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Mendelian randomization evidence for the causal effects of socio-economic inequality on human longevity among Europeans

Nature Human Behaviour volume 7, pages 1357–1370 (2023)Cite this article

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Abstract

Human longevity correlates with socio-economic status, and there is evidence that educational attainment increases human lifespan. However, to inform meaningful health policies, we need fine-grained causal evidence on which dimensions of socio-economic status affect longevity and the mediating roles of modifiable factors such as lifestyle and disease. Here we performed two-sample Mendelian randomization analyses applying genetic instruments of education, income and occupation (n = 248,847 to 1,131,881) to estimate their causal effects and consequences on parental lifespan and self-longevity (n = 28,967 to 1,012,240) from the largest available genome-wide association studies in populations of European ancestry. Each 4.20 years of additional educational attainment were causally associated with a 3.23-year-longer parental lifespan independently of income and occupation and were causally associated with 30–59% higher odds of self-longevity, suggesting that education was the primary determinant. By contrast, each one-standard-deviation-higher income and one-point-higher occupation was causally associated with 3.06-year-longer and 1.29-year-longer parental lifespans, respectively, but not independently of the other socio-economic indicators. We found no evidence for causal effects of income or occupation on self-longevity. Mediation analyses conducted in predominantly European-descent individuals through two-step Mendelian randomization suggested that among 59 candidates, cigarettes per day, body mass index, waist-to-hip ratio, hypertension, coronary heart disease, myocardial infarction, stroke, Alzheimer’s disease, type 2 diabetes, heart failure and lung cancer individually played substantial mediating roles (proportion mediated, >10%) in the effect of education on specific longevity outcomes. These findings inform interventions for remediating longevity disparities attributable to socio-economic inequality.

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Fig. 1: Overview of the MR study design.
Fig. 2: UVMR and MVMR estimates for the causal associations of education, income and occupation with parental lifespan.
Fig. 3: Selection process for mediators of the causal associations of education with parental lifespan and self-longevity.
Fig. 4: Mediating role of each mediator in the causal associations of education with parental lifespan and self-longevity.

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Data availability

All GWAS summary statistics analysed in this study are publicly available for download by qualified researchers as shown in Table 1. The GWAS data for education can be obtained through the SSGAC data portal (http://www.thessgac.org/data). The GWAS data for income can be obtained at https://gwas.mrcieu.ac.uk/datasets/?trait__icontains=Household%20income. The GWAS data for occupation can be obtained from the GWAS catalogue (http://ftp.ebi.ac.uk/pub/databases/gwas/summary_statistics/GCST90102001-GCST90103000/GCST90102253/). The GWAS data for parental lifespan can be obtained at https://doi.org/10.7488/ds/2463. The GWAS data for self-longevity can be obtained at https://www.longevitygenomics.org/downloads and through GRASP (https://grasp.nhlbi.nih.gov/FullResults.aspx) and the NHGRI-EBI GWAS Catalog (https://www.ebi.ac.uk/gwas/downloads/summary-statistics). All data generated in the current study can be obtained from the Supplementary Information.

Code availability

All the analyses used in this study were conducted using the R packages TwoSampleMR (version 0.5.6), MVMR (version 0.3), MRPRESSO (version 1.0) and MRlap (version 0.0.3.0) in R software (version 4.0.3; R Development Core Team). Custom code that supports the findings of this study is available at https://github.com/yechaojie/2SMR.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (nos 82022011, 81970706, 82088102 and 81970728), the ‘Shanghai Municipal Education Commission–Gaofeng Clinical Medicine Grant Support’ from Shanghai Jiao Tong University School of Medicine (no. 20171901 Round 2) and the Innovative Research Team of High-Level Local Universities in Shanghai. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We thank the participants in all the GWASs used in this manuscript and the investigators who made these GWAS data publicly available.

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  1. These authors contributed equally: Chao-Jie Ye, Li-Jie Kong, Yi-Ying Wang.

Authors and Affiliations

  1. Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Chao-Jie Ye, Li-Jie Kong, Yi-Ying Wang, Chun Dou, Jie Zheng, Min Xu, Yu Xu, Mian Li, Zhi-Yun Zhao, Jie-Li Lu, Yu-Hong Chen, Guang Ning, Wei-Qing Wang, Yu-Fang Bi & Tian-Ge Wang

  2. Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Chao-Jie Ye, Li-Jie Kong, Yi-Ying Wang, Chun Dou, Jie Zheng, Min Xu, Yu Xu, Mian Li, Zhi-Yun Zhao, Jie-Li Lu, Yu-Hong Chen, Guang Ning, Wei-Qing Wang, Yu-Fang Bi & Tian-Ge Wang

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Contributions

C.-J.Y. and T.-G.W. contributed to the conception and design of the study. C.-J.Y. performed the statistical analysis and drafted the manuscript. T.-G.W. critically revised the manuscript and checked the statistical analysis. T.-G.W., Y.-F.B., W.-Q.W. and G.N. obtained the funding. All authors contributed to the acquisition or interpretation of data, proofreading of the manuscript for important intellectual content and the final approval of the version to be published. T.-G.W. is the guarantor of this work and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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Correspondence to Wei-Qing Wang, Yu-Fang Bi or Tian-Ge Wang.

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Nature Human Behaviour thanks Yongfu Yu, Shuai Yuan and Brenda Cabrera-Mendoza for their contribution to the peer review of this work.

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Supplementary Methods, Tables 1–12 and Figs. 1 and 2.

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Ye, CJ., Kong, LJ., Wang, YY. et al. Mendelian randomization evidence for the causal effects of socio-economic inequality on human longevity among Europeans. Nat Hum Behav 7, 1357–1370 (2023). https://doi.org/10.1038/s41562-023-01646-1

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