Identification of molecular subtypes of dementia by using blood-proteins interaction-aware graph propagational network.

Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due to their low variability, cost-effectiveness, and minimal invasiveness in diagnostic procedures. Machine learning (ML) methods have been applied to enhance accuracy of the biomarker discovery. However, previous ML-based studies often overlook interactions between proteins, which are crucial in complex disorders like dementia. While protein-protein interactions (PPIs) have been used in network models, these models often fail to fully capture the diverse properties of PPIs due to their local awareness. This drawback increases the chance of neglecting critical components and magnifying the impact of noisy interactions. In this study, we propose a novel graph-based ML model for dementia subtype diagnosis, the graph propagational network (GPN). By propagating the independent effect of plasma proteins on PPI network, the GPN extracts the globally interactive effects between proteins. Experimental results showed that the interactive effect between proteins yielded to further clarify the differences between dementia subtype groups and contributed to the performance improvement where the GPN outperformed existing methods by 10.4% on average.

Ethnic differences in the prevalence of amyloid positivity and cognitive trajectories.

INTRODUCTION: We investigated the prevalence of amyloid beta (Aß) positivity (+) and cognitive trajectories in Koreans and non-Hispanic Whites (NHWs). METHODS: We included 5121 Koreans from multiple centers across South Korea and 929 NHWs from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Participants underwent Aß positron emission tomography and were categorized into cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia stages. Age, sex, education, and apolipoprotein E. genotype were adjusted using multivariable logistic regression and stabilized inverse probability of treatment weights based on the propensity scores to mitigate imbalances in these variables. RESULTS: The prevalence of Aß+ was lower in CU Koreans than in CU NHWs (adjusted odds ratio 0.60). Aß+ Koreans showed a faster cognitive decline than Aß+ NHWs in the CU (B = -0.314, p = .004) and MCI stages (B = -0.385, p < .001). DISCUSSION: Ethnic characteristics of Aß biomarkers should be considered in research and clinical application of Aß-targeted therapies in diverse populations. HIGHLIGHTS: Koreans have a lower prevalence of Aß positivity compared to NHWs in the CU stage. The effects of Alzheimer's risk factors on Aß positivity differ between Koreans and NHWs. Aß-positive (Aß+) Koreans show faster cognitive decline than Aß+ NHWs in the CU and MCI stages.

Assessing cognitive impairment and disability in older adults through the lens of whole brain white matter patterns.

INTRODUCTION: This study aimed to explore the potential of whole brain white matter patterns as novel neuroimaging biomarkers for assessing cognitive impairment and disability in older adults. METHODS: We conducted an in-depth analysis of magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) scans in 454 participants, focusing on white matter patterns and white matter inter-subject variability (WM-ISV). RESULTS: The white matter pattern ensemble model, combining MRI and amyloid PET, demonstrated a significantly higher classification performance for cognitive impairment and disability. Participants with Alzheimer's disease (AD) exhibited higher WM-ISV than participants with subjective cognitive decline, mild cognitive impairment, and vascular dementia. Furthermore, WM-ISV correlated significantly with blood-based biomarkers (such as glial fibrillary acidic protein and phosphorylated tau-217 [p-tau217]), and cognitive function and disability scores. DISCUSSION: Our results suggest that white matter pattern analysis has significant potential as an adjunct neuroimaging biomarker for clinical decision-making and determining cognitive impairment and disability. HIGHLIGHTS: The ensemble model combined both magnetic resonance imaging (MRI) and amyloid positron emission tomography (PET) and demonstrated a significantly higher classification performance for cognitive impairment and disability. Alzheimer's disease (AD) revealed a notably higher heterogeneity compared to that in subjective cognitive decline, mild cognitive impairment, or vascular dementia. White matter inter-subject variability (WM-ISV) was significantly correlated with blood-based biomarkers (glial fibrillary acidic protein and phosphorylated tau-217 [p-tau217]) and with the polygenic risk score for AD. White matter pattern analysis has significant potential as an adjunct neuroimaging biomarker for clinical decision-making processes and determining cognitive impairment and disability.

Independent replication of advanced brain age in mild cognitive impairment and dementia: detection of future cognitive dysfunction.

