Evidence map›Paper›PMID 38472333›Full record

ArticleCommunications medicine2024

Unravelling the complex causal effects of substance use behaviours on common diseases.

Angli Xue, Zhihong Zhu, Huanwei Wang, Longda Jiang, Peter M Visscher, Jian Zeng, Jian Yang

Open access · goldAbstract read
In one paragraph

Article in Communications medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
11.6field-weighted citation impact, top 1% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

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  13. Deriving Mendelian Randomization-Based Causal Networks of Brain Imaging Phenotypes and Bipolar Disorder.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026
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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

7 authors at 2 institutions in 3 countries.

Angli XueInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.ORCID http://orcid.org/0000-0002-0285-0426
Zhihong ZhuInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.ORCID http://orcid.org/0000-0002-6783-3037
Huanwei WangInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.ORCID http://orcid.org/0000-0002-6137-3391
Longda JiangInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
Peter M VisscherInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.ORCID http://orcid.org/0000-0002-2143-8760
Jian ZengInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.ORCID http://orcid.org/0000-0001-8801-5220
Jian YangInstitute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia. jian.yang@westlake.edu.cn.ORCID http://orcid.org/0000-0003-2001-2474
The University of Queensland · AUGarvan Institute of Medical Research · AU

Funding

Department of Education and Training | Australian Research Council (ARC) FL180100072Department of Education and Training | Australian Research Council (ARC) FT180100186Department of Health | National Health and Medical Research Council (NHMRC) 1113400Department of Health | National Health and Medical Research Council (NHMRC) 1177268
6 · The paper itself

Abstract

backgroundSubstance use behaviours (SUB) including smoking, alcohol consumption, and coffee intake are associated with many health outcomes. However, whether the health effects of SUB are causal remains controversial, especially for alcohol consumption and coffee intake.

methodsIn this study, we assess 11 commonly used Mendelian Randomization (MR) methods by simulation and apply them to investigate the causal relationship between 7 SUB traits and health outcomes. We also combine stratified regression, genetic correlation, and MR analyses to investigate the dosage-dependent effects.

resultsWe show that smoking initiation has widespread risk effects on common diseases such as asthma, type 2 diabetes, and peripheral vascular disease. Alcohol consumption shows risk effects specifically on cardiovascular diseases, dyslipidemia, and hypertensive diseases. We find evidence of dosage-dependent effects of coffee and tea intake on common diseases (e.g., cardiovascular disease and osteoarthritis). We observe that the minor allele effect of rs4410790 (the top signal for tea intake level) is negative on heavy tea intake

conclusionOur study reveals the complexity of the health effects of SUB and informs design for future studies aiming to dissect the causal relationships between behavioural traits and complex diseases.

Identifiers

PMID38472333
PMCPMC10933313
OpenAlexW4394764523

What OpenQuestion holds

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LicenceCC BY
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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.