Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Biomarkers for predicting degree of weight loss

一种生物标志物、体重减轻的技术，应用在生物测试、生物材料分析、测量装置等方向，能够解决不能提供体重减轻程度的预测或指示、无预测价值等问题

Inactive Publication Date: 2017-04-19
SOC DES PROD NESTLE SA
View PDF12 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these methods do not provide a prediction or indication of the degree of weight loss obtainable in a particular subject
No predictive value when studying association of biomarker levels with weight loss

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Biomarkers for predicting degree of weight loss
  • Biomarkers for predicting degree of weight loss

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0144] Example 1 - Predicting the Extent of Weight Loss Following a Hypocaloric Meal

[0145] Subjects participated in the Diogenes study. This study is a pan-European, randomized and controlled dietary intervention study investigating the effect of dietary protein and glycemic index on weight loss and weight maintenance in obese and overweight households in eight European centers (Larsen et al., Obesity reviews (2009), 11, 76-91 (Larsen et al., Obesity Review, 2009, Vol. 11, pp. 76-91)).

[0146] Example 1 involved 938 European individuals, of whom 782 completed the 8-week LCD program and 714 completed all required measurements in a range acceptable for live subjects. The general parameters of the individuals are shown in Table 1.

[0147] parameter mean (standard deviation) female percentage 64 (not applicable) age 41.5(6.3) BMI in front of the LCD (BMI1) 34.6(4.9) BMI after LCD (BMI2) 30.8(4.4) Fasting level of fructosamine (μmo...

Embodiment 2

[0161] Example 2 - Stratification of subjects according to predicted weight loss

[0162] Example 2 involves the same subjects as Example 1, but instead of predicting BMI2 (BMI after hypocaloric intervention), it focuses on predicting the probability that a subject is "weight loss sensitive" or "weight loss tolerant" .

[0163] Table 4 includes the coefficients for the biomarkers, and the significance of the corresponding predicted probabilities for "weight loss tolerance" and "weight loss sensitivity", where probabilities are adjusted for age and sex.

[0164]

[0165] Table 4: Probability of predicting "weight loss tolerance" and "weight loss sensitivity" using the following definitions and cut-off values Signs and p-values ​​of biomarker coefficients in rates (adjusted for age and sex): "Weight loss tolerance" means predicted The measured BMI reduction is less than the 30th (15th) percentile of the expected BMI reduction. "Weight loss sensitivity" refers to the ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

A method for predicting the degree of weight loss attainable by applying one or more dietary interventions to a subject, said method comprising determining the level of one or more biomarkers in one or more samples obtained from the subject, wherein the biomarkers are selected from fructosamine and factor VII.

Description

technical field [0001] The present invention provides various biomarkers and combinations of biomarkers that can be used to predict the degree of weight loss obtainable by applying one or more dietary interventions to a subject. Background technique [0002] Obesity is a chronic metabolic disorder that has reached epidemic proportions in many parts of the world. Obesity is a major risk factor for serious comorbidities such as type 2 diabetes, cardiovascular disease, dyslipidemia and certain types of cancer (World Health Organ Tech Rep Ser. 2000; 894:i-xii, 1-253 (World Health Organization Technical Report Series 2000;894:i-xii,1-253)). [0003] It has long been recognized that hypocaloric dietary interventions are very effective in reducing body weight and that this weight loss is often accompanied by an improvement in the risk of obesity-related comorbidities, especially type 2 diabetes (World Health Organ TechRep Ser. 2000; 894: i- xii, 1-253 (World Health Organization T...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G01N33/573G01N33/86
CPCG01N33/573G01N33/86G01N2333/52G01N2333/62G01N2800/044G01N33/66G01N33/6893G01N2333/765G01N2333/96447G16H20/60G16H50/20
Inventor J·哈格尔I·伊林奇瓦A·瓦尔塞西亚W·萨里斯A·阿斯楚普
Owner SOC DES PROD NESTLE SA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com