التفاصيل البيبلوغرافية
| العنوان: |
Applying Mendelian randomization to appraise causality in relationships between nutrition and cancer |
| المؤلفون: |
Wade, Kaitlin, Yarmolinsky, James, Giovannucci, Edward, Lewis, Sarah J., Millwood, Iona Y, Munafo, Marcus Robert, Meddens, Fleur, Burrows, Kimberley, Bell, Joshua A, Davies, Neil Martin, Mariosa, Daniela, Kanerva, Noora, Vincent, Emma E, Smith-Byrne, Karl, Guida, Florence, Gunter, Marc J., Sanderson, Eleanor, Dudbridge, Frank, Burgess, Stephen, Cornelis, Marilyn C, Richardson, Tom, Borges, Maria Carolina, Bowden, Jack, Hemani, Gibran, Cho, Yoonsu, Spiller, Wes, Richmond, Rebecca, Carter, Alice, Langdon, Ryan, Lawlor, Deborah A, Walters, Robin G, Vimaleswaran, Karani Santhanakrishnan, Anderson, Annie, Sandu, Meda, Tilling, Kate, Smith, George Davey, Martin, Richard, Relton, Caroline, group, in Nutrition and Cancer working |
| بيانات النشر: |
Center for Open Science |
| سنة النشر: |
2021 |
| الوصف: |
Dietary factors are assumed to play an important role in cancer risk, apparent in consensus recommendations for cancer prevention that promote nutritional changes. However, the evidence in this field has been generated predominantly through observational studies, which may result in biased effect estimates because of confounding, exposure misclassification, and reverse causality. With major geographical differences and rapid changes in cancer incidence over time, it is crucial to establish which of the observational associations reflect causality and to identify novel risk factors as these may be modified to prevent the onset of cancer and reduce its progression. Mendelian randomization (MR) uses the special properties of germline genetic variation to strengthen causal inference regarding potentially modifiable exposures and disease risk. MR can be implemented through instrumental variable (IV) analysis and, when robustly performed, is generally less prone to confounding, reverse causation and measurement error than conventional observational methods and has different sources of bias (discussed in detail below). It is increasingly used to facilitate causal inference in epidemiology and provides an opportunity to explore the effects of nutritional exposures on cancer incidence and progression in a cost-effective and timely manner.Here, we introduce the concept of MR and discuss its current application in understanding the impact of nutritional factors (e.g., any measure of diet and nutritional intake, circulating biomarkers, patterns, preference or behaviour) on cancer aetiology and, thus, opportunities for MR to contribute to the development of nutritional recommendations and policies for cancer prevention. We provide applied examples of MR studies examining the role of nutritional factors in cancer to illustrate how this method can be used to help prioritise or deprioritise the evaluation of specific nutritional factors as intervention targets in randomised controlled trials. We describe possible biases when ... |
| نوع الوثيقة: |
other/unknown material |
| اللغة: |
unknown |
| DOI: |
10.31219/osf.io/9uyc7 |
| الإتاحة: |
https://doi.org/10.31219/osf.io/9uyc7Test |
| حقوق: |
https://creativecommons.org/licenses/by/4.0/legalcodeTest |
| رقم الانضمام: |
edsbas.8B7A38AA |
| قاعدة البيانات: |
BASE |
