Development of a prediction model for cognitive impairment of sarcopenia using multimodal neuroimaging in non-demented older adults.

INTRODUCTION: Despite prior research on the association between sarcopenia and cognitive impairment in the elderly, a comprehensive model that integrates various brain pathologies is still lacking. METHODS: We used data from 528 non-demented older adults with or without sarcopenia in the Catholic Aging Brain Imaging (CABI) database, containing magnetic resonance imaging scans, positron emission tomography scans, and clinical data. We also measured three key components of sarcopenia: skeletal muscle index (SMI), hand grip strength (HGS), and the five times sit-to-stand test (5STS). RESULTS: All components of sarcopenia were significantly correlated with global cognitive function, but cortical thickness and amyloid-beta (Aß) retention had distinctive relationships with each measure. In the path model, brain atrophy resulting in cognitive impairment was mediated by Aß retention for SMI and periventricular white matter hyperintensity for HGS, but directly affected by the 5STS. DISCUSSION: Treatments targeting each sub-domain of sarcopenia should be considered to prevent cognitive decline. HIGHLIGHTS: We identified distinct impacts of three sarcopenia measures on brain structure and Aß. Muscle mass is mainly associated with Aß and has an influence on the brain atrophy. Muscle strength linked with periventricular WMH and brain atrophy. Muscle function associated with cortical thinning in specific brain regions. Interventions on sarcopenia may be important to ease cognitive decline in the elderly.

A Comparative Analysis of Two Automated Quantification Methods for Regional Cerebral Amyloid Retention: PET-Only and PET-and-MRI-Based Methods.

Accurate quantification of amyloid positron emission tomography (PET) is essential for early detection of and intervention in Alzheimer's disease (AD) but there is still a lack of studies comparing the performance of various automated methods. This study compared the PET-only method and PET-and-MRI-based method with a pre-trained deep learning segmentation model. A large sample of 1180 participants in the Catholic Aging Brain Imaging (CABI) database was analyzed to calculate the regional standardized uptake value ratio (SUVR) using both methods. The logistic regression models were employed to assess the discriminability of amyloid-positive and negative groups through 10-fold cross-validation and area under the receiver operating characteristics (AUROC) metrics. The two methods showed a high correlation in calculating SUVRs but the PET-MRI method, incorporating MRI data for anatomical accuracy, demonstrated superior performance in predicting amyloid-positivity. The parietal, frontal, and cingulate importantly contributed to the prediction. The PET-MRI method with a pre-trained deep learning model approach provides an efficient and precise method for earlier diagnosis and intervention in the AD continuum.

A regional brain volume-based age prediction model for neonates and the derived brain maturation index.

OBJECTIVE: To develop a postmenstrual age (PMA) prediction model based on segmentation volume and to evaluate the brain maturation index using the proposed model. METHODS: Neonatal brain MRIs without clinical illness or structural abnormalities were collected from four datasets from the Developing Human Connectome Project, the Catholic University of Korea, Hammersmith Hospital (HS), and Dankook University Hospital (DU). T1- and T2-weighted images were used to train a brain segmentation model. Another model to predict the PMA of neonates based on segmentation data was developed. Accuracy was assessed using mean absolute error (MAE), root mean square error (RMSE), and mean error (ME). The brain maturation index was calculated as the difference between the PMA predicted by the model and the true PMA, and its correlation with postnatal age was analyzed. RESULTS: A total of 247 neonates (mean gestation age 37 ± 4 weeks; range 24-42 weeks) were included. Thirty-one features were extracted from each neonate and the three most contributing features for PMA prediction were the right lateral ventricle, left caudate, and corpus callosum. The predicted and true PMA were positively correlated (coefficient = 0.88, p < .001). MAE, RMSE, and ME of the external dataset of HS and DU were 1.57 and 1.33, 1.79 and 1.37, and 0.37 and 0.06 weeks, respectively. The brain maturation index negatively correlated with postnatal age (coefficient = - 0.24, p < .001). CONCLUSION: A model that calculates the regional brain volume can predict the PMA of neonates, which can then be utilized to show the brain maturation degree. CLINICAL RELEVANCE STATEMENT: A brain maturity index based on regional volume of neonate's brain can be used to measure brain maturation degree, which can help identify the status of early brain development. KEY POINTS: • Neonatal brain MRI segmentation model could be used to assess neonatal brain maturation status. • A postmenstrual age (PMA) prediction model was developed based on a neonatal brain MRI segmentation model. • The brain maturation index, derived from the PMA prediction model, enabled the estimation of the neonatal brain maturation status.

