Machine learning-based quantification for disease uncertainty increases the statistical power of genetic association studies.

MOTIVATION: Allowance for increasingly large samples is a key to identify the association of genetic variants with Alzheimer's disease (AD) in genome-wide association studies (GWAS). Accordingly, we aimed to develop a method that incorporates patients with mild cognitive impairment and unknown cognitive status in GWAS using a machine learning-based AD prediction model. RESULTS: Simulation analyses showed that weighting imputed phenotypes method increased the statistical power compared to ordinary logistic regression using only AD cases and controls. Applied to real-world data, the penalized logistic method had the highest AUC (0.96) for AD prediction and weighting imputed phenotypes method performed well in terms of power. We identified an association (P<5.0×10-8) of AD with several variants in the APOE region and rs143625563 in LMX1A. Our method, which allows the inclusion of individuals with mild cognitive impairment, improves the statistical power of GWAS for AD. We discovered a novel association with LMX1A. AVAILABILITY AND IMPLEMENTATION: Simulation codes can be accessed at https://github.com/Junkkkk/wGEE_GWAS.

Multi-ancestry meta-analysis and fine-mapping in Alzheimer's disease.

Genome-wide association studies (GWAS) of Alzheimer's disease are predominantly carried out in European ancestry individuals despite the known variation in genetic architecture and disease prevalence across global populations. We leveraged published GWAS summary statistics from European, East Asian, and African American populations, and an additional GWAS from a Caribbean Hispanic population using previously reported genotype data to perform the largest multi-ancestry GWAS meta-analysis of Alzheimer's disease and related dementias to date. This method allowed us to identify two independent novel disease-associated loci on chromosome 3. We also leveraged diverse haplotype structures to fine-map nine loci with a posterior probability >0.8 and globally assessed the heterogeneity of known risk factors across populations. Additionally, we compared the generalizability of multi-ancestry- and single-ancestry-derived polygenic risk scores in a three-way admixed Colombian population. Our findings highlight the importance of multi-ancestry representation in uncovering and understanding putative factors that contribute to risk of Alzheimer's disease and related dementias.

Predicting mild cognitive impairments from cognitively normal brains using a novel brain age estimation model based on structural magnetic resonance imaging.

Brain age prediction is a practical method used to quantify brain aging and detect neurodegenerative diseases such as Alzheimer's disease (AD). However, very few studies have considered brain age prediction as a biomarker for the conversion of cognitively normal (CN) to mild cognitive impairment (MCI). In this study, we developed a novel brain age prediction model using brain volume and cortical thickness features. We calculated an acceleration of brain age (ABA) derived from the suggested model to estimate different diagnostic groups (CN, MCI, and AD) and to classify CN to MCI and MCI to AD conversion groups. We observed a strong association between ABA and the 3 diagnostic groups. Additionally, the classification models for CN to MCI conversion and MCI to AD conversion exhibited acceptable and robust performances, with area under the curve values of 0.66 and 0.76, respectively. We believe that our proposed model provides a reliable estimate of brain age for elderly individuals and can identify those at risk of progressing from CN to MCI. This model has great potential to reveal a diagnosis associated with a change in cognitive decline.

Heritability of cognitive abilities and regional brain structures in middle-aged to elderly East Asians.

This study examined the single-nucleotide polymorphism heritability and genetic correlations of cognitive abilities and brain structural measures (regional subcortical volume and cortical thickness) in middle-aged and elderly East Asians (Korean) from the Gwangju Alzheimer's and Related Dementias cohort study. Significant heritability was found in memory function, caudate volume, thickness of the entorhinal cortices, pars opercularis, superior frontal gyri, and transverse temporal gyri. There were 3 significant genetic correlations between (i) the caudate volume and the thickness of the entorhinal cortices, (ii) the thickness of the superior frontal gyri and pars opercularis, and (iii) the thickness of the superior frontal and transverse temporal gyri. This is the first study to describe the heritability and genetic correlations of cognitive and neuroanatomical traits in middle-aged to elderly East Asians. Our results support the previous findings showing that genetic factors play a substantial role in the cognitive and neuroanatomical traits in middle to advanced age. Moreover, by demonstrating shared genetic effects on different brain regions, it gives us a genetic insight into understanding cognitive and brain changes with age, such as aging-related cognitive decline, cortical atrophy, and neural compensation.