We previously developed a novel machine-learning-based brain age model that was sensitive to amyloid. We aimed to independently validate it and to demonstrate its utility using independent clinical data. We recruited 650 participants from South Korean memory clinics to undergo magnetic resonance imaging and clinical assessments. We employed a pretrained brain age model that used data from an independent set of largely Caucasian individuals (n = 757) who had no or relatively low levels of amyloid as confirmed by positron emission tomography (PET). We investigated the association between brain age residual and cognitive decline. We found that our pretrained brain age model was able to reliably estimate brain age (mean absolute error = 5.68 years, r(650) = 0.47, age range = 49-89 year) in the sample with 71 participants with subjective cognitive decline (SCD), 375 with mild cognitive impairment (MCI), and 204 with dementia. Greater brain age was associated with greater amyloid and worse cognitive function [Odds Ratio, (95% Confidence Interval {CI}): 1.28 (1.06-1.55), p = 0.030 for amyloid PET positivity; 2.52 (1.76-3.61), p < 0.001 for dementia]. Baseline brain age residual was predictive of future cognitive worsening even after adjusting for apolipoprotein E e4 and amyloid status [Hazard Ratio, (95% CI): 1.94 (1.33-2.81), p = 0.001 for total 336 follow-up sample; 2.31 (1.44-3.71), p = 0.001 for 284 subsample with baseline Clinical Dementia Rating ≤ 0.5; 2.40 (1.43-4.03), p = 0.001 for 240 subsample with baseline SCD or MCI]. In independent data set, these results replicate our previous findings using this model, which was able to delineate significant differences in brain age according to the diagnostic stages of dementia as well as amyloid deposition status. Brain age models may offer benefits in discriminating and tracking cognitive impairment in older adults.

Trans-ethnic genomic informed risk assessment for Alzheimer's disease: An International Hundred K+ Cohorts Consortium study.

BACKGROUND: As a collaboration model between the International HundredK+ Cohorts Consortium (IHCC) and the Davos Alzheimer's Collaborative (DAC), our aim was to develop a trans-ethnic genomic informed risk assessment (GIRA) algorithm for Alzheimer's disease (AD). METHODS: The GIRA model was created to include polygenic risk score calculated from the AD genome-wide association study loci, the apolipoprotein E haplotypes, and non-genetic covariates including age, sex, and the first three principal components of population substructure. RESULTS: We validated the performance of the GIRA model in different populations. The proteomic study in the participant sites identified proteins related to female infertility and autoimmune thyroiditis and associated with the risk scores of AD. CONCLUSIONS: As the initial effort by the IHCC to leverage existing large-scale datasets in a collaborative setting with DAC, we developed a trans-ethnic GIRA for AD with the potential of identifying individuals at high risk of developing AD for future clinical applications.

Dementia key gene identification with multi-layered SNP-gene-disease network.

MOTIVATION: Recently, various approaches for diagnosing and treating dementia have received significant attention, especially in identifying key genes that are crucial for dementia. If the mutations of such key genes could be tracked, it would be possible to predict the time of onset of dementia and significantly aid in developing drugs to treat dementia. However, gene finding involves tremendous cost, time and effort. To alleviate these problems, research on utilizing computational biology to decrease the search space of candidate genes is actively conducted.In this study, we propose a framework in which diseases, genes and single-nucleotide polymorphisms are represented by a layered network, and key genes are predicted by a machine learning algorithm. The algorithm utilizes a network-based semi-supervised learning model that can be applied to layered data structures. RESULTS: The proposed method was applied to a dataset extracted from public databases related to diseases and genes with data collected from 186 patients. A portion of key genes obtained using the proposed method was verified in silico through PubMed literature, and the remaining genes were left as possible candidate genes. AVAILABILITY AND IMPLEMENTATION: The code for the framework will be available at http://www.alphaminers.net/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Risk of Mortality in Elderly Coronavirus Disease 2019 Patients With Mental Health Disorders: A Nationwide Retrospective Study in South Korea.

