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Previous preclinical studies have suggested a close relationship between cerebrovascular disease (CVD) and Alzheimer's disease. However, a direct correlation between CVD and amyloid burden has not yet been shown in humans. If there is a relationship between CVD and amyloid burden, it is possible that the apolipoprotein E4 (APOE4) genotype may have an effect on this relationship because APOE4 is a risk factor for the development of AD. We therefore evaluated the effects of APOE4 on the relationship between white matter hyperintensities (WMH), a marker of CVD, and amyloid burden, measured by 11C-Pittsburgh compound B (PiB) PET. We recruited 53 patients with subcortical vascular cognitive impairments, who had both WMH on MRI and amyloid deposition assessed by PiB PET. Twenty-two of these patients were APOE4 carriers (41.5%). In the APOE4 non-carriers, a significant positive correlation was shown between the volume of WMH and PiB retention (β = 7.0 × 10-3, p = 0.034) while no significant correlation was found in APOE4 carriers (β = -9.0 × 10-3, p = 0.085). Statistical parametric mapping analyses in APOE4 non-carriers showed that WMH were associated with PiB retention in the bilateral medial occipitotemporal gyrus, cuneus, and superior cerebellum. Our results suggested that WMH are correlated with amyloid burden especially in the posterior brain regions in APOE4 non-carriers. However, this correlation was not observed in APOE4 carriers, perhaps because in these subjects the influence of APOE4 overrides the effect of CVD. [ABSTRACT FROM AUTHOR]

Abstract: Although patients with amnestic mild cognitive impairment (aMCI) are at higher risk of developing Alzheimer's disease (AD), their pathologies could be heterogeneous. We aimed to evaluate structural changes in amyloid-negative and amyloid-positive aMCI patients. Forty-eight aMCI patients who underwent Pittsburgh compound B (PiB) positron emission tomography were recruited. They were classified as PiB (−) aMCI (N = 16) and PiB (+) (N = 32). Hippocampal shape and regional cortical thickness were compared with 41 subjects with normal cognition (NC). Relative to NC, PiB(−) aMCI exhibited hippocampal deformity in the right cornu ammonis 1, whereas PiB(+) aMCI exhibited hippocampal deformity in bilateral subiculum and cornu ammonis 1 subregions. Relative to NC, PiB(−) aMCI showed cortical thinning in the left medial prefrontal and right anterior temporal regions, whereas PiB(+) aMCI exhibited cortical thinning in bilateral medial temporal regions, temporoparietal junctions and precuneus, and prefrontal cortices. Our findings suggest that structural changes in PiB(−) aMCI might be due to several possible pathologic changes, whereas structural changes in PiB(+) aMCI reflect AD-like structural changes. [Copyright &y& Elsevier]

Abstract: Cerebrovascular disease (CVD) and amyloid burden are the most frequent pathologies in subjects with cognitive impairment. However, the relationship between CVD, amyloid burden, and cognition are largely unknown. We aimed to evaluate whether CVD (lacunes, white matter hyperintensities, and microbleeds) and amyloid burden (Pittsburgh compound B [PiB] retention ratio) contribute to cognitive impairment independently or interactively. We recruited 136 patients with subcortical vascular cognitive impairment who underwent magnetic resonance imaging, PiB–positron emission tomography, and neuropsychological testing. The number of lacunes was associated with memory, frontal dysfunctions, and disease severity. The volume of white matter hyperintensities and the PiB retention ratio were associated only with memory dysfunction. There was no direct correlation between CVD markers and PiB retention ratio except that the number of lacunes was negatively correlated with the PiB retention ratio. In addition, there were no interactive effects of CVD and PiB retention ratio on cognition. Our findings suggest that CVD and amyloid burden contribute independently and not interactively to specific patterns of cognitive dysfunction in patients with subcortical vascular cognitive impairment. [Copyright &y& Elsevier]

Background: Patients with early-onset Alzheimer's disease (EOAD) may differ from those with late-onset Alzheimer's disease (LOAD) in cognitive impairment profiles and clinical course. Postmortem studies also reported that EOAD has a greater pathologic burden than LOAD. We examined the effects of age at onset on the burden and distribution of amyloid plaques in patients with AD, using a statistical parametric mapping (SPM) and regions of interest (ROIs) analyses of the Pittsburgh compound B (PiB)-PET. Methods: We initially recruited 72 patients with AD who had completed the [11C] PiB-PET scan, but four patients were excluded due to familial AD or incomplete MRI data. Of the 68 patients, 61 were classified as PiB-positive (PiB+) and seven as PiB-negative (PiB-) using the measured global PiB uptake ratio values. Of the 61 patients with PiB+ AD, in order to maximize the effect of onset age, we excluded 20 patients in their 60 s. Thus among the remaining 41 patients, the amyloid deposition of only 17 patients with EOAD (age onset <60 years) and 24 patients with LOAD (onset age &nvge;70 years) were compared. Results: There were no significant differences in the global mean PiB index between EOAD and LOAD patients, whereas SPM and ROIs analyses showed that those with EOAD retained higher levels of PiB in the bilateral basal ganglia, bilateral thalamus, left superior temporal cortex, and left cuneus compared to those with LOAD. Conclusion: Our findings demonstrated that EOAD patients differed from those with LOAD in the topography of amyloid deposition, which may partly account for the findings from previous studies that extrapyramidal symptoms and frontal dysfunction are more common in EOAD than in LOAD patients. [ABSTRACT FROM AUTHOR]

