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Milk intake and incident stroke and coronary heart disease in populations of European descent : A Mendelian Randomization study

Vissers, L. E.T. ; Sluijs, I. ; Burgess, S. ; Forouhi, N. G. ; Freisling, H. ; Imamura, F. ; Nilsson, T. K. ; Renström, F. ; Weiderpass, E. and Aleksandrova, K. , et al. (2022) In British Journal of Nutrition 128(9). p.1789-1797
Abstract

Higher milk intake has been associated with a lower stroke risk, but not with risk of coronary heart disease (CHD). Residual confounding or reverse causation cannot be excluded. Therefore, we estimated the causal association of milk consumption with stroke and CHD risk through instrumental variable (IV) and gene-outcome analyses. IV analysis included 29,328 participants (4,611 stroke; 9,828 CHD) of the EPIC-CVD (8 European countries) and EPIC-NL case-cohort studies. rs4988235, a lactase persistence (LP) single nucleotide polymorphism which enables digestion of lactose in adulthood was used as genetic instrument. Intake of milk was first regressed on rs4988235 in a linear regression model. Next, associations of genetically predicted milk... (More)

Higher milk intake has been associated with a lower stroke risk, but not with risk of coronary heart disease (CHD). Residual confounding or reverse causation cannot be excluded. Therefore, we estimated the causal association of milk consumption with stroke and CHD risk through instrumental variable (IV) and gene-outcome analyses. IV analysis included 29,328 participants (4,611 stroke; 9,828 CHD) of the EPIC-CVD (8 European countries) and EPIC-NL case-cohort studies. rs4988235, a lactase persistence (LP) single nucleotide polymorphism which enables digestion of lactose in adulthood was used as genetic instrument. Intake of milk was first regressed on rs4988235 in a linear regression model. Next, associations of genetically predicted milk consumption with stroke and CHD were estimated using Prentice-weighted Cox regression. Gene-outcome analysis included 777,024 participants (50,804 cases) from MEGASTROKE (including EPIC-CVD), UK Biobank and EPIC-NL for stroke, and 483,966 participants (61,612 cases) from CARDIoGRAM, UK Biobank and EPIC-CVD and EPIC-NL for CHD. In IV analyses, each additional LP allele was associated with a higher intake of milk in EPIC-CVD (β=13.7 g/day; 95%CI: 8.4-19.1) and EPIC-NL (36.8 g/day; 20.0-53.5). Genetically predicted milk intake was not associated with stroke (HR per 25 g/day 1.05; 95%CI: 0.94-1.16) or CHD (1.02; 0.96-1.08). In gene-outcome analyses, there was no association of rs4988235 with risk of stroke (odds ratios 1.02; 0.99-1.05) or CHD (0.99; 0.95-1.03). Current Mendelian Randomization analysis does not provide evidence for a causal inverse relationship between milk consumption and stroke or CHD risk.

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organization
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type
Contribution to journal
publication status
published
subject
keywords
CHD, dairy, Mendelian Randomization, Milk, stroke
in
British Journal of Nutrition
volume
128
issue
9
pages
1789 - 1797
publisher
Cambridge University Press
external identifiers
  • pmid:34670632
  • scopus:85119366658
ISSN
0007-1145
DOI
10.1017/S0007114521004244
language
English
LU publication?
yes
id
3bc09ba6-914d-4dff-adf3-086eb20ea3be
date added to LUP
2021-12-13 14:02:58
date last changed
2023-04-02 20:11:48
@article{3bc09ba6-914d-4dff-adf3-086eb20ea3be,
  abstract     = {{<p>Higher milk intake has been associated with a lower stroke risk, but not with risk of coronary heart disease (CHD). Residual confounding or reverse causation cannot be excluded. Therefore, we estimated the causal association of milk consumption with stroke and CHD risk through instrumental variable (IV) and gene-outcome analyses. IV analysis included 29,328 participants (4,611 stroke; 9,828 CHD) of the EPIC-CVD (8 European countries) and EPIC-NL case-cohort studies. rs4988235, a lactase persistence (LP) single nucleotide polymorphism which enables digestion of lactose in adulthood was used as genetic instrument. Intake of milk was first regressed on rs4988235 in a linear regression model. Next, associations of genetically predicted milk consumption with stroke and CHD were estimated using Prentice-weighted Cox regression. Gene-outcome analysis included 777,024 participants (50,804 cases) from MEGASTROKE (including EPIC-CVD), UK Biobank and EPIC-NL for stroke, and 483,966 participants (61,612 cases) from CARDIoGRAM, UK Biobank and EPIC-CVD and EPIC-NL for CHD. In IV analyses, each additional LP allele was associated with a higher intake of milk in EPIC-CVD (β=13.7 g/day; 95%CI: 8.4-19.1) and EPIC-NL (36.8 g/day; 20.0-53.5). Genetically predicted milk intake was not associated with stroke (HR per 25 g/day 1.05; 95%CI: 0.94-1.16) or CHD (1.02; 0.96-1.08). In gene-outcome analyses, there was no association of rs4988235 with risk of stroke (odds ratios 1.02; 0.99-1.05) or CHD (0.99; 0.95-1.03). Current Mendelian Randomization analysis does not provide evidence for a causal inverse relationship between milk consumption and stroke or CHD risk.</p>}},
  author       = {{Vissers, L. E.T. and Sluijs, I. and Burgess, S. and Forouhi, N. G. and Freisling, H. and Imamura, F. and Nilsson, T. K. and Renström, F. and Weiderpass, E. and Aleksandrova, K. and Dahm, C. C. and Perez-Cornago, A. and Schulze, M. B. and Tong, T. Y.N. and Aune, D. and Bonet, C. and Boer, J. M.A. and Boeing, H. and Chirlaque, M. D. and Conchi, M. I. and Imaz, L. and Jäger, S. and Krogh, V. and Kyrø, C. and Masala, G. and Melander, O. and Overvad, K. and Panico, S. and Sánches, M. J. and Sonestedt, E. and Tjønneland, A. and Tzoulaki, I. and Verschuren, W. M.M. and Riboli, E. and Wareham, N. J. and Danesh, J. and Butterworth, A. S. and Van Der Schouw, Y. T.}},
  issn         = {{0007-1145}},
  keywords     = {{CHD; dairy; Mendelian Randomization; Milk; stroke}},
  language     = {{eng}},
  number       = {{9}},
  pages        = {{1789--1797}},
  publisher    = {{Cambridge University Press}},
  series       = {{British Journal of Nutrition}},
  title        = {{Milk intake and incident stroke and coronary heart disease in populations of European descent : A Mendelian Randomization study}},
  url          = {{http://dx.doi.org/10.1017/S0007114521004244}},
  doi          = {{10.1017/S0007114521004244}},
  volume       = {{128}},
  year         = {{2022}},
}