Association of moderate alcohol intake with in vivo amyloid-beta deposition in human brain: A cross-sectional study.

BACKGROUND: An emerging body of literature has indicated that moderate alcohol intake may be protective against Alzheimer disease (AD) dementia. However, little information is available regarding whether moderate alcohol intake is related to reductions in amyloid-beta (Aß) deposition, or is protective via amyloid-independent mechanisms in the living human brain. Here we examined the associations of moderate alcohol intake with in vivo AD pathologies, including cerebral Aß deposition, neurodegeneration of AD-signature regions, and cerebral white matter hyperintensities (WMHs) in the living human brain. METHODS AND FINDINGS: The present study was part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease (KBASE), an ongoing prospective cohort study that started in 2014. As of November 2016, 414 community-dwelling individuals with neither dementia nor alcohol-related disorders (280 cognitively normal [CN] individuals and 134 individuals with mild cognitive impairment [MCI]) between 56 and 90 years of age (mean age 70.9 years ± standard deviation 7.8; male, n [%] = 180 [43.5]) were recruited from 4 sites (i.e., 2 university hospitals and 2 public centers for dementia prevention and management) around Seoul, South Korea. All the participants underwent comprehensive clinical assessments comprising lifetime and current histories of alcohol intake and multimodal brain imaging, including [11C] Pittsburgh compound B positron emission tomography (PET), [18F] fluorodeoxyglucose (FDG) PET, and magnetic resonance imaging (MRI) scans. Lifetime and current alcohol intake were categorized as follows: no drinking, <1 standard drink (SD)/week, 1-13 SDs/week, and 14+ SDs/week. A moderate lifetime alcohol intake (1-13 SDs/week) was significantly associated with a lower Aß positivity rate compared to the no drinking group, even after controlling for potential confounders (odds ratio 0.341, 95% confidence interval 0.163-0.714, p = 0.004). In contrast, current alcohol intake was not associated with amyloid deposition. Additionally, alcohol intake was not related to neurodegeneration of AD-signature regions or cerebral WMH volume. The present study had some limitations in that it had a cross-sectional design and depended on retrospective recall for alcohol drinking history. CONCLUSIONS: In this study, we observed in middle- and old-aged individuals with neither dementia nor alcohol-related disorders that moderate lifetime alcohol intake was associated with lower cerebral Aß deposition compared to a lifetime history of not drinking. Moderate lifetime alcohol intake may have a beneficial influence on AD by reducing pathological amyloid deposition rather than amyloid-independent neurodegeneration or cerebrovascular injury.

Neuroticism, conscientiousness, and in vivo Alzheimer pathologies measured by amyloid PET and MRI.

AIM: It has been suggested that personality traits, particularly neuroticism and conscientiousness, are risk factors for Alzheimer's disease (AD) and related cognitive decline. However, the underlying pathological links between personality traits and AD-related cognitive impairments remain unclear. Thus, the present study investigated associations of neuroticism and conscientiousness with in vivo cerebral amyloid-beta (Aß) burden, AD-signature regional neurodegeneration, and white matter hyperintensities (WMH) in non-demented middle- and old-aged adults. METHODS: A total of 397 non-demented participants underwent comprehensive clinical and neuropsychological assessments, 11 C-labeled Pittsburgh Compound B positron emission tomography, and magnetic resonance imaging. Additionally, the NEO Five-Factor Inventory was administered to both the participants and their informants to measure neuroticism and conscientiousness. RESULTS: Neither neuroticism nor conscientiousness was associated with cerebral Aß deposition or WMH. In contrast, higher neuroticism and lower conscientiousness, reported by informants in particular, were significantly associated with reduced AD-signature region cortical thickness. In regards to the direct and indirect effect of each personality on AD-signature region cortical thickness, only the direct effects were found, whereas indirect effects via Aß deposition or WMH were not. CONCLUSION: The present findings suggest that amyloid-independent regional neurodegeneration might underlie relations of neuroticism and conscientiousness with AD.

Adaptive template generation for amyloid PET using a deep learning approach.

