Cargando…
Risk assessment of type 2 diabetes in northern China based on the logistic regression model
BACKGROUND: Type 2 diabetes mellitus (T2DM) is a complex disease with high incidence and serious harm associated with polygenic determination. This study aimed to develop a predictive model so as to assess the risk of T2DM and apply it to health care and disease prevention in northern China. OBJECTI...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
IOS Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8158054/ https://www.ncbi.nlm.nih.gov/pubmed/33682772 http://dx.doi.org/10.3233/THC-218033 |
_version_ | 1783699803702558720 |
---|---|
author | Li, Chunrui Liu, Manjiao An, Yunhe Tian, Yanjie Guan, Di Wu, Huijuan Pei, Zhiyong |
author_facet | Li, Chunrui Liu, Manjiao An, Yunhe Tian, Yanjie Guan, Di Wu, Huijuan Pei, Zhiyong |
author_sort | Li, Chunrui |
collection | PubMed |
description | BACKGROUND: Type 2 diabetes mellitus (T2DM) is a complex disease with high incidence and serious harm associated with polygenic determination. This study aimed to develop a predictive model so as to assess the risk of T2DM and apply it to health care and disease prevention in northern China. OBJECTIVE: Based on genotyping results, a risk warning model for type 2 diabetes was established. METHODS: Blood samples of 1042 patients with T2DM in northern China were collected. Multiplex polymerase chain reaction and high-throughput sequencing (NGS) techniques were used to design the amplification-based targeted sequencing panel to sequence the 21 T2DM susceptibility genes. RESULT: The related key gene KQT-like subfamily member 1 played an important role in the T2DM risk model, and single-nucleotide polymorphism rs2237892 was highly significant, with a [Formula: see text] value of 1.2 [Formula: see text] 10 [Formula: see text]. CONCLUSIONS: Susceptibility genes in different populations were examined, and a model was developed to assess the risk-based genetic analysis. The performance of the model reached 92.8%. |
format | Online Article Text |
id | pubmed-8158054 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | IOS Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-81580542021-06-10 Risk assessment of type 2 diabetes in northern China based on the logistic regression model Li, Chunrui Liu, Manjiao An, Yunhe Tian, Yanjie Guan, Di Wu, Huijuan Pei, Zhiyong Technol Health Care Research Article BACKGROUND: Type 2 diabetes mellitus (T2DM) is a complex disease with high incidence and serious harm associated with polygenic determination. This study aimed to develop a predictive model so as to assess the risk of T2DM and apply it to health care and disease prevention in northern China. OBJECTIVE: Based on genotyping results, a risk warning model for type 2 diabetes was established. METHODS: Blood samples of 1042 patients with T2DM in northern China were collected. Multiplex polymerase chain reaction and high-throughput sequencing (NGS) techniques were used to design the amplification-based targeted sequencing panel to sequence the 21 T2DM susceptibility genes. RESULT: The related key gene KQT-like subfamily member 1 played an important role in the T2DM risk model, and single-nucleotide polymorphism rs2237892 was highly significant, with a [Formula: see text] value of 1.2 [Formula: see text] 10 [Formula: see text]. CONCLUSIONS: Susceptibility genes in different populations were examined, and a model was developed to assess the risk-based genetic analysis. The performance of the model reached 92.8%. IOS Press 2021-03-25 /pmc/articles/PMC8158054/ /pubmed/33682772 http://dx.doi.org/10.3233/THC-218033 Text en © 2021 – The authors. Published by IOS Press. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial (CC BY-NC 4.0) License (https://creativecommons.org/licenses/by-nc/4.0/) , which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Chunrui Liu, Manjiao An, Yunhe Tian, Yanjie Guan, Di Wu, Huijuan Pei, Zhiyong Risk assessment of type 2 diabetes in northern China based on the logistic regression model |
title | Risk assessment of type 2 diabetes in northern China based on the logistic regression model |
title_full | Risk assessment of type 2 diabetes in northern China based on the logistic regression model |
title_fullStr | Risk assessment of type 2 diabetes in northern China based on the logistic regression model |
title_full_unstemmed | Risk assessment of type 2 diabetes in northern China based on the logistic regression model |
title_short | Risk assessment of type 2 diabetes in northern China based on the logistic regression model |
title_sort | risk assessment of type 2 diabetes in northern china based on the logistic regression model |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8158054/ https://www.ncbi.nlm.nih.gov/pubmed/33682772 http://dx.doi.org/10.3233/THC-218033 |
work_keys_str_mv | AT lichunrui riskassessmentoftype2diabetesinnorthernchinabasedonthelogisticregressionmodel AT liumanjiao riskassessmentoftype2diabetesinnorthernchinabasedonthelogisticregressionmodel AT anyunhe riskassessmentoftype2diabetesinnorthernchinabasedonthelogisticregressionmodel AT tianyanjie riskassessmentoftype2diabetesinnorthernchinabasedonthelogisticregressionmodel AT guandi riskassessmentoftype2diabetesinnorthernchinabasedonthelogisticregressionmodel AT wuhuijuan riskassessmentoftype2diabetesinnorthernchinabasedonthelogisticregressionmodel AT peizhiyong riskassessmentoftype2diabetesinnorthernchinabasedonthelogisticregressionmodel |