症诊断生物标志物。然而,也有报道称它与年龄、体重指数(BMI)和合并症(如糖尿病、高血压、慢性肾脏疾病(CKD)、中风和心血管疾病)有关。本研究旨在探讨泰国人群血浆NfL水平、认知能力和日常生活活动(ADL)之间的关系,以及影响NfL水平的合并症。方法将48名受试者分为正常认知组(n = 4)、轻度认知障碍组(n = 18)和痴呆组(n = 26)进行初步研究。采用单分子阵列(SiMoA)技术分析血浆NfL水平。统计分析,包括Mann - Whitney U检验和Spearman的rho相关性,用于检查NfL水平与其他变量之间的关系。结果参与者平均年龄为70.8±12.0岁,女性占58.3%。痴呆组中位血浆NFL水平(44.3,IQR45.9)显著高于MCI组(18.7,IQR13.9)和正常认知组(8.6,IQR15.8) (p <0.05)。较高的NFL水平与较低的认知得分显著相关,包括泰国精神状态检查得分(r=‐0.58,p <0.001)和蒙特利尔认知评估得分(r=‐0.55,p <0.001)。他们还与较差的功能相关,通过基本和辅助ADL评分的总和和临床痴呆评定量表-框的总和来衡量(r分别=0.61和0.64,p <0.001)。血浆NFL水平与血清白蛋白(r=‐0.37,p = 0.028)和BMI (r=‐0.37,p = 0.023)显著相关。年龄和合并症,包括糖尿病、高血压、血脂异常、CKD、心脑血管疾病、血尿素氮水平、肌酐、肝酶、脂质谱和甲状腺功能,对NfL浓度没有显著影响。然而,较高的肌酐(r=0.31, p = 0.051)和CKD病史(p = 0.054)显示出血浆NfL水平升高的趋势。在我们的初步研究中,血浆NfL水平与痴呆分期、ADL、血清白蛋白和BMI显著相关,并显示出与肾功能障碍相关的趋势。系统健康和NfL水平之间的相互作用强调了痴呆研究中共病评估的必要性,为未来验证NfL的研究奠定了基础,并扩大了其在不同人群中的适用性。
{"title":"Plasma NfL Levels Across Cognitive Stages and the Impact of Comorbidities in a Thai Cohort","authors":"Chatchawan Rattanabannakit,&nbsp;Kristsana Khuranae,&nbsp;Natthamon Wongkom,&nbsp;Pathitta Dujada,&nbsp;Paphawadee Phoyoo,&nbsp;Leatchai Wachirutmanggur,&nbsp;Vorapun Senanarong","doi":"10.1002/alz70856_106886","DOIUrl":"10.1002/alz70856_106886","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;Elevated plasma neurofilament light chain (NfL) is a promising biomarker for dementia diagnosis. However, it has also been reported to be associated with age, body mass index (BMI), and comorbidities such as diabetes, hypertension, chronic kidney disease (CKD), stroke, and cardiovascular diseases. This study aimed to investigate the relationship between plasma NfL levels, cognitive performance, and activities of daily living (ADL) in a Thai population, as well as the comorbidities influencing NfL levels.&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;A pilot study was conducted with 48 participants categorized into normal cognition (&lt;i&gt;n&lt;/i&gt; = 4), mild cognitive impairment (MCI)(&lt;i&gt;n&lt;/i&gt; = 18), and dementia (&lt;i&gt;n&lt;/i&gt; = 26) groups. Plasma NfL levels were analyzed using Single Molecule Arrays (SiMoA) technology. Statistical analyses, including Mann-Whitney U Test and Spearman's rho correlations, were used to examine associations between NfL levels and other variables.&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 mean age of participants was 70.8±12.0 years, and 58.3% were female. Median plasma NFL levels were significantly higher (&lt;i&gt;p&lt;/i&gt; &lt;0.05) in the dementia group (44.3, IQR45.9) compared to the MCI (18.7, IQR13.9) and normal cognition groups (8.6, IQR15.8). Higher NFL levels were significantly associated with lower cognitive scores, including Thai Mental State Examination scores (r=-0.58, &lt;i&gt;p&lt;/i&gt; &lt;0.001) and Montreal Cognitive Assessment scores (r=-0.55, &lt;i&gt;p&lt;/i&gt; &lt;0.001). They also correlated with poorer function, as measured by the sum of basic and instrumental ADL scores, and Clinical Dementia Rating scale-sum of boxes (r=0.61 and 0.64, respectively, &lt;i&gt;p&lt;/i&gt; &lt;0.001). Plasma NFL levels were significantly correlated with serum albumin (r=-0.37, &lt;i&gt;p&lt;/i&gt; = 0.028) and BMI (&lt;i&gt;r&lt;/i&gt; =-0.37, &lt;i&gt;p&lt;/i&gt; = 0.023). Age and comorbidities, including diabetes, hypertension, dyslipidemia, CKD, cardiovascular and cerebrovascular disease, levels of blood urea nitrogen, creatinine, liver enzymes, lipid profiles, and thyroid functions, did not significantly influence NfL concentrations. However, higher creatinine (r=0.31, &lt;i&gt;p&lt;/i&gt; = 0.051) and a history of CKD (&lt;i&gt;p&lt;/i&gt; = 0.054) showed a trend toward an associate with elevated plasma NfL levels.&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;In our pilot study, plasma NfL levels are significantly associated with dementia stages, ADL, serum albumin, and BMI and showed a trend toward an associated with renal dysfunction. The interplay between systemic health and NfL levels underscores the need for comorbidity assessments in dementia resear","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_106886","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955240","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