Association of long-term hyperglycaemia and insulin resistance with brain atrophy and cognitive decline: A longitudinal cohort study.

AIM: To investigate the longitudinal changes in brain volume and cognitive function associated with diabetes at midlife, and to examine whether long-term hyperglycaemia, insulin resistance or secretory function is associated with brain atrophy and cognitive decline. MATERIALS AND METHODS: We used data from 2377 participants with both baseline and 4-year follow-up brain magnetic resonance images and neuropsychological measures from the Ansan cohort of the Korean Genome Epidemiology Study. Time-weighted mean glycaemic values were calculated using all measurements over an average duration of 10.6 years from cohort initiation to baseline visits. RESULTS: Type 2 diabetes was associated with greater white matter volume reduction (adjusted volume difference = -1.96 ml, 95% CI: -3.73, -0.18) and executive function decline (adjusted Z score difference = -0.14, 95% CI: -0.23, -0.05) during the follow-up period of 4.2 years. Decline of verbal and visual memory or verbal fluency was not associated with diabetes. Greater executive function decline was associated with higher time-weighted mean HbA1c level over the preceding 10.6 years (P < .001), but not with insulin resistance markers in the diabetes group. Participants with diabetes, whose time-weighted average HbA1c level was maintained above 6.5% over the previous decade, showed greater decline in executive function and global cognition than the normal glucose group. CONCLUSIONS: Long-term hyperglycaemia was a major independent factor associated with rapid cognitive decline in middle-aged adults with diabetes. Maintaining ideal glucose levels in diabetes at midlife might prevent later rapid cognitive decline.

A Fully Automated Visual Grading System for White Matter Hyperintensities of T2-Fluid Attenuated Inversion Recovery Magnetic Resonance Imaging.

BACKGROUND: The Fazekas scale is one of the most commonly used visual grading systems for white matter hyperintensity (WMH) for brain disorders like dementia from T2-fluid attenuated inversion recovery magnetic resonance (MR) images (T2-FLAIRs). However, the visual grading of the Fazekas scale suffers from low-intra and inter-rater reliability and high labor-intensive work. Therefore, we developed a fully automated visual grading system using quantifiable measurements. METHODS: Our approach involves four stages: (1) the deep learning-based segmentation of ventricles and WMH lesions, (2) the categorization into periventricular white matter hyperintensity (PWMH) and deep white matter hyperintensity (DWMH), (3) the WMH diameter measurement, and (4) automated scoring, following the quantifiable method modified for Fazekas grading. We compared the performances of our method and that of the modified Fazekas scale graded by three neuroradiologists for 404 subjects with T2-FLAIR utilized from a clinical site in Korea. RESULTS: The Krippendorff's alpha across our method and raters (A) versus those only between the radiologists (R) were comparable, showing substantial (0.694 vs. 0.732; 0.658 vs. 0.671) and moderate (0.579 vs. 0.586) level of agreements for the modified Fazekas, the DWMH, and the PWMH scales, respectively. Also, the average of areas under the receiver operating characteristic curve between the radiologists (0.80 ± 0.09) and the radiologists against our approach (0.80 ± 0.03) was comparable. CONCLUSIONS: Our fully automated visual grading system for WMH demonstrated comparable performance to the radiologists, which we believe has the potential to assist the radiologist in clinical findings with unbiased and consistent scoring.

Cognitive Normal Older Adults with APOE-2 Allele Show a Distinctive Functional Connectivity Pattern in Response to Cerebral Aß Deposition.