Accurate spatial normalization (SN) of amyloid positron emission tomography (PET) images for Alzheimer's disease assessment without coregistered anatomical magnetic resonance imaging (MRI) of the same individual is technically challenging. In this study, we applied deep neural networks to generate individually adaptive PET templates for robust and accurate SN of amyloid PET without using matched 3D MR images. Using 681 pairs of simultaneously acquired 11 C-PIB PET and T1-weighted 3D MRI scans of AD, MCI, and cognitively normal subjects, we trained and tested two deep neural networks [convolutional auto-encoder (CAE) and generative adversarial network (GAN)] that produce adaptive best PET templates. More specifically, the networks were trained using 685,100 pieces of augmented data generated by rotating 527 randomly selected datasets and validated using 154 datasets. The input to the supervised neural networks was the 3D PET volume in native space and the label was the spatially normalized 3D PET image using the transformation parameters obtained from MRI-based SN. The proposed deep learning approach significantly enhanced the quantitative accuracy of MRI-less amyloid PET assessment by reducing the SN error observed when an average amyloid PET template is used. Given an input image, the trained deep neural networks rapidly provide individually adaptive 3D PET templates without any discontinuity between the slices (in 0.02 s). As the proposed method does not require 3D MRI for the SN of PET images, it has great potential for use in routine analysis of amyloid PET images in clinical practice and research.

Development and Validation of the Rappel Indicé-24: Behavioral and Brain Morphological Evidence.

The primary goals of the present study were to develop and validate the Rappel Indicé 24 (RI-24), a shorter version of the original Rappel Indicé, which includes 48 items (RI-48), and to identify the specific brain regions that were correlated with scores on the RI-24. Using these clinical scales, the present study evaluated 91 elderly Korean participants who were classified into 3 groups: normal control (NC; n = 34), patients with mild cognitive impairment (MCI; n = 29), and patients with Alzheimer disease (AD; n = 28). Of the 91 participants, 77 also underwent magnetic resonance imaging scans. The RI-24 delayed cued recall (DCR) scores significantly differed among the NC, MCI, and AD groups. A receiver-operating characteristic curve analysis revealed that the RI-24 was very sensitive (89%) and specific (91%) for the detection of AD. Furthermore, although the time needed to administer the RI-24 was half that needed for the RI-48, the 24-item version showed a high correlation (r= .85 for the DCR score) with the 48-item version. In terms of brain morphological characteristics, voxel-based morphometry analyses revealed a significant positive correlation between DCR score and gray matter volume in the parahippocampal gyrus (r= .468), which plays a role in cued recall. Taken together, the present findings indicate that the RI-24 is a sensitive and reliable test for the detection of memory impairments in patients with MCI and AD despite its brief administration time.

Clinical Performance Evaluation of an Artificial Intelligence-Powered Amyloid Brain PET Quantification Method.

Purpose: This study assesses the clinical performance of BTXBrain-Amyloid, an artificial intelligence-powered software for quantifying amyloid uptake in brain PET images. Methods: 150 amyloid brain PET images were visually assessed by experts and categorized as negative and positive. Standardized uptake value ratio (SUVR) was calculated with cerebellum grey matter as the reference region, and receiver operating characteristic (ROC) and precision-recall (PR) analysis for BTXBrain-Amyloid were conducted. For comparison, same image processing and analysis was performed using Statistical Parametric Mapping (SPM) program. In addition, to evaluate the spatial normalization (SN) performance, mutual information (MI) between MRI template and spatially normalized PET images was calculated and SPM group analysis was conducted. Results: Both BTXBrain and SPM methods discriminated between negative and positive groups. However, BTXBrain exhibited lower SUVR standard deviation (0.06 and 0.21 for negative and positive, respectively) than SPM method (0.11 and 0.25). In ROC analysis, BTXBrain had an AUC of 0.979, compared to 0.959 for SPM, while PR curves showed an AUC of 0.983 for BTXBrain and 0.949 for SPM. At the optimal cut-off, the sensitivity and specificity were 0.983 and 0.921 for BTXBrain and 0.917 and 0.921 for SPM12, respectively. MI evaluation also favored BTXBrain (0.848 vs. 0.823), indicating improved SN. In SPM group analysis, BTXBrain exhibited higher sensitivity in detecting basal ganglia differences between negative and positive groups. Conclusion: BTXBrain-Amyloid outperformed SPM in clinical performance evaluation, also demonstrating superior SN and improved detection of deep brain differences. These results suggest the potential of BTXBrain-Amyloid as a valuable tool for clinical amyloid PET image evaluation.

