Evidence map›Paper›PMID 35684039›Full record

ArticleNutrients2022

Metabolomic Profile of Different Dietary Patterns and Their Association with Frailty Index in Community-Dwelling Older Men and Women.

Toshiko Tanaka, Sameera A Talegawkar, Yichen Jin, Julián Candia, Qu Tian, Ruin Moaddel, Eleanor M Simonsick, Luigi Ferrucci

Abstract read
In one paragraph

Article in Nutrients, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  5. Impact of Daily Rhythms and Postprandial Responses on the Plasma Metabolome.International journal of molecular sciences · 2026
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  6. Review
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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

8 authors.

Toshiko TanakaLongitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA.ORCID 0000-0002-4161-3829
Sameera A TalegawkarDepartment of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC 20052, USA.
Yichen JinDepartment of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC 20052, USA.
Julián CandiaLongitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA.ORCID 0000-0001-5793-8989
Qu TianLongitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA.ORCID 0000-0003-2706-1439
Ruin MoaddelLaboratory of Clinical Investigation, National Institute on Aging, Baltimore, MD 21224, USA.
Eleanor M SimonsickLongitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA.
Luigi FerrucciLongitudinal Studies Section, National Institute on Aging, Baltimore, MD 21224, USA.

Funding

The Baltimore Longitudinal Study Of AgingZIAAG000015 · NIA · NATIONAL INSTITUTE ON AGING · PI SIMONSICK, ELEANOR MARIE · 2009 to 2025
$116.9M
Associations of diet trajectories over the adult life course with cardiovascular risk factors, age-related functional declines and mortalityR01AG051752 · NIA · GEORGE WASHINGTON UNIVERSITY · PI TALEGAWKAR, SAMEERA A · 2016 to 2018
$886k
NIA NIH HHS R01 AG051752NIH HHS R01AG051752
6 · The paper itself

Abstract

Diet quality has been associated with slower rates of aging; however, the mechanisms underlying the role of a healthy diet in aging are not fully understood. To address this question, we aimed to identify plasma metabolomic biomarkers of dietary patterns and explored whether these metabolites mediate the relationship between diet and healthy aging, as assessed by the frailty index (FI) in 806 participants of the Baltimore Longitudinal Study of Aging. Adherence to different dietary patterns was evaluated using the Mediterranean diet score (MDS), Mediterranean-DASH Diet Intervention for Neurodegenerative Delay (MIND) score, and Alternate Healthy Eating Index-2010 (AHEI). Associations between diet, FI, and metabolites were assessed using linear regression models. Higher adherence to these dietary patterns was associated with lower FI. We found 236, 218, and 278 metabolites associated with the MDS, MIND, and AHEI, respectively, with 127 common metabolites, which included lipids, tri/di-glycerides, lyso/phosphatidylcholine, amino acids, bile acids, ceramides, cholesterol esters, fatty acids and acylcarnitines, indoles, and sphingomyelins. Metabolomic signatures of diet explained 28%, 37%, and 38% of the variance of the MDS, MIND, and AHEI, respectively. Signatures of MIND and AHEI mediated 55% and 61% of the association between each dietary pattern with FI, while the mediating effect of MDS signature was not statistically significant. The high number of metabolites associated with the different dietary patterns supports the notion of common mechanisms that underly the relationship between diet and frailty. The identification of multiple metabolite classes suggests that the effect of diet is complex and not mediated by any specific biomarkers. Furthermore, these metabolites may serve as biomarkers for poor diet quality to identify individuals for targeted dietary interventions.

Indexed as

Diet, MediterraneanFrailtyAgedBiomarkersFemaleHumansIndependent LivingLongitudinal StudiesMaleBiomarkersagingdietary patternsfrailtymediationmetabolomics

Identifiers

PMID35684039
PMCPMC9182888

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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.