OBJECTIVE: This study aimed to investigate the different clinical characteristics among elderly coronavirus disease 2019 (COVID-19) patients with and without mental disorders in South Korea and determine if these characteristics have an association with underlying mental disorders causing mortality. METHOD: A population-based comparative cohort study was conducted using the national claims database. Individuals aged ≥65 years with confirmed COVID-19 between January 1, 2020 and April 10, 2020 were assessed. The endpoints for evaluating mortality for all participants were death, 21 days after diagnosis, or April 10, 2020. The risk of mortality associated with mental disorders was estimated using Cox hazards regression. RESULTS: We identified 814 elderly COVID-19 patients (255 [31.3%] with mental disorder and 559 [68.7%] with nonmental disorder). Individuals with mental disorders were found more likely to be older, taking antithrombotic agents, and had diabetes, hypertension, chronic obstructive lung disease, and urinary tract infections than those without mental disorders. After propensity score stratification, our study included 781 patients in each group (236 [30.2%] with mental disorder and 545 [69.8%] with nonmental disorder). The mental disorder group showed higher mortality rates than the nonmental disorder group (12.7% [30/236] versus 6.8% [37/545]). However, compared to patients without mental disorders, the hazard ratio (HR) for mortality in elderly COVID-19 patients with mental disorders was not statistically significant (HR: 1.57, 95%CI: 0.95-2.56). CONCLUSION: Although the association between mental disorders in elderly individuals and mortality in COVID-19 is unclear, this study suggests that elderly patients with comorbid conditions and those taking psychiatric medications might be at a higher risk of COVID-19.

The association of diabetes duration and glycemic control with depression in elderly men with type 2 diabetes mellitus.

BACKGROUND: The prevalence of depression and type 2 diabetes mellitus (T2DM) are increasing in the elderly and are reportedly related to each other. We evaluated the relationship between T2DM-related factors and the degree of depression in elderly patients with T2DM based on gender. MATERIALS AND METHODS: A total of 155 patients with T2DM (56 males and 99 females aged ≥ 65 years) from seven hospitals were included in the study. To assess the status of depressive symptoms, the short form of the Geriatric Depression Scale-Korean version (SGDS-K) was used. We evaluated DM-related factors, such as T2DM duration, hemoglobin A1c (HbA1c) levels, and T2DM complications, as well as other possible factors that could affect depression, such as cognitive function, physical function, education level, and other personal factors. RESULTS: Mean age of the participants was 71.3 years with a mean HbA1c level of 7.6%. Males in the good glycemic control group (HbA1c <7%) showed lower SGDS-K scores compared to those in the poor glycemic control group, and the mean SGDS-K score was higher in the group with a longer duration of DM (M10 years); however, no difference was observed in females. Males and females with microvascular and macrovascular complications tended to have higher SGDS-K scores than participants with no microvascular or macrovascular complications. A multiple linear regression analysis revealed that DM duration and HbA1c level were independently associated with SGDS-K scores in males. CONCLUSION: Greater depression was associated with poorer glycemic control and a longer duration of DM in elderly males with T2DM.

The moderating effect of religiosity on caregiving burden and depressive symptoms in caregivers of patients with dementia.

OBJECTIVES: This study explored whether religiosity/spirituality has a protective role against negative caregiving outcomes, in a large multicenter nationwide sample of caregivers of patients with dementia in South Korea. Additionally, this study was the first to examine whether religiosity/spirituality could affect caregiving outcomes according to the various religious affiliations of caregivers. METHODS: The study was conducted on a sample of 476 caregivers of patients with dementia participated in the Clinical Research Center for Dementia of South Korea (CREDOS). We examined the moderating effect of each of the three dimensions of religiosity/spirituality (organizational religious activity, ORA; non-organizational religious activity, NORA; intrinsic religiosity, IR) on the relationship between activities of daily living (ADL) of patients with dementia and caregiving burden and depressive symptoms of caregivers, using a series of hierarchical regression analyses. In addition, these analyses were conducted according to the religious affiliations of the caregivers. RESULTS: ORA, NORA, and IR of religiosity/spirituality alleviated the effect of ADL of patients on caregiving burden. ORA and IR moderated the relationship between ADL of patients and depressive symptoms of caregivers. These moderating effects of religiosity on caregiving outcomes were different according to various religious groups. CONCLUSION: We have identified religiosity/spirituality as a protective factor for caregivers of patients with dementia. The sub-dimensions of religiosity as moderators were different by religious affiliations of caregivers. Further studies are needed to investigate the specific religiosity-related factors which could positively impact the mental health of the caregivers of patients with dementia by religions.

