Letter | Published:

Causal associations of blood lipids with risk of ischemic stroke and intracerebral hemorrhage in Chinese adults

Abstract

Stroke is the second leading cause of death worldwide and accounts for >2 million deaths annually in China1,2. Ischemic stroke (IS) and intracerebral hemorrhage (ICH) account for an equal number of deaths in China, despite a fourfold greater incidence of IS1,2. Stroke incidence and ICH proportion are higher in China than in Western populations3,4,5, despite having a lower mean low-density lipoprotein cholesterol (LDL-C) concentration. Observational studies reported weaker positive associations of LDL-C with IS than with coronary heart disease (CHD)6,7, but LDL-C-lowering trials demonstrated similar risk reductions for IS and CHD8,9,10. Mendelian randomization studies of LDL-C and IS have reported conflicting results11,12,13, and concerns about the excess risks of ICH associated with lowering LDL-C14,15 may have prevented the more widespread use of statins in China. We examined the associations of biochemically measured lipids with stroke in a nested case-control study in the China Kadoorie Biobank (CKB) and compared the risks for both stroke types associated with equivalent differences in LDL-C in Mendelian randomization analyses. The results demonstrated positive associations of LDL-C with IS and equally strong inverse associations with ICH, which were confirmed by genetic analyses and LDL-C-lowering trials. Lowering LDL-C is still likely to have net benefit for the prevention of overall stroke and cardiovascular disease in China.

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Data availability

R.Clarke, D.B., L.L., and Z.C. have full access to all the study data and take responsibility for the integrity of the data and the accuracy of the data analysis. Data from the baseline survey, first resurvey, and cause-specific mortality are available to all bona fide researchers (www.ckbiobank.org). Additional data can also be made available on a collaborative basis by contacting the study investigators. All data requests are reviewed monthly by the CKB Data Access Committee, which is composed of senior scientists from Beijing and Oxford.

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Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Acknowledgements

We wish to thank the participants, project staff, and staff of the China Center for Disease Control and its regional offices for access to death and disease registries. The Chinese National Health Insurance scheme provided electronic linkage to all hospitalization data. The CKB study is jointly coordinated by the University of Oxford and the Chinese Academy of Medical Sciences. The funding body for the baseline survey was the Kadoorie Charitable Foundation, Hong Kong, China. Z.C. was funded for the long-term continuation of the study by Wellcome Trust grants (nos. 202922/Z/16/Z, 104085/Z/14/Z, and 088158/Z/09/Z). L.L. was funded by the National Natural Science Foundation of China (grant nos. 81390540, 81390541, and 81390544) and the National Key Research and Development Program of China (grant nos. 2016YFC0900500, 2016YFC0900501, 2016YFC0900504, and 2016YFC1303904). Core funding was also provided to the Clinical Trial Service Unit, University of Oxford, by the British Heart Foundation, the UK Medical Research Council, and Cancer Research UK. L.S. received a Clarendon Scholarship from the University of Oxford. The funders played no role in the design or conduct of the study, including data collection, management, analysis, or interpretation of the results; the preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication.

Author information

L.S., R.Clarke, D.B., R.P., and Z.C. designed and planned the analysis and manuscript. L.S. performed the data analyses and wrote the first draft of the manuscript. R.Clarke, D.B., S.P., R.P., and Z.C. provided scientific interpretation of the results and revised the manuscript. R.Clarke, Z.C., L.L., R.P., R.Collins, R.W., J.L., and J.C., as members of the CKB steering committee, designed and supervised the overall conduct of the study and obtained the funding. Y.G., Y.C., Z.B., C.Y., and Z.C. coordinated the data acquisition (for baseline, resurveys, and long-term follow-up). R.W., Y.G., I.M., Z.B., and M.H. coordinated the genotyping analyses in China and the laboratory analyses in Oxford. All authors provided critical comments on the final version of the manuscript.

Competing interests

The authors declare no competing interests.

Correspondence to Robert Clarke or Zhengming Chen.