Estimating explainable Alzheimer's disease likelihood map via clinically-guided prototype learning.

Identifying Alzheimer's disease (AD) involves a deliberate diagnostic process owing to its innate traits of irreversibility with subtle and gradual progression. These characteristics make AD biomarker identification from structural brain imaging (e.g., structural MRI) scans quite challenging. Using clinically-guided prototype learning, we propose a novel deep-learning approach through eXplainable AD Likelihood Map Estimation (XADLiME) for AD progression modeling over 3D sMRIs. Specifically, we establish a set of topologically-aware prototypes onto the clusters of latent clinical features, uncovering an AD spectrum manifold. Considering this pseudo map as an enriched reference, we employ an estimating network to approximate the AD likelihood map over a 3D sMRI scan. Additionally, we promote the explainability of such a likelihood map by revealing a comprehensible overview from clinical and morphological perspectives. During the inference, this estimated likelihood map served as a substitute for unseen sMRI scans for effectively conducting the downstream task while providing thorough explainable states.

Infection of the murine placenta by Listeria monocytogenes induces sex-specific responses in the fetal brain.

BACKGROUND: Epidemiological data indicate that prenatal infection is associated with an increased risk of several neurodevelopmental disorders in the progeny. These disorders display sex differences in presentation. The role of the placenta in the sex-specificity of infection-induced neurodevelopmental abnormalities is not well-defined. We used an imaging-based animal model of the bacterial pathogen Listeria monocytogenes to identify sex-specific effects of placental infection on neurodevelopment of the fetus. METHODS: Pregnant CD1 mice were infected with a bioluminescent strain of Listeria on embryonic day 14.5 (E14.5). Excised fetuses were imaged on E18.5 to identify the infected placentas. The associated fetal brains were analyzed for gene expression and altered brain structure due to infection. The behavior of adult offspring affected by prenatal Listeria infection was analyzed. RESULTS: Placental infection induced sex-specific alteration of gene expression patterns in the fetal brain and resulted in abnormal cortical development correlated with placental infection levels. Furthermore, male offspring exhibited abnormal social interaction, whereas females exhibited elevated anxiety. CONCLUSION: Placental infection by Listeria induced sex-specific abnormalities in neurodevelopment of the fetus. Prenatal infection also affected the behavior of the offspring in a sex-specific manner. IMPACT: Placental infection with Listeria monocytogenes induces sexually dichotomous gene expression patterns in the fetal brains of mice. Abnormal cortical lamination is correlated with placental infection levels. Placental infection results in autism-related behavior in male offspring and heightened anxiety levels in female offspring.

Listeria monocytogenes Infection Alters the Content and Function of Extracellular Vesicles Produced by Trophoblast Stem Cells.

Placental immunity is critical for fetal health during pregnancy, as invading pathogens spread from the parental blood to the fetus through this organ. However, inflammatory responses in the placenta can adversely affect both the fetus and the pregnant person, and the balance between protective placental immune response and detrimental inflammation is poorly understood. Extracellular vesicles (EVs) are membrane-enclosed vesicles that play a critical role in placental immunity. EVs produced by placental trophoblasts mediate immune tolerance to the fetus and to the placenta itself, but these EVs can also activate detrimental inflammatory responses. The regulation of these effects is not well characterized, and the role of trophoblast EVs (tEVs) in the response to infection has yet to be defined. The Gram-positive bacterial pathogen Listeria monocytogenes infects the placenta, serving as a model to study tEV function in this context. We investigated the effect of L. monocytogenes infection on the production and function of tEVs, using a trophoblast stem cell (TSC) model. We found that tEVs from infected TSCs can induce the production of the proinflammatory cytokine tumor necrosis factor alpha (TNF-α) in recipient cells. Surprisingly, this tEV treatment could confer increased susceptibility to subsequent L. monocytogenes infection, which has not been reported previously as an effect of EVs. Proteomic analysis and RNA sequencing revealed that tEVs from infected TSCs had altered cargo compared with those from uninfected TSCs. However, no L. monocytogenes proteins were detected in tEVs from infected TSCs. Together, these results suggest an immunomodulatory role for tEVs during prenatal infection.

SPIN90 Deficiency Ameliorates Amyloid ß Accumulation by Regulating APP Trafficking in AD Model Mice.

