Predictors Of Cognitive Impairment Research Articles

Prediction of Cognitive Impairment Using Sleep Lifelog Data and LSTM Model

Rapid elderly population growth has increased the number of patients with cognitive impairment (CI). Early detection and ongoing medical treatment can slow CI progression and significantly reduce the cost of managing patients. However, distinguishing CI from natural cognitive decline associated with aging is challenging. Previous studies conducted to identify patients with CI using lifelog data did not consider changes in lifelog data over time because each data point was learned individually. This study introduces a model that predicts patients with CI based on sleep lifelog data and analyzes significant sleep factors that influence cognitive decline. This study followed three steps: (1) collecting sleep lifelog data from elderly Korean people and reconstructing sleep lifelog data as time-series data; (2) building a model to classify CI using a time series of sleep lifelog data and a long short-term memory model; and (3) identifying sleep factors that influence the onset of CI using an explainable AI algorithm. The proposed CI classification model achieved a sensitivity of 0.89, a specificity of 0.80, and an area under the receiver operating characteristic curve of 0.92. This study will facilitate the noninvasive screening, diagnosis, and continuous monitoring of CI in the elderly.

Predictors of cognitive impairment in patients with substance use disorder in Kiambu County, Kenya

Predictors of cognitive impairment in patients with substance use disorder in Kiambu County, Kenya

Serum Retinoic Acid as a Predictor of Cognitive Impairment after Acute Ischemic Stroke

Serum Retinoic Acid as a Predictor of Cognitive Impairment after Acute Ischemic Stroke

Olfactory Function as a Potential Predictor of Cognitive Impairment in Men and Women.

Different previous studies indicated olfactory function as a predictor of several types of cognitive impairment, in particular related to neurodegenerative disease. However, scanty data are available on the role of odor threshold (OT), odor discrimination (OD), and odor identification (OI) as a predictor of cognitive impairment. The aim of this study was to evaluate potential correlations between each factor of the olfactory function versus each specific cognitive domain of the Montreal Cognitive Assessment (MoCA) test on healthy subjects in relation to gender and age. Sniffin' Sticks and MoCA tests were used to determine olfactory function and cognitive abilities, respectively. In men, significant correlations were found in OT versus language index score and OI versus language and executive index score, while in women, OD and OI were correlated to visuospatial index score. Our data suggested that olfactory function (OT, OD, and OI) may be considered a predictor for cognitive impairment in relation to gender and age.

Association between Cardiometabolic Index and Cognitive Function: A Cross-Sectional Study in a Diabetic-Based Population

s Introduction: Diabetes is a significant risk factor for cognitive impairment. Therefore, early identification of cognitive impairment in diabetic patients is particularly important. The aim of this study was to assess the relationship between Cardiometabolic index (CMI) and cognitive function in a diabetic population. Methods: A cross-sectional study was conducted by collecting information from the National Health and Nutrition Examination Survey (NHANES) 2011–2014. Multiple linear regression models were used to investigate the correlation between CMI and low cognitive function in a diabetic population. Threshold effects analysis and fitted smoothing curves were used to describe the nonlinear links. Interaction tests and subgroup analyses were also performed. Results: A total of 1,050 people participated in this study, including 561 men and 489 women. In the fully corrected model, CMI was positively associated with low cognitive performance as assessed by CERAD Word List Learning Test (CERAD W-L), Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST) (OR = 1.37 [1.14, 1.72], p = 7.4 × 10−3), (OR = 1.21 [1.04, 1.51], p = 1.26 × 10−2), and (OR = 1.27 [1.08, 1.63], p = 2.53 × 10−2). Our study found that diabetic patients with higher CMI were at greater risk of developing low cognitive function. The effect of the subgroups on the positive association of CMI with cognitive impairment was not significant. A non-linear association between low cognitive performance and CMI was determined by CERAD W-L, AFT, and DSST (log-likelihood ratio <5 × 10−2). In addition, our also study found that CMI was a better predictor of cognitive impairment in diabetes than weight-adjusted waist index (WWI). Conclusion: Increased CMI is associated with an increased risk of cognitive impairment in people with diabetes. CMI can be used as a new anthropometric measure for predicting cognitive impairment in diabetes, with stronger predictive power than WWI.