Spatiotemporal Heterogeneity of Alzheimer's Disease-Related Functional Brain Network Dedifferentiation 阿尔茨海默病相关脑功能网络去分化的时空异质性
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_107430
Roy Massett, Ziwei Zhang, Micaela Chan, Gagan S Wig, Alzheimer's Disease Neuroimaging Initiative (ADNI), Wig Neuroimaging Lab
<div> <section> <h3> Background</h3> <p>Alzheimer's disease (AD) is a highly heterogeneous condition both in terms of the distribution of pathology deposition and clinical manifestation. The organization of functional brain networks is related to AD pathology, with recent work showing that higher dementia severity is related to the desegregation of brain networks (Zhang <i>et al</i>., 2023). However, the spatiotemporal heterogeneity of these changes in network segregation and how they contribute to different cognitive deficit profiles remains an open area of research. To contribute to this question, we applied a clustering-based data-driven disease progression model to system-level measures of network organization.</p> </section> <section> <h3> Method</h3> <p>We included 754 resting-state functional magnetic resonance imaging (fMRI) scans from cognitively impaired individuals (CDR > 0) enrolled in the Alzheimer's Disease Neuroimaging Initiative. The correlations of fMRI resting-state time series between nodes were used to construct brain networks (Chan <i>et al</i>., 2014). Nodes were assigned to a functional system based on a previously defined functional atlas (Power <i>et al</i>., 2011). Network segregation was calculated for each brain system as measures of system-level organization. The SuStaIn algorithm was used to simultaneously stage and subtype subjects according to their patterns of network segregation (Young <i>et al</i>., 2018). Functional systems that were clustered together were further analyzed collectively using linear regression models.</p> </section> <section> <h3> Result</h3> <p>SuStaIn identified two subtypes of alterations in system-level network segregation, which were upheld in <i>k</i>-fold cross validation. One cluster showed decreases in the segregation of sensory-motor systems and several additional systems, including the superior temporal gyrus, salience, and medial temporal parietal systems. The other cluster showed decreases primarily in segregation of association systems including the default mode network, task control systems, attention systems, and memory retrieval systems. Further, we observed a significant interaction effect between system-type and model-estimated disease stage and subtype.</p> </section> <section> <h3> Conclusion</h3> <p>Resting-state fMRI signals can be used to identify dissociable patterns of AD-related brain network desegregation relating to different profiles of brain network dysfunction and cognitive impairment. These findings begin to describe the spatiotemporal heterogeneity in brain network decline, and their relation to cognitive trajectories, which is relevant not o