Influence of personality on depression, burden, and health-related quality of life in family caregivers of persons with dementia.

BACKGROUND: Personality may predispose family caregivers to experience caregiving differently in similar situations and influence the outcomes of caregiving. A limited body of research has examined the role of some personality traits for health-related quality of life (HRQoL) among family caregivers of persons with dementia (PWD) in relation to burden and depression. METHODS: Data from a large clinic-based national study in South Korea, the Caregivers of Alzheimer's Disease Research (CARE), were analyzed (N = 476). Path analysis was performed to explore the association between family caregivers' personality traits and HRQoL. With depression and burden as mediating factors, direct and indirect associations between five personality traits and HRQoL of family caregivers were examined. RESULTS: Results demonstrated the mediating role of caregiver burden and depression in linking two personality traits (neuroticism and extraversion) and HRQoL. Neuroticism and extraversion directly and indirectly influenced the mental HRQoL of caregivers. Neuroticism and extraversion only indirectly influenced their physical HRQoL. Neuroticism increased the caregiver's depression, whereas extraversion decreased it. Neuroticism only was mediated by burden to influence depression and mental and physical HRQoL. CONCLUSIONS: Personality traits can influence caregiving outcomes and be viewed as an individual resource of the caregiver. A family caregiver's personality characteristics need to be assessed for tailoring support programs to get the optimal benefits from caregiver interventions.

Psychometric evaluation of the Korean version of the Suicidal Ideation Scale in mentally ill patients living in the community.

OBJECTIVE: The purpose of this study was to translate the Suicidal Ideation Scale (SIS) into Korean (SIS-K) and then evaluate its psychometric properties in mentally ill Korean patients living in the community. METHODS: The SIS-K was translated into Korean using a translation and back-translation technique. A sample of 396 patients with mental disorders was recruited from regional mental health centres in Korea. Factorial-construct validity was tested using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The data were randomly split into two subsamples: one used for EFA to identify the underlying structure of the items, and the other used for CFA to test whether the underlying structure was supported by actual data. Convergent validity, known-groups validity and internal-consistency reliability were tested. RESULTS: Exploratory factor analysis extracted nine items clustered into two subscales that accounted for 68.59% of the variance. One item ('I feel there is no solution to my problems other than taking my own life') was deleted. The structure of the two subscales was supported by CFA. The SIS-K score was moderately correlated with depression, and the scale demonstrated convergent validity. The SIS-K scores were significantly higher in patients who had attempted suicide, implying the presence of satisfactory known-groups validity. Cronbach's alpha of the total SIS-K was 0.91. CONCLUSIONS: The study has demonstrated the excellent psychometric properties of the SIS-K. The SIS-K is brief and easy to complete, and so it can be applied in both practice and research to patients with mental disorders. This cultural validation of the SIS-K will promote both domestic and international studies of suicidal ideation.

Factors related to prevalence, persistence, and incidence of depressive symptoms in mild cognitive impairment: vascular depression construct.

OBJECTIVE: Depression is prevalent among elders with cognitive impairment. Cerebral white matter hyperintensities (WMH) have consistently been implicated in late-life depression and in cognitive impairment. This study aims to clarify the factors related to prevalence, persistence, and new onset of depressive symptoms in subjects with mild cognitive impairment (MCI). METHODS: As part of a multicenter prospective study, the Clinical Research Center for Dementia of South Korea (CREDOS) Study, we enrolled 590 subjects diagnosed with MCI and with no prior history of depression. Depressive symptoms were assessed by the Korean version of the Geriatric Depression Scale short form (SGDS-K) at baseline and at follow-up visits. Brain magnetic resonance imaging was performed at baseline to quantify WMH using a visual rating scale. RESULTS: The baseline prevalence of clinically significant depressive symptoms (SGDS-K ≥5) was 51.4%, and this feature was associated with younger age, lower educational achievement, and higher Clinical Dementia Rating Sum of Boxes (CDR-SB) scores. Persistence of depressive symptoms across the study period was significantly associated with baseline CDR-SB and depression scores. New onset of depression (SGDS-K ≥8; incidence 15.7%) among subjects free of depressive symptoms (SGDS-K <5) at baseline was associated with severe deep subcortical, but not periventricular, WMH. CONCLUSIONS: In patients with MCI aged 50 years or older, depressive symptoms were highly prevalent. Cognitive status was closely related to both prevalence and persistence of depressive symptoms, while new onset of depression was associated with deep subcortical WMH severity in this MCI cohort. Our findings provide prospective evidence consistent with the vascular depression hypothesis. Copyright © 2015 John Wiley & Sons, Ltd.