Fast and Accurate Amyloid Brain PET Quantification Without MRI Using Deep Neural Networks.

This paper proposes a novel method for automatic quantification of amyloid PET using deep learning-based spatial normalization (SN) of PET images, which does not require MRI or CT images of the same patient. The accuracy of the method was evaluated for 3 different amyloid PET radiotracers compared with MRI-parcellation-based PET quantification using FreeSurfer. Methods: A deep neural network model used for the SN of amyloid PET images was trained using 994 multicenter amyloid PET images (367 18F-flutemetamol and 627 18F-florbetaben) and the corresponding 3-dimensional MR images of subjects who had Alzheimer disease or mild cognitive impairment or were cognitively normal. For comparison, PET SN was also conducted using version 12 of the Statistical Parametric Mapping program (SPM-based SN). The accuracy of deep learning-based and SPM-based SN and SUV ratio quantification relative to the FreeSurfer-based estimation in individual brain spaces was evaluated using 148 other amyloid PET images (64 18F-flutemetamol and 84 18F-florbetaben). Additional external validation was performed using an unseen independent external dataset (30 18F-flutemetamol, 67 18F-florbetaben, and 39 18F-florbetapir). Results: Quantification results using the proposed deep learning-based method showed stronger correlations with the FreeSurfer estimates than SPM-based SN using MRI did. For example, the slope, y-intercept, and R 2 values between SPM and FreeSurfer for the global cortex were 0.869, 0.113, and 0.946, respectively. In contrast, the slope, y-intercept, and R 2 values between the proposed deep learning-based method and FreeSurfer were 1.019, -0.016, and 0.986, respectively. The external validation study also demonstrated better performance for the proposed method without MR images than for SPM with MRI. In most brain regions, the proposed method outperformed SPM SN in terms of linear regression parameters and intraclass correlation coefficients. Conclusion: We evaluated a novel deep learning-based SN method that allows quantitative analysis of amyloid brain PET images without structural MRI. The quantification results using the proposed method showed a strong correlation with MRI-parcellation-based quantification using FreeSurfer for all clinical amyloid radiotracers. Therefore, the proposed method will be useful for investigating Alzheimer disease and related brain disorders using amyloid PET scans.

Erratum: A Comparison Between the Performances of Verbal and Nonverbal Fluency Tests in Discriminating Between Mild Cognitive Impairments and Alzheimer's Disease Patients and Their Brain Morphological Correlates.

[This corrects the article on p. 17 in vol. 21, PMID: 35154337.].

A Comparison Between the Performances of Verbal and Nonverbal Fluency Tests in Discriminating Between Mild Cognitive Impairments and Alzheimer's Disease Patients and Their Brain Morphological Correlates.

BACKGROUND AND PURPOSE: Verbal and nonverbal fluency tests are the conventional methods for examining executive function in the elderly population. However, differences in impairments result in fluency tests in patients with mild cognitive impairments (MCIs) and Alzheimer's disease (AD) and in neural correlates underlying the tests still necessitate concrete evidence. METHODS: We compared the test performances in 27 normal controls, 28 patients with MCI, and 20 with AD, and investigated morphological changes in association with the test performances using structural magnetic imaging. RESULTS: Patients with AD performed poorly across all the fluency tests, and a receiver operating characteristics curve analysis revealed that only category fluency test discriminated all the 3 groups. Association, category, and design fluency tests involved temporal and frontal regions, while letter fluency involved the cerebellum and caudate. CONCLUSIONS: Category fluency is a reliable measure for screening patients with AD and MCI, and this efficacy might be related to morphological correlates that underlie semantic and executive processing.

Impact of a multidomain lifestyle intervention on regional spontaneous brain activity.