Background: Amyloid-β (Aβ) commonly coexists and impacts prognosis in subcortical vascular cognitive impairment (SVCI). Objective: This study aimed to examine the differences in clinical and neuroimaging variables between Aβ-positive and Aβ-negative SVCI and to propose a prediction model for Aβ positivity in clinically diagnosed SVCI patients. Methods: A total of 130 patients with SVCI were included in model development, and a separate cohort of 70 SVCI patients was used in external validation. The variables for the prediction model were selected by comparing the characteristics of the Aβ-negative and Aβ-positive SVCI groups. The final model was determined using a stepwise method. The model performance was evaluated using the receiver operating characteristic (ROC) curve and a calibration curve. A nomogram was used for visualization. Results: Among 130 SVCI patients, 70 (53.8%) were Aβ-positive. The Aβ-positive SVCI group was characterized by older age, tendency to be in the dementia stage, a higher prevalence of APOEɛ4, a lower prevalence of lacune, and more severe medial temporal atrophy (MTA). The final prediction model, which excluded MTA grade following the stepwise method for variable selection, demonstrated good accuracy in distinguishing between Aβ-positive and Aβ-negative SVCI, with an area under the curve (AUC) of 0.80. The external validation demonstrated an AUC of 0.71. Conclusions: The findings suggest that older age, dementia stage, APOEɛ4 carrier, and absence of lacunes may be predictive of Aβ positivity in clinically diagnosed SVCI patients. [ABSTRACT FROM AUTHOR]

Several programs are widely used for clinical and research purposes to automatically quantify the degree of amyloid deposition in the brain using positron emission tomography (PET) images. Given that very few studies have investigated the use of Heuron, a PET image quantification software approved for clinical use, this study aimed to compare amyloid deposition values quantified from 18F-flutemetamol PET images using PMOD and Heuron. Amyloid PET data obtained from 408 patients were analysed using each quantitative program; moreover, the standardized uptake value ratios (SUVRs) of target areas were obtained by dividing the standardized uptake value (SUV) of the target region by the SUV of cerebellar grey matter as a reference. Compared with PMOD, Heuron yielded significantly higher SUVRs for all target areas (paired sample t-test, p < 0.001), except for the PC/PCC (p = 0.986). However, the Bland–Altman plot analysis indicated that the two quantitative methods may be used interchangeably. Moreover, receiver operating characteristic curve analysis revealed no significant between-method difference in the performance of the SUVRs in evaluating the visual positivity of amyloid deposits (p = 0.948). In conclusion, Heuron and PMOD have comparable performance in quantifying the degree of amyloid deposits in PET images. [ABSTRACT FROM AUTHOR]

Background: Accessible and cost-effective diagnostic tools are urgently needed to accurately quantify blood biomarkers to support early diagnosis of Alzheimer's disease (AD). In this study, we investigated the ability of plasma amyloid-beta (Aβ)42/Aβ40 ratio measured by an antibody-free mass-spectrometric (MS) method, ABtest-MS, to detect early pathological changes of AD. Methods: This cohort study included data from the baseline and 2-year follow-up visits from the Fundació ACE Healthy Brain Initiative (FACEHBI) study. Plasma Aβ42/Aβ40 was measured with ABtest-MS and compared to 18F-Florbetaben PET as the reference standard (cutoff for early amyloid deposition of 13.5 centiloids). Cross-validation was performed in an independent DPUK-Korean cohort. Additionally, associations of plasma Aβ42/Aβ40 with episodic memory performance and brain atrophy were assessed. Results: The FACEHBI cohort at baseline included 200 healthy individuals with subjective cognitive decline (SCD), of which 36 (18%) were Aβ-PET positive. Plasma Aβ42/Aβ40 levels were significantly lower in Aβ-PET positive individuals (median [interquartile range, IQR], 0.215 [0.203–0.236]) versus Aβ-PET negative subjects (median [IQR], 0.261 [0.244–0.279]) (P <.001). Plasma Aβ42/Aβ40 was significantly correlated with Aβ-PET levels (rho = −0.390; P <.001) and identified Aβ-PET status with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% confidence interval [CI], 0.80–0.93). A cutoff for the Aβ42/Aβ40 ratio of 0.241 (maximum Youden index) yielded a sensitivity of 86.1% and a specificity of 80.5%. These findings were cross-validated in an independent DPUK-Korean cohort (AUC 0.86 [95% CI 0.77–0.95]). Lower plasma Aβ42/Aβ40 ratio was associated with worse episodic memory performance and increased brain atrophy. Plasma Aβ42/Aβ40 at baseline predicted clinical conversion to mild cognitive impairment and longitudinal changes in amyloid deposition and brain atrophy at 2-year follow-up. Conclusions: This study suggests that plasma Aβ42/Aβ40, as determined by this MS-based assay, has potential value as an accurate and cost-effective tool to identify individuals in the earliest stages of AD, supporting its implementation in clinical trials, preventative strategies and clinical practice. [ABSTRACT FROM AUTHOR]

Background: The standard Centiloid (CL) method was proposed to harmonize and quantify global 18F-labeled amyloid beta (Aβ) PET ligands using MRI as an anatomical reference. However, there is need for harmonizing and quantifying regional Aβ uptakes between ligands using CT as an anatomical reference. In the present study, we developed and validated a CT-based regional direct comparison of 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) Centiloid (rdcCL). Methods: For development of MRI-based or CT-based rdcCLs, the cohort consisted of 63 subjects (20 young controls (YC) and 18 old controls (OC), and 25 participants with Alzheimer's disease dementia (ADD)). We performed a direct comparison of the FMM-FBB rdcCL method using MRI and CT images to define a common target region and the six regional VOIs of frontal, temporal, parietal, posterior cingulate, occipital, and striatal regions. Global and regional rdcCL scales were compared between MRI-based and CT-based methods. For clinical validation, the cohort consisted of 2245 subjects (627 CN, 933 MCI, and 685 ADD). Results: Both MRI-based and CT-based rdcCL scales showed that FMM and FBB were highly correlated with each other, globally and regionally (R2 = 0.96~0.99). Both FMM and FBB showed that CT-based rdcCL scales were highly correlated with MRI-based rdcCL scales (R2 = 0.97~0.99). Regarding the absolute difference of rdcCLs between FMM and FBB, the CT-based method was not different from the MRI-based method, globally or regionally (p value = 0.07~0.95). In our clinical validation study, the global negative group showed that the regional positive subgroup had worse neuropsychological performance than the regional negative subgroup (p < 0.05). The global positive group also showed that the striatal positive subgroup had worse neuropsychological performance than the striatal negative subgroup (p < 0.05). Conclusions: Our findings suggest that it is feasible to convert regional FMM or FBB rdcSUVR values into rdcCL scales without additional MRI scans. This allows a more easily accessible method for researchers that can be applicable to a variety of different conditions. [ABSTRACT FROM AUTHOR]