Extended data

Extended Data Fig. 1 Effect of progressive adjustment for potential confounders on the risk of IS and ICH with usual LDL-C.

Cox regression was used to estimate adjusted RRs (95% confidence intervals (CI)) for the risk of different stroke types per 1 mmol l−1 higher concentrations of usual LDL-C. Each square has an area inversely proportional to the variance of the log risk. The horizontal lines represent the 95% CIs.

Extended Data Fig. 2 Associations of usual LDL-C with risk of IS and ICH in population subgroups at baseline.

Cox regression was used to estimate the adjusted RRs (95% CIs) for the risk of different stroke types per 1 mmol l−1 higher concentrations of usual LDL-C. Chi-squared tests were used to assess heterogeneity and trend; the d.f. are provided as subscripts. All two-sided P values were uncorrected for multiple testing. Symbols and conventions as in Extended Data Fig. 1.

Extended Data Fig. 3 Adjusted RRs for the risk of IS by usual concentrations of LDL-C and HDL-C in observational analyses in the CKB.

Symbols and conventions as in Extended Data Fig. 1. The number of IS cases and controls were 5,475 and 6,290, respectively.

Extended Data Fig. 4 Adjusted RRs for the risk of IS and ICH by usual concentrations of apolipoprotein B and A1, and lipoprotein(a) in observational analyses in the CKB.

ac, Cox regression was used to estimate the RRs (95% CIs) for IS (N = 5,475) and ICH (N = 4,776) by fifths of usual apolipoprotein B (a), usual apolipoprotein A1 (b), and usual lipoprotein(a) (c), respectively. The line represents the slope from a weighted linear regression with the weights based on the inverse variance of the log RR. Symbols and conventions as in Extended Data Fig. 1.

Extended Data Fig. 5 Associations of the GRS for LDL-C with major vascular risk factors.

The analyses were conducted in 17,567 CKB participants with available data, adjusted for sex, age, age2, and case status. General linear regression was used to estimate s.d. differences in all traits (after rank inverse normal transformation) per 1 s.d. higher GRS. All two-sided P values were uncorrected for multiple testing.

Extended Data Fig. 6 Meta-analysis of randomized trials of LDL-C-lowering treatment with statins, ezetimibe, or PCSK9 inhibitor and risk of IS and ICH.

Study-specific RRs (95% CI) were obtained from the published results of the LDL-C-lowering trials. The overall RRs (95% CIs) were obtained by inverse variance-weighted meta-analysis of the study-specific RRs per 1 mmol l−1 lower LDL-C concentration.

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Further reading

Fig. 1: Adjusted RRs for risk of IS and ICH by fifths of usual concentrations of LDL-C, HDL-C, and triglycerides in observational analyses in the CKB.
Fig. 2: Adjusted RRs for risk of IS and ICH associated with 1 mmol l−1 lower LDL-C in observational and genetic analyses in the CKB, and in randomized trials of LDL-C-lowering drug treatment in Western populations.
Fig. 3: Predicted number of events avoided for IS, MCEs, and ICH per 10,000 patients treated by lowering LDL-C by 1 mmol l−1 with statins for 5 years in Chinese adults with different levels of vascular risk.
Extended Data Fig. 1: Effect of progressive adjustment for potential confounders on the risk of IS and ICH with usual LDL-C.
Extended Data Fig. 2: Associations of usual LDL-C with risk of IS and ICH in population subgroups at baseline.
Extended Data Fig. 3: Adjusted RRs for the risk of IS by usual concentrations of LDL-C and HDL-C in observational analyses in the CKB.
Extended Data Fig. 4: Adjusted RRs for the risk of IS and ICH by usual concentrations of apolipoprotein B and A1, and lipoprotein(a) in observational analyses in the CKB.
Extended Data Fig. 5: Associations of the GRS for LDL-C with major vascular risk factors.
Extended Data Fig. 6: Meta-analysis of randomized trials of LDL-C-lowering treatment with statins, ezetimibe, or PCSK9 inhibitor and risk of IS and ICH.