In the SoUth Korean study to PrEvent cognitive impaiRment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN), we evaluated the impact of multidomain lifestyle intervention on regional homogeneity (ReHo) in resting-state functional brain magnetic resonance imaging (MRI) data. Of 152 participants aged 60-79 years without dementia assigned to either facility-based multidomain intervention (FMI), home-based MI, or controls, we analyzed 56 scanned MRIs at baseline and 24 weeks. ReHo values from regions with significant longitudinal changes were compared between the intervention and control groups and their correlations with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) or serum brain-derived neurotrophic factor (BDNF) were evaluated. ReHo values in the left medial orbitofrontal gyrus and right superior parietal lobule were increased [p = 0.021, correlated positively with serum BDNF changes (r = 0.504, p = 0.047)] and decreased [p = 0.021, correlated negatively with changes in the total (r = -0.509, p = 0.044) and attention (r = -0.562, p = 0.023). RBANS], respectively, in the participants assigned to the FMI group than those of the controls. Our results suggest that facility-based group preventive strategies may have cognitive benefits through neuroplastic changes in functional processing circuits in the brain areas which play a crucial role in the adaptive learning and internally directed cognition.

Key Intrinsic Connectivity Networks for Individual Identification With Siamese Long Short-Term Memory.

In functional magnetic resonance imaging (fMRI) analysis, many studies have been conducted on inter-subject variability as well as intra-subject reproducibility. These studies indicate that fMRI could have unique characteristics for individuals. In this study, we hypothesized that the dynamic information during 1 min of fMRI was unique and repetitive enough for each subject, so we applied long short-term memory (LSTM) using initial time points of dynamic resting-state fMRI for individual identification. Siamese network is used to obtain robust individual identification performance without additional learning on a new dataset. In particular, by adding a new structure called region of interest-wise average pooling (RAP), individual identification performance could be improved, and key intrinsic connectivity networks (ICNs) for individual identification were also identified. The average performance of individual identification was 97.88% using the test dataset in eightfold cross-validation analysis. Through the visualization of features learned by Siamese LSTM with RAP, ICNs spanning the parietal region were observed as the key ICNs in identifying individuals. These results suggest the key ICNs in fMRI could represent individual uniqueness.

Deep learning-Based 3D inpainting of brain MR images.

The detailed anatomical information of the brain provided by 3D magnetic resonance imaging (MRI) enables various neuroscience research. However, due to the long scan time for 3D MR images, 2D images are mainly obtained in clinical environments. The purpose of this study is to generate 3D images from a sparsely sampled 2D images using an inpainting deep neural network that has a U-net-like structure and DenseNet sub-blocks. To train the network, not only fidelity loss but also perceptual loss based on the VGG network were considered. Various methods were used to assess the overall similarity between the inpainted and original 3D data. In addition, morphological analyzes were performed to investigate whether the inpainted data produced local features similar to the original 3D data. The diagnostic ability using the inpainted data was also evaluated by investigating the pattern of morphological changes in disease groups. Brain anatomy details were efficiently recovered by the proposed neural network. In voxel-based analysis to assess gray matter volume and cortical thickness, differences between the inpainted data and the original 3D data were observed only in small clusters. The proposed method will be useful for utilizing advanced neuroimaging techniques with 2D MRI data.

Brain Structural Alterations, Diabetes Biomarkers, and Cognitive Performance in Older Adults With Dysglycemia.

Despite the high risk of dementia in older adults with type 2 diabetes, the neuroanatomical correlates of cognitive dysfunction that are particularly affected by diabetes are not well characterized. This study is aimed to examine the structural brain alterations in dysglycemic older adults. Using voxel-based morphometric and tract-based spatial statistics, we examined changes in gray matter volume, white matter volume, and microstructural integrity in older adults with prediabetes and diabetes. We also assessed the correlation of these structural changes with diabetes biomarkers and cognitive performance. A total of 74 non-demented older adults (normal, n = 14; prediabetes, n = 37; and diabetes, n = 23) participated in this study and underwent structural and diffusion magnetic resonance imaging (MRI) scans and neuropsychological tests. Subjects with diabetes showed reduced volume of cerebellar gray matter and frontal white matter and diffuse white matter dysintegrity, while those with prediabetes only showed reduced volume of insular gray matter. Atrophic changes in the cerebellum and frontal lobe and frontal white matter dysintegrity were correlated with chronic hyperglycemia and insulin resistance and worse performance in verbal memory recognition and executive function tests. Our findings suggest that chronic hyperglycemia and insulin resistance may alter brain structures forming the fronto-cerebellar network, which may cause cognitive dysfunction in older adults.