The ε2 allele of apolipoprotein E (ε2) has neuroprotective effects against beta-amyloid (Aß) pathology in Alzheimer's disease (AD). However, its impact on the functional connectivity and hub efficiency in cognitively normal older adults (CN) with ε2 is unclear. We investigated the functional connectivity differences in the default mode network (DMN), salience network, and central executive network (CEN) between A-PET-negative (N = 29) and A-PET-positive (N = 15) CNs with ε2/ε2 or ε2/ε3 genotypes. The A-PET-positive CNs exhibited a lower anterior DMN functional connectivity, higher posterior DMN functional connectivity, and increased CEN functional connectivity compared to the A-PET-negative CNs. Cerebral Aß retention was negatively correlated with anterior DMN functional connectivity and positively correlated with posterior DMN and anterior CEN functional connectivity. A graph theory analysis showed that the A-PET-positive CNs displayed a higher betweenness centrality in the middle frontal gyrus (left) and medial fronto-parietal regions (left). The betweenness centrality in the middle frontal gyrus (left) was positively correlated with Aß retention. Our findings reveal a reversed anterior-posterior dissociation in the DMN functional connectivity and heightened CEN functional connectivity in A-PET-positive CNs with ε2. Hub efficiencies, measured by betweenness centrality, were increased in the DMN and CEN of the A-PET-positive CNs with ε2. These results suggest unique functional connectivity responses to Aß pathology in CN individuals with ε2.

Sex-Related Disparities in the Resting State Functional Connectivity of the Locus Coeruelus and Salience Network in Preclinical Alzheimer's Disease.

Recent studies have demonstrated the pivotal role of locus coeruleus (LC) and salience network (SN) resting state functional connectivity (rsFC) changes in the early stage of Alzheimer's disease (AD). Moreover, sex has been a crucial point of discussion in understanding AD pathology. We aimed to demonstrate the sex-related disparities in the functional connectivity (FC) of the SN and LC in preclinical AD. A total of 89 cognitively normal patients with evidence of amyloid beta (Aß) accumulation ([18F] flutemetamol +) were recruited in the study. A seed-to-voxel analysis was conducted to measure the LC and SN rsFC differences between sexes. In addition, sex by Aß interactive effects on FC values were analyzed with a general linear model. There were statistically significant sex by regional standardized uptake value ratio (SUVR) interactions in the LC FC with the parietal, frontal, and occipital cortices. Moreover, there was a significant sex by global SUVR interaction in the SN FC with the temporal cortex. The findings suggest that there are differential patterns of LC FC and SN FC in males and females with preclinical AD, which interact with regional Aß deposition.

The Effect of Hearing Loss on Cognitive Function in Subjective Cognitive Decline.

INTRODUCTION: Subjective cognitive decline (SCD) is a self-reported cognitive decline without objective cognitive impairment. The relationship between audiometric hearing loss (HL) and cognitive function has not been reported in SCD. The purpose of this study was to investigate whether HL affects cognition-related indexes in SCD individuals. METHODS: This is a cross-sectional study that used the baseline data of a multicenter cohort study that monitors clinical progression from SCD to dementia. Individuals aged ≥60 years who reported cognitive decline but had no objective cognitive impairment on comprehensive neuropsychological tests were recruited. Participants were grouped into the normal-hearing (NH) and bilateral HL groups. The demographics, clinical characteristics, dementia biomarkers, global cognition, questionnaire scores, neuropsychological test scores, and segmental brain volumes from MRI were compared between the groups. RESULTS: Of a total of 120 participants, one hundred and two had NH (n = 57) or bilateral HL (n = 45). There were no group differences in the demographic and clinical data except the age. The biomarkers, global cognition, and questionnaire scores were not different between the groups. The HL group performed worse (the z-score of -0.06) in the Stroop Color Word Test than the NH group (0.27) (p = 0.025). Brain volumetric analysis revealed that the HL group had reduced gray matter volumes in four brain subregions: left temporal pole, left caudal middle frontal gyrus, left hippocampus, and right isthmus of the cingulate gyrus. CONCLUSION: In SCD, HL exerted an adverse effect on cognitive function, primarily frontal executive function tested in the Stroop task. HL was also related to gray matter volume reductions in brain subregions, although causality needs further investigation. This study may provide evidence for a potential link between hearing and cognition in SCD, an emerging clinical entity.

Sleep Duration, Sleep Apnea, and Gray Matter Volume.

This study aimed to evaluate the effect of sleep duration on brain structures in the presence versus absence of sleep apnea in middle-aged and older individuals. The study investigated a population-based sample of 2,560 individuals, aged 49-80 years. The presence of sleep apnea and self-reported sleep duration were examined in relation to gray matter volume (GMV) in total and lobar brain regions. We identified ranges of sleep duration associated with maximal GMV using quadratic regression and bootstrap sampling. A significant quadratic association between sleep duration and GMV was observed in total and lobar brain regions of men with sleep apnea. In the fully adjusted model, optimal sleep durations associated with peak GMV between brain regions ranged from 6.7 to 7.0 hours. Shorter and longer sleep durations were associated with lower GMV in total and 4 sub-regions of the brain in men with sleep apnea.