背景阿尔茨海默病(AD)无论在病理沉积分布还是临床表现上都是一个高度异质性的疾病。功能性脑网络的组织与AD病理有关,最近的研究表明,较高的痴呆严重程度与脑网络的去隔离有关(Zhang et al., 2023)。然而,这些网络隔离变化的时空异质性以及它们如何导致不同的认知缺陷概况仍然是一个开放的研究领域。为了回答这个问题,我们将一个基于聚类的数据驱动的疾病进展模型应用于网络组织的系统级度量。方法:我们纳入了参加阿尔茨海默病神经影像学计划的认知受损个体(CDR > 0)的754张静息状态功能磁共振成像(fMRI)扫描。利用节点间fMRI静息状态时间序列的相关性构建脑网络(Chan et al., 2014)。节点被分配到基于先前定义的功能图谱的功能系统(Power et al., 2011)。计算每个大脑系统的网络隔离,作为系统级组织的度量。使用SuStaIn算法根据受试者的网络隔离模式同时对其进行分期和分型(Young等人,2018)。聚在一起的功能系统进一步使用线性回归模型进行集体分析。结果SuStaIn在系统级网络隔离中发现了两种亚型的改变,这在k-fold交叉验证中得到了证实。一个集群显示感觉-运动系统和其他几个系统的分离减少,包括颞上回、显著性和内侧颞顶叶系统。另一组主要表现为关联分离系统的减少,包括默认模式网络、任务控制系统、注意系统和记忆检索系统。此外,我们观察到系统类型和模型估计的疾病分期和亚型之间存在显著的相互作用效应。结论静息状态fMRI信号可用于识别ad相关脑网络分离的可解离模式,该模式与脑网络功能障碍和认知障碍的不同特征有关。这些发现开始描述大脑网络衰退的时空异质性及其与认知轨迹的关系,这不仅与阿尔茨海默病的预后有关,而且还与评估认知不同患者群体的临床试验结果有关。
{"title":"Spatiotemporal Heterogeneity of Alzheimer's Disease-Related Functional Brain Network Dedifferentiation","authors":"Roy Massett,&nbsp;Ziwei Zhang,&nbsp;Micaela Chan,&nbsp;Gagan S Wig,&nbsp;Alzheimer's Disease Neuroimaging Initiative (ADNI),&nbsp;Wig Neuroimaging Lab","doi":"10.1002/alz70856_107430","DOIUrl":"https://doi.org/10.1002/alz70856_107430","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) is a highly heterogeneous condition both in terms of the distribution of pathology deposition and clinical manifestation. The organization of functional brain networks is related to AD pathology, with recent work showing that higher dementia severity is related to the desegregation of brain networks (Zhang &lt;i&gt;et al&lt;/i&gt;., 2023). However, the spatiotemporal heterogeneity of these changes in network segregation and how they contribute to different cognitive deficit profiles remains an open area of research. To contribute to this question, we applied a clustering-based data-driven disease progression model to system-level measures of network organization.&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 included 754 resting-state functional magnetic resonance imaging (fMRI) scans from cognitively impaired individuals (CDR &gt; 0) enrolled in the Alzheimer's Disease Neuroimaging Initiative. The correlations of fMRI resting-state time series between nodes were used to construct brain networks (Chan &lt;i&gt;et al&lt;/i&gt;., 2014). Nodes were assigned to a functional system based on a previously defined functional atlas (Power &lt;i&gt;et al&lt;/i&gt;., 2011). Network segregation was calculated for each brain system as measures of system-level organization. The SuStaIn algorithm was used to simultaneously stage and subtype subjects according to their patterns of network segregation (Young &lt;i&gt;et al&lt;/i&gt;., 2018). Functional systems that were clustered together were further analyzed collectively using linear regression models.&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;SuStaIn identified two subtypes of alterations in system-level network segregation, which were upheld in &lt;i&gt;k&lt;/i&gt;-fold cross validation. One cluster showed decreases in the segregation of sensory-motor systems and several additional systems, including the superior temporal gyrus, salience, and medial temporal parietal systems. The other cluster showed decreases primarily in segregation of association systems including the default mode network, task control systems, attention systems, and memory retrieval systems. Further, we observed a significant interaction effect between system-type and model-estimated disease stage and subtype.&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;Resting-state fMRI signals can be used to identify dissociable patterns of AD-related brain network desegregation relating to different profiles of brain network dysfunction and cognitive impairment. These findings begin to describe the spatiotemporal heterogeneity in brain network decline, and their relation to cognitive trajectories, which is relevant not o","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_107430","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145964253","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