Protocol for a construct and clinical validation study of MyCog Mobile: a remote smartphone-based cognitive screener for older adults

IntroductionAnnual cognitive screening in older adults is essential for early detection of cognitive impairment, yet primary care settings face time constraints that present barriers to routine screening. A remote cognitive...

Chronic Active Lesions and Larger Choroid Plexus Explain Cognition and Fatigue in Multiple Sclerosis.

Chronic inflammation may contribute to cognitive dysfunction and fatigue in patients with multiple sclerosis (MS). Paramagnetic rim lesions (PRLs) and choroid plexus (CP) enlargement have been proposed as markers of chronic inflammation in MS being associated with a more severe disease course. However, their relation with cognitive impairment and fatigue has not been fully explored yet. Here, we investigated the contribution of PRL number and volume and CP enlargement to cognitive impairment and fatigue in patients with MS. Brain 3T MRI, neurologic evaluation, and neuropsychological assessment, including the Brief Repeatable Battery of Neuropsychological Tests and Modified Fatigue Impact Scale, were obtained from 129 patients with MS and 73 age-matched and sex-matched healthy controls (HC). PRLs were identified on phase images of susceptibility-weighted imaging, whereas CP volume was quantified using a fully automatic method on brain three-dimensional T1-weighted and fluid-attenuated inversion recovery MRI sequences. Predictors of cognitive impairment and fatigue were identified using random forest. Thirty-six (27.9%) patients with MS were cognitively impaired, and 31/113 (27.4%) patients had fatigue. Fifty-nine (45.7%) patients with MS had ≥1 PRLs (median = 0, interquartile range = 0;2). Compared with HC, patients with MS showed significantly higher T2-hyperintense white matter lesion (WM) volume; lower normalized brain, thalamic, hippocampal, caudate, cortical, and WM volumes; and higher normalized CP volume (p from <0.001 to 0.040). The predictors of cognitive impairment (relative importance) (out-of-bag area under the curve [OOB-AUC] = 0.707) were normalized brain volume (100%), normalized caudate volume (89.1%), normalized CP volume (80.3%), normalized cortical volume (70.3%), number (67.3%) and volume (66.7%) of PRLs, and T2-hyperintense WM lesion volume (64.0%). Normalized CP volume was the only predictor of the presence of fatigue (OOB-AUC = 0.563). Chronic inflammation, with higher number and volume of PRLs and enlarged CP, may contribute to cognitive impairment in MS in addition to gray matter atrophy. The contribution of enlarged CP in explaining fatigue supports the relevance of immune-related processes in determining this manifestation independently of disease severity. PRLs and CP enlargement may contribute to the pathophysiology of cognitive impairment and fatigue in MS, and they may represent clinically relevant therapeutic targets to limit the impact of these clinical manifestations in MS.

Prediction of cognitive impairment using higher order item response theory and machine learning models.

Timely detection of cognitive impairment (CI) is critical for the wellbeing of elderly individuals. The MyCog assessment employs two validated iPad-based measures from the NIH Toolbox® for Assessment of Neurological and Behavioral Function (NIH Toolbox). These measures assess pivotal cognitive domains: Picture Sequence Memory (PSM) for episodic memory and Dimensional Change Card Sort Test (DCCS) for cognitive flexibility. The study involved 86 patients and explored diverse machine learning models to enhance CI prediction. This encompassed traditional classifiers and neural-network-based methods. After 100 bootstrap replications, the Random Forest model stood out, delivering compelling results: precision at 0.803, recall at 0.758, accuracy at 0.902, F1 at 0.742, and specificity at 0.951. Notably, the model incorporated a composite score derived from a 2-parameter higher order item response theory (HOIRT) model that integrated DCCS and PSM assessments. The study's pivotal finding underscores the inadequacy of relying solely on a fixed composite score cutoff point. Instead, it advocates for machine learning models that incorporate HOIRT-derived scores and encompass relevant features such as age. Such an approach promises more effective predictive models for CI, thus advancing early detection and intervention among the elderly.

Serum level of YWHAG as a diagnostic marker of cognitive impairment in Parkinson's disease patients.

