Evidence map›Paper›PMID 36424608›Full record

SynthesisBMC medicine2022

Health effects of milk consumption: phenome-wide Mendelian randomization study.

Shuai Yuan, Jing Sun, Ying Lu, Fengzhe Xu, Doudou Li, Fangyuan Jiang, Zhongxiao Wan, Xue Li, Li-Qiang Qin, Susanna C Larsson

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in BMC medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
4.7field-weighted citation impact, top 5% 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

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

  1. Pooled it
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  6. Nutrition: A non-negligible factor in the pathogenesis and treatment of Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    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

10 authors at 5 institutions in 2 countries.

Shuai YuanDepartment of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Jing SunDepartment of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Ying LuDepartment of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Fengzhe XuKey Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou, China.
Doudou LiDepartment of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Fangyuan JiangDepartment of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Zhongxiao WanDepartment of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou, China.
Xue LiDepartment of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. xueli157@zju.edu.cn.
Li-Qiang QinDepartment of Nutrition and Food Hygiene, School of Public Health, Soochow University, Suzhou, China. qinliqiang@suda.edu.cn.
Susanna C LarssonUnit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. susanna.larsson@surgsci.uu.se.ORCID 0000-0003-0118-0341
Second Affiliated Hospital of Zhejiang University · CNSoochow University · CNKarolinska Institutet · SEUppsala University · SEWestlake University · CN

Funding

Forskningsrådet om Hälsa, Arbetsliv och Välfärd 2018-00123Hjärt-Lungfonden 20210351Medical Research Council MC_PC_17228Medical Research Council MC_QA137853Vetenskapsrådet 2019-00977
6 · The paper itself

Abstract

backgroundWe performed phenome-wide Mendelian randomization analysis (MR-PheWAS), two-sample MR analysis, and systemic review to comprehensively explore the health effects of milk consumption in the European population.

methodsRs4988235 located upstream of the LCT gene was used as the instrumental variable for milk consumption. MR-PheWAS analysis was conducted to map the association of genetically predicted milk consumption with 1081 phenotypes in the UK Biobank study (n=339,197). The associations identified in MR-PheWAS were examined by two-sample MR analysis using data from the FinnGen study (n=260,405) and international consortia. A systematic review of MR studies on milk consumption was further performed.

resultsPheWAS and two-sample MR analyses found robust evidence in support of inverse associations of genetically predicted milk consumption with risk of cataract (odds ratio (OR) per 50 g/day increase in milk consumption, 0.89, 95% confidence interval (CI), 0.84-0.94; p=3.81×10

conclusionsThis study suggests several health effects of milk consumption in the European population.

Indexed as

Diabetes Mellitus, Type 2Kidney NeoplasmsAnimalsHumansMendelian Randomization AnalysisMilkPolymorphism, Single NucleotideHealthMendelian randomizationMilkPheWASSystematic review

Identifiers

PMID36424608
PMCPMC9694907
OpenAlexW4309891357

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.