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Record W4206472369 · doi:10.1002/alz.050921

The gut microbiome and cognitive function in midlife: The CARDIA study

2021· article· en· W4206472369 on OpenAlexaboutno aff
Katie A. Meyer

Bibliographic record

VenueAlzheimer s & Dementia · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsnot available
Fundersnot available
KeywordsStroop effectDigit symbol substitution testMontreal Cognitive AssessmentVerbal fluency testCognitionCognitive declineTrail Making TestAudiologyPsychologyClinical psychologyMedicineDementiaInternal medicineNeuropsychologyPsychiatryDiseaseCognitive impairmentPathology

Abstract

fetched live from OpenAlex

Abstract Background Based on experimental and clinical studies of specific patients, a gut‐brain axis has been hypothesized as mechanism connecting peripheral metabolic and immunologic activity to the brain, including cognitive functioning. Few studies have investigated the association of gut microbial composition to cognition in large community samples. Method Cross‐sectional data were from a subsample (n=597) of participants in the U.S.‐based bi‐racial Coronary Artery Risk Development in Young Adults (CARDIA) study (2015‐16). Participants were aged 48‐60 years, 45% male, and 45% Black (Table). V3‐V4 regions of 16S rRNA were sequenced from stool DNA with Illumina MiSeq technology and. microbial taxonomic measures generated from the sequenced data. After filtering out rare taxa, 107 genera (of 375 originally assigned) were included in the analysis. Participants completed six interviewer‐administered cognitive tests: Montreal Cognitive Assessment (MoCA), Digit Symbol Substitution Test (DSST), Rey‐Auditory Verbal Learning Test (RAVLT), timed Stroop test, and letter and category fluency tests. Higher scores on all tests reflect greater cognitive functioning, except for Stroop, for which faster (lower time) is better. Result Regression analysis of cognitive test scores on genera included adjustment for sequencing batch; and participant age, sex, race, BMI, and diabetes. Eleven genera were associated with two or more cognitive measures at FDR<0.10, and 31 genera were associated with two or more at FDR<0.20 (Figure): Barnesiella was positively associated with DSST and category fluency; Lachnospira was positively associated with DSST, RAVLT, MoCA, category fluency, and negatively associated with the timed Stroop test; Sutterella was negatively associated with MoCA, RAVLT, and DSST. Seven of the 11 genera with shared associations at FDR<0.10 (and 22 of the 31 at FDR<0.20) were from within the Clostridia class. Conclusion Tests of global cognition and psychomotor speed were associated with specific microbes in the gut. These microbes, particularly those stemming from Clostridia class, may be involved in short‐chain fatty acid production and inflammatory pathways. Our data contribute to a growing body of literature suggesting that the gut microbiota may relate to cognitive function. These signals must be replicated and further researched to identify relevant genetic, metabolic, and inflammatory pathways.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.014
GPT teacher head0.268
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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