Association of Retinal Changes With Alzheimer Disease Neuroimaging Biomarkers in Cognitively Normal Individuals.

IMPORTANCE: Retinal biomarkers reflecting in vivo brain Alzheimer disease (AD) pathologic abnormalities could be a useful tool for screening cognitively normal (CN) individuals at the preclinical stage of AD. OBJECTIVES: To investigate the association of both functional and structural alterations of the retina with in vivo AD pathologic abnormalities in CN older adults and model a screening tool for detection of preclinical AD. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study included a total of 49 CN individuals, and all assessment was done at the Seoul National University Hospital, Seoul, South Korea. All participants underwent complete ophthalmic examination, including swept-source optical coherence tomography (SS-OCT) and multifocal electroretinogram as well as amyloid-ß (Aß) positron emission tomography and magnetic resonance imaging. Data were collected from January 1, 2016, through October 31, 2017, and analyzed from February 1, 2018, through June 30, 2020. MAIN OUTCOMES AND MEASURES: For structural parameters of the retina, the thickness of the macula and layer-specific thicknesses, including peripapillary retinal nerve fiber layer and ganglion cell-inner plexiform layer measured by SS-OCT, were used for analysis. For functional parameters of the retina, implicit time and amplitude of rings 1 to 6 measured by multifocal electroretinogram were used. RESULTS: Of the 49 participants, 25 were women (51.0%); mean (SD) age was 70.6 (9.4) years. Compared with 33 CN individuals without Aß deposition (Aß-CN), the 16 participants with Aß (Aß+CN) showed reduced inner nasal macular thickness (mean [SD], 308.9 [18.4] vs 286.1 [22.5] µm; P = .007) and retinal nerve fiber layer thickness, particularly in the inferior quadrant (133.8 [17.9] vs 103.8 [43.5] µm; P = .003). In addition, the Aß+CN group showed prolonged implicit time compared with the Aß-CN group, particularly in ring 5 (41.3 [4.0] vs 38.2 [1.3] milliseconds; P = .002). AD-related neurodegeneration was correlated with the thickness of the ganglion cell-inner plexiform layer only (r = 0.41, P = .005). The model to differentiate the Aß+CN vs Aß-CN groups derived from the results showed 90% accuracy. CONCLUSIONS AND RELEVANCE: The findings of this study showing both functional as well as structural changes of retina measured by multifocal electroretinogram and SS-OCT in preclinical AD suggest the potential use of retinal biomarkers as a tool for early detection of in vivo AD pathologic abnormalities in CN older adults.

Differential associations of age and Alzheimer's disease with sleep and rest-activity rhythms across the adult lifespan.

This study aimed to identify differences between physiological age-related and Alzheimer's disease (AD)-related alterations in sleep and rest-activity rhythm. All participants (n = 280; 20-90 years) underwent clinical assessments, [11C] Pittsburgh compound B-positron emission tomography, and actigraphic monitoring. In cognitively normal adults without cerebral amyloid-ß, older age was associated with earlier timing of circadian phase and robust rest-activity rhythm, but sleep quantity and quality were mostly unaffected by age. While preclinical AD was associated with earlier circadian timing, clinical AD exhibited later timing of daily rhythm and increased sleep duration. In conclusion, our findings suggest that older age itself leads to a more regular daily activity rhythm, but does not affect sleep duration. While preclinical AD made the effects of age-related phase advance more prominent, clinical AD was related to later circadian timing and increased sleep duration.

Sex-Specific Association of Lifetime Body Mass Index with Alzheimer's Disease Neuroimaging Biomarkers.