Obesity and muscle may have synergic effect more than independent effects on brain volume in community-based elderly.

OBJECTIVE: To evaluate the individual and combined effects of obesity and muscle mass on brain volume in a community-dwelling healthy older population. METHODS: One thousand two hundred nine participants (M:F = 574:635, mean age 63.6 ± 6.9 years) were included. The cross-sectional area of visceral fat (VF), the height-adjusted appendicular skeletal muscle mass (ASM/height2), and the ratio of thigh muscle to visceral fat (TM/VF) represented obesity, muscle mass, and their integrated value, respectively. Linear regression analysis was performed to establish associations between 215 brain compartment volumes and VF, ASM/height2, and TM/VF after adjusting for covariates. RESULTS: On regression analysis, TM/VF had a positive correlation to the volumes of temporal lobe and cerebellum. TM/VF was associated with volumes of 10 subcompartments. TM/VF was positively correlated with the volumes of left entorhinal cortex, right temporal pole and inferior temporal gyrus related to cognition (p < 0.05, respectively), and the volumes of cerebellum and right pallidum related to movement (p < 0.05, respectively). However, VF had a negative correlation to temporal lobe volume and ASM/height2 had no significant correlation to any of the brain lobes. VF and ASM/height2 were correlated with volumes of 5 subcompartments and one subcompartment, respectively, CONCLUSIONS: TM/VF reflects the integrated effect of obesity and muscle mass and is associated with the volume of more brain regions compared to indices of obesity or muscle mass alone. The positive effect of muscle mass and the negative effect of obesity change the volumes of brain regions related to cognition and movement which were not significantly affected by obesity or muscle mass alone. KEY POINTS: • If obesity and muscle mass were considered together, we could find more significant brain volume changes which were not found in obesity or muscle alone. • The ratio of thigh muscle to visceral fat was positively correlated with the volumes of entorhinal cortex, temporal pole, and inferior temporal gyrus related to cognition. • The ratio of thigh muscle to visceral fat was positively correlated with the volumes of cerebellum and pallidum related to movement.

Sarcopenia is associated with decreased gray matter volume in the parietal lobe: a longitudinal cohort study.

BACKGROUND: Substantial evidence supports an association between physical activity and cognitive function. However, the role of muscle mass and function in brain structural changes is not well known. This study investigated whether sarcopenia, defined as low muscle mass and strength, accelerates brain volume atrophy. METHODS: A total of 1284 participants with sarcopenic measurements and baseline and 4-year follow-up brain magnetic resonance images were recruited from the Korean Genome and Epidemiology Study. Muscle mass was represented as appendicular skeletal muscle mass divided by the body mass index. Muscle function was measured by handgrip strength. The low mass and strength groups were defined as being in the lowest quintile of each variable for one's sex. Sarcopenia was defined as being in the lowest quintile for both muscle mass and handgrip strength. RESULTS: Of the 1284 participants, 12·6%, 10·8%, and 5·4% were classified as the low mass, low strength, and sarcopenia groups, respectively. The adjusted mean changes of gray matter (GM) volume during 4-year follow-up period were - 9·6 mL in the control group, whereas - 11·6 mL in the other three groups (P < 0·001). The significantly greater atrophy in parietal GM was observed in the sarcopenia group compared with the control group. In a joint regression model, low muscle mass, but not muscle strength, was an independent factor associated with a decrease of GM volume. CONCLUSIONS: Sarcopenia is associated with parietal GM volume atrophy, in a middle-aged population. Maintaining good levels of muscle mass could be important for brain health in later adulthood.

Neck Circumference and Cerebral Gray Matter Volume.