Synergistic effects of amyloid deposition and cerebral small vessel disease (CSVD) on the systematic disruption of large-scale brain anatomical organization are not well known. We investigated the brain structural covariance network (SCN) in 245 cognitively impaired older adults with the information of amyloid deposition and CSVD represented by white matter hyperintensities (WMH). We stratified the participants into 4 groups based on amyloid burden (A+/A -) and WMH severity (W+/W-). Using source-based morphometry analysis, we selected 13 independent components (ICs) in functional brain networks. SCNs between ICs were defined using Pearson correlations between individual weights; SCNs of the A+W+ group were compared with those of other groups using Fisher's r-to-z transformation. Our results revealed that SCN characteristics related to amyloid burden with CSVD could be represented by decreased intra- and increased cortico-subcortical inter-network connectivity in the salience (SN) and default mode networks (DMN), decreased cortico-subcortical internetwork connectivity in the central executive network (CEN), and altered internetwork connectivity among DMN-SN-CEN. Amyloid deposition and CSVD maybe associated with altered connectivity in structural networks in the brain and should be considered when assessing network disruption. [ABSTRACT FROM AUTHOR]

The clinical outcomes of patients with amyloid beta-positive (Aβ+) mild cognitive impairment (MCI) are heterogeneous. We therefore developed prediction models for distinguishable cognitive trajectories in Aβ+ participants with MCI. We included 238 Aβ+ participants with MCI from the Alzheimer's Disease Neuroimaging Initiative to develop a group-based trajectory model and 63 Aβ+ participants with MCI from the Samsung Medical Center for external validation. Three distinguishable classes, slow decliners (18.5%), intermediate decliners (42.9%), and fast decliners (38.7%), were identified. Intermediate decliners were associated with older age, higher AV45 standardized uptake value ratios (SUVR) and lower fluorodeoxyglucose (FDG) SUVR than slow decliners. Fast decliners were associated with older age, presence of APOE ε4 , higher AV45 SUVR and lower FDG SUVR than slow decliners. Prediction models of cognitive decline showed good discrimination and calibration capabilities in the development and validation data sets. Our analysis yields novel insights into the cognitive trajectories of Aβ+ patients with MCI, which will facilitate their effective stratification in Aβ-targeted clinical trials. [ABSTRACT FROM AUTHOR]

Background and purpose: Previous studies have developed several cognitive composites in preclinical Alzheimer disease (AD). However, more sensitive measures to track cognitive changes and therapeutic efficacy in preclinical AD are needed considering the diverse sociocultural and linguistic backgrounds. This study developed a composite score that can sensitively detect the amyloid‐β (Aβ)‐related cognitive trajectory of preclinical AD using Korean data. Methods: A total of 196 cognitively normal participants who underwent amyloid positron emission tomography were followed‐up with neuropsychological assessments. We developed the Longitudinal Amyloid Cognitive Composite in Preclinical AD (LACPA) using the linear mixed‐effects model (LMM) and z scores. The LMM was also used to investigate the longitudinal sensitivity of the LACPA and the association between time‐varying brain atrophy and the LACPA. Results: Considering the group‐time interaction effects of each subtest, the Seoul Verbal Learning Test‐Elderly version immediate recall/delayed recall/recognition, the Korean Trail Making Test B Time, and the Korean Mini‐Mental State Examination were selected as components of the LACPA. The LACPA exhibited a significant group‐time interaction effect between the Aβ+ and Aβ− groups (t = −3.288, p = 0.001). Associations between time‐varying LACPA and brain atrophy were found in the bilateral medial temporal, right lateral parietal, and right lateral frontal regions, and hippocampal volume. Conclusions: The LACPA may contribute to reduction in time and financial burden when monitoring Aβ‐related cognitive decline and therapeutic efficacy of the disease‐modifying agents specifically targeting Aβ in secondary prevention trials. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) and normal pressure hydrocephalus (NPH) commonly coexist.Objective: We aimed to characterize an overlapping syndrome of AD and NPH that presents with gait disturbance, ventriculomegaly on magnetic resonance imaging, and significant amyloid deposition on positron emission tomography (PET).Methods: Of 114 patients who underwent cerebrospinal fluid (CSF) drainage for a possible diagnosis of NPH between 2015 and 2020 in Samsung Medical Center, we identified 24 patients (21.1%) with the NPH patients with amyloid deposition on PET, which we referred to as hydrocephalic AD in this study. We compared their clinical and imaging findings with those of 123 typical AD without hydrocephalic signs/symptoms. We also investigated the frequency and potential predictors of the tap test response in hydrocephalic AD.Results: Evans' index was 0.36±0.03, and a disproportionately enlarged subarachnoid space was present in 54.2% of the hydrocephalic AD patients. The mean age (75.2±7.3 years) and the APOE4 frequency (68.2%) did not differ from those of AD controls. However, the hydrocephalic AD patients showed better memory and language performance, and a thinner cingulate cortex. About 42% of the hydrocephalic AD patients responded to the tap test, of whom seven underwent shunt surgery. Cognition did not improve, whereas gait improved after shunt surgery in all.Conclusion: Hydrocephalic AD has different neuropsychological and imaging characteristics from typical AD. Future studies are warranted to further investigate the effect of CSF removal on their clinical course and to elucidate the pathophysiological interaction between amyloid and NPH. [ABSTRACT FROM AUTHOR]