BACKGROUND: Although recent studies indicate that the relationship between body mass index (BMI) and Alzheimer's disease (AD) may differ by both sex and age of BMI measurement, little information is available on sex- or age-specific associations between BMI and AD neuropathologies. OBJECTIVE: To examined whether sex-specific BMIs measured at different life-stages (in early adulthood, midlife, and late life) were associated with cerebral amyloid-ß (Aß) deposition and AD-signature region cortical thickness (AD-CT) in cognitively normal (CN) older adults. METHODS: A total of 212 CN subjects aged 60-90 years (females 108, males 104), who participated in the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease (KBASE), an ongoing prospective cohort study, were included. All participants underwent comprehensive clinical and neuropsychological assessments, [11C] Pittsburgh Compound B positron emission tomography, and brain magnetic resonance imaging. BMIs at different life stages were calculated. Multiple regression analyses were performed separately for either sex. RESULTS: In males, lower early adulthood or midlife BMI was associated with greater cerebral Aß deposition, but late life BMI was not. Lower midlife BMI was associated with reduced AD-CT, but the BMI in early adulthood and late life was not. In females, no significant association was observed between any lifetime BMI and Aß deposition or AD-CT. CONCLUSION: Our results support a male-specific association between BMI prior to late life, and in vivo AD pathologies. Avoiding underweight status early in life may be important to prevent AD dementia in males, but not females.

Genetic associations of in vivo pathology influence Alzheimer's disease susceptibility.

INTRODUCTION: Although the heritability of sporadic Alzheimer's disease (AD) is estimated to be 60-80%, addressing the genetic contribution to AD risk still remains elusive. More specifically, it remains unclear whether genetic variants are able to affect neurodegenerative brain features that can be addressed by in vivo imaging techniques. METHODS: Targeted sequencing analysis of the coding and UTR regions of 132 AD susceptibility genes was performed. Neuroimaging data using 11C-Pittsburgh Compound B positron emission tomography (PET), 18F-fluorodeoxyglucose PET, and MRI that are available from the KBASE (Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's disease) cohort were acquired. A total of 557 participants consisted of 336 cognitively normal (CN) adults, 137 mild cognitive impairment (MCI), and 84 AD dementia (ADD) groups. RESULTS: We called 5391 high-quality single nucleotide variants (SNVs) on AD susceptibility genes and selected significant associations between variants and five in vivo AD pathologies: (1) amyloid ß (Aß) deposition, (2) AD-signature region cerebral glucose metabolism (AD-Cm), (3) posterior cingulate cortex (PCC) cerebral glucose metabolism (PCC-Cm), (4) AD-signature region cortical thickness (AD-Ct), and (5) hippocampal volume (Hv). The association analysis for common variants (allele frequency (AF) > 0.05) yielded several novel loci associated with Aß deposition (PIWIL1-rs10848087), AD-Cm (NME8-rs2722372 and PSEN2-rs75733498), AD-Ct (PSEN1-rs7523) and, Hv (CASS4-rs3746625). Meanwhile, in a gene-based analysis for rare variants (AF < 0.05), cases carrying rare variants in LPL, FERMT2, NFAT5, DSG2, and ITPR1 displayed associations with the neuroimaging features. Exploratory voxel-based brain morphometry between the variant carriers and non-carriers was performed subsequently. Finally, we document a strong association of previously reported APOE variants with the in vivo AD pathologies and demonstrate that the variants exert a causal effect on AD susceptibility via neuroimaging features. CONCLUSIONS: This study provides novel associations of genetic factors to Aß accumulation and AD-related neurodegeneration to influence AD susceptibility.

Multiparity, Brain Atrophy, and Cognitive Decline.

BACKGROUND: Multiparity - grand multiparity (i.e., five or more childbirths) in particular - has been reported to have an association with increased risk of Alzheimer's disease (AD) dementia or related cognitive decline in women. However, the pathological links underlying this relationship are still unknown. This study was conducted to examine the relationships of multiparity with cerebral amyloid-beta (Aß) deposition, brain atrophy, and white matter hyperintensities (WMHs). METHODS: In this study, total of 237 older women with 148 cognitively normal and 89 mild cognitive impairment from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease (KBASE) were included. Participants underwent clinical and neuropsychological assessments in addition to 11C-labeled Pittsburgh Compound B positron emission tomography, and magnetic resonance imaging. The associations of parity with Aß deposition, hippocampal volume, cortical volume, WMH volume and mini-mental status examination (MMSE) score were examined. RESULTS: Participants with grand multiparity showed significantly reduced adjusted hippocampal volume, spatial pattern of atrophy for recognition of AD volume and spatial pattern of atrophy for recognition of brain aging volume even after controlling for potential confounders. Furthermore, MMSE score was also significantly lower in this group. In contrast, grand multiparity did not show any association with global Aß retention, Aß positivity rate, or WMH volume, regardless of covariates. CONCLUSION: Our findings suggest that grand multiparity contributes to cognitive decline or increased dementia risk in older women by aggravating amyloid-independent hippocampal or cortical atrophy.

