Evidence map›Paper›PMID 40001252›Full record

ArticleHuman genomics2025

Causal effects of education, intelligence, and income on COVID-19: evidence from a Mendelian randomization study.

Yuqing Song, Ancha Baranova, Hongbao Cao, Weihua Yue, Fuquan Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Human genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Yuqing SongInstitute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
Ancha BaranovaSchool of Systems Biology, George Mason University, Manassas, 20110, USA.
Hongbao CaoSchool of Systems Biology, George Mason University, Manassas, 20110, USA.
Weihua YueInstitute of Mental Health, Peking University Sixth Hospital, Beijing, 100191, China.
Fuquan ZhangInstitute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China. zhangfq@njmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe protective effects of higher educational attainment (EA) and intelligence on COVID-19 outcomes are not yet understood with regard to their dependency on income. The objective of our study was to examine the overall as well as independent effects of the three psychosocial factors on the susceptibility to and severity of COVID-19. To accomplish this, we utilized genetic correlation, Mendelian randomization (MR), and multivariable MR (MVMR) analyses to evaluate genetic associations between EA, intelligence, household income, and three specific COVID-19 outcomes: SARS-CoV-2 infection, hospitalized COVID-19, and critical COVID-19.

resultsThe genetic correlation analysis revealed that COVID-19 outcomes were negatively correlated with the three psychosocial factors (r

conclusionsOur findings indicated that EA could significantly reduce the risk and severity of COVID-19, regardless of intelligence and income. However, the impact of intelligence or income on COVID-19 severity was not supported by our research.

Indexed as

COVID-19Health EducationIncomeIntelligenceDatasets as TopicHospitalizationHumansMendelian Randomization AnalysisRisk FactorsTreatment OutcomeCOVID-19Educational attainmentGeneticsIncomeIntelligenceMendelian randomizationSocioeconomic status

Identifiers

PMID40001252
PMCPMC11863516

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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.