Alzheimer's disease (AD), a common form of dementia, is caused in part by the aggregation and accumulation in the brain of amyloid ß (Aß), a product of the proteolytic cleavage of amyloid precursor protein (APP) in endosomes. Trafficking of APP, such as surface-intracellular recycling, is an early critical step required for Aß generation. Less is known, however, about the molecular mechanism regulating APP trafficking. This study investigated the mechanism by which SPIN90, along with Rab11, modulates APP trafficking, Aß motility and accumulation, and synaptic functionality. Brain Aß deposition was lower in the progeny of 5xFAD-SPIN90KO mice than in 5xFAD-SPIN90WT mice. Analysis of APP distribution and trafficking showed that the surface fraction of APP was locally distinct in axons and dendrites, with these distributions differing significantly in 5xFAD-SPIN90WT and 5xFAD-SPIN90KO mice, and that neural activity-driven APP trafficking to the surface and intracellular recycling were more actively mobilized in 5xFAD-SPIN90KO neurons. In addition, SPIN90 was found to be cotrafficked with APP via axons, with ablation of SPIN90 reducing the intracellular accumulation of APP in axons. Finally, synaptic transmission was restored over time in 5xFAD-SPIN90KO but not in 5xFAD-SPIN90WT neurons, suggesting SPIN90 is implicated in Aß production through the regulation of APP trafficking.

Genome-wide association study of non-tuberculous mycobacterial pulmonary disease.

BACKGROUND: The prevalence of non-tuberculous mycobacterial pulmonary disease (NTM-PD) is increasing in South Korea and many parts of the world. However, the genetic factors underlying susceptibility to this disease remain elusive. METHODS: To identify genetic variants in patients with NTM-PD, we performed a genome-wide association study with 403 Korean patients with NTM-PD and 306 healthy controls from the Healthy Twin Study, Korea cohort. Candidate variants from the discovery cohort were subsequently validated in an independent cohort. The Genotype-Tissue Expression (GTEx) database was used to identify expression quantitative trait loci (eQTL) and to conduct Mendelian randomisation (MR). RESULTS: We identified a putatively significant locus on chromosome 7p13, rs849177 (OR, 2.34; 95% CI, 1.71 to 3.21; p=1.36×10-7), as the candidate genetic variant associated with NTM-PD susceptibility. Its association was subsequently replicated and the combined p value was 4.92×10-8. The eQTL analysis showed that a risk allele at rs849177 was associated with lower expression levels of STK17A, a proapoptotic gene. In the MR analysis, a causal effect of STK17A on NTM-PD development was identified (ß, -4.627; 95% CI, -8.768 to -0.486; p=0.029). CONCLUSIONS: The 7p13 genetic variant might be associated with susceptibility to NTM-PD in the Korean population by altering the expression level of STK17A.

Tonicity-responsive enhancer-binding protein promotes diabetic neuroinflammation and cognitive impairment via upregulation of lipocalin-2.

BACKGROUND: Diabetic individuals have increased circulating inflammatory mediators which are implicated as underlying causes of neuroinflammation and memory deficits. Tonicity-responsive enhancer-binding protein (TonEBP) promotes diabetic neuroinflammation. However, the precise role of TonEBP in the diabetic brain is not fully understood. METHODS: We employed a high-fat diet (HFD)-only fed mice or HFD/streptozotocin (STZ)-treated mice in our diabetic mouse models. Circulating TonEBP and lipocalin-2 (LCN2) levels were measured in type 2 diabetic subjects. TonEBP haploinsufficient mice were used to investigate the role of TonEBP in HFD/STZ-induced diabetic mice. In addition, RAW 264.7 macrophages were given a lipopolysaccharide (LPS)/high glucose (HG) treatment. Using a siRNA, we examined the effects of TonEBP knockdown on RAW264 cell' medium/HG-treated mouse hippocampal HT22 cells. RESULTS: Circulating TonEBP and LCN2 levels were higher in experimental diabetic mice or type 2 diabetic patients with cognitive impairment. TonEBP haploinsufficiency ameliorated the diabetic phenotypes including adipose tissue macrophage infiltrations, neuroinflammation, blood-brain barrier leakage, and memory deficits. Systemic and hippocampal LCN2 proteins were reduced in diabetic mice by TonEBP haploinsufficiency. TonEBP (+ / -) mice had a reduction of hippocampal heme oxygenase-1 (HO-1) expression compared to diabetic wild-type mice. In particular, we found that TonEBP bound to the LCN2 promoter in the diabetic hippocampus, and this binding was abolished by TonEBP haploinsufficiency. Furthermore, TonEBP knockdown attenuated LCN2 expression in lipopolysaccharide/high glucose-treated mouse hippocampal HT22 cells. CONCLUSIONS: These findings indicate that TonEBP may promote neuroinflammation and cognitive impairment via upregulation of LCN2 in diabetic mice.

