Leveraging family history data to disentangle time-varying effects on disease risk using lifecourse Mendelian randomization

Tom G Richardson; Helena Urquijo; Michael V Holmes; George Davey Smith

doi:10.21203/rs.3.rs-1862835/v1

Leveraging family history data to disentangle time-varying effects on disease risk using lifecourse Mendelian randomization

Tom G Richardson^*, Helena Urquijo, Michael V Holmes, George Davey Smith

^*Corresponding author for this work

Research output: Contribution to journal › Article (Academic Journal) › peer-review

4 Citations (Scopus)

Abstract

Lifecourse Mendelian randomization is a causal inference technique which harnesses genetic variants with time-varying effects to develop insight into the influence of age-dependent lifestyle factors on disease risk. Here, we apply this approach to evaluate whether childhood body size has a direct consequence on 8 major disease endpoints by analysing parental history data from the UK Biobank study.

Our findings suggest that, whilst childhood body size increases later risk of outcomes such as heart disease (odds ratio (OR)=1.15, 95% CI=1.07 to 1.23, P=7.8x10-5) and diabetes (OR=1.43, 95% CI=1.31 to 1.56, P=9.4x10-15) based on parental history data, these findings are likely attributed to a sustained influence of being overweight for many years over the lifecourse. Likewise, we found evidence that remaining overweight throughout the lifecourse increases risk of lung cancer, which was partially mediated by lifetime smoking index. In contrast, using parental history data provided evidence that being overweight in childhood may have a protective effect on risk of breast cancer (OR=0.87, 95% CI=0.78 to 0.97, P=0.01), corroborating findings from observational studies and large-scale genetic consortia.

Large-scale family disease history data can provide a complementary source of evidence for epidemiological studies to exploit, particularly given that they are likely more robust to sources of selection bias (e.g. survival bias) compared to conventional case control studies. Leveraging these data using approaches such as lifecourse Mendelian randomization can help elucidate additional layers of evidence to dissect age-dependent effects on disease risk.

Original language	English
Pages (from-to)	765-769
Number of pages	5
Journal	European Journal of Epidemiology
Volume	38
Issue number	7
Early online date	8 May 2023
DOIs	https://doi.org/10.21203/rs.3.rs-1862835/v1 https://doi.org/10.1007/s10654-023-01001-8
Publication status	Published - 1 Jul 2023

Bibliographical note

Funding Information:
We would like to thank the participants of the UK Biobank study for making this research possible. GDS conducts research at the NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.

Funding Information:
This work was supported by the Integrative Epidemiology Unit which receives funding from the UK Medical Research Council and the University of Bristol (MC_UU_00011/1). HU is supported by a grant from the British Heart Foundation (BHF) (grant FS/17/60/33474).

Publisher Copyright:
© 2023, The Author(s).

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IEU: MRC Integrative Epidemiology Unit Quinquennial renewal
Gaunt, L. F. (Principal Investigator) & Davey Smith, G. (Principal Investigator)
1/04/18 → 31/03/23
Project: Research

Cite this

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abstract = "Lifecourse Mendelian randomization is a causal inference technique which harnesses genetic variants with time-varying effects to develop insight into the influence of age-dependent lifestyle factors on disease risk. Here, we apply this approach to evaluate whether childhood body size has a direct consequence on 8 major disease endpoints by analysing parental history data from the UK Biobank study.Our findings suggest that, whilst childhood body size increases later risk of outcomes such as heart disease (odds ratio (OR)=1.15, 95% CI=1.07 to 1.23, P=7.8x10-5) and diabetes (OR=1.43, 95% CI=1.31 to 1.56, P=9.4x10-15) based on parental history data, these findings are likely attributed to a sustained influence of being overweight for many years over the lifecourse. Likewise, we found evidence that remaining overweight throughout the lifecourse increases risk of lung cancer, which was partially mediated by lifetime smoking index. In contrast, using parental history data provided evidence that being overweight in childhood may have a protective effect on risk of breast cancer (OR=0.87, 95% CI=0.78 to 0.97, P=0.01), corroborating findings from observational studies and large-scale genetic consortia.Large-scale family disease history data can provide a complementary source of evidence for epidemiological studies to exploit, particularly given that they are likely more robust to sources of selection bias (e.g. survival bias) compared to conventional case control studies. Leveraging these data using approaches such as lifecourse Mendelian randomization can help elucidate additional layers of evidence to dissect age-dependent effects on disease risk. ",

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note = "Funding Information: We would like to thank the participants of the UK Biobank study for making this research possible. GDS conducts research at the NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. Funding Information: This work was supported by the Integrative Epidemiology Unit which receives funding from the UK Medical Research Council and the University of Bristol (MC_UU_00011/1). HU is supported by a grant from the British Heart Foundation (BHF) (grant FS/17/60/33474). Publisher Copyright: {\textcopyright} 2023, The Author(s).",

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N1 - Funding Information: We would like to thank the participants of the UK Biobank study for making this research possible. GDS conducts research at the NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health. Funding Information: This work was supported by the Integrative Epidemiology Unit which receives funding from the UK Medical Research Council and the University of Bristol (MC_UU_00011/1). HU is supported by a grant from the British Heart Foundation (BHF) (grant FS/17/60/33474). Publisher Copyright: © 2023, The Author(s).

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N2 - Lifecourse Mendelian randomization is a causal inference technique which harnesses genetic variants with time-varying effects to develop insight into the influence of age-dependent lifestyle factors on disease risk. Here, we apply this approach to evaluate whether childhood body size has a direct consequence on 8 major disease endpoints by analysing parental history data from the UK Biobank study.Our findings suggest that, whilst childhood body size increases later risk of outcomes such as heart disease (odds ratio (OR)=1.15, 95% CI=1.07 to 1.23, P=7.8x10-5) and diabetes (OR=1.43, 95% CI=1.31 to 1.56, P=9.4x10-15) based on parental history data, these findings are likely attributed to a sustained influence of being overweight for many years over the lifecourse. Likewise, we found evidence that remaining overweight throughout the lifecourse increases risk of lung cancer, which was partially mediated by lifetime smoking index. In contrast, using parental history data provided evidence that being overweight in childhood may have a protective effect on risk of breast cancer (OR=0.87, 95% CI=0.78 to 0.97, P=0.01), corroborating findings from observational studies and large-scale genetic consortia.Large-scale family disease history data can provide a complementary source of evidence for epidemiological studies to exploit, particularly given that they are likely more robust to sources of selection bias (e.g. survival bias) compared to conventional case control studies. Leveraging these data using approaches such as lifecourse Mendelian randomization can help elucidate additional layers of evidence to dissect age-dependent effects on disease risk.

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DO - 10.21203/rs.3.rs-1862835/v1

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Leveraging family history data to disentangle time-varying effects on disease risk using lifecourse Mendelian randomization

Abstract

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IEU: MRC Integrative Epidemiology Unit Quinquennial renewal

Cite this