BACKGROUND: While obesity is linked with brain atrophy and dementia incidence, associations with regional adiposity are uncertain. Our goal was to determine whether cerebral gray matter volume is related to neck circumference (NC), a measure of regional adiposity having unique relationships with metabolic disorders and cardiovascular disease. METHODS: Magnetic resonance imaging and NC were cross-sectionally assessed from 2011 to 2014 in a population-based sample of 2916 men and women in the Korean Genome and Epidemiology Study. RESULTS: For men, NC was inversely associated with total and regional gray matter in the frontal, temporal, and occipital lobes after adjusting for age and intracranial brain volume. Associations were especially strong in the presence of diabetes. With further adjustment for indices of body composition and other characteristics, total and frontal gray matter in diabetic men were lowered by 6.1 mL (95% confidence interval: 2.5-9.7, P=0.004) and 2.9 mL (95% confidence interval: 1.0-4.9, P=0.017), respectively, per SD increase in NC (2.3 cm). For men without diabetes, and in all women, associations were less apparent. CONCLUSIONS: In men with diabetes, NC was inversely associated with cerebral gray matter volume. The link between neck anthropometry and brain aging in diabetic men warrants further consideration.

A Novel Transgenic Rat Model of Robust Cerebral Microvascular Amyloid with Prominent Vasculopathy.

Accumulation of fibrillar amyloid ß protein in blood vessels of the brain, a condition known as cerebral amyloid angiopathy (CAA), is a common pathology of elderly individuals, a prominent comorbidity of Alzheimer disease, and a driver of vascular cognitive impairment and dementia. Although several transgenic mouse strains have been generated that develop varying levels of CAA, consistent models of associated cerebral microhemorrhage and vasculopathy observed clinically have been lacking. Reliable preclinical animal models of CAA and microhemorrhage are needed to investigate the molecular pathogenesis of this condition. Herein, we describe the generation and characterization of a novel transgenic rat (rTg-DI) that produces low levels of human familial CAA Dutch/Iowa E22Q/D23N mutant amyloid ß protein in brain and faithfully recapitulates many of the pathologic aspects of human small-vessel CAA. rTg-DI rats exhibit early-onset and progressive accumulation of cerebral microvascular fibrillar amyloid accompanied by early-onset and sustained behavioral deficits. Comparable to CAA in humans, the cerebral microvascular amyloid in rTg-DI rats causes capillary structural alterations, promotes prominent perivascular neuroinflammation, and produces consistent, robust microhemorrhages and small-vessel occlusions that are readily detected by magnetic resonance imaging. The rTg-DI rats provide a new model to investigate the pathogenesis of small-vessel CAA and microhemorrhages, to develop effective biomarkers for this condition and to test therapeutic interventions.

Longitudinal diffusion changes in prodromal and early HD: Evidence of white-matter tract deterioration.

INTRODUCTION: Huntington's disease (HD) is a genetic neurodegenerative disorder that primarily affects striatal neurons. Striatal volume loss is present years before clinical diagnosis; however, white matter degradation may also occur prior to diagnosis. Diffusion-weighted imaging (DWI) can measure microstructural changes associated with degeneration that precede macrostructural changes. DWI derived measures enhance understanding of degeneration in prodromal HD (pre-HD). METHODS: As part of the PREDICT-HD study, N = 191 pre-HD individuals and 70 healthy controls underwent two or more (baseline and 1-5 year follow-up) DWI, with n = 649 total sessions. Images were processed using cutting-edge DWI analysis methods for large multicenter studies. Diffusion tensor imaging (DTI) metrics were computed in selected tracts connecting the primary motor, primary somato-sensory, and premotor areas of the cortex with the subcortical caudate and putamen. Pre-HD participants were divided into three CAG-Age Product (CAP) score groups reflecting clinical diagnosis probability (low, medium, or high probabilities). Baseline and longitudinal group differences were examined using linear mixed models. RESULTS: Cross-sectional and longitudinal differences in DTI measures were present in all three CAP groups compared with controls. The high CAP group was most affected. CONCLUSIONS: This is the largest longitudinal DWI study of pre-HD to date. Findings showed DTI differences, consistent with white matter degeneration, were present up to a decade before predicted HD diagnosis. Our findings indicate a unique role for disrupted connectivity between the premotor area and the putamen, which may be closely tied to the onset of motor symptoms in HD. Hum Brain Mapp 38:1460-1477, 2017. © 2017 Wiley Periodicals, Inc.

Sex-specific effects of the Huntington gene on normal neurodevelopment.