Purpose: In this study, we used machine learning to develop a new method derived from a ligand-independent amyloid (Aβ) positron emission tomography (PET) classifier to harmonise different Aβ ligands. Methods: We obtained 107 paired 18F-florbetaben (FBB) and 18F-flutemetamol (FMM) PET images at the Samsung Medical Centre. To apply the method to FMM ligand, we transferred the previously developed FBB PET classifier to test similar features from the FMM PET images for application to FMM, which in turn developed a ligand-independent Aβ PET classifier. We explored the concordance rates of our classifier in detecting cortical and striatal Aβ positivity. We investigated the correlation of machine learning-based cortical tracer uptake (ML-CTU) values quantified by the classifier between FBB and FMM. Results: This classifier achieved high classification accuracy (area under the curve = 0.958) even with different Aβ PET ligands. In addition, the concordance rate of FBB and FMM using the classifier (87.5%) was good to excellent, which seemed to be higher than that in visual assessment (82.7%) and lower than that in standardised uptake value ratio cut-off categorisation (93.3%). FBB and FMM ML-CTU values were highly correlated with each other (R = 0.903). Conclusion: Our findings suggested that our novel classifier may harmonise FBB and FMM ligands in the clinical setting which in turn facilitate the biomarker-guided diagnosis and trials of anti-Aβ treatment in the research field. [ABSTRACT FROM AUTHOR]

Background: We assessed the feasibility of plasma Aβ42/Aβ40 determined using a novel liquid chromatography-mass spectrometry method (LC-MS) as a useful biomarker of PET status in a Korean cohort from the DPUK Study. Methods: A total of 580 participants belonging to six groups, Alzheimer's disease dementia (ADD, n = 134), amnestic mild cognitive impairment (aMCI, n = 212), old controls (OC, n = 149), young controls (YC, n = 15), subcortical vascular cognitive impairment (SVCI, n = 58), and cerebral amyloid angiopathy (CAA, n = 12), were included in this study. Plasma Aβ40 and Aβ42 were quantitated using a new antibody-free, LC-MS, which drastically reduced the sample preparation time and cost. We performed receiver operating characteristic (ROC) analysis to develop the cutoff of Aβ42/Aβ40 and investigated its performance predicting centiloid-based PET positivity (PET+). Results: Plasma Aβ42/Aβ40 were lower for PET+ individuals in ADD, aMCI, OC, and SVCI (p < 0.001), but not in CAA (p = 0.133). In the group of YC, OC, aMCI, and ADD groups, plasma Aβ42/Aβ40 predicted PET+ with an area under the ROC curve (AUC) of 0.814 at a cutoff of 0.2576. When adding age, APOE4, and diagnosis, the AUC significantly improved to 0.912. Conclusion: Plasma Aβ42/Aβ40, as measured by this novel LC-MS method, showed good discriminating performance based on PET positivity. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence suggests that BMI1 confers protective effects against Alzheimer's disease (AD). However, the mechanism remains elusive. Based on recent pathophysiological evidence, we sought for the first time to identify genetic variants in BMI1 as associated with AD biomarkers, including amyloid-β. Methods: We used genetic, longitudinal cognition, and cerebrospinal fluid (CSF) biomarker data from participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (N = 1565). First, we performed a gene-based association analysis of common single nucleotide polymorphisms (SNPs) (minor allele frequency (MAF) > 5%) located within ± 20 kb of the gene boundary of BMI1, an optimal width for including potential regulatory SNPs in the 5′ and 3′ untranslated regions (UTR) of BMI1, with CSF Aβ1-42 levels. Second, we performed cross-sectional and longitudinal association analyses of SNPs in BMI1 with cognitive performance using linear and mixed-effects models. We replicated association of SNPs in BMI1 with cognitive performance in an independent cohort (N=1084), Religious Orders Study and the Rush Memory and Aging Project (ROS/MAP). Results: Gene-based genetic association analysis showed that BMI1 was significantly associated with CSF Aβ1-42 levels after adjusting for multiple testing using permutation (permutation-corrected p value=0.005). rs17415557 in BMI1 showed the most significant association with CSF Aβ1-42 levels. Participants with minor alleles of rs17415557 have increased CSF Aβ1-42 levels compared to those with no minor alleles. Further analysis identified and replicated the minor allele of rs17415557 as being significantly associated with slower cognitive decline rates in AD. Conclusions: Our findings provide fundamental evidence that BMI1 rs17415557 may serve as a protective mechanism related to AD pathogenesis, which supports the results of previous studies linking BMI1 to protection against AD. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence suggests that BMI1 confers protective effects against Alzheimer's disease (AD). However, the mechanism remains elusive. Based on recent pathophysiological evidence, we sought for the first time to identify genetic variants in BMI1 as associated with AD biomarkers, including amyloid-β. Methods: We used genetic, longitudinal cognition, and cerebrospinal fluid (CSF) biomarker data from participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (N = 1565). First, we performed a gene-based association analysis of common single nucleotide polymorphisms (SNPs) (minor allele frequency (MAF) > 5%) located within ± 20 kb of the gene boundary of BMI1, an optimal width for including potential regulatory SNPs in the 5′ and 3′ untranslated regions (UTR) of BMI1, with CSF Aβ1-42 levels. Second, we performed cross-sectional and longitudinal association analyses of SNPs in BMI1 with cognitive performance using linear and mixed-effects models. We replicated association of SNPs in BMI1 with cognitive performance in an independent cohort (N=1084), Religious Orders Study and the Rush Memory and Aging Project (ROS/MAP). Results: Gene-based genetic association analysis showed that BMI1 was significantly associated with CSF Aβ1-42 levels after adjusting for multiple testing using permutation (permutation-corrected p value=0.005). rs17415557 in BMI1 showed the most significant association with CSF Aβ1-42 levels. Participants with minor alleles of rs17415557 have increased CSF Aβ1-42 levels compared to those with no minor alleles. Further analysis identified and replicated the minor allele of rs17415557 as being significantly associated with slower cognitive decline rates in AD. Conclusions: Our findings provide fundamental evidence that BMI1 rs17415557 may serve as a protective mechanism related to AD pathogenesis, which supports the results of previous studies linking BMI1 to protection against AD. [ABSTRACT FROM AUTHOR]