Serum Uric Acid, Alzheimer-Related Brain Changes, and Cognitive Impairment.

BACKGROUND: Despite known associations of lower serum uric acid (UA) with Alzheimer's disease (AD) dementia or AD-related cognitive impairment, little is known regarding the underlying patho-mechanisms. We aimed to examine the relationships of serum UA with in vivo AD pathologies including cerebral beta-amyloid (Aß) and tau deposition, AD-signature region cerebral glucose metabolism (AD-CM), and white matter hyperintensities (WMH). We also investigated the association between serum UA and cognitive performance, and then assessed whether such an association is mediated by the brain pathologies. METHODS: A total of 430 non-demented older adults underwent comprehensive clinical assessments, measurement of serum UA level, and multimodal brain imaging, including Pittsburgh compound B-positron emission tomography (PET), AV-1451 PET, fluorodeoxyglucose (FDG)-PET, and magnetic resonance imaging scans. Mini-Mental State Examination (MMSE) and word list recall (WLR) test scores were used to measure cognitive performance. RESULTS: Serum UA level was significantly associated with AD-CM, but not with Aß deposition, tau deposition, or WMH volume. Serum UA levels also had significant association with WLR and marginal association with MMSE; such associations disappeared when AD-CM was controlled as a covariate, indicating that AD-CM has a mediating effect. CONCLUSION: The findings of the present study indicate that there is an association of low serum UA with AD-related cerebral hypometabolism, and whether this represents a causal relationship remains to be determined.

Serum albumin and beta-amyloid deposition in the human brain.

OBJECTIVES: To investigate the relationships of serum albumin with in vivo Alzheimer disease (AD) pathologies, including cerebral ß-amyloid (Aß) protein deposition, neurodegeneration of AD-signature regions, and cerebral white matter hyperintensities (WMH), in the human brain. METHODS: A total of 396 older adults without dementia underwent comprehensive clinical assessments, measurement of serum albumin level, and multimodal brain imaging, including [11C] Pittsburgh compound B-PET, 18F-fluorodeoxyglucose-PET, and MRI. Serum albumin was categorized as follows: <4.4 g/dL (low albumin), 4.4 to 4.5 g/dL (middle albumin), and >4.5 g/dL (high albumin; used as a reference category). Aß positivity, AD-signature region cerebral glucose metabolism (AD-CM), AD-signature region cortical thickness (AD-CT), and WMH volume were used as outcome measures. RESULTS: Serum albumin level (as a continuous variable) was inversely associated with Aß deposition and Aß positivity. The low albumin group showed a significantly higher Aß positivity rate compared to the high albumin group (odds ratio 3.40, 95% confidence interval 1.67-6.92, p = 0.001), while the middle albumin group showed no difference (odds ratio 1.74, 95% confidence interval 0.80-3.77, p = 0.162). Neither serum albumin level (as a continuous variable) nor albumin categories were related to AD-CM, AD-CT, or WMH volume. CONCLUSIONS: Low serum albumin may increase the risk of AD dementia by elevating amyloid accumulation. In terms of AD prevention, more attention needs to be paid to avoid a low serum albumin level, even within the clinical normal range, by clinicians.

Corrigendum: Behavioral and Neuroimaging Evidence for Facial Emotion Recognition in Elderly Korean Adults with Mild Cognitive Impairment, Alzheimer's Disease, and Frontotemporal Dementia.

[This corrects the article DOI: 10.3389/fnagi.2017.00389.].