Decreased hemoglobin levels, cerebral small-vessel disease, and cortical atrophy: among cognitively normal elderly women and men.

BACKGROUND: Decreased hemoglobin levels increase the risk of developing dementia among the elderly. However, the underlying mechanisms that link decreased hemoglobin levels to incident dementia still remain unclear, possibly due to the fact that few studies have reported on the relationship between low hemoglobin levels and neuroimaging markers. We, therefore, investigated the relationships between decreased hemoglobin levels, cerebral small-vessel disease (CSVD), and cortical atrophy in cognitively healthy women and men. METHODS: Cognitively normal women (n = 1,022) and men (n = 1,018) who underwent medical check-ups and magnetic resonance imaging (MRI) were enrolled at a health promotion center. We measured hemoglobin levels, white matter hyperintensities (WMH) scales, lacunes, and microbleeds. Cortical thickness was automatically measured using surface based methods. Multivariate regression analyses were performed after controlling for possible confounders. RESULTS: Decreased hemoglobin levels were not associated with the presence of WMH, lacunes, or microbleeds in women and men. Among women, decreased hemoglobin levels were associated with decreased cortical thickness in the frontal (Estimates, 95% confidence interval, -0.007, (-0.013, -0.001)), temporal (-0.010, (-0.018, -0.002)), parietal (-0.009, (-0.015, -0.003)), and occipital regions (-0.011, (-0.019, -0.003)). Among men, however, no associations were observed between hemoglobin levels and cortical thickness. CONCLUSION: Our findings suggested that decreased hemoglobin levels affected cortical atrophy, but not increased CSVD, among women, although the association is modest. Given the paucity of modifiable risk factors for age-related cognitive decline, our results have important public health implications.

Gender differences in risk factors for transition from mild cognitive impairment to Alzheimer's disease: A CREDOS study.

BACKGROUND: Women are subject to a disproportionate burden from Alzheimer's disease (AD) and sex differences exist in treatment response and prognosis of the disease. Yet gender-specific risk factors have not been widely studied. We aimed to investigate gender-specific risk factors for AD in subjects with mild cognitive impairment (MCI). METHODS: Participants (n=294) with MCI were recruited from a nationwide, prospective cohort study of dementia and were followed for a median (range) of 13.8 (6.0-36.0) months. Sex-stratified associations of progression to AD with baseline characteristics were explored. RESULTS: Seventy-four individuals (25.2%) developed incident dementia (67 AD) during follow-up. Significant risk factors for probable AD differed by sex. In men, the significant risk factors were severe periventricular white matter hyperintensities, and poorer global cognitive function. In women, older age, clinically significant depressive symptoms at baseline, and positive APOE ε4 alleles were the significant risk factors. CONCLUSIONS: Risk factors for progression from MCI to probable AD differed in men and women. These results may translate to gender-specific preventative or therapeutic strategies for patients with MCI.

Association of alcohol drinking with verbal and visuospatial memory impairment in older adults: Clinical Research Center for Dementia of South Korea (CREDOS) study.

BACKGROUND: The study's aim was to examine the association of alcohol consumption with verbal and visuospatial memory impairment in older people. METHODS: Participants were 1,572, aged ≥60 years, in the hospital-based registry of the Clinical Research Center for Dementia of South Korea (CREDOS). Moderate drinking was defined as no more than seven drinks per week and three drinks per day. Memory impairment was defined as performance with more than 1 standard deviation below the mean value on the Seoul Verbal Learning Test and Rey Complex Figure Test. RESULTS: Those who consumed alcohol moderately, compared with abstainers, had a lower odds of verbal memory impairment (Odds Ratio [OR] = 0.64; 95% Confidence Interval [CI]: 0.46-0.87), adjusting for covariates. Visuospatial memory, however, was not significantly associated with alcohol consumption. CONCLUSIONS: Moderate alcohol drinking is associated with a reduced likelihood of verbal memory impairment among older people attending memory clinics.

