Evidence map›Paper›PMID 41692848›Full record

ArticleTranslational psychiatry2026

Lipidomic signatures reveal biomarkers of mild cognitive impairment.

Jayashankar Jayaprakash, Siddabasave Gowda B Gowda, Divyavani Gowda, MiaGB Consortium, Shalini Jain, Hariom Yadav, Shu-Ping Hui

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Translational psychiatry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Jayashankar JayaprakashGraduate School of Global Food Resources, Hokkaido University, Kita-9, Nishi-9, Kita-Ku, Sapporo, 060-0809, Japan.
Siddabasave Gowda B GowdaGraduate School of Global Food Resources, Hokkaido University, Kita-9, Nishi-9, Kita-Ku, Sapporo, 060-0809, Japan. gowda@gfr.hokudai.ac.jp.ORCID http://orcid.org/0000-0002-7972-9982
Divyavani GowdaFaculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan.
MiaGB Consortium
Shalini JainMicrobiome in aging Gut and Brain (MiaGB) consortium, USF Center for Microbiome Research, Microbiomes Institute, University of South Florida, 3515 E Fletcher Avenue, Tampa, FL, 33612, USA.
Hariom YadavMicrobiome in aging Gut and Brain (MiaGB) consortium, USF Center for Microbiome Research, Microbiomes Institute, University of South Florida, 3515 E Fletcher Avenue, Tampa, FL, 33612, USA. hyadav@usf.edu.
Shu-Ping HuiFaculty of Health Sciences, Hokkaido University, Kita-12, Nishi-5, Kita-ku, Sapporo, 060-0812, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mild cognitive impairment (MCI) is an early stage in the progression toward dementia. Lipids are central to neurodegeneration, yet the biomarker potential of lipidomics from saliva, plasma, and feces remains underexplored. As part of the Microbiome in Aging Gut and Brain (MiaGB) consortium, saliva, plasma, and fecal samples were collected from older adults with MCI and healthy controls. Samples were analyzed by high-performance liquid chromatography coupled with high-resolution mass spectrometry (LC/MS), to profile lipidomic alterations and identify candidate biomarkers. Lipidomic profiling annotated over 200 molecular species spanning five major lipid classes. Compared with controls, MCI patients exhibited increased oxidized triacylglycerols (oxTGs) in saliva, reduced cholesteryl linoleate (CE 18:2) in plasma, and decreased fatty acid esters of hydroxy fatty acids (FAHFAs) in feces. Receiver operating characteristic (ROC) analysis identified α-linolenic acid (FA 18:3), docosapentaenoic acid (FA 22:5), and CE 18:2 as discriminatory metabolites with notable diagnostic performance. Moreover, elevated fecal triacylglycerols containing medium-chain fatty acids (TG-MCFAs) were observed in MCI, suggesting impaired lipid absorption or altered metabolism. This multi-sample lipidomics strategy highlights TG-MCFAs as fecal biomarkers for MCI detection, supporting further mechanistic and longitudinal validation.

Indexed as

Cognitive DysfunctionLipidomicsAgedBiomarkersCase-Control StudiesChromatography, High Pressure LiquidFatty AcidsFatty Acids, UnsaturatedFecesFemaleHumansMaleTriglyceridesBiomarkersdocosapentaenoic acidFatty AcidsFatty Acids, UnsaturatedTriglycerides

Identifiers

PMID41692848
PMCPMC12948972

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.