Evidence map›Paper›PMID 38489176›Full record

ArticleJournal of Alzheimer's disease : JAD2024

Mendelian Randomization of Blood Metabolites Suggests Circulating Glutamine Protects Against Late-Onset Alzheimer's Disease.

Ferris A Ramadan, Gayatri Arani, Ayan Jafri, Tingting Thompson, Victoria L Bland, Benjamin Renquist, David A Raichlen, Gene E Alexander, Yann C Klimentidis

Open access · greenAbstract read
In one paragraph

Article in Journal of Alzheimer's disease : JAD, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.2field-weighted citation impact, top 13% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Ferris A RamadanDepartment of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA.
Gayatri AraniDepartment of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA.
Ayan JafriDepartment of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA.
Tingting ThompsonDepartment of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA.
Victoria L BlandDepartment of Nutritional Sciences, University of Arizona, Tucson, AZ, USA.
Benjamin RenquistSchool of Animal and Comparative Biomedical Sciences, University of Arizona, Tucson, AZ, USA.
David A RaichlenDepartment of Biological Sciences and Anthropology, Human and Evolutionary Biology Section, University of Southern California, Los Angeles, CA, USA.
Gene E AlexanderDepartment of Psychology, University of Arizona, Tucson, AZ, USA.
Yann C KlimentidisDepartment of Epidemiology and Biostatistics, University of Arizona, Tucson, AZ, USA.
University of Arizona · USUniversity of Southern California · US

Funding

Research Education ComponentP30AG019610 · NIA · SUN HEALTH RESEARCH INSTITUTE · PI REIMAN, ERIC MICHAEL · 2001 to 2020
$32.5M
Research Education ComponentP30AG072980 · NIA · BANNER HEALTH · PI Nicholas Ashton · 2021 to 2026
$24.9M
Revitalizing Cognition in Older Adults at Risk for Alzheimer's Disease with Near-Infrared Photobiomodulation: Diversity SupplementR01AG064587 · NIA · UNIVERSITY OF FLORIDA · PI ALEXANDER, GENE E, BOWERS, DAWN · 2019 to 2023
$4.0M
Inactivity, sedentary behavior, and the risk for Alzheimer’s disease in middle aged to older adultsR01AG072445 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI GENE E ALEXANDER, Yann Charles Klimentidis · 2022 to 2026
$3.3M
Genetics at the Interface of Lipid and Glycemic TraitsR01HL136528 · NHLBI · UNIVERSITY OF ARIZONA · PI KLIMENTIDIS, YANN CHARLES · 2018 to 2020
$1.1M
Physical activity predictors of cognitive and brain health in the risk for Alzheimer's diseaseR56AG067200 · NIA · UNIVERSITY OF ARIZONA · PI ALEXANDER, GENE E, RAICHLEN, DAVID · 2020 to 2020
$767k
NHLBI NIH HHS R01 HL136528NIA NIH HHS P30 AG019610NIA NIH HHS P30 AG072980NIA NIH HHS R01 AG064587NIA NIH HHS R01 AG072445NIA NIH HHS R56 AG067200
6 · The paper itself

Abstract

Background: Late-onset Alzheimer's disease (LOAD) represents a growing health burden. Previous studies suggest that blood metabolite levels influence risk of LOAD. Objective: We used a genetics-based study design which may overcome limitations of other epidemiological studies to assess the influence of metabolite levels on LOAD risk. Methods: We applied Mendelian randomization (MR) to evaluate bi-directional causal effects using summary statistics from the largest genome-wide association studies (GWAS) of 249 blood metabolites (n = 115,082) and GWAS of LOAD (ncase = 21,982, ncontrol = 41,944). Results: MR analysis of metabolites as exposures revealed a negative association of genetically-predicted glutamine levels with LOAD (Odds Ratio (OR) = 0.83, 95% CI = 0.73, 0.92) that was consistent in multiple sensitivity analyses. We also identified a positive association of genetically-predicted free cholesterol levels in small LDL (OR = 1.79, 95% CI = 1.36, 2.22) on LOAD. Using genetically-predicted LOAD as the exposure, we identified associations with phospholipids to total lipids ratio in large LDL (OR = 0.96, 95% CI = 0.94, 0.98), but not with glutamine, suggesting that the relationship between glutamine and LOAD is unidirectional. Conclusions: Our findings support previous evidence that higher circulating levels of glutamine may be a target for protection against LOAD.

Indexed as

Alzheimer DiseaseGlutamineGenome-Wide Association StudyHumansMendelian Randomization AnalysisOdds RatioPolymorphism, Single NucleotideGlutamineAlzheimer’s diseaseglutamineMendelian randomizationmetabolites

Identifiers

PMID38489176
PMCPMC11805495
OpenAlexW4392845701

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.