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Cognitive performance protects against Alzheimer’s disease independently of educational attainment and intelligence

Molecular Psychiatry volume 27, pages 4297–4306 (2022)Cite this article

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Abstract

Mendelian-randomization (MR) studies using large-scale genome-wide association studies (GWAS) have identified causal association between educational attainment and Alzheimer’s disease (AD). However, the underlying mechanisms are still required to be explored. Here, we conduct univariable and multivariable MR analyses using large-scale educational attainment, cognitive performance, intelligence and AD GWAS datasets. In stage 1, we found significant causal effects of educational attainment on cognitive performance (beta = 0.907, 95% confidence interval (CI): 0.884–0.930, P < 1.145E−299), and vice versa (beta = 0.571, 95% CI: 0.557–0.585, P < 1.145E−299). In stage 2, we found that both increase in educational attainment (odds ratio (OR) = 0.72, 95% CI: 0.66–0.78, P = 1.39E−14) and cognitive performance (OR = 0.69, 95% CI: 0.64–0.75, P = 1.78E−20) could reduce the risk of AD. In stage 3, we found that educational attainment may protect against AD dependently of cognitive performance (OR = 1.07, 95% CI: 0.90–1.28, P = 4.48E−01), and cognitive performance may protect against AD independently of educational attainment (OR = 0.69, 95% CI: 0.53–0.89, P = 5.00E−03). In stage 4, we found significant causal effects of cognitive performance on intelligence (beta = 0.907, 95% CI: 0.877–0.938, P < 1.145E−299), and vice versa (beta = 0.957, 95% CI: 0.937–0.978, P < 1.145E−299). In stage 5, we identified that cognitive performance may protect against AD independently of intelligence (OR = 0.74, 95% CI: 0.61–0.90, P = 2.00E−03), and intelligence may protect against AD dependently of cognitive performance (OR = 1.17, 95% CI: 0.40–3.43, P = 4.48E−01). Collectively, our univariable and multivariable MR analyses highlight the protective role of cognitive performance in AD independently of educational attainment and intelligence. In addition to the intelligence, we extend the mechanisms underlying the associations of educational attainment with AD.

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Fig. 1: The flow chart about the MR study design.
Fig. 2: Individual estimates about the causal effect of educational attainment on AD using IVW method.
Fig. 3: Individual estimates about the causal effect of cognitive performance on AD using IVW method.

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Data availability

All relevant data are within the paper. The authors confirm that all data underlying the findings are either fully available without restriction through consortia websites, or may be made available from consortia upon request. AD GWAS dataset is available at https://www.niagads.org/datasets/ng00075; Educational attainment and cognitive performance GWAS datasets are available at https://www.thessgac.org/data; Intelligence GWAS dataset is available at https://ctg.cncr.nl/software/summary_statistics.

Code availability

Two-sample MR analyses and multivariable MR analysis was conducted using MendelianRandomization (version 0.5.0) packages in R. Codes associated with the current submission can be requested by contacting the corresponding author.

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Acknowledgements

We thank the International Genomics of Alzheimer’s Project (IGAP) and Complex Trait Genetics lab (CTGlab), Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University & VU Medical Centre Amsterdam for providing summary results data. The investigators within IGAP contributed to the design and implementation of IGAP and/or provided data but did not participate in analysis or writing of this report. IGAP was made possible by the generous participation of the control subjects, the patients, and their families. The i-Select chips was funded by the French National Foundation on AD and related disorders. EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital. GERAD was supported by the Medical Research Council (Grant n° 503480), Alzheimer’s Research UK (Grant no 503176), the Wellcome Trust (Grant no 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant no 01GI0102, 01GI0711, 01GI0420. CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01-AG-12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University. ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer’s Association grant ADGC-10-196728. This research has been conducted using the UK Biobank resource (https://www.ukbiobank.ac.uk). We thank the individual patients who provided the sample that made data available; without them the study would not have been possible.

Funding

This work was supported by funding from the National Natural Science Foundation of China (Grant No. 82071212, and 81901181), Beijing Natural Science Foundation (Grant No. JQ21022), the Mathematical Tianyuan Fund of the National Natural Science Foundation of China (Grant No. 12026414), and Beijing Ten Thousand Talents Project (Grant No. 2020A15). This work was also partially supported by funding from the Science and Technology Beijing One Hundred Leading Talent Training Project (Z141107001514006), the Beijing Municipal Administration of Hospitals’ Mission Plan (SML20150802), the Funds of Academic Promotion Programme of Shandong First Medical University & Shandong Academy of Medical Sciences (Nos. 2019QL016 and 2019PT007).

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150080, China

    Yang Hu

  2. Department of Pathology, The Affiliated Hospital of Weifang Medical University, Weifang, 261053, China

    Yan Zhang

  3. Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, 100069, China

    Haihua Zhang, Shan Gao & Guiyou Liu

  4. Department of Anesthesiology, The Affiliated Hospital of Weifang Medical University, Weifang, 261053, China

    Longcai Wang

  5. Chinese Institute for Brain Research, Beijing, China

    Tao Wang & Guiyou Liu

  6. State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, China

    Zhifa Han

  7. Key Laboratory of Cerebral Microcirculation in Universities of Shandong; Department of Neurology, Second Affiliated Hospital; Shandong First Medical University & Shandong Academy of Medical Sciences, Taian, 271000, Shandong, China

    Bao-liang Sun & Guiyou Liu

  8. Beijing Key Laboratory of Hypoxia Translational Medicine, National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China

    Guiyou Liu

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Contributions

GYL and YH designed the study; GYL and YH analyzed the data; all authors contributed to the interpretation of the results and critical revision of the manuscript for important intellectual content and approved the final version of the manuscript.

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Correspondence to Guiyou Liu.

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Hu, Y., Zhang, Y., Zhang, H. et al. Cognitive performance protects against Alzheimer’s disease independently of educational attainment and intelligence. Mol Psychiatry 27, 4297–4306 (2022). https://doi.org/10.1038/s41380-022-01695-4

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  • DOI: https://doi.org/10.1038/s41380-022-01695-4

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