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Method for predicting complex diseases and phenotypic related metabolites based on Mendel randomization

A metabolite and randomization technology, applied in the field of life sciences, can solve the problems of environmental factor interference, poor stability of plasma metabolite detection, large individual differences, etc., and achieve the effect of improving statistical power

Pending Publication Date: 2020-06-26
XI AN JIAOTONG UNIV
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Problems solved by technology

At present, metabolomics research on complex diseases and phenotypes has discovered a number of metabolic characteristics, but the detection stability of plasma metabolite levels is poor, and there are problems of large individual differences and large interference by environmental factors

Method used

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  • Method for predicting complex diseases and phenotypic related metabolites based on Mendel randomization
  • Method for predicting complex diseases and phenotypic related metabolites based on Mendel randomization

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Embodiment

[0059] The development of height will be affected by congenital genetics and acquired environmental factors, and its growth process follows the law of rapid growth in infancy, slow growth in mid-childhood and growth spurt in adolescence. Previous studies have found strong relationships between height at different growth stages and environmental factors such as dietary habits, socioeconomic status, and health, suggesting that increases in human height are associated with overall improvements in human lifestyles. How to scientifically and effectively promote children's height through nutritional supplements has become an important issue of concern to parents.

[0060] Human blood metabolites are intermediate products in the metabolic process of the human body, which can describe the results of the interaction between the human body and the body, and reveal the potential mechanism of environmental and genetic factors on human metabolism. Observational and retrospective studies ha...

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Abstract

The invention discloses a method for predicting complex diseases and phenotypic related metabolites based on Mendel randomization analysis. The method comprises the following steps: (1) collecting andsorting blood metabolite whole genome association research data; (2) screening tool variables and removing multiple effects; and (3) performing double-sample Mendel randomization analysis according to the screened tool variables, and obtaining metabolites related to diseases or phenotypes by integrating judgment of effect values and sensitivity analysis of multiple analysis methods. According tothe method, the influence of 363 blood metabolites on complex diseases and phenotypes is predicted through double-sample Mendel randomization analysis in combination with screening and discriminationof multiple methods, and an important foundation is laid for subsequent searching of drug targets for the blood metabolites and nutrition intervention.

Description

technical field [0001] The invention relates to the field of life sciences, in particular to a method for predicting complex diseases and phenotype-related metabolites based on Mendelian randomization. Background technique [0002] Mendelian randomization is an epidemiological research method that can use genetic variation related to exposure factors as an instrumental variable to assess the causal relationship between two phenotypes, and has been widely used in disease research. Different from genome-wide association studies, Mendelian randomization can effectively screen the "causal" factors affecting outcome variables, rather than traditional correlation studies, and previous genome-wide association studies have only reported a small number of disease / phenotype associations genetic loci, the statistical power is limited by the population sample size. However, large-scale genome-wide association studies can provide us with rich genetic variation information and use it in ...

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Application Information

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IPC IPC(8): G16H50/30G16B20/20
CPCG16H50/30G16B20/20Y02A90/10
Inventor 杨铁林张堃郭燕吴昊郭婧丁景苗
Owner XI AN JIAOTONG UNIV
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