Effects of a multidomain lifestyle modification on cognitive function in older adults: an eighteen-month community-based cluster randomized controlled trial.

BACKGROUND: A healthy lifestyle may protect against cognitive decline. We examined outcomes in elderly individuals after 18 months of a five-group intervention program consisting of various modalities to prevent cognitive decline. METHODS: We conducted a cluster randomized controlled trial assessing 460 community-dwelling individuals aged 60 years and older in a geriatric community mental health center in Suwon, Republic of Korea, between 2008 and 2010. We developed an intervention program based on the principles of contingency management, which could be delivered by ordinary primary health workers. Group A (n = 81) received standard care services. Group B (n = 80) received bimonthly (once every 2 months) telephonic care management. Group C (n = 111) received monthly telephonic care management and educational materials similar to those in group B. Group D (n = 93) received bimonthly health worker-initiated visits and counseling. Group E (n = 94) received bimonthly health worker-initiated visits, counseling, and rewards for adherence to the program. RESULTS: The primary outcome was the change in Mini-Mental State Examination (MMSE) scores from baseline to the final follow-up visit at 18 months. Group E showed superior cognitive function to group A (adjusted coefficient ß = 0.99, p = 0.044), with participation in cognitive activities being the most important determining factor among several health behaviors (adjusted coefficient ß = 1.04, p < 0.01). CONCLUSIONS: Engaging in cognitive activities, in combination with positive health behaviors, may be most beneficial in preserving cognitive abilities in community-dwelling older adults.

A new classification system for ischemia using a combination of deep and periventricular white matter hyperintensities.

The Clinical Research Center for Dementia of South Korea (CREDOS) group developed a new classification system for ischemia using a combination of deep and periventricular white matter hyperintensities (WMHs). In this study, we aimed to evaluate the validity of the CREDOS ischemia classification system. A total of 352 patients with cognitive impairments were included. Their WMH scores were rated using the CREDOS WMH visual rating scale. These patients were divided into 3 groups according to the CREDOS ischemia classification system. The volume of WMH was also automatically measured. The number of lacunes and microbleeds (MBs) were counted. The CREDOS ischemia classification system was revised with factor analysis using vascular risk factors and cerebrovascular disease (CVD) markers (WMH volume, lacunes, and MBs). External validation was performed in another group of patients with cognitive impairment using multinomial logistic regression analysis. The CREDOS WMH visual rating scale showed excellent correlation with the automatically measured volume of WMH. The factor analysis showed that the severe group was expanded to D3P1 and D3P2 in the revised CREDOS ischemia classification system. In the validation group, the presence of vascular risk factors and the severity of CVD markers could be distinguished according to the revised CREDOS ischemia classification. We validated a newly developed classification system for ischemia. This simple visual classification system was capable of providing information on vascular risk factors and CVD markers by simply rating WMH on magnetic resonance imaging.

Association of Geriatric Depressive Symptoms and Government-Initiated Senior Employment Program: A Population-Based Study.

OBJECTIVE: The impact of the government-initiated senior employment program (GSEP) on geriatric depressive symptoms is underexplored. Unearthing this connection could facilitate the planning of future senior employment programs and geriatric depression interventions. In the present study, we aimed to elucidate the possible association between geriatric depressive symptoms and GSEP in older adults. METHODS: This study employed data from 9,287 participants aged 65 or older, obtained from the 2020 Living Profiles of Older People Survey. We measured depressive symptoms using the Korean version of the 15-item Geriatric Depression Scale. The principal exposure of interest was employment status and GSEP involvement. Data analysis involved multiple linear regression. RESULTS: Employment, independent of income level, showed association with decreased depressive symptoms compared to unemployment (p<0.001). After adjustments for confounding variables, participation in GSEP jobs showed more significant reduction in depressive symptoms than non-GSEP jobs (ß=-0.968, 95% confidence interval [CI]=-1.197 to -0.739, p<0.001 for GSEP jobs, ß=-0.541, 95% CI=-0.681 to -0.401, p<0.001 for non-GSEP jobs). Notably, the lower income tertile in GSEP jobs showed a substantial reduction in depressive symptoms compared to all income tertiles in non-GSEP jobs. CONCLUSION: The lower-income GSEP group experienced lower depressive symptoms and life dissatisfaction compared to non-GSEP groups regardless of income. These findings may provide essential insights for the implementation of government policies and community-based interventions.