Identifying reliable biomarkers for early detection and prediction of cognitive impairment in Parkinson's disease (PD) is crucial for optimal patient care. This study set out to investigate the potential of YWHAG as a diagnostic biomarker for cognitive impairment in PD. We enrolled a total of 331 PD patients and selected 241 patients that met the criteria for cognitive impairment analysis. The patients were classified into three groups: PD-NC: PD patients with normal cognition, PD-MCI: PD patients with mild cognitive impairment, and PD-D: PD patients with dementia. ELISA was employed to assess YWHAG expression, as well as the neurofilament light chain (NfL). Additionally, cognitive impairment was evaluated using MoCA scores. Correlation analysis and receiver operating curve analysis (ROC) were performed to clarify the relationship between YWHAG expression and cognitive impairment. Our findings revealed a significant upregulation of YWHAG expression in both the PD-MCI and PD-D groups compared to the PD-NC group. This observation aligned with the elevated expression of NfL in the PD-MCI and PD-D groups. YWHAG and NfL expression levels displayed negative correlations with MoCA scores and positive associations with age. Furthermore, ROC curve analysis demonstrated the diagnostic efficacy of YWHAG expression in distinguishing individuals with PD-NC, PD-MCI, and PD-D. Our findings indicate that YWHAG could serve as a promising biomarker for cognitive impairment in PD. The upregulation of YWHAG expression in PD-MCI and PD-D groups, its association with cognitive impairment, and its correlations with MoCA scores and NfL levels support its potential clinical utility.

The identification of cognitive impairment in Parkinson's disease using biofluids, neuroimaging, and artificial intelligence.

Parkinson's disease (PD) is a neurodegenerative movement disorder causing severe disability and cognitive impairment as the disease progresses. It is necessary to develop biomarkers for cognitive decline in PD for earlier detection and prediction of disease progression. We reviewed literature which used artificial intelligence-based techniques, which can be more sensitive than other analyses, to determine potential biomarkers for cognitive impairment in PD. We found that combining biomarker types, including those from neuroimaging and biofluids, resulted in higher accuracy. Focused analysis on each biomarker type revealed that using structural and functional magnetic resonance imaging (MRI) resulted in accuracy and area under the curve (AUC) values above 80%/0.80, and that beta-amyloid-42 and tau were able to classify PD subjects by cognitive function with accuracy and AUC values above 90%/0.90. We can conclude that applying both blood-based and imaging-based biomarkers may improve diagnostic accuracy and prediction of cognitive impairment in PD.

HEARING LOSS AS A MODIFIABLE RISK FACTOR FOR DEMENTIA IN UK BIOBANK

Abstract Age-related hearing loss is a predictor of cognitive impairment and dementia. The mechanisms of the observed associations are unclear but could involve depletion of cognitive reserve, the occupation of cognitive resources, and lack of sensory input to the brain. Hearing loss may therefore represent a preventable or treatable causative risk factor for dementia. Indeed, many studies report on lower rates of cognitive decline among hearing aid users when compared to non-users. However, most investigations to date have been observational or with relatively short follow-ups, thus precluding clear interpretations of the underlying mechanism. In our study using UK Biobank data with n=502,386 participants followed up from ~2008 to 2021, we emulate a randomised clinical trial to probe the role of initiating the use of hearing aids in people with conductive hearing loss or with self-reported hearing difficulties in the diagnosis dementia. Diagnosis of dementia was ascertained through hospital and death records, and self-reports in such a way as to increase the positive predictive value. Among participants with hearing loss or hearing difficulties, 2,914 (2.1%) were diagnosed with dementia, compared to 4,982 (1.4%) in those without hearing loss or hearing difficulties. Additional results on the relationship between hearing aid use and dementia, and stratified analyses by sex/gender and ethnicity will be presented. We discuss the modifiability of hearing loss and recommend studies with longer follow-ups to determine the efficacy of hearing loss interventions in reducing the risk of cognitive decline and dementia.

Association of cognitive impairment and arterial hypertension

Impaired cognitive function (CF) is a common manifestation of brain damage as a target organ of arterial hypertension (AH). The presence of hypertension in middle age increases the risk of developing cognitive impairment (CI) and dementia in old age. At the same time, changes in certain indicators characteristic of AH may serve as predictors of CI and dementia in the future. The review presents data on the effects of endothelial dysfunction and increased arterial stiffness on CF. The small number of papers on the effects of hypertension in middle-aged people on the development of CI emphasizes the importance of investigating this topic, as the incidence of CI in young and middle-aged people has increased in recent years.