Sex and APOE status moderate locus coeruleus network related resilience in preclinical Alzheimer's disease 性别和APOE状态对临床前阿尔茨海默病蓝斑网络相关恢复力的调节作用
IF 11.1 1区 医学 Q1 CLINICAL NEUROLOGY Pub Date : 2026-01-11 DOI: 10.1002/alz70856_107257
Timothy Lawn, Ibai Diez, Elisenda Bueichekú2, Maxime Van Egroo, Gillian T Coughlan, Rachel F. Buckley, Dorene M. Rentz, Keith A. Johnson, Reisa A. Sperling, Jorge Sepulcre, Heidi I.L. Jacobs
<div> <section> <h3> Background</h3> <p>Brainstem nuclei such as the locus coeruleus (LC) are amongst the earliest regions affected by tau pathology in Alzheimer's disease (AD). The LC's extensive noradrenergic projections shape brain network architecture and its structural integrity is associated with resilience against cognitive decline. However, the role of LC network connectivity in cognitive resilience remains unclear, as does its potential differential impact across distinct population subgroups who might specifically benefit from its augmentation.</p> </section> <section> <h3> Methods</h3> <p>We included 393 cognitively unimpaired Aβ+ individuals (centiloid > 19) from the A4 study who underwent baseline resting-state fMRI and florbetapir Aβ-PET as well as longitudinal Preclinical Alzheimer's Cognitive Composite (PACC) assessment. Pearsons's correlation coefficient was used to create maps of LC functional connectivity (LC-FC) to 454 parcels of the Schaefer-Tian parcellation which were harmonised across scanners using NeuroCombat. Mixed-effects models with natural cubic splines (2 DOF) were used to test whether global, Yeo17 network, and individual parcel level LC-FC moderated PACC decline over time as well as in interaction with centiloid, sex, and APOΕ4 status, controlling for age, education, framewise displacement, treatment, and sex (when not interacted). Analyses were deemed significant following Benjamini-Hochberg false-discovery rate correction for multiple comparisons.</p> </section> <section> <h3> Results</h3> <p>The LC showed widespread connectivity that was strongest within the limbic regions, hippocampus, and thalamus (Figure 1a). Greater global LC-FC was associated with attenuated cognitive decline (Figure 1b, <i>p</i> = 0.014), especially at higher levels of Aβ (Figure 1c, <i>p</i> <0.001). At the network level, LC-FC resilience was predominantly related to task-positive (control and dorsal/ventral attentional) networks, whilst in the default mode network greater LC-FC was associated with reduced cognitive decline at lower Aβ (Figure 1b/c). The effect of LC-FC on PACC decline was particularly pronounced in females at high Aβ levels (Figure 2b) and APOE-e4 carriers (Figure 2c), demonstrating a synergistic effect of sex and genetic risk on LC-mediated cognitive resilience (Figure 2d).</p> </section> <section> <h3> Conclusions</h3> <p>Our findings further support the role of the LC in cognitive resilience and suggest this particularly manifests from modulation of task-positive attentional and frontoparietal control networks. M
脑干核如蓝斑核(LC)是阿尔茨海默病(AD)中最早受tau病理影响的区域之一。脑皮层广泛的去肾上腺素能投射塑造了大脑网络结构,其结构完整性与抵御认知能力下降的弹性有关。然而,LC网络连通性在认知弹性中的作用尚不清楚,其潜在的差异影响也不清楚,不同的人群亚群可能特别受益于其增强。方法我们纳入了来自A4研究的393名认知未受损的Aβ+个体(centiloid > 19),他们接受了基线静息状态fMRI和florbetapir Aβ‐PET以及纵向临床前阿尔茨海默氏症认知复合(PACC)评估。Pearsons的相关系数被用于创建Schaefer - Tian包裹的454个包裹的LC - FC功能连接图,这些地图使用NeuroCombat在扫描仪上进行协调。使用自然三次样条(2 DOF)的混合效应模型来测试全球、Yeo17网络和单个包裹水平的LC - FC是否随时间以及与centiloid、性别和APOΕ4状态的相互作用,控制年龄、教育、框架位移、治疗和性别(当不相互作用时)减缓PACC的下降。在多次比较的Benjamini - Hochberg错误发现率校正后,分析被认为是显著的。LC显示了广泛的连通性,在边缘区域、海马和丘脑中最强(图1a)。更大的LC‐FC与认知能力下降的减轻有关(图1b, p = 0.014),特别是在高水平的Aβ(图1c, p <0.001)。在网络水平上,LC - FC弹性主要与任务正性(控制和背侧/腹侧注意)网络相关,而在默认模式网络中,LC - FC的增加与低a - β认知衰退的减少有关(图1b/c)。LC‐FC对PACC下降的影响在高a β水平的女性(图2b)和APOE‐e4携带者(图2c)中尤为明显,这表明性别和遗传风险对LC‐介导的认知恢复能力有协同作用(图2d)。结论:我们的研究结果进一步支持了脑皮层皮层在认知弹性中的作用,并表明这种作用尤其体现在任务正性注意和额顶叶控制网络的调节上。此外,女性e4‐携带者表现出更明显的认知衰退衰减,这表明她们可能特别受益于去甲肾上腺素能功能的增强。