Background: Accumulating evidence suggests that BMI1 confers protective effects against Alzheimer's disease (AD). However, the mechanism remains elusive. Based on recent pathophysiological evidence, we sought for the first time to identify genetic variants in BMI1 as associated with AD biomarkers, including amyloid-β. Methods: We used genetic, longitudinal cognition, and cerebrospinal fluid (CSF) biomarker data from participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (N = 1565). First, we performed a gene-based association analysis of common single nucleotide polymorphisms (SNPs) (minor allele frequency (MAF) > 5%) located within ± 20 kb of the gene boundary of BMI1, an optimal width for including potential regulatory SNPs in the 5′ and 3′ untranslated regions (UTR) of BMI1, with CSF Aβ1-42 levels. Second, we performed cross-sectional and longitudinal association analyses of SNPs in BMI1 with cognitive performance using linear and mixed-effects models. We replicated association of SNPs in BMI1 with cognitive performance in an independent cohort (N=1084), Religious Orders Study and the Rush Memory and Aging Project (ROS/MAP). Results: Gene-based genetic association analysis showed that BMI1 was significantly associated with CSF Aβ1-42 levels after adjusting for multiple testing using permutation (permutation-corrected p value=0.005). rs17415557 in BMI1 showed the most significant association with CSF Aβ1-42 levels. Participants with minor alleles of rs17415557 have increased CSF Aβ1-42 levels compared to those with no minor alleles. Further analysis identified and replicated the minor allele of rs17415557 as being significantly associated with slower cognitive decline rates in AD. Conclusions: Our findings provide fundamental evidence that BMI1 rs17415557 may serve as a protective mechanism related to AD pathogenesis, which supports the results of previous studies linking BMI1 to protection against AD. [ABSTRACT FROM AUTHOR]

Microglial activation is a central player in the pathophysiology of Alzheimer's disease (AD). The soluble fragment of triggering receptor expressed on myeloid cells 2 (sTREM2) can serve as a marker for microglial activation and has been shown to be overexpressed in AD. However, the relationship of sTREM2 with other AD biomarkers has not been extensively studied. We investigated the relationship between cerebrospinal fluid (CSF) sTREM2 and other AD biomarkers and examined the correlation of plasma sTREM2 with CSF sTREM2 in a cohort of individuals with AD and without AD. Participants were consecutively recruited from Asan Medical Center from 2018 to 2020. Subjects were stratified by their amyloid positivity and clinical status. Along with other AD biomarkers, sTREM2 level was measured in the plasma as well as CSF. In 101 patients with either amyloid-positive or negative status, CSF sTREM2 was closely associated with CSF T-tau and P-tau and not with Abeta42. CSF sTREM2 levels were found to be strongly correlated with CSF neurofilament light chain. The comparison of CSF and plasma sTREM2 levels tended to have an inverse correlation. Plasma sTREM2 and P-tau levels were oppositely influenced by age. Our results suggest that neuroinflammation may be closely associated with tau-induced neurodegeneration. [ABSTRACT FROM AUTHOR]

Predicting amyloid positivity in patients with mild cognitive impairment (MCI) is crucial. In the present study, we predicted amyloid positivity with structural MRI using a radiomics approach. From MR images (including T1, T2 FLAIR, and DTI sequences) of 440 MCI patients, we extracted radiomics features composed of histogram and texture features. These features were used alone or in combination with baseline non-imaging predictors such as age, sex, and ApoE genotype to predict amyloid positivity. We used a regularized regression method for feature selection and prediction. The performance of the baseline non-imaging model was at a fair level (AUC = 0.71). Among single MR-sequence models, T1 and T2 FLAIR radiomics models also showed fair performances (AUC for test = 0.71–0.74, AUC for validation = 0.68–0.70) in predicting amyloid positivity. When T1 and T2 FLAIR radiomics features were combined, the AUC for test was 0.75 and AUC for validation was 0.72 (p vs. baseline model < 0.001). The model performed best when baseline features were combined with a T1 and T2 FLAIR radiomics model (AUC for test = 0.79, AUC for validation = 0.76), which was significantly better than those of the baseline model (p < 0.001) and the T1 + T2 FLAIR radiomics model (p < 0.001). In conclusion, radiomics features showed predictive value for amyloid positivity. It can be used in combination with other predictive features and possibly improve the prediction performance. [ABSTRACT FROM AUTHOR]

