Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Objectives: This study aimed to investigate the relationship between blood microbiota,specifically bacterial DNA, and cognitive decline in individuals with subjective cognitive decline (SCD) and amnestic mild cognitive impairment (aMCI). The objective was to identify potential microbial signatures that could serve as biomarkers for cognitive deterioration. Methods: Forty-seven participants were recruited, including 13 with aMCI, 20 with SCD, and 14 normal cognition (NC). Blood samples were collected, and microbial DNA was analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Bioinformatics analyses—including α- and β-diversity measures and differential abundance testing (using edgeR)—were employed to assess microbial diversity and differences in bacterial composition among groups. Logistic regression models were used to evaluate the predictive impact of the microbiota on cognitive decline. Results: Microbial diversity differed significantly between groups, with NC exhibiting the highest α-diversity. Both the aMCI and SCD groups showed reduced diversity. Taxa such as Bacteroidia, Alphaproteobacteria, and Clostridia were significantly decreased in the aMCI group compared to NC (p < 0.05). In contrast, Gammaproteobacteria increased significantly in the aMCI group compared to both NC and SCD, indicating progressive microbial changes from SCD to aMCI. No significant differences were found between the NC and SCD groups. Conclusion Distinct bacterial taxa—particularly the increase in Gammaproteobacteria along with decreases in Bacteroidia, Alphaproteobacteria, and Clostridia—are associated with the progression of cognitive decline. These findings suggest that blood microbiota could serve as potential biomarkers for the early detection of aMCI. However, the small sample size and the lack of control for confounding factors such as diet and medication limit the findings. Larger studies are needed to validate these results and further explore the role of microbiota in neurodegeneration.

Background: and Purpose: We developed a new digital cognitive assessment called Seoul Cognitive Status Test (SCST), formerly called Inbrain Cognitive Screening Test. The purpose of this study was to validate the clinical utility of the SCST by comparing its scores of those with subjective cognitive decline (SCD), amnestic mild cognitive impairment (aMCI), and dementia diagnosed by the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease Assessment Packet (CERAD-K). Methods: All participants (n=296) who completed the CERAD-K, SCST, and Instrumental Activities of Daily Living tests were included in this study. Total score, cognitive domain scores, and subtest scores of the SCST were compared among the 3 groups (SCD, aMCI, and dementia). Additionally, correlations between SCST and CERAD-K subtests were examined. Results: Cognitive domain scores and total score of the SCST showed significant differences among the three groups, with scores being the highest in the order of SCD, aMCI, and dementia (p<0.001). Most subtests of the SCST also showed higher scores in the order of SCD, aMCI, and dementia (p<0.001). However, SCD and aMCI groups showed no significant differences in scores of the Phonemic Word Fluency Test (p=0.083) or Korean Trail Making Test-Elderly version Part A (p=0.434). Additionally, there was no significant difference in the score of Place Recognition (p=0.274) of the Word-Place Association Test between aMCI and dementia groups. Conclusions In conclusion, differences in total score, cognitive domain scores, and subtest scores of the SCST among the 3 groups of participants diagnosed using CERAD-K confirm the clinical utility of the SCST for cognitive assessment.

Background: and Purpose: We aimed to develop the diagnostic matrix of the Seoul Cognitive Status Test (SCST) and compare its performance with traditional paper-and-pencil neuropsychological tests, including the Seoul Neuropsychological Screening Battery-II (SNSB-II) and the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD-K). Methods: We recruited 197 participants from the head-to-head SCST-SNSB cohort, and 204 participants from the head-to-head SCST-CERAD cohort. They underwent either SNSB-II or CERAD-K, in addition to SCST. The diagnostic matrix was developed by combining cognitive function, determined by neuropsychological tests, and activities of daily living (ADL), determined by Instrumental-ADL scales. Results: The diagnostic agreement between the SCST and the SNSB-II was 83.9% (weighted kappa=0.87). The agreement between the SCST and the CERAD-K was 84.3% (weighted kappa=0.88). In the SCST-SNSB cohort, all differences in SCST scores between the cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia diagnosed with the SNSB-II were significant in all cognitive domains (all p<0.01), except for the executive domain between CU and MCI (p=0.145). In the SCST-CERAD cohort, all differences in SCST scores between the 3 groups diagnosed with the CERAD-K were significant in all cognitive domains (all p<0.01), except for the language and visuospatial domains between MCI and dementia (p=0.169 and p=0.778, respectively). Conclusions Our findings suggest that the tablet-based SCST may be another option to traditional paper-and-pencil neuropsychological tests, especially in situations where time and space are relatively limited, and neuropsychological testing specialists are not available.

Background: and Purpose: We aimed to develop the diagnostic matrix of the Seoul Cognitive Status Test (SCST) and compare its performance with traditional paper-and-pencil neuropsychological tests, including the Seoul Neuropsychological Screening Battery-II (SNSB-II) and the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD-K). Methods: We recruited 197 participants from the head-to-head SCST-SNSB cohort, and 204 participants from the head-to-head SCST-CERAD cohort. They underwent either SNSB-II or CERAD-K, in addition to SCST. The diagnostic matrix was developed by combining cognitive function, determined by neuropsychological tests, and activities of daily living (ADL), determined by Instrumental-ADL scales. Results: The diagnostic agreement between the SCST and the SNSB-II was 83.9% (weighted kappa=0.87). The agreement between the SCST and the CERAD-K was 84.3% (weighted kappa=0.88). In the SCST-SNSB cohort, all differences in SCST scores between the cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia diagnosed with the SNSB-II were significant in all cognitive domains (all p<0.01), except for the executive domain between CU and MCI (p=0.145). In the SCST-CERAD cohort, all differences in SCST scores between the 3 groups diagnosed with the CERAD-K were significant in all cognitive domains (all p<0.01), except for the language and visuospatial domains between MCI and dementia (p=0.169 and p=0.778, respectively). Conclusions Our findings suggest that the tablet-based SCST may be another option to traditional paper-and-pencil neuropsychological tests, especially in situations where time and space are relatively limited, and neuropsychological testing specialists are not available.

Background: and Purpose: We aimed to develop the diagnostic matrix of the Seoul Cognitive Status Test (SCST) and compare its performance with traditional paper-and-pencil neuropsychological tests, including the Seoul Neuropsychological Screening Battery-II (SNSB-II) and the Korean version of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD-K). Methods: We recruited 197 participants from the head-to-head SCST-SNSB cohort, and 204 participants from the head-to-head SCST-CERAD cohort. They underwent either SNSB-II or CERAD-K, in addition to SCST. The diagnostic matrix was developed by combining cognitive function, determined by neuropsychological tests, and activities of daily living (ADL), determined by Instrumental-ADL scales. Results: The diagnostic agreement between the SCST and the SNSB-II was 83.9% (weighted kappa=0.87). The agreement between the SCST and the CERAD-K was 84.3% (weighted kappa=0.88). In the SCST-SNSB cohort, all differences in SCST scores between the cognitively unimpaired (CU), mild cognitive impairment (MCI), and dementia diagnosed with the SNSB-II were significant in all cognitive domains (all p<0.01), except for the executive domain between CU and MCI (p=0.145). In the SCST-CERAD cohort, all differences in SCST scores between the 3 groups diagnosed with the CERAD-K were significant in all cognitive domains (all p<0.01), except for the language and visuospatial domains between MCI and dementia (p=0.169 and p=0.778, respectively). Conclusions Our findings suggest that the tablet-based SCST may be another option to traditional paper-and-pencil neuropsychological tests, especially in situations where time and space are relatively limited, and neuropsychological testing specialists are not available.