Cargando…

Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity

Type 2 diabetes mellitus (T2DM) is closely linked to cognitive decline and alterations in brain structure and function. Resting-state functional magnetic resonance imaging (rs-fMRI) is used to diagnose neurodegenerative diseases, such as cognitive impairment (CI), Alzheimer’s disease (AD), and vascu...

Descripción completa

Detalles Bibliográficos
Autores principales: Wu, Jinjian, Fang, Yuqi, Tan, Xin, Kang, Shangyu, Yue, Xiaomei, Rao, Yawen, Huang, Haoming, Liu, Mingxia, Qiu, Shijun, Yap, Pew-Thian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998866/
https://www.ncbi.nlm.nih.gov/pubmed/36894561
http://dx.doi.org/10.1038/s41598-023-28163-5
_version_ 1784903543386275840
author Wu, Jinjian
Fang, Yuqi
Tan, Xin
Kang, Shangyu
Yue, Xiaomei
Rao, Yawen
Huang, Haoming
Liu, Mingxia
Qiu, Shijun
Yap, Pew-Thian
author_facet Wu, Jinjian
Fang, Yuqi
Tan, Xin
Kang, Shangyu
Yue, Xiaomei
Rao, Yawen
Huang, Haoming
Liu, Mingxia
Qiu, Shijun
Yap, Pew-Thian
author_sort Wu, Jinjian
collection PubMed
description Type 2 diabetes mellitus (T2DM) is closely linked to cognitive decline and alterations in brain structure and function. Resting-state functional magnetic resonance imaging (rs-fMRI) is used to diagnose neurodegenerative diseases, such as cognitive impairment (CI), Alzheimer’s disease (AD), and vascular dementia (VaD). However, whether the functional connectivity (FC) of patients with T2DM and mild cognitive impairment (T2DM-MCI) is conducive to early diagnosis remains unclear. To answer this question, we analyzed the rs-fMRI data of 37 patients with T2DM and mild cognitive impairment (T2DM-MCI), 93 patients with T2DM but no cognitive impairment (T2DM-NCI), and 69 normal controls (NC). We achieved an accuracy of 87.91% in T2DM-MCI versus T2DM-NCI classification and 80% in T2DM-NCI versus NC classification using the XGBoost model. The thalamus, angular, caudate nucleus, and paracentral lobule contributed most to the classification outcome. Our findings provide valuable knowledge to classify and predict T2DM-related CI, can help with early clinical diagnosis of T2DM-MCI, and provide a basis for future studies.
format Online
Article
Text
id pubmed-9998866
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Nature Publishing Group UK
record_format MEDLINE/PubMed
spelling pubmed-99988662023-03-11 Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity Wu, Jinjian Fang, Yuqi Tan, Xin Kang, Shangyu Yue, Xiaomei Rao, Yawen Huang, Haoming Liu, Mingxia Qiu, Shijun Yap, Pew-Thian Sci Rep Article Type 2 diabetes mellitus (T2DM) is closely linked to cognitive decline and alterations in brain structure and function. Resting-state functional magnetic resonance imaging (rs-fMRI) is used to diagnose neurodegenerative diseases, such as cognitive impairment (CI), Alzheimer’s disease (AD), and vascular dementia (VaD). However, whether the functional connectivity (FC) of patients with T2DM and mild cognitive impairment (T2DM-MCI) is conducive to early diagnosis remains unclear. To answer this question, we analyzed the rs-fMRI data of 37 patients with T2DM and mild cognitive impairment (T2DM-MCI), 93 patients with T2DM but no cognitive impairment (T2DM-NCI), and 69 normal controls (NC). We achieved an accuracy of 87.91% in T2DM-MCI versus T2DM-NCI classification and 80% in T2DM-NCI versus NC classification using the XGBoost model. The thalamus, angular, caudate nucleus, and paracentral lobule contributed most to the classification outcome. Our findings provide valuable knowledge to classify and predict T2DM-related CI, can help with early clinical diagnosis of T2DM-MCI, and provide a basis for future studies. Nature Publishing Group UK 2023-03-09 /pmc/articles/PMC9998866/ /pubmed/36894561 http://dx.doi.org/10.1038/s41598-023-28163-5 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wu, Jinjian
Fang, Yuqi
Tan, Xin
Kang, Shangyu
Yue, Xiaomei
Rao, Yawen
Huang, Haoming
Liu, Mingxia
Qiu, Shijun
Yap, Pew-Thian
Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity
title Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity
title_full Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity
title_fullStr Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity
title_full_unstemmed Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity
title_short Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity
title_sort detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9998866/
https://www.ncbi.nlm.nih.gov/pubmed/36894561
http://dx.doi.org/10.1038/s41598-023-28163-5
work_keys_str_mv AT wujinjian detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT fangyuqi detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT tanxin detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT kangshangyu detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT yuexiaomei detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT raoyawen detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT huanghaoming detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT liumingxia detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT qiushijun detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity
AT yappewthian detectingtype2diabetesmellituscognitiveimpairmentusingwholebrainfunctionalconnectivity