Plasma protein-based identification of neuroimage-driven subtypes in mild cognitive impairment via protein-protein interaction aware explainable graph propagational network.

As an early indicator of dementia, mild cognitive impairment (MCI) requires specialized treatment according to its subtypes for the effective prevention and management of dementia progression. Based on the neuropathological characteristics, MCI can be classified into Alzheimer's disease (AD)-related cognitive impairment (ADCI) and subcortical vascular cognitive impairment (SVCI), being more likely to progress to AD and subcortical vascular dementia (SVD), respectively. For identifying MCI subtypes, plasma protein biomarkers are recently seen as promising tools due to their minimal invasiveness and cost-effectiveness in diagnostic procedures. Furthermore, the application of machine learning (ML) has led the preciseness in the biomarker discovery and the resulting diagnostics. Nevertheless, previous ML-based studies often fail to consider interactions between proteins, which are essential in complex neurodegenerative disorders such as MCI and dementia. Although protein-protein interactions (PPIs) have been employed in network models, these models frequently do not fully capture the diverse properties of PPIs due to their local awareness. This limitation increases the likelihood of overlooking critical components and amplifying the impact of noisy interactions. In this study, we introduce a new graph-based ML model for classifying MCI subtypes, called eXplainable Graph Propagational Network (XGPN). The proposed method extracts the globally interactive effects between proteins by propagating the independent effect of plasma proteins on the PPI network, and thereby, MCI subtypes are predicted by estimation of the risk effect of each protein. Moreover, the process of model training and the outcome of subtype classification are fully explainable due to the simplicity and transparency of XGPN's architecture. The experimental results indicated that the interactive effect between proteins significantly contributed to the distinct differences between MCI subtype groups, resulting in an enhanced classification performance with an average improvement of 10.0 % compared to existing methods, also identifying key biomarkers and their impact on ADCI and SVCI.

Higher HbA1c Is Associated With Greater 2-Year Progression of White Matter Hyperintensities.

White matter hyperintensity (WMH) lesions on brain MRI images are surrogate markers of cerebral small vessel disease. Longitudinal studies examining the association between diabetes and WMH progression have yielded mixed results. Thus, in this study, we investigated the association between HbA1c, a biomarker for the presence and severity of hyperglycemia, and longitudinal WMH change after adjusting for known risk factors for WMH progression. We recruited 64 participants from South Korean memory clinics to undergo brain MRI at the baseline and a 2-year follow-up. We found the following. First, higher HbA1c was associated with greater global WMH volume (WMHV) changes after adjusting for known risk factors (ß = 7.7 × 10-4; P = 0.025). Second, the association between baseline WMHV and WMHV progression was only significant at diabetic levels of HbA1c (P < 0.05, when HbA1c >6.51%), and non-apolipoprotein E (APOE) ε4 carriers had a stronger association between HbA1c and WMHV progression (ß = -2.59 × 10-3; P = 0.004). Third, associations of WMHV progression with HbA1c were particularly apparent for deep WMHV change (ß = 7.17 × 10-4; P < 0.01) compared with periventricular WMHV change and, for frontal (ß = 5.00 × 10-4; P < 0.001) and parietal (ß = 1.53 × 10-4; P < 0.05) lobes, WMHV change compared with occipital and temporal WMHV change. In conclusion, higher HbA1c levels were associated with greater 2-year WMHV progression, especially in non-APOE ε4 participants or those with diabetic levels of HbA1c. These findings demonstrate that diabetes may potentially exacerbate cerebrovascular and white matter disease.