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Human body biological age prediction and human body aging degree evaluation method based on whole peripheral blood transcriptome

A peripheral blood, transcriptome technology, applied in genomics, biostatistics, bioinformatics, etc., can solve the problem of inaccurate aging degree

Active Publication Date: 2021-09-10
ZHEJIANG UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, routine physical examination indicators can only roughly reflect the short-term and apparent health status of the human body, and are not accurate enough to measure the degree of aging

Method used

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  • Human body biological age prediction and human body aging degree evaluation method based on whole peripheral blood transcriptome
  • Human body biological age prediction and human body aging degree evaluation method based on whole peripheral blood transcriptome
  • Human body biological age prediction and human body aging degree evaluation method based on whole peripheral blood transcriptome

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0047] 522 volunteers were collected, and the transcription group sequencing for the peripheral blood samples of the volunteers, and the resulting expression matrix did data pretreatment: 1. Remove the repeating gene (repeated retention expression amount), the expression matrix is ​​standardized; 2. Remove 11 samples of the total number of sequencing and median distances greater than the average absolute dispersion (MAD); 3. Filtering a gene with a lower expression of expression (only in total samples of less than 10%); 4. According to the overall age, the sample is removed from the median distance greater than the average absolute dispersion (MAD), that is, the sample is greater than 70 years (4 cases). After pre-treatment, the proportion of 3: 1 is randomly divided into training sets and test sets. 13684 genes and genders such as filtering all neuropathic growth factor 2 (Nell2) were used as characteristics, and data was normalized to normal distribution, and the elastic network...

Embodiment 2

[0053] Example 2: Collect 522 volunteers, to perform transcription group sequencing for the peripheral blood samples of volunteers, and the resulting expression matrix is ​​preprocessing with Example 1. By pre-treatment, the genes of genes with age have been linearly equipped with age, and the significance of the relationship between the primary and age changes and the significance of gender is obtained. G i Indicates the expression of the i-th gene. Linear fittings for each gene is performed by the following formula.

[0054] G i ~ Agn + sex

[0055] The Sum of Square is obtained by the ANOVA. In order to explore the influence of gender and age on a gene expression, explore the relative proportion of variance interpreted by two variables, calculate the ETA party:

[0056]

[0057] The gene of less than 0.05 and gender ETA <0.9 * age ETA is determined as a aging gene, a total of 1038, with a characteristic selection of subsequent modeling.

[0058] Note: The analysis process is ...

Embodiment 3

[0060] 522 volunteers were collected, and the peripheral blood samples of volunteers were collected, and the resulting expression matrix was preprocessed with Example 1. After pre-treatment, the proportion of 3: 1 is divided into training sets and test sets. Using the support vector machine regression algorithm, 1038 aging genes and gender are used as a characteristic, and the data is normalized to normal distribution, and training is carried out in training. After 5, the fork verification parameter search is obtained, and the model is: linear core, parameter regularization parameter c = 1, EPSILON = 1. Verify the aging clock model based on the support vector machine regression on the test set.

[0061] Support vector machine regression is an application that supports vector machine in regression problem. First, use a core function to map data to a feature space, and then find a super plane, minimize loss functions, and loss functions It is ξ to the residual of the region in the ...

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Abstract

The invention relates to a human body biological age prediction and human body aging degree evaluation method based on a whole peripheral blood transcriptome, and the method comprises the steps: employing a generalized elastic network (including lasso regression and ridge regression), support vector machine regression, progressive gradient regression, random forest regression, a deep neural network and other machine learning and deep learning algorithms to construct an aging clock model for the human transcriptome data; further performing analyzing to obtain aging genes and subsets thereof, and optimizing a human body aging clock model; and predicting test data by using the optimized aging clock model, and comparing the difference between the predicted age and the actual age so as to evaluate the biological age and the aging speed of the human body. The method can be used for evaluating the anti-aging effect of various anti-aging intervention measures and the inflammation state, the health state, the aging state and the like of an individual system, so that a personalized and precise anti-aging scheme and a clinical intervention scheme are established.

Description

Technical field: [0001] The present invention relates to the field of life and health, in particular, the present invention relates to a prediction based on transcripts of human whole blood age, body assess the extent of aging process. Background technique: [0002] World population is rapidly aging. By 2050, the global population aged 60 and over will increase to 20 billion. Since 1999, our country had already entered the aging society, as of 2018, my country's population aged 60 and over reached 250 million, accounting for 17.9%. By 2030, the proportion of the population aged 60 and over in Chinese rural and urban areas respectively amounted to 21.8% and 14.8%. China's aging population base large, rapidly growing, how to protect the health of the elderly, health is essential for achieving the strategic objectives of China. On the other hand, with the general improvement in the quality of people's lives, people are no longer satisfied to cure the sick elderly, but for a healthy ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16B30/00G16B5/00G16B40/00G16B20/00G16H50/30
CPCG16B30/00G16B5/00G16B40/00G16B20/00G16H50/30Y02A90/10
Inventor 欧阳宏伟吴兵兵沈夕琳蒋炜李余邹晓晖
Owner ZHEJIANG UNIV
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