Thalamic Atrophy, Duration of Illness, and Years of Education are the Best Predictors of Cognitive Impairment in Multiple Sclerosis

Thalamic Atrophy, Duration of Illness, and Years of Education are the Best Predictors of Cognitive Impairment in Multiple Sclerosis

Developing a DNAm Surrogate to Predict Cognitive Functioning among Older Adults

AbstractBackgroundBlood‐based epigenetic measures are being developed and used to predict aging‐related health outcomes. Specifically, researchers have developed “epigenetic clocks” based on predictions of chronological age and age‐related health declines by DNA methylation. However, these markers are meant to predict aging per se and are not disease specific. Recently, scholars have developed “DNAm surrogates” to predict specific outcomes. This methodological technique has yet to be applied to cognitive functioning despite its potential to improve prediction of cognitive health in later life and provide insight into the role of biological aging.MethodThis study developed a novel DNAm surrogate measure for cognitive functioning (DNAmCogScore) based on an elastic net approach linking using 833,865 CpG sites predicting the Telephone Interview Cognitive Status score (TICS) available in the Health and Retirement Study (HRS), a nationally representative sample of older adults in the United States. Additionally, we evaluate the association of this DNAm surrogate and other neuropathology biomarkers. We used used ridge regression to create DNAmCogScore with 50% of the sample for training and 50% for testing (N = 2009 for each subsample). The Irish Longitudinal Study of Aging (TILDA) will be used for validation (results forthcoming).ResultWe find a positive association and modest predictive value between DNAmCogScore and TICS (see Figure 1, r = .4). Table 1 shows the strong associations with the DNAmCogScore and demographic characteristics. Overall, we find a strong positive coefficient between DNAmCogScore with attenuation after controlling for demographic characteristics, from 1.12 in Model 1 to .20 in Model 3, but remaining statistically significant throughout. Table 3 shows modest negative correlations between DNAmCogScore and NfL, pTau181, and GFAP (ranging from ‐.24 to ‐.36) and no correlation with AB42:40.ConclusionThis study is among the first to create a DNA methylation surrogate measure of cognitive functioning. Our measure is associated with cognitive functioning, even after adjusting for key demographic characteristics. And it has the expected association with other more neuropathology biomarkers. Overall, it suggests that changes in DNA methylation may be a molecular‐level mechanisms by which biological aging impacts cognitive health, and this measure may provide useful prediction of cognitive impairment before the onset of symptoms.

Usefulness of Serum Translocator Protein as a Potential Predictive Biochemical Marker of Three-Month Cognitive Impairment After Acute Intracerebral Hemorrhage: A Prospective Observational Cohort Study.

Translocator protein (TSPO) is a biomarker of neuroinflammation and brain injury. This study aimed to ascertain the potential of serum TSPO as a predictor of cognitive impairment after acute intracerebral hemorrhage (ICH). In this prospective observational cohort study, 276 patients with supratentorial ICH were randomly assigned to two groups (184 patients in the study group and 92 in the validation group) in a 2:1 ratio. Serum TSPO levels were gauged at admission, and cognitive status was assessed using the Montreal Cognitive Assessment Scale (MoCA) post-stroke 3 months. A MoCA score of < 26 was considered indicative of cognitive impairment. Serum TSPO levels were inversely correlated with MoCA scores (ρ=-0.592; P<0.001). Multivariate linear regression analysis showed that serum TSPO levels were independently associated with MoCA scores (β, -0.934; 95% confidence interval (CI), -1.412--0.455; VIF, 1.473; P<0.001). Serum TSPO levels were substantially higher in patients with cognitive impairment than in the remaining patients (median, 2.7 versus 1.6 ng/mL; P<0.001). Serum TSPO levels were linearly correlated with the risk of cognitive impairment under a restricted cubic spline (P=0.325) and independently predicted cognitive impairment (odds ratio, 1.589; 95% CI, 1.139-2.216; P=0.016). Subgroup analysis showed that the relationship between serum TSPO levels and cognitive impairment was not markedly influenced by other parameters, such as age, sex, drinking, smoking, hypertension, diabetes mellitus, body mass index, and dyslipidemia (all P for interaction > 0.05). The model, which contained serum TSPO, National Institutes of Health Stroke Scale scores and hematoma volume, performed well under the receiver operating characteristic curve, calibration curve and decision curve, and using the Hosmer-Lemeshow test. This model was validated in the validation group. Serum TSPO level upon admission after ICH was independently associated with cognitive impairment, substantializing serum TSPO as a reliable predictor of post-ICH cognitive impairment.