Spearman's hypothesis tested comparing Korean young adults with various other groups of young adults on the items of the Advanced Progressive Matrices.

Spearman's hypothesis tested at the subtest level of an IQ battery states that differences between races on the subtests of an IQ battery are a function of the g loadings of these subtests, such that there are small differences between races on subtests with low g loadings and large differences between races on subtests with high g loadings. Jensen (1998) stated that Spearman's hypothesis is a law-like phenomenon. It has also been confirmed many times at the level of items of the Raven's Progressive Matrices. This study hypothesizes that with concern to Spearman's hypothesis, subtests and items function in fundamentally the same way, and tested whether Spearman's hypothesis is confirmed at the item level for White-East Asian comparisons. A group of Korean young adults (N=205) was compared with other groups of young adults from Canada, the US, Russia, Peru and South Africa (total N=4770) who took the Advanced Progressive Matrices. Spearman's hypothesis was strongly confirmed with a sample-size-weighted r with a value of 0.63. Computing the g loadings of the items of the Raven with either the Raven-g or the Wechsler-g led to the same conclusions. Tests of Spearman's hypothesis yielded less-strong outcomes when the 36-item Advanced Progressive Matrices were used than when the 60-item Standard Progressive Matrices were used. There is a substantial correlation between sample size and the outcome of Spearman's hypothesis. So, all four hypotheses were confirmed, showing that a part of the subtest-level nomological net replicates at the item level, strengthening the position that, with concern to Spearman's hypothesis, subtests and items function fundamentally the same. It is concluded that Spearman's hypothesis is still a law-like phenomenon. Detailed suggestions for follow-up research are made.

Crystal structure of CagL from Helicobacter pylori K74 strain.

Helicobacter pylori (Hp) CagL is a component of the type IV secretion system (T4SS) and interacts with integrin in host cells through its flexible RGD domain to translocate CagA. Differences in CagL amino acid polymorphisms between Western and East-Asian Hps are correlated with clinical outcome. CagL of East-Asian clinical Hp isolate K74 (CagL(K74)) contains multiple residue variations upstream of RGD motif and has different integrin binding affinities compared to those of CagL from Western Hp 26695. Here, we report the crystal structure of CagL(K74). The structure displayed a six-helix bundle including two short α-helices, and the RGD motif was found in the long rigid α2 helix flanked by the conserved protease-sensitive and RGD-helper sequences, as observed in CagL(26695). However, two additional salt bridges were found between the helices compared with the CagL(26695) structure, suggesting that the putative flexible region harboring the RGD motif may be more stable in this CagL variant.

NO CLEAR LINK BETWEEN G LOADINGS AND HERITABILITY: A TWIN STUDY FROM KOREA.

A fundamental theoretical question in intelligence research is to what extent the g factor and heritability coefficients of the subtests of an IQ battery are correlated. Five studies from Western countries showed modest to strong positive correlations (range = .43-.77), and six studies from a Japanese meta-analysis showed zero to modest correlations (range = -0.01-0.59). The Western and Japanese studies were compared with a Korean sample of 24 monozygotic and 20 dizygotic young adult twin pairs administered the Korean Wechsler Adult Intelligence Scale-Revised (WAIS-R). A univariate twin model was applied to all subscale scores leading to estimates of heritability for all scales. g loadings were also computed using principal-axis factor analysis. Finally, the correlation between the heritabilities and the g loadings of these scales were computed. The correlations of r = -.15 were not in line with previous studies. It could be that Spearman's hypothesis is less strongly confirmed for Northeast Asians, but it is also possible that the study will be an outlier in a future meta-analysis. More primary research and a meta-analysis of all studies are needed.

SPIN90 dephosphorylation is required for cofilin-mediated actin depolymerization in NMDA-stimulated hippocampal neurons.