Background: Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer's disease. However, Aβ evaluation through Aβ positron emission tomography (PET) is limited due to high cost and safety issues.Objective: We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers.Methods: We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers).Results: Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity.Conclusion: Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to compare the diagnostic accuracy of antemortem 11C‐Pittsburgh compound B (PIB) and 18F‐fluorodeoxyglucose (FDG) positron emission tomography (PET) versus autopsy diagnosis in a heterogenous sample of patients. Methods: One hundred one participants underwent PIB and FDG PET during life and neuropathological assessment. PET scans were visually interpreted by 3 raters blinded to clinical information. PIB PET was rated as positive or negative for cortical retention, whereas FDG scans were read as showing an Alzheimer disease (AD) or non‐AD pattern. Neuropathological diagnoses were assigned using research criteria. Majority visual reads were compared to intermediate–high AD neuropathological change (ADNC). Results: One hundred one participants were included (mean age = 67.2 years, 41 females, Mini‐Mental State Examination = 21.9, PET‐to‐autopsy interval = 4.4 years). At autopsy, 32 patients showed primary AD, 56 showed non‐AD neuropathology (primarily frontotemporal lobar degeneration [FTLD]), and 13 showed mixed AD/FTLD pathology. PIB showed higher sensitivity than FDG for detecting intermediate–high ADNC (96%, 95% confidence interval [CI] = 89–100% vs 80%, 95% CI = 68–92%, p = 0.02), but equivalent specificity (86%, 95% CI = 76–95% vs 84%, 95% CI = 74–93%, p = 0.80). In patients with congruent PIB and FDG reads (77/101), combined sensitivity was 97% (95% CI = 92–100%) and specificity was 98% (95% CI = 93–100%). Nine of 24 patients with incongruent reads were found to have co‐occurrence of AD and non‐AD pathologies. Interpretation: In our sample enriched for younger onset cognitive impairment, PIB‐PET had higher sensitivity than FDG‐PET for intermediate–high ADNC, with similar specificity. When both modalities are congruent, sensitivity and specificity approach 100%, whereas mixed pathology should be considered when PIB and FDG are incongruent. ANN NEUROL 2021;89:389–401 [ABSTRACT FROM AUTHOR]

Background: As Alzheimer's disease (AD) and cerebral small vessel disease (CSVD) commonly coexist, the interaction between two has been of the considerable interest.Objective: We determined whether the association of Aβ and tau with cognitive decline differs by the presence of significant CSVD.Methods: We included 60 subcortical vascular cognitive impairment (SVCI) from Samsung Medical Center and 82 Alzheimer's disease-related cognitive impairment (ADCI) from ADNI, who underwent Aβ (florbetaben or florbetapir) and tau (flortaucipir, FTP) PET imaging. They were retrospectively assessed for 5.0±3.9 and 5.6±1.9 years with Clinical Dementia Rating-sum of boxes (CDR-SB)/Mini-Mental State Examination (MMSE). Mixed effects models were used to investigate the interaction between Aβ/tau and group on CDR-SB/MMSE changes.Results: The frequency of Aβ positivity (45% versus 54.9%, p = 0.556) and mean global FTP SUVR (1.17±0.21 versus 1.16±0.17, p = 0.702) were not different between the two groups. We found a significant interaction effect of Aβ positivity and SVCI group on CDR-SB increase/MMSE decrease (p = 0.013/p < 0.001), and a significant interaction effect of global FTP uptake and SVCI group on CDR-SB increase/MMSE decrease (p < 0.001 and p = 0.030). Finally, the interaction effects of regional tau and group were prominent in the Braak III/IV (p = 0.001) and V/VI (p = 0.003) not in Braak I/II region (p = 0.398).Conclusion: The association between Aβ/tau and cognitive decline is stronger in SVCI than in ADCI. Therefore, our findings suggested that Aβ positivity or tau burden (particularly in the Braak III/IV or V/VI regions) and CSVD might synergistically affect cognitive decline. [ABSTRACT FROM AUTHOR]

Recently, the focus of Alzheimer's disease (AD) research has shifted from the clinical stage to the preclinical stage. We, therefore, aimed to develop a cognitive composite score that can detect the subtle cognitive differences between the amyloid positive (Aβ+) and negative (Aβ−) status in cognitively normal (CN) participants. A total of 423 CN participants with Aβ positron emission tomography images were recruited. The multiple-indicators multiple-causes model found the latent mean difference between the Aβ+ and Aβ− groups in the domains of verbal memory, visual memory, and executive functions. The multivariate analysis of covariance (MANCOVA) showed that the Aβ+ group performed worse in tests related to the verbal and visual delayed recall, semantic verbal fluency, and inhibition of cognitive inference within the three cognitive domains. The Preclinical Amyloid Sensitive Composite (PASC) model we developed using the result of MANCOVA and the MMSE presented a good fit with the data. The accuracy of the PASC score when applied with age, sex, education, and APOE ε4 for distinguishing between Aβ+ and Aβ− was adequate (AUC = 0.764; 95% CI = 0.667–0.860) in the external validation set (N = 179). We conclude that the PASC can eventually contribute to facilitating more prevention trials in preclinical AD. [ABSTRACT FROM AUTHOR]

Background: Cerebrospinal fluid (CSF) amyloid-β1-42 (Aβ1-42), total tau protein (t-Tau), and phosphorylated Tau (p-Tau) are ATN biomarkers for Alzheimer's disease (AD) and reflect pathogenic changes in the brain. CSF biomarkers of AD are considered for inclusion in the diagnostic criteria for research and clinical purposes to reduce the uncertainty of clinical diagnosis and to distinguish among AD stages.Objective: This study aims to compare two commercially available analytical platforms with respect to accuracy and the potential for early diagnosis of AD.Methods: A total of 211 CSF samples from healthy control (HC) and AD subjects were analyzed using two analytical platforms, INNOTEST ELISA and INNOBIA AlzBio3 xMAP kits. The accuracy of diagnosis and AUC values distinguishing study groups were compared between the two analytical platforms.Results: The absolute values for Aβ1-42, t-Tau, and p-Tau181 levels differed between the two platforms. The Aβ1-42 levels decreased, while t-Tau and p-Tau levels increased according to the AD stages. The AUC of Aβ1-42 and t-Tau, which distinguish the early stages of AD (preclinical and prodromal AD), were similar between the two platforms, whereas there were significant differences in p-Tau AUC values. CSF p-Tau using the INNOBIA was highly accurate for distinguishing both preclinical AD (AUC = 0.826, cut-off score≥38.89) and prodromal AD (AUC = 0.862, cut-off score≥41.88) from HC.Conclusion: The accuracy of CSF p-Tau levels in the preclinical and prodromal AD is higher for the INNOBIA than the INNOTEST, and the early stage AD can be accurately distinguished from HC. [ABSTRACT FROM AUTHOR]

