Functional Connectome Hierarchy Distortions in Female Nurses With Occupational Burnout and Its Gene Expression Signatures

Author:

Shang Yingying1,Su Qian23,Ma Rong1,Chen Miao1,Zhao Ziyang1,Yao Chaofan1,Han Lin234,Yao Zhijun1,Hu Bin156ORCID

Affiliation:

1. Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering Lanzhou University Lanzhou Gansu Province China

2. Department of Nursing Gansu Provincial Hospital Lanzhou Gansu Province China

3. The First Clinical Medical School Lanzhou University Lanzhou Gansu Province China

4. School of Nursing Lanzhou University Lanzhou Gansu Province China

5. Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University & Institute of Semiconductors Chinese Academy of Sciences Lanzhou Gansu Province China

6. Engineering Research Center of Open Source Software and Real‐Time System (Lanzhou University) Ministry of Education Lanzhou Gansu Province China

Abstract

BackgroundBurnout has become a serious public health issue worldwide, particularly during the COVID‐19 pandemic. Functional connectome impairments associated with occupational burnout were widely distributed, involving both low‐level sensorimotor cortices and high‐level association cortices.PurposeTo investigate whether there are hierarchical perturbations in the functional connectomes and if these perturbations are potentially influenced by genetic factors in nurses who feel “burned out.”Study TypeProspective, case control.PopulationThirty‐three female nurses with occupational burnout (aged 27–40, 32.42 ± 3.37) and 32 matched nurses who were not feeling burned out (aged 27–42, 32.50 ± 4.21).Field Strength/Sequence3.0 T, gradient‐echo echo‐planar imaging sequence (GE‐EPI).AssessmentGradient‐based techniques were used to depict the perturbations in the multi‐dimensional hierarchical structure of the macroscale connectome. Gene expression data were acquired from the Allen Human Brain Atlas.Statistical TestsCortex‐wide multivariate analyses were used for between‐group differences in gradients as well as association analyses between the hierarchy distortions and the MBI score (FDR corrected). Partial least squares, spin test and bootstrapping were utilized together to select the gene sets (FDR corrected). Gene enrichment analyses (GO, KEGG and cell‐type) were further performed. Significance level: P < 0.05.ResultsThere were significant gradient distortions, with strong between‐group effects in the somatosensory network and moderate effects in the higher‐order default‐mode network, which were significantly correlated with the gene expression profiles (r = 0.3171). The most related genes were broadly involved in the cellular response to minerals, neuronal plasticity, and the circadian rhythm pathway (q value < 0.01). Significant enrichments were found in excitatory (r = 0.2588), inhibitory neurons (r = 0.2610), and astrocytes cells (r = 0.2633). Regions affected by burnout severity were mainly distributed in the association and visual cortices.Data ConclusionBy connecting in vivo imaging to genes, cell classes, and clinical data, this study provides a framework to understand functional impairments in occupational burnout and how the microscopic genetic architecture drive macroscopic distortions.Evidence Level1Technical EfficacyStage 2

Funder

National Basic Research Program of China

National Natural Science Foundation of China

Science and Technology Program of Gansu Province

Publisher

Wiley

Subject

Radiology, Nuclear Medicine and imaging

Reference40 articles.

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