Aberrant brain functional networks in type 2 diabetes mellitus : A graph theoretical and support-vector machine approach
Lin, L., Zhang, J., Liu, Y., Hao, X., Shen, J., Yu, Y., Xu, H., Cong, F., Li, H., & Wu, J. (2022). Aberrant brain functional networks in type 2 diabetes mellitus : A graph theoretical and support-vector machine approach. Frontiers in Human Neuroscience, 16, Article 974094. https://doi.org/10.3389/fnhum.2022.974094
Julkaistu sarjassa
Frontiers in Human NeurosciencePäivämäärä
2022Oppiaine
TekniikkaSecure Communications Engineering and Signal ProcessingEngineeringSecure Communications Engineering and Signal ProcessingTekijänoikeudet
© 2022 Lin, Zhang, Liu, Hao, Shen, Yu, Xu, Cong, Li and Wu.
Objective: Type 2 diabetes mellitus (T2DM) is a high risk of cognitive decline and dementia, but the underlying mechanisms are not yet clearly understood. This study aimed to explore the functional connectivity (FC) and topological properties among whole brain networks and correlations with impaired cognition and distinguish T2DM from healthy controls (HC) to identify potential biomarkers for cognition abnormalities.
Methods: A total of 80 T2DM and 55 well-matched HC were recruited in this study. Subjects’ clinical data, neuropsychological tests and resting-state functional magnetic resonance imaging data were acquired. Whole-brain network FC were mapped, the topological characteristics were analyzed using a graph-theoretic approach, the FC and topological characteristics of the network were compared between T2DM and HC using a general linear model, and correlations between networks and clinical and cognitive characteristics were identified. The support vector machine (SVM) model was used to identify differences between T2DM and HC.
Results: In patients with T2DM, FC was higher in two core regions [precuneus/posterior cingulated cortex (PCC)_1 and later prefrontal cortex_1] in the default mode network and lower in bilateral superior parietal lobes (within dorsal attention network), and decreased between the right medial frontal cortex and left auditory cortex. The FC of the right frontal medial-left auditory cortex was positively correlated with the Montreal Cognitive Assessment scales and negatively correlated with the blood glucose levels. Long-range connectivity between bilateral auditory cortex was missing in the T2DM. The nodal degree centrality and efficiency of PCC were higher in T2DM than in HC (P < 0.005). The nodal degree centrality in the PCC in the SVM model was 97.56% accurate in distinguishing T2DM patients from HC, demonstrating the reliability of the prediction model.
Conclusion: Functional abnormalities in the auditory cortex in T2DM may be related to cognitive impairment, such as memory and attention, and nodal degree centrality in the PCC might serve as a potential neuroimaging biomarker to predict and identify T2DM.
...
Julkaisija
Frontiers Media SAISSN Hae Julkaisufoorumista
1662-5161Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/160487428
Metadata
Näytä kaikki kuvailutiedotKokoelmat
Lisätietoja rahoituksesta
This work was supported by National Natural Science Foundation of China (grant number: 82071911) and from the Dalian Science and Technology Innovation Fund (2021JJ12SN38).Lisenssi
Samankaltainen aineisto
Näytetään aineistoja, joilla on samankaltainen nimeke tai asiasanat.
-
Verbal and academic skills in children with type 1 diabetes
Hannonen, Riitta (Jyväskylän yliopisto, 2011) -
Activity level in left auditory cortex predicts behavioral performance in inhibition tasks in children
van Bijnen, Sam; Parkkonen, Lauri; Parviainen, Tiina (Elsevier, 2022)Sensory processing during development is important for the emerging cognitive skills underlying goal-directed behavior. Yet, it is not known how auditory processing in children is related to their cognitive functions. Here, ... -
The relationship between structural properties of frontal cortical regions and response inhibition in 6–14-year-old children
Kujala, Jan; Matveinen, Sannamari; van Bijnen, Sam; Parviainen, Tiina (Elsevier, 2024)Development of attentional skills and inhibitory control rely on maturational changes in the brain across childhood and youth. However, both brain anatomy and different components of attention and inhibition show notable ... -
Reading Difficulties Identification : A Comparison of Neural Networks, Linear, and Mixture Models
Psyridou, Maria; Tolvanen, Asko; Patel, Priyanka; Khanolainen, Daria; Lerkkanen, Marja-Kristiina; Poikkeus, Anna-Maija; Torppa, Minna (Taylor & Francis, 2023)Purpose We aim to identify the most accurate model for predicting adolescent (Grade 9) reading difficulties (RD) in reading fluency and reading comprehension using 17 kindergarten-age variables. Three models (neural ... -
Biologically Informed Polygenic Scores for Brain Insulin Receptor Network Are Associated with Cardiometabolic Risk Markers and Diabetes in Women
Selenius, Jannica S.; Silveira, Patricia P.; Bonsdorff, Mikaela von; Lahti, Jari; Koistinen, Hannu; Koistinen, Riitta; Seppälä, Markku; Eriksson, Johan G.; Wasenius, Niko S. (Korean Diabetes Association, 2024)Background To investigate associations between variations in the co-expression-based brain insulin receptor polygenic score and cardiometabolic risk factors and diabetes mellitus. Methods This cross-sectional study ...
Ellei toisin mainittu, julkisesti saatavilla olevia JYX-metatietoja (poislukien tiivistelmät) saa vapaasti uudelleenkäyttää CC0-lisenssillä.