Evidence map›Paper›PMID 37398015›Full record

ArticlemedRxiv : the preprint server for health sciences2023

Circulating Metabolites May Illustrate Relationship of Alcohol Consumption with Cardiovascular Disease.

Yi Li, Mengyao Wang, Xue Liu, Jian Rong, Patricia Emogene Miller, Roby Joehanes, Tianxiao Huan, Xiuqing Guo, Jerome Rotter, Jennifer Smith and 5 more

Open access · greenAbstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 6 institutions in 1 country.

Yi LiDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA, U.S.
Mengyao WangDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA, U.S.
Xue LiuDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA, U.S.
Jian RongDepartment of Neurology, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, U.S.
Patricia Emogene MillerDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA, U.S.
Roby JoehanesPopulation Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, US.
Tianxiao HuanPopulation Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, US.
Xiuqing GuoThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, U.S.
Jerome RotterThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, U.S.
Jennifer SmithDepartment of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, U.S.
Bing YuDepartment of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, U.S.
Matthew NayorSections of Cardiovascular Medicine and Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, MA, U.S.
Daniel LevyPopulation Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, US.
Chunyu LiuDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA, U.S.
Jiantao MaFriedman School of Nutrition Science and Policy, Tufts University, Boston, MA, U.S.
Boston University · USNational Institutes of Health · USUCLA Medical Center · USThe University of Texas Health Science Center at Houston · USTufts University · USUniversity of Michigan · US

Funding

FRAMINGHAM HEART STUDY - YEAR 5 EXAM75N92019D00031 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · 2019 to 2024
$29.8M
Trans-omic Analysis of Alcohol Consumption and its Relation to Cardiovascular DiseaseR01AA028263 · NIAAA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI LIU, CHUNYU, MA, JIANTAO · 2021 to 2025
$2.6M
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NHLBI NIH HHS 75N92019D00031NHLBI NIH HHS HHSN268201500001CNHLBI NIH HHS HHSN268201500001INHLBI NIH HHS N01 HC025195NIAAA NIH HHS R01 AA028263
6 · The paper itself

Abstract

Background: Metabolite signatures of long-term alcohol consumption are lacking. To better understand the molecular basis linking alcohol drinking and cardiovascular disease (CVD), we investigated circulating metabolites associated with long-term alcohol consumption and examined whether these metabolites were associated with incident CVD. Methods: Cumulative average alcohol consumption (g/day) was derived from the total consumption of beer, wine and liquor on average of 19 years in 2,428 Framingham Heart Study Offspring participants (mean age 56 years, 52% women). We used linear mixed models to investigate the associations of alcohol consumption with 211 log-transformed plasma metabolites, adjusting for age, sex, batch, smoking, diet, physical activity, BMI, and familial relationship. Cox models were used to test the association of alcohol-related metabolite scores with fatal and nonfatal incident CVD (myocardial infarction, coronary heart disease, stroke, and heart failure). Results: We identified 60 metabolites associated with cumulative average alcohol consumption (p<0.05/211≈0.00024). For example, one g/day increase of alcohol consumption was associated with higher levels of cholesteryl esters (e.g., CE 16:1, beta=0.023±0.002, p=6.3e-45) and phosphatidylcholine (e.g., PC 32:1, beta=0.021±0.002, p=3.1e-38). Survival analysis identified that 10 alcohol-associated metabolites were also associated with a differential CVD risk after adjusting for age, sex, and batch. Further, we built two alcohol consumption weighted metabolite scores using these 10 metabolites and showed that, with adjustment age, sex, batch, and common CVD risk factors, the two scores had comparable but opposite associations with incident CVD, hazard ratio 1.11(95% CI=[1.02, 1.21],p=0.02) vs 0.88 (95% CI=[0.78, 0.98], p=0.02). Summary: We identified 60 long-term alcohol consumption-associated metabolites. The association analysis with incident CVD suggests a complex metabolic basis between alcohol consumption and CVD.

Indexed as

alcohol consumptioncardiovascular diseasemetabolites

Identifiers

PMID37398015
PMCPMC10312833
OpenAlexW4379106475

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.