Actin plays a fundamental role in the regulation of spine morphology (both shrinkage and enlargement) upon synaptic activation. In particular, actin depolymerization is crucial for the spine shrinkage in NMDAR-mediated synaptic depression. Here, we define the role of SPIN90 phosphorylation/dephosphorylation in regulating actin depolymerization via modulation of cofilin activity. When neurons were treated with NMDA, SPIN90 was dephosphorylated by STEP61 (striatal-enriched protein tyrosine phosphatase) and translocated from the spines to the dendritic shafts. In addition, phosphorylated SPIN90 bound cofilin and then inhibited cofilin activity, suggesting that SPIN90 dephosphorylation is a prerequisite step for releasing cofilin so that cofilin can adequately sever actin filaments into monomeric form. We found that SPIN90 YE, a phosphomimetic mutant, remained in the spines after NMDAR activation where it bound cofilin, thereby effectively preventing actin depolymerization. This led to inhibition of the activity-dependent redistribution of cortactin and drebrin A, as well as of the morphological changes in the spines that underlie synaptic plasticity. These findings indicate that NMDA-induced SPIN90 dephosphorylation and translocation initiates cofilin-mediated actin dynamics and spine shrinkage within dendritic spines, thereby modulating synaptic activity.

Implementation of an ultra-sensitive microwell-based electrochemical sensor for the detection of Alzheimer's disease.

Alzheimer's Disease (AD) is one of the most common neurodegenerative disorders in elderly people. It is diagnosed by detecting amyloid beta (Aß) protein in cerebrospinal fluid (CSF) obtained by lumbar puncture or through expensive positron emission tomography (PET) imaging. Although blood-based diagnosis of AD offers a less invasive and cost-effective alternative, the quantification of Aß is technically challenging due to its low abundance in peripheral blood. To address this, we developed a compact yet highly sensitive microwell-based electrochemical sensor with a densely packed microelectrode array (20 by 20) for enhancing sensitivity. Employing microwells on the working and counter electrodes minimized the leakage current from the metallic conductors into the assay medium, refining the signal fidelity. We achieved a detection limit <10 fg/mL for Aß by elevating the signal-to-noise ratio, thus capable of AD biomarker quantification. Moreover, the microwell structure maintained the performance irrespective of variations in bead number, indicative of the sensor's robustness. The sensor's efficacy was validated through the analysis of Aß concentrations in plasma samples from 96 subjects, revealing a significant distinction between AD patients and healthy controls with an area under the receiver operating characteristic curve (AUC) of 0.85. Consequently, our novel microwell-based electrochemical biosensor represents a highly sensitive platform for detecting scant blood-based biomarkers, including Aß, offering substantial potential for advancing AD diagnostics.

Prefrontal intra-individual ERP variability and its asymmetry: exploring its biomarker potential in mild cognitive impairment.

BACKGROUND: The worldwide trend of demographic aging highlights the progress made in healthcare, albeit with health challenges like Alzheimer's Disease (AD), prevalent in individuals aged 65 and above. Its early detection at the mild cognitive impairment (MCI) stage is crucial. Event-related potentials (ERPs) obtained by averaging EEG segments responded to repeated events are vital for cognitive impairment research. Consequently, examining intra-trial ERP variability is vital for comprehending fluctuations within psychophysiological processes of interest. This study aimed to investigate cognitive deficiencies and instability in MCI using ERP variability and its asymmetry from a prefrontal two-channel EEG device. METHODS: In this study, ERP variability for both target and non-target responses was examined using the response variance curve (RVC) in a sample comprising 481 participants with MCI and 1,043 age-matched healthy individuals. The participants engaged in auditory selective attention tasks. Cognitive decline was assessed using the Seoul Neuropsychological Screening Battery (SNSB) and the Mini-Mental State Examination (MMSE). The research employed various statistical methods, including independent t-tests, and univariate and multiple logistic regression analyses. These analyses were conducted to investigate group differences and explore the relationships between neuropsychological test results, ERP variability and its asymmetry measures, and the prevalence of MCI. RESULTS: Our results showed that patients with MCI exhibited unstable cognitive processing, characterized by increased ERP variability compared to cognitively normal (CN) adults. Multiple logistic regression analyses confirmed the association between ERP variability in the target and non-target responses with MCI prevalence, independent of demographic and neuropsychological factors. DISCUSSION: The unstable cognitive processing in the MCI group compared to the CN individuals implies abnormal neurological changes and reduced and (or) unstable attentional maintenance during cognitive processing. Consequently, utilizing ERP variability measures from a portable EEG device could serve as a valuable addition to the conventional ERP measures of latency and amplitude. This approach holds significant promise for identifying mild cognitive deficits and neural alterations in individuals with MCI.