{"title":"Sex and APOE status moderate locus coeruleus network related resilience in preclinical Alzheimer's disease","authors":"Timothy Lawn,&nbsp;Ibai Diez,&nbsp;Elisenda Bueichekú2,&nbsp;Maxime Van Egroo,&nbsp;Gillian T Coughlan,&nbsp;Rachel F. Buckley,&nbsp;Dorene M. Rentz,&nbsp;Keith A. Johnson,&nbsp;Reisa A. Sperling,&nbsp;Jorge Sepulcre,&nbsp;Heidi I.L. Jacobs","doi":"10.1002/alz70856_107257","DOIUrl":"10.1002/alz70856_107257","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;Brainstem nuclei such as the locus coeruleus (LC) are amongst the earliest regions affected by tau pathology in Alzheimer's disease (AD). The LC's extensive noradrenergic projections shape brain network architecture and its structural integrity is associated with resilience against cognitive decline. However, the role of LC network connectivity in cognitive resilience remains unclear, as does its potential differential impact across distinct population subgroups who might specifically benefit from its augmentation.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Methods&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;We included 393 cognitively unimpaired Aβ+ individuals (centiloid &gt; 19) from the A4 study who underwent baseline resting-state fMRI and florbetapir Aβ-PET as well as longitudinal Preclinical Alzheimer's Cognitive Composite (PACC) assessment. Pearsons's correlation coefficient was used to create maps of LC functional connectivity (LC-FC) to 454 parcels of the Schaefer-Tian parcellation which were harmonised across scanners using NeuroCombat. Mixed-effects models with natural cubic splines (2 DOF) were used to test whether global, Yeo17 network, and individual parcel level LC-FC moderated PACC decline over time as well as in interaction with centiloid, sex, and APOΕ4 status, controlling for age, education, framewise displacement, treatment, and sex (when not interacted). Analyses were deemed significant following Benjamini-Hochberg false-discovery rate correction for multiple comparisons.&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Results&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;The LC showed widespread connectivity that was strongest within the limbic regions, hippocampus, and thalamus (Figure 1a). Greater global LC-FC was associated with attenuated cognitive decline (Figure 1b, &lt;i&gt;p&lt;/i&gt; = 0.014), especially at higher levels of Aβ (Figure 1c, &lt;i&gt;p&lt;/i&gt; &lt;0.001). At the network level, LC-FC resilience was predominantly related to task-positive (control and dorsal/ventral attentional) networks, whilst in the default mode network greater LC-FC was associated with reduced cognitive decline at lower Aβ (Figure 1b/c). The effect of LC-FC on PACC decline was particularly pronounced in females at high Aβ levels (Figure 2b) and APOE-e4 carriers (Figure 2c), demonstrating a synergistic effect of sex and genetic risk on LC-mediated cognitive resilience (Figure 2d).&lt;/p&gt;\u0000 &lt;/section&gt;\u0000 \u0000 &lt;section&gt;\u0000 \u0000 &lt;h3&gt; Conclusions&lt;/h3&gt;\u0000 \u0000 &lt;p&gt;Our findings further support the role of the LC in cognitive resilience and suggest this particularly manifests from modulation of task-positive attentional and frontoparietal control networks. M","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_107257","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145955173","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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Alzheimer's & Dementia
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