Background: Subjective memory complaints (SMC) are a risk factor for Alzheimer's disease.Objective: We aimed to explore the association between SMC and regional amyloid-β (Aβ) deposition in mild cognitive impairment (MCI).Methods: Sixty-eight individuals with MCI were recruited. [18F]Florbetaben PET scans were performed. T1-weighted 3D volumes were also acquired for co-registration with PET and for defining the regions of interest (ROI). Two step exploratory partial correlation analyses between SMC and Aβ deposition were performed with covariates of age, sex, education, and depression. Furthermore, for the priori ROI that had the most significant partial correlation, we investigated the correlation between the SMC and regional Aβ burden using a multiple linear regression model controlling for depression, age, sex, and education.Results: Significant positive correlations between the SMC and Aβ burden was found in the medial temporal ROI (first step) and in the left parahippocampus ROI (second step). In the priori left parahippocampus, we found significant correlation between the SMC and Aβ burden (R2 = 0.473, p = 0.014).Conclusions: Our study suggested that the SMC was associated with amyloid accumulation, especially in the left parahippocampus, in individuals with MCI. [ABSTRACT FROM AUTHOR]

Purpose: We investigated the frequency and clinical significance of amyloid β (Aβ) positivity on PET in patients with cerebral amyloid angiopathy (CAA). Methods: We recruited 65 patients who met the modified Boston criteria for probable CAA. All underwent amyloid PET, MRI, APOE genotyping and neuropsychological testing, and we obtained information on MRI markers of CAA and ischemic cerebral small-vessel disease (CSVD). We investigated the CAA/ischemic CSVD burden and APOE genotypes in relation to Aβ positivity and investigated the effect of Aβ positivity on longitudinal cognitive decline. Results: Among the 65 CAA patients, 43 (66.2%) showed Aβ PET positivity (Aβ+). Patients with Aβ+ CAA had more lobar microbleeds (median 9, interquartile range 2–41, vs. 3, 2–8; P = 0.045) and a higher frequency of cortical superficial siderosis (34.9% vs. 9.1%; P = 0.025), while patients with Aβ− CAA had more lacunes (1, 0–2, vs. 0, 0–1; P = 0.029) and a higher frequency of severe white matter hyperintensities (45.5% vs. 20.9%; P = 0.040). The frequency of ε4 carriers was higher in Aβ+ patients (57.1%) than in Aβ− patients (18.2%; P = 0.003), while the frequency of ε2 carriers did not differ between the two groups. Finally, Aβ positivity was associated with faster decline in multiple cognitive domains including language (P < 0.001), visuospatial function (P < 0.001), and verbal memory (P < 0.001) in linear mixed effects models. Conclusion: Our findings suggest that a significant proportion of patients with probable CAA in a memory clinic are Aβ− on PET. Aβ positivity in CAA patients is associated with a distinct pattern of CSVD biomarker expression, and a worse cognitive trajectory. Aβ positivity has clinical relevance in CAA and might represent either advanced CAA or additional Alzheimer's disease neuropathological changes. [ABSTRACT FROM AUTHOR]

Abstract Background and purpose To investigate small vessel abnormalities in patients with cognitive impairment, we compared retinal microvascular alterations between patients with cognitive impairment related to Alzheimer's disease (ADCI) and those with subcortical vascular cognitive impairment (SVCI). Methods We prospectively recruited 29 amyloid-positive ADCI patients, 28 amyloid-negative SVCI patients that were confirmed by 11C-PiB-PET scan and 34 individuals with normal cognition (NC). The three groups were compared in terms of retinal vascular variables (retinal fractal dimension, vascular caliber, tortuosity and branching angle) by using a semi-automated, computer-assisted analysis of digital fundus photographs. We also investigated the relationship between retinal variables and white matter hyperintensities (WMH) on MRI. Results Compared to NC individuals, the SVCI patients had smaller total and arteriolar fractal dimensions, whereas there was no significant difference of fractal dimension between ADCI and NC. Other retinal variables did not differ among the three groups. A significant correlation existed between fractal dimension and WMH volume. Conclusions Retinal microvascular alterations, especially retinal fractal dimension, may be useful markers that reflect cerebral microvascular changes in patients with SVCI as opposed to ADCI, who had no definite difference in retinal variables compared to the NC group. Highlights • The SVCI group had smaller retinal fractal dimensions compared to the NC group. • There was no significant difference of retinal variables between ADCI and NC. • The arteriolar fractal dimension was inversely correlated with WMH volume. • The fractal dimension was associated with language and visuospatial functions. [ABSTRACT FROM AUTHOR]

Late life depression is related to pathologic burdens, such as cerebral small vascular disease (CSVD) and amyloid, which are associated with brain network changes and cortical thinning. To examine the associations of various CSVD imaging markers, amyloid, and network changes with depression in cognitively impaired patients, we prospectively recruited 228 cognitively impaired patients having various degrees of amyloid and CSVD who underwent diffuse tensor image and PiB PET. Greater CSVD burden was associated with greater Geriatric Depression Scale (GDS) (white matter hyperintensities, WMH: p = 0.025, lacunes: p < 0.001) but not with amyloid (p = 0.095), and cortical thinning (p = 0.630) was not associated with greater GDS. The changes in white matter networks were related to GDS with decreasing integration (global efficiency: p < 0.001) and increasing segregation (clustering coefficient: p = 0.009). The network changes mediated the relationships of WMH and lacunes with GDS. Our findings provide insight to better understand how CSVD burdens contribute to depression in cognitively impaired patients having varying degrees of amyloid and vascular burdens. [ABSTRACT FROM AUTHOR]