A screening method for mild cognitive impairment in elderly individuals combining bioimpedance and MMSE.

We investigated a screening method for mild cognitive impairment (MCI) that combined bioimpedance features and the Korean Mini-Mental State Examination (K-MMSE) score. Data were collected from 539 subjects aged 60 years or older at the Gwangju Alzheimer's & Related Dementias (GARD) Cohort Research Center, A total of 470 participants were used for the analysis, including 318 normal controls and 152 MCI participants. We measured bioimpedance, K-MMSE, and the Seoul Neuropsychological Screening Battery (SNSB-II). We developed a multiple linear regression model to predict MCI by combining bioimpedance variables and K-MMSE total score and compared the model's accuracy with SNSB-II domain scores by the area under the receiver operating characteristic curve (AUROC). We additionally compared the model performance with several machine learning models such as extreme gradient boosting, random forest, support vector machine, and elastic net. To test the model performances, the dataset was divided into a training set (70%) and a test set (30%). The AUROC values of SNSB-II scores were 0.803 in both sexes, 0.840 for males, and 0.770 for females. In the combined model, the AUROC values were 0.790 (0.773) for males (and females), which were significantly higher than those from the model including MMSE scores alone (0.723 for males and 0.622 for females) or bioimpedance variables alone (0.640 for males and 0.615 for females). Furthermore, the accuracies of the combined model were comparable to those of machine learning models. The bioimpedance-MMSE combined model effectively distinguished the MCI participants and suggests a technique for rapid and improved screening of the elderly population at risk of cognitive impairment.

Early onset diagnosis in Alzheimer's disease patients via amyloid-ß oligomers-sensing probe in cerebrospinal fluid.

Amyloid-ß (Aß) oligomers are implicated in the onset of Alzheimer's disease (AD). Herein, quinoline-derived half-curcumin-dioxaborine (Q-OB) fluorescent probe was designed for detecting Aß oligomers by finely tailoring the hydrophobicity of the biannulate donor motifs in donor-π-acceptor structure. Q-OB shows a great sensing potency in dynamically monitoring oligomerization of Aß during amyloid fibrillogenesis in vitro. In addition, we applied this strategy to fluorometrically analyze Aß self-assembly kinetics in the cerebrospinal fluids (CSF) of AD patients. The fluorescence intensity of Q-OB in AD patients' CSF revealed a marked change of log (I/I0) value of 0.34 ± 0.13 (cognitive normal), 0.15 ± 0.12 (mild cognitive impairment), and 0.14 ± 0.10 (AD dementia), guiding to distinguish a state of AD continuum for early diagnosis of AD. These studies demonstrate the potential of our approach can expand the currently available preclinical diagnostic platform for the early stages of AD, aiding in the disruption of pathological progression and the development of appropriate treatment strategies.

Multi-Ethnic Norms for Volumes of Subcortical and Lobar Brain Structures Measured by Neuro I: Ethnicity May Improve the Diagnosis of Alzheimer's Disease1.

Background: We previously demonstrated the validity of a regression model that included ethnicity as a novel predictor for predicting normative brain volumes in old age. The model was optimized using brain volumes measured with a standard tool FreeSurfer. Objective: Here we further verified the prediction model using newly estimated brain volumes from Neuro I, a quantitative brain analysis system developed for Korean populations. Methods: Lobar and subcortical volumes were estimated from MRI images of 1,629 normal Korean and 786 Caucasian subjects (age range 59-89) and were predicted in linear regression from ethnicity, age, sex, intracranial volume, magnetic field strength, and scanner manufacturers. Results: In the regression model predicting the new volumes, ethnicity was again a substantial predictor in most regions. Additionally, the model-based z-scores of regions were calculated for 428 AD patients and the matched controls, and then employed for diagnostic classification. When the AD classifier adopted the z-scores adjusted for ethnicity, the diagnostic accuracy has noticeably improved (AUC = 0.85, ΔAUC = + 0.04, D = 4.10, p < 0.001). Conclusions: Our results suggest that the prediction model remains robust across different measurement tool, and ethnicity significantly contributes to the establishment of norms for brain volumes and the development of a diagnostic system for neurodegenerative diseases.