Huntington disease is a neurodegenerative disorder caused by a gene (HTT) with a unique feature of trinucleotide repeats ranging from 10 to 35 in healthy people; when expanded beyond 39 repeats, Huntington disease develops. Animal models demonstrate that HTT is vital to brain development; however, this has not been studied in humans. Moreover, evidence suggests that triplet repeat genes may have been vital in evolution of the human brain. Here we evaluate brain structure using magnetic resonance imaging and brain function using cognitive tests in a sample of school-aged children ages 6 to 18 years old. DNA samples were processed to quantify the number of CAG repeats within HTT. We find that the number of repeats in HTT, below disease threshold, confers advantageous changes in brain structure and general intelligence (IQ): the higher the number of repeats, the greater the change in brain structure, and the higher the IQ. The pattern of structural brain changes associated with HTT is strikingly different between males and females. HTT may confer an advantage or a disadvantage depending on the repeat length, playing a key role in either the evolution of a superior human brain or development of a uniquely human brain disease. © 2016 Wiley Periodicals, Inc.

Prefrontal cortex white matter tracts in prodromal Huntington disease.

Huntington disease (HD) is most widely known for its selective degeneration of striatal neurons but there is also growing evidence for white matter (WM) deterioration. The primary objective of this research was to conduct a large-scale analysis using multisite diffusion-weighted imaging (DWI) tractography data to quantify diffusivity properties along major prefrontal cortex WM tracts in prodromal HD. Fifteen international sites participating in the PREDICT-HD study collected imaging and neuropsychological data on gene-positive HD participants without a clinical diagnosis (i.e., prodromal) and gene-negative control participants. The anatomical prefrontal WM tracts of the corpus callosum (PFCC), anterior thalamic radiations (ATRs), inferior fronto-occipital fasciculi (IFO), and uncinate fasciculi (UNC) were identified using streamline tractography of DWI. Within each of these tracts, tensor scalars for fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity coefficients were calculated. We divided prodromal HD subjects into three CAG-age product (CAP) groups having Low, Medium, or High probabilities of onset indexed by genetic exposure. We observed significant differences in WM properties for each of the four anatomical tracts for the High CAP group in comparison to controls. Additionally, the Medium CAP group presented differences in the ATR and IFO in comparison to controls. Furthermore, WM alterations in the PFCC, ATR, and IFO showed robust associations with neuropsychological measures of executive functioning. These results suggest long-range tracts essential for cross-region information transfer show early vulnerability in HD and may explain cognitive problems often present in the prodromal stage. Hum Brain Mapp 36:3717-3732, 2015. © 2015 Wiley Periodicals, Inc.

Increased Likelihood of Dementia with Coexisting Atrophy of Multiple Regions of Interest.

BACKGROUND: Brain volume is associated with cognitive decline in later life, and cortical brain atrophy exceeding the normal range is related to inferior cognitive and behavioral outcomes in later life. OBJECTIVE: To investigate the likelihood of cognitive decline, mild cognitive impairment (MCI), or dementia, when regional atrophy is present in participants' magnetic resonance imaging (MRI). METHODS: Multi-center MRI data of 2,545 adults were utilized to measure regional volumes using NEUROPHET AQUA. Four lobes (frontal, parietal, temporal, and occipital), four Alzheimer's disease-related regions (entorhinal, fusiform, inferior temporal, and middle temporal area), and the hippocampus in the left and right hemispheres were measured and analyzed. The presence of regional atrophy from brain MRI was defined as ≤1.5 standard deviation (SD) compared to the age- and sex-matched cognitively normal population. The risk ratio for cognitive decline was investigated for participants with regional atrophy in contrast to those without regional atrophy. RESULTS: The risk ratio for cognitive decline was significantly higher when hippocampal atrophy was present (MCI, 1.84, p < 0.001; dementia, 4.17, p < 0.001). Additionally, participants with joint atrophy in multiple regions showed a higher risk ratio for dementia, e.g., 9.6 risk ratio (95% confidence interval, 8.0-11.5), with atrophy identified in the frontal, temporal, and hippocampal gray matter, than those without atrophy. CONCLUSIONS: Our study showed that individuals with multiple regional atrophy (either lobar or AD-specific regions) have a higher likelihood of developing dementia compared to the age- and sex-matched population without atrophy. Thus, further consideration is needed when assessing MRI findings.

Development of Efficient Brain Age Estimation Method Based on Regional Brain Volume From Structural Magnetic Resonance Imaging.