HLA-C*07:01 and HLA-DQB1*02:01 protect against white matter hyperintensities and deterioration of cognitive function: A population-based cohort study

BackgroundNeuroinflammation and aberrant immune regulation are increasingly implicated in the pathophysiology of white matter hyperintensities (WMH), an imaging marker of cerebrovascular pathologies and predictor of cognitive impairment. The role of human leukocyte antigen (HLA) genes, critical in immunoregulation and associated with susceptibility to neurodegenerative diseases, in WMH pathophysiology remains unexplored. MethodsWe performed association analyses between classical HLA alleles and WMH volume, derived from MRI scans of 38 302 participants in the UK Biobank. To identify independent functional alleles driving these associations, we conducted conditional forward stepwise regression and lasso regression. We further investigated whether these functional alleles showed consistent associations with WMH across subgroups characterized by varying levels of clinical determinants. Additionally, we validated the clinical relevance of the identified alleles by examining their association with cognitive function (n = 147 549) and dementia (n = 460 029) in a larger cohort. FindingsFour HLA alleles (DQB1*02:01, DRB1*03:01, C*07:01, and B*08:01) showed an association with reduced WMH volume after Bonferroni correction for multiple comparisons. Among these alleles, DQB1*02:01 exhibited the most significant association (β = −0.041, 95 % CI: −0.060 to −0.023, p = 1.04 × 10−5). Forward selection and lasso regression analyses indicated that DQB1*02:01 and C*07:01 primarily drove this association. The protective effect against WMH conferred by DQB1*02:01 and C*07:01 persisted in clinically relevant subgroups, with a stronger effect observed in older participants. Carrying DQB1*02:01 and C*07:01 was associated with higher cognitive function, but no association with dementia was found. InterpretationOur population-based findings support the involvement of immune-associated mechanisms, particularly both HLA class I and class II genes, in the pathogenesis of WMH and subsequent consequence of cognitive functions.

Depressive Symptomatology as a Predictor of Cognitive Impairment: Evidence from the Korean Longitudinal Study of Aging (KLOSA), 2006-2020.

Depressive symptoms are recognized as risk factors for cognitive impairment with intricate underlying biological mechanisms. We explored the link between depressive symptoms and cognitive impairment onset; we also assessed how this association is influenced by educational levels. This study included 5843 individuals aged ≥45 years, comprising 27,908 observations from 2006 to 2020. Based on repeated measurements of each participant, we estimated the association between depressive symptoms and cognitive impairment onset after a 2-year follow-up by using generalized estimating equations. The incidence rate was 9.4% among those individuals without depressive symptoms, which was in contrast with a rate of 21.0% among those individuals experiencing depressive symptoms. The odds ratio (OR) (95% confidence interval [CI]) for the association between depressive symptoms and cognitive impairment onset in the overall sample was 1.61 (1.47-1.76). This association was more pronounced among individuals with higher educational levels. Specifically, the OR (95% CI) of the association between depressive symptoms and cognitive impairment was highest among individuals with a college education (2.60 [1.78-3.81]), and the association was lowest among individuals with elementary or no education levels (1.45 [1.28-1.63]). Our findings highlight the idea that although individuals with higher educational backgrounds exhibit a diminished risk of cognitive impairment, the detrimental impacts of depressive symptoms on cognitive performance are particularly more pronounced within this group.

Serum levels of 25-OH vitamin D levels predict cognitive impairments among acute coronary syndrome patients.

The cognitive impairment after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS) has become a crucial clinical concern that cannot be ignored. However, studies on the early warning factors of cognitive impairment after PCI are still insufficient. This study reviewed the postoperative cognitive function of 284 patients who underwent PCI in our hospital from June 2019 to June 2022. During the 21-day follow-up, all participants included in the analysis were divided into the cognitive impairment (CI) group (n = 82) and the noncognitive impairment (NCI) group (n = 186) according to their Montreal cognitive assessment (MoCA) scale. Participants' serum 25(OH)D3 levels on admission and serum neuron-specific enolase (NSE), glial fibrillary acidic protein (GFAP) and S100β levels were measured 21 days after surgery. Age more than 65 years, hypertension, operation time longer than 60 min, left ventricular ejection fraction less than 50% and serum 25(OH)D3 less than 31.41 ng/ml were the risk factors for cognitive dysfunction in ACS patients 21 days after PCI. Serum levels of 25(OH)D3, NSE, S100β and GFAP were significantly higher in patients with cognitive impairment than in patients without cognitive impairment. Postoperative serum NSE, S100β and GFAP levels were significantly negatively correlated with serum 25(OH)D3 levels at admission. The serum 25(OH)D3 level is a risk factor and predictor of cognitive impairment in patients with ACS after PCI.