Amyloid positron emission tomography ([18F] florbetaben (FBB) PET) can be used to determine concomitant Alzheimer's disease (AD) in idiopathic normal pressure hydrocephalus (iNPH) patients. FBB PET scans and the tap test were performed in 31 patients with clinically suspected iNPH, and amyloid positive (iNPH/FBB+) and negative (iNPH/FBB−) groups were compared with respect to clinical characteristics. We evaluated prognostic value of FBB PET scans by analyzing the response to the tap test using a linear mixed model. We also performed a multivariable regression analysis to investigate whether amyloid PET positivity can predict the positive tap test response independent of other AD biomarkers. The results showed that the iNPH/FBB+ group (7/31, 22.6%) had a higher percentage of APOE4 carriers, lower Aβ42, higher CSF t-tau, and p-tau/Aβ42 ratio than the iNPH/FBB− group (24/31, 77.4%), while the two groups did not differ in imaging characteristics. The iNPH/FBB− group had a higher percentage of tap responders and showed a greater improvement in gait scores after the tap test than the iNPH/FBB+ group (group-tap test effect interaction, p = 0.035). A multivariable logistic regression analysis showed that amyloid positivity on PET scans (OR 0.03, p = 0.029) and CSF p-tau (OR 0.87, p = 0.044) were independently associated with the positive tap test response. Among 21 tap responders in the iNPH/FBB− group, 14 patients received shunt surgery and 12/14 (85.7%) patients showed symptom improvement. Our findings suggest that amyloid PET scans can help determine which iNPH patients will benefit from shunt surgery by discriminating concomitant AD. [ABSTRACT FROM AUTHOR]

We investigated the amyloid and vascular burden in Pittsburgh compound B (PiB)–negative subcortical vascular mild cognitive impairment (svMCI) and PiB-negative subcortical ischemic vascular dementia (SIVD) to elucidate the potential roles of amyloid deposition and small vessel disease (SVD). Thirty-eight svMCI patients and 42 SIVD patients were enrolled. The regional PiB uptake values and SVD markers were obtained and compared between groups. Additionally, correlations among amyloid burden, SVD, and cognition were made. Patients with PiB-negative SIVD showed more amyloid deposition than those with PiB-negative svMCI, particularly in the cuneus, lingual gyrus, supramarginal, and angular gyri. Despite subthreshold levels for amyloid deposition, our findings showed a marked regional difference in amyloid uptake between svMCI and SIVD, particularly in posteriorly located brain areas. However, lacune, a proxy for vascular burden, showed a broader association with cognition and had more impacts on developing dementia than amyloid burden. The topographical pattern of amyloid deposition and its impact on clinical status in pure subcortical vascular cognitive impairment were different from those in Alzheimer's disease. [ABSTRACT FROM AUTHOR]

There is growing evidence that the human brain is a large scale complex network. The structural network is reported to be disrupted in cognitively impaired patients. However, there have been few studies evaluating the effects of amyloid and small vessel disease (SVD) markers, the common causes of cognitive impairment, on structural networks. Thus, we evaluated the association between amyloid and SVD burdens and structural networks using diffusion tensor imaging (DTI). Furthermore, we determined if network parameters predict cognitive impairments. Graph theoretical analysis was applied to DTI data from 232 cognitively impaired patients with varying degrees of amyloid and SVD burdens. All patients underwent Pittsburgh compound-B (PiB) PET to detect amyloid burden, MRI to detect markers of SVD, including the volume of white matter hyperintensities and the number of lacunes, and detailed neuropsychological testing. The whole-brain network was assessed by network parameters of integration (shortest path length, global efficiency) and segregation (clustering coefficient, transitivity, modularity). PiB retention ratio was not associated with any white matter network parameters. Greater white matter hyperintensity volumes or lacunae numbers were significantly associated with decreased network integration (increased shortest path length, decreased global efficiency) and increased network segregation (increased clustering coefficient, increased transitivity, increased modularity). Decreased network integration or increased network segregation were associated with poor performances in attention, language, visuospatial, memory, and frontal-executive functions. Our results suggest that SVD alters white matter network integration and segregation, which further predicts cognitive dysfunction. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Abstract: Neuropsychiatric symptoms (NPS) affect the quality of life of patients with dementia and increase the burden on caregivers. We aimed to evaluate how small vessel disease (SVD) such as lacunae or white matter hyperintensities (WMH), and amyloid burden affect NPS. We recruited 127 patients with subcortical vascular cognitive impairment who were assessed with brain magnetic resonance imaging, Pittsburgh compound-B (PiB) positron emission tomography and the neuropsychiatric inventory (NPI). To explore the association between lacunae, WMH, or PiB retention ratio and NPS, we performed multivariate regression analysis after controlling for possible confounders. Each additional lacuna, especially in the frontal region, was associated with higher odds of depression, apathy, aberrant motor behavior, nighttime behavior, appetite changes, and higher score of total NPI; larger WMH volume, especially in the frontal region, was associated with higher odds of apathy and higher score of total NPI. Furthermore, for the effects of lacunae or WMH on total NPI score we set Clinical Dementia Rating Sum of Boxes as the mediator. Greater PiB retention ratio was associated with higher odds of delusions and irritability. The SVD and amyloid pathologies did not show interactive effects on NPS. Our findings suggested that SVD and amyloid burden independently affected specific NPS. [Copyright &y& Elsevier]