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Background: The Test of Practical Judgement (TOP‐J) in its 9‐item (TOPJ9) and 15‐item (TOPJ15) versions (Rabin et el., 2007), validated for assessing practical judgement, encompasses day‐to‐day scenarios in medical, financial, safety, and social/ethical domains. This study seeks to evaluate its utility in distinguishing cognitively unimpaired (CU) individuals from those with Mild Cognitive Impairment (MCI) within a Southeast Asian population. This investigation aims to contribute insights into the cross‐cultural applicability of TOP‐J in assessing practical judgement across varying cognitive states in the Southeast Asian context. Method: A cohort of 126 non‐demented participants from the Biomarker and Cognition Study, Singapore (BIOCIS) database underwent a comprehensive neuropsychological assessment, including TOPJ9, TOPJ15, Visual Cognitive Assessment Test (VCAT), Weschler Memory Scale (WMS‐IV) Logical Memory Story Delayed Recall, and Rey Auditory Verbal Learning Test (RAVLT) delayed test in a single session. MCI was diagnosed using the Petersen criteria (Petersen et al., 2001). Additionally, mean scores for neuropsychological tests were compared. Receiver Operating Characteristic (ROC) curve was used to assess the discriminative performance of TOP‐J between CU and MCI groups. Two‐by‐two tables facilitated the calculation of test sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV) for each test. Result: The mean age of the 126 participants were 60.34 years ± 9.64, 38% male, mean education of 15.16 years ± 3.11, and 82% Chinese ethnicity. Significant mean differences between groups were observed for each test (p<0.05) (Table 1). ROC Analysis indicated optimal cut‐offs for MCI identification were determined for TOPJ9 (<16.5, AUC = 0.76, Sn = 0.71, Sp = 0.7, PPV = 0.57, NPV = 0.81) and TOPJ15 (<25.5, AUC = 0.79, Sn = 0.55, Sp = 0.9, PPV = 0.75, NPV = 0.78). Discriminative properties with story delayed and RAVLT delayed are detailed in Table 2. Conclusion: Both TOP‐J 9 and 15 items are useful for the detection of MCI in a Southeast Asian population. They exhibit comparable efficacy with other neuropsychological tests for MCI detection in Southeast Asian participants. Further validation through a longitudinal study is essential to solidify their diagnostic utility in this population. [ABSTRACT FROM AUTHOR]

Background: Visual Cognitive Assessment Test(VCAT) is a visual‐based cognitive evaluation tool which can be administered to multilingual populations without translation. VCAT has shown to be effective in differentiating mild cognitive impairment(MCI) from cognitively normal and useful for diagnosing MCI and mild AD(Kandiah et al., 2016). However, whether VCAT is also useful for differentiating between vascular and non‐vascular MCI remains to be explored. Method: 604 non‐demented participants were recruited from the community as part of the Southeast Asian Biomarker and Cognition Study, Singapore(BIOCIS). All participants completed a comprehensive neuropsychological battery, including VCAT, Rey Auditory Verbal Learning(RAVLT) Delayed, and Color Trails 2(CT2). Classification of MCI was based on Petersen's criteria(Petersen et al., 2001). Participants also underwent neuroimaging using a 3T MRI scanner. T1‐weighted and fluid‐attenuated inversion recovery MRI was used for white matter hyperintensity visual ratings as per the modified Fazekas scale (Vipin et al., 2021). Participants with Fazekas total score of 5 and above were classified as the vascular group. Therefore, participants were divided into three groups: Cognitively Normal without cerebrovascular disease(NV‐CN), Non‐Vascular MCI(NV‐MCI), and Vascular MCI(V‐MCI) and their tests mean scores and cerebral perfusion were compared. Additionally, all neuropsychological tests and perfusion were compared in differentiating between NV‐CN and V‐MCI. Results: Participant demographics included a mean age of 60.34 years±10.76, Male 44%, and mean education years of 14.44 years±3.71. After adjusting for age and education years, mean of neuropsychological test, perfusion scores were significantly different between the three groups(p < 0.05). Tukey HSD post‐hoc test showed pairwise differences between all groups, except for perfusion scores(Table 1). ROC analysis was conducted to explore the discriminative performance of VCAT in differentiating between CN and V‐MCI. The analysis indicated an AUC of 0.74 with the optimal VCAT cut‐off for differentiating between CN and V‐MCI as 25.5 with specificity 0.85 and sensitivity 0.48. In an additional ROC analysis, we compared the discriminative properties of VCAT, RAVLT Delayed, CT2 and Perfusion. Conclusion: The results of our study suggest that VCAT is useful in discriminating between CN and V‐MCI, especially in comparison to other neuropsychological tests and perfusion. Future longitudinal studies are needed for further investigation. [ABSTRACT FROM AUTHOR]

