Understanding the Causality between the risk of Cancer and Sugar Intake
China (IFMSA-China) - Nanjing Medical University, Nanjing
Biotechnologies and Informatics
Department of Biostatistics
Yang Zhao
4 weeks
Cities/Months Jan Feb Mar Apr May Jun Jul Augt Sep Oct Nov Dec
No No Yes No No No No No Yes No No No
Type of Research Project
- Basic science
What is the background of the project?
Previous studies have reported the association between cancer risk and sugar intake. While some studies described the increased risk of cancer by sugar intaking, no matter on natural sugar or artificial sugar, we also observed some protective effect for artificial sugar. Thus, causality of sugar on cancer still need to be confirmed. Sugar intake may be associated with factors including economic situation, diary activity, and genetics. These factors are also associated with cancer risk, leading to potential confounding and bias. At present, several large-scale cohort studies have provided detailed information on cancer outcome, behavior and genetics, making it possible to understand the causal relationship between sugar intake and cancer risk. Based on the datasets we have collected; we aim to use causal inference techniques to understand the potential causal mechanisms between sugar intake and cancer risk.
What is the aim of the project?
The aim of the project is to using the public datasets which we have collected to understand the causality between sugar intake and cancer risk. 1. Using Mendelian randomization analysis to understand the causality between sugar and cancer. 2. Using Mediation Analysis to understand the potential path between genetics, behavior and cancer.
What techniques and methods are used?
This is an analytic project, thus, the following techniques should be used: 1. Using statistical software for data management and analysis. SAS (Statistical Analysis System), SPSS (Statistical Product and Service Solutions) or R (statistical software) will be used. 2. Using descriptive statistics to understand the characteristics of the datasets. 3. Using multiple linear/logistic/Cox models to better understand the risk of sugar on cancer. Other elementary statistical tests, such as t test, F test, chi-square test and Wilcoxon rank sum test will also be used. 4. Using Mendelian Randomization and other methods on confounding for better understanding of causality. 5. Using Mediation Analysis to understand the direct or in-direct effect of sugar intake on cancer.
What is the role of the student?
- The student will observe the practical experiments but will be highly involved in the analysis of the results
- The tasks will be done under supervision
What are the tasks expected to be accomplished by the student?
1. Sorting, cleaning and merging of various datasets using Excel or SAS software. 2. Data Analysis. Statistical Analysis will be performed using SAS, SPSS, Stata or R (statistic software), whichever the students have the ability. The students will firstly use means or frequencies to describe the data. He will then use elementary statistical tests (t, F or chi-sq. tests) to perform univariate analysis. Later, he will perform multiple logistic or Cox regression analysis to further evaluate the risk of sugar intake. Finally, the students will perform causal analysis, including mediation analysis and Mendelian randomization analysis, to illustrate the potential causal mechanism. 3. Drafting Paper.
Will there be any theoretical teaching provided (preliminary readings, lectures, courses, seminars etc)
The department will provide training on data analysis skills. The student will also be involved in the school’s international courses. Preliminary readings will be provided, jointly by the faculties and senior graduate students. The readings will be given every two weeks. In addition, the tutor will discuss and explain in detail about the project that students will be conducting.
What is expected from the student at the end of the research exchange? What will be the general outcome of the student?
- The student will prepare a presentation
- The student will prepare a scientific report
- The student’s name will be mentioned in a future publication
What skills are required of the student? Is there any special knowledge or a certain level of studies needed?
This is an analytic project. Thus, strong skills in statistical programming using SAS, R or Stata is necessary. The students should also have knowledge on elementary and advanced statistical methods, including t test, chi-sq. test, linear regression, logistic regression and Cox model.
Are there any legal limitations in the student’s involvement
Type of students accepted
This project accepts:
- Medical students
- Graduated students (less than 6 months)
- Students in biomedical fields
- Consumption of sugar-sweetened and artificially-sweetened soft drinks and risk of cancers not related to obesity. Bassett JK; Milne RL; English DR; Giles GG; Hodge AM. Int J Cancer. 2019 Nov 6. doi: 10.1002/ijc.32772.