Cognitive impairment and dementia in young onset Parkinson's disease.

Patients with young-onset Parkinson's disease (YOPD) have a slower progression. Our aim was to analyze the change in cognitive function in YOPD compared to patients with a later onset and controls. Patients with Parkinson's disease (PD) and controls from the COPPADIS cohort were included. Cognitive function was assessed with the Parkinson's Disease Cognitive Rating Scale (PD-CRS) at baseline (V0), 2-year ± 1month (V2y), and 4-year ± 3months follow-up (V4y). Regarding age from symptoms onset, patients were classified as YOPD (< 50years) or non-YOPD (≥ 50). A score in the PD-CRS < 81 was defined as cognitive impairment (CI): ≤ 64 dementia; 65-80 mild cognitive impairment (MCI). One-hundred and twenty-four YOPD (50.7 ± 7.9years; 66.1% males), 234 non-YOPD (67.8 ± 7.8years; 59.3% males) patients, and 205 controls (61 ± 8.3years; 49.5% males) were included. The score on the PD-CRS and its subscore domains was higher at all visits in YOPD compared to non-YOPD patients and to controls (p < 0.0001 in all analysis), but no differences were detected between YOPD patients and controls. Only non-YOPD patients had significant impairment in their cognitive function from V0 to V4y (p < 0.0001). At V4y, the frequency of dementia and MCI was 5% and 10% in YOPD compared to 25.2% and 22.3% in non-YOPD patients (p < 0.0001). A lower score on the Parkinson's Disease Sleep Scale at baseline was a predictor of CI at V4y in YOPD patients (Adjusted R2 = 0.61; OR = 0.965; p = 0.029). Cognitive dysfunction progressed more slowly in YOPD than in non-YOPD patients.

Predictor of cognitive impairment: metabolic syndrome or circadian syndrome

BackgroundIt was reported that metabolic syndrome increases the risk for cognitive impairment and circadian rhythm may influence cognition behavior. Identifying the potential risk factors is essential to screen individuals with neuronal dysfunction, neuronal loss, and cognitive decline and prevent cognitive impairment and dementia development.MethodsWe clarified participants by the presence of metabolic syndrome (MetS) and circadian syndrome (CircS) and employed three multivariable Generalized Estimating Equation (GEE) models to control the potential confounding factors and estimate the β values for cognitive function using as referents those had neither MetS nor CircS at baseline. The cognitive function consists of episodic memory and executive function was estimated via the modified Telephone Interview for Cognitive Status (TICS) every two years until 2015.ResultsThe mean age of the participants was 58.80 (8.93) years and 49.92% (male). The prevalence of MetS and CircS was 42.98% and 36.43%, respectively. 1,075 (11.00%) and 435 (4.45%) participants had either MetS or CircS alone and 3,124 (31.98%) had both CircS and MetS. Participants with both MetS and CircS compared with normal had a significantly decreased cognitive function score during the 4-years cohort (β = -0.32, 95% CI: -0.63, -0.01) with the complete model, as well as among participants who suffered from CircS alone (β = -0.82, 95% CI: -1.47, -0.16), while not among participants with MetS alone (β = 0.13, 95% CI: -0.27, 0.53). Specifically, compared with the normal population a significantly lower score was discovered in the episodic memory (β = -0.51, 95% CI: -0.95, -0.07), while slightly lower in executive function (β = -0.33, 95% CI: -0.68, -0.01) among individuals with CircS alone.ConclusionsIndividuals with CircS alone or both MetS and CircS have a high risk of cognitive impairment. The association was even stronger in participants with CircS alone than those with both MetS and CircS, suggesting CircS probably have a stronger association with cognitive functioning than MetS and could be a better predictor for cognitive impairment.