OBJECTIVE: We aimed to create an efficient and valid predicting model which can estimate individuals' brain age by quantifying their regional brain volumes. METHODS: A total of 2,560 structural brain magnetic resonance imaging (MRI) scans, along with demographic and clinical data, were obtained. Pretrained deep-learning models were employed to automatically segment the MRI data, which enabled fast calculation of regional brain volumes. Brain age gaps for each subject were estimated using volumetric values from predefined 12 regions of interest (ROIs): bilateral frontal, parietal, occipital, and temporal lobes, as well as bilateral hippocampus and lateral ventricles. A larger weight was given to the ROIs having a larger mean volumetric difference between the cognitively unimpaired (CU) and cognitively impaired group including mild cognitive impairment (MCI), and dementia groups. The brain age was predicted by adding or subtracting the brain age gap to the chronological age according to the presence or absence of the atrophy region. RESULTS: The study showed significant differences in brain age gaps among CU, MCI, and dementia groups. Furthermore, the brain age gaps exhibited significant correlations with education level and measures of cognitive function, including the clinical dementia rating sum-of-boxes and the Korean version of the Mini-Mental State Examination. CONCLUSION: The brain age that we developed enabled fast and efficient brain age calculations, and it also reflected individual's cognitive function and cognitive reserve. Thus, our study suggested that the brain age might be an important marker of brain health that can be used effectively in real clinical settings.

Associations between Education Years and Resting-state Functional Connectivity Modulated by APOE ε4 Carrier Status in Cognitively Normal Older Adults.

Objective: : Cognitive reserve has emerged as a concept to explain the variable expression of clinical symptoms in the pathology of Alzheimer's disease (AD). The association between years of education, a proxy of cognitive reserve, and resting-state functional connectivity (rFC), a representative intermediate phenotype, has not been explored in the preclinical phase, considering risk factors for AD. We aimed to evaluate whether the relationship between years of education and rFC in cognitively preserved older adults differs depending on amyloid-beta deposition and APOE ε4 carrier status as effect modifiers. Methods: : A total of 121 participants underwent functional magnetic resonance imaging, [18F] flutemetamol positron emission tomography-computed tomography, APOE genotyping, and a neuropsychological battery. Potential interactions between years of education and AD risk factors for rFC of AD-vulnerable neural networks were assessed with whole-brain voxel-wise analysis. Results: : We found a significant education years-by-APOE ε4 carrier status interaction for the rFC from the seed region of the central executive (CEN) and dorsal attention networks. Moreover, there was a significant interaction of rFC between right superior occipital gyrus and the CEN seed region by APOE ε4 carrier status for memory performances and overall cognitive function. Conclusion: : In preclinical APOE ε4 carriers, higher years of education were associated with higher rFC of the AD vulnerable network, but this contributed to lower cognitive function. These results contribute to a deeper understanding of the impact of cognitive reserve on sensitive functional intermediate phenotypic markers in the preclinical phase of AD.

Impact of Apolipoprotein E4 on the Locus Coeruleus Functional Connectivity in Preclinical Alzheimer's Disease.

Background: Recent interest has surged in the locus coeruleus (LC) for its early involvement in Alzheimer's disease (AD), notably concerning the apolipoprotein ɛ4 allele (APOE4). Objective: This study aimed to discern LC functional connectivity (FC) variations in preclinical AD subjects, dissecting the roles of APOE4 carrier status and amyloid-ß (Aß) deposition. Methods: A cohort of 112 cognitively intact individuals, all Aß-positive, split into 70 APOE4 noncarriers and 42 carriers, underwent functional MRI scans, neuropsychological assessments, and APOE genotyping. The research utilized seed to voxel analysis for illustrating LC rsFC discrepancies between APOE4 statuses and employed a general linear model to examine the interactive influence of APOE4 carrier status and Aß deposition on LC FC values. Results: The investigation revealed no significant differences in sex, age, or SUVR between APOE4 carriers and noncarriers. It found diminished LC FC with the occipital cortex in APOE4 carriers and identified a significant interaction between APOE4 carrier status and temporal lobe SUVR in LC FC with the occipital cortex. This interaction suggested a proportional increase in LC FC for APOE4 carriers. Additional notable interactions were observed affecting LC FC with various brain regions, indicating a proportional decrease in LC FC for APOE4 carriers. Conclusions: These findings confirm that APOE4 carrier status significantly influences LC FC in preclinical AD, showcasing an intricate relationship with regional Aß deposition. This underscores the critical role of genetic and pathological factors in early AD pathophysiology, offering insights into potential biomarkers for early detection and intervention strategies.