Inflammation‐Linked Microbiome Alterations Associated with Cognitive Impairment in Older Adults: Insights from the MiaGB Consortium
Bibliographic record
Abstract
Abstract Background The increasing prevalence of cognitive decline and dementia poses a significant public health challenge for older adults, and effective preventive and therapeutic strategies remain elusive. This is largely due to an incomplete understanding of the precise etiology and contributing factors underlying these conditions. Increased systemic inflammation is suspected to elevate the risk of dementia and cognitive decline, yet the causes of chronic inflammation remain poorly understood. Emerging evidence suggests that gut microbiome abnormalities are linked to increased inflammation and a higher risk of dementia. However, it remains unclear whether the rate of cognitive impairment differs with higher systemic inflammation and whether unique microbiome signatures are associated with inflamed cognitive decline and dementia. Method Using 165 samples from the Microbiome in Aging Gut and Brain (MiaGB) consortium cohort, systemic inflammatory marker interleukin‐6 (IL‐6) was measured in human plasma via ELISA. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) questionnaire, and fecal microbiomes were analyzed through shotgun metagenomic sequencing. Subjects were grouped based on IL‐6 levels (high and low) and cognitive status (normal cognition and cognitive impairment), and their corresponding microbiome signatures were analyzed. Result Interestingly, individuals with high IL‐6 levels (IL‐6 High ) exhibited over twice the prevalence of mild cognitive impairment (MCI) compared to those with low IL‐6 levels (IL‐6 Low ) ( n = 41 IL‐6 High vs. 18 IL‐6 Low ). Older adults with low IL‐6 and MCI displayed higher abundances of Bacteroides , Prevotella , Alistipes , Fusicatenibacter , and Parabacteroides , but lower levels of Lachnospira , Akkermansia , and Subdoligranulum compared to sex‐ and age‐matched cognitively healthy controls with low IL‐6. Conversely, those with high IL‐6 and MCI exhibited higher abundances of Blautia , Prevotella , and Fusicatenibacter and lower abundances of Lachnospira , Akkermansia , and Subdoligranulum compared to IL‐6 High controls with normal cognition. Conclusion These findings reveal that butyrate‐producing genera such as Lachnospira , Akkermansia , and Subdoligranulum are significantly reduced, while potentially pathogenic Fusicatenibacter and commensal Prevotella are elevated in individuals with MCI and high IL‐6 levels. These distinct microbial profiles may serve as biomarkers for the early detection of cognitive decline in older adults, highlighting potential targets for therapeutic strategies to preserve brain health during aging.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".