Background: The Visual Cognitive Assessment Test (VCAT) is a visual based, language neutral cognitive assessment validated across cultures and ethnicities, that allows for early diagnosis of cognitive impairment. The VCAT assess domains of cognition – Memory, Visuospatial function, attention, language and Executive function. The Mild Behavioural Impairment Checklist (MBI‐C) was developed to assess five domains of NPS – Decreased motivation, emotional dysregulation, impulse control, social inappropriateness and abnormal beliefs/perceptions Current research indicates an association between MBI symptom severity and poorer cognitive performance in the domains of memory. We examined the association between mild behavioural impairment and domains of cognition as assessed by the VCAT in a multi‐ethnic Southeast Asian population. Method: 204 participants with vascular mild cognitive impairment (VMCI) were recruited from the community living in Singapore. VMIC was defined by Fazekas White Matter Hyperintensity(WMH) visual ratings of 4 and above. The mean age = 66.82 years, mean education = 13.54years with 39.8% males. Participants underwent neuropsychological assessments including the VCAT administered by trained raters and self‐reported questionnaires including the Mild Behavioural Impairment‐Checklist (MBI‐C). Result: The VCAT‐Attention domain had a significant negative correlation with MBIC‐social subdomain (r = ‐0.276, p<0.05). With every 1 point increase in VCAT‐Attention. MBIC‐social subdomain decreased by 9% (estimate ‐0.357; 95% CI[0.516, 0.239]; p = 0.022). Conclusion: Current research indicated that social isolation is one of the biggest risk factors for cognitive impairment, and our results reveal that social issues are associated with behavioural impairment as well. Attentional difficulties could lead to issues in inhibitory control, resulting in social inappropriateness. The V‐CAT's ability to associate specific subdomains with MBI‐C subdomains suggest both tools could be a valuable tool for early detection and intervention in cognitive disorders. [ABSTRACT FROM AUTHOR]

Background: Mild Behavioral Impairment (MBI) is the onset of sustained neuropsychiatric symptoms that are considered as a possible precursor to neurodegenerative conditions, especially dementia. The concept of MBI recognizes that behavioral changes may be an early sign of brain changes due to neurodegeneration. Very recent research has shown behavioral changes in MBI might be linked to changes in brain structure, including cortical thickness. Cortical thickness is associated with various neurodegenerative diseases, including Alzheimer's disease and other forms of dementia. We examined the association between cortical thickness and neuropsychiatric symptoms(NPS) in a multi‐ethnic Southeast Asian population. Method: 657 participants were recruited from the community living in Singapore. 399 were cognitively unimpaired (CU), 253 with mild cognitive impairment (MCI), and overall, the mean age = 59.86 years, mean education = 14.52 years with 40.2% males. Participants completed the Mild Behavioural Impairment‐Checklist (MBI‐C), a self‐reported questionnaire. Mild Behavioural Impairment(MBI) classification was based on established clinical cut‐offs of 8.5. Participants underwent magnetic resonance imaging (MRI) scan on a 3T Siemens Prisma Fit (Siemens, Erlangen, Germany). Structural MRI was acquired using T1‐weighted MPRAGE sequence. Structural images were preprocessed using FreeSurfer (https://surfer.nmr.mgh.harvard.edu/, software version 7.2). For each participant's T1 images, automated segmentation and cortical parcellation was carried out using the FreeSurfer "recon‐all" processing stream, which included motion correction, removal of nonbrain tissue, automated Talairach transformation, intensity correction, volumetric segmentation, and cortical surface reconstruction and parcellation. Result: In the left hemisphere, the cortical thickness of the cuneus, entorhinal, parstriangularis, precuneus, rostral anterior cingulate, was significantly associated with the likelihood of being classified as MBI. The right – entorhinal, inferior parietal, pars orbitalis, supramarginal and frontal pole cortical thickness was significantly associated with the likelihood of being classified as MBI. Conclusion: The results highlight the importance of MBI as potential early indicators of cognitive impairment and suggest that these impairments are associated with changes in cortical thickness and increased risk of cognitive decline. The complex interplay between behavioral and cognitive symptoms in aging and neurodegenerative diseases needs to be defined. [ABSTRACT FROM AUTHOR]

Background: Oligomeric Amyloid Beta (OAβ), is representative of a soluble, neurotoxic and pathogenic form of Aβ, which has been found to function as upstream drivers of Alzheimer's Disease pathology (Tolar et al., 2021). It serves as a contributory factor towards the formation of cortical Aβ plaques and neurofibrillary Tau tangles, and has been found to induce oxidative stress, synaptic toxicity and neuroinflammation (Tolar et al., 2021). The pathology culminates in neuronal dysfunction/death and resultant neurodegeneration which has been found to manifest clinically as symptoms of cognitive decline. OAβ has been found to correlate with the severity of cognitive performance, as well as brain volume reduction (An et al., 2017, Wang et al., 2017, Meng et al., 2019, Youn et al., 2019, Babapour Mofrad et al., 2021). Nevertheless, its effect on language neutral cognitive tests ‐ the novel Visual Cognitive Assessment Test (VCAT) developed and validated by our team of neurologist and neuropsychologists; remains to be evaluated (Kandiah et al., 2016, Lim et al., 2018, Low et al., 2020). Methods: A cross‐sectional pilot study was conducted in a cohort of 63 patients, clinically diagnosed with mild cognitive impairment (MCI). The patients underwent cognitive evaluation tests, Multimer Detection System (MDS) based plasma OAβ analysis and MRI based cortical grey matter evaluations (Wang et al., 2017, Youn et al., 2019, Pyun et al., 2021, Vipin et al., 2021). Pearson's correlation evaluated associations between plasma OAβ, cognitive scores [Mini‐Mental State Examination (MMSE), VCAT] and brain volume measures [Grey Matter Volume (GMV) / Intracranial Volume (ICV)]. Results: Increasing plasma OAβ expression associated with decreasing, VCAT scores (r = ‐0.291, 95% CI = ‐0.504 to ‐0.044, p = 0.022) and MMSE scores (r = ‐0.272, 95% CI = ‐0.489 to ‐0.024, p = 0.032), in MCI patients (Figure 1A, B). Additionally increasing plasma OAβ expression also associated with decreasing and GMV/ ICV ratio (r = ‐0.264, 95% CI = ‐0.489 to ‐0.007, p = 0.045), in MCI patients (Figure 1C). Conclusion: Findings from this study, emphasise on the promising clinical utility of plasma OAβ as a biomarker. Future longitudinal studies will validate these associations across the Alzheimer's disease spectrum. [ABSTRACT FROM AUTHOR]