AUTHOR=Yang Yang , Liang Wei , Wang Yongjun , Peng Dechang , Gong Liang , Wang Na , Huang Zhongjie , Yang Weikang 

TITLE=Hippocampal atrophy in neurofunctional subfields in insomnia individuals

JOURNAL=Frontiers in Neurology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2022.1014244

DOI=10.3389/fneur.2022.1014244

ISSN=1664-2295

ABSTRACT=Objectives: To investigate the pattern of volume changes in neurofunctional hippocampal subfields in patients with insomnia, and their associations with risk of development of insomnia.
Methods: A total of 12 0 insomnia patients (78 females, 42 males; mean age ± standard deviation, 43.74 ± 13.02 years) and 120 good sleepers (67 females, 53 males; mean age, 42.69 ± 12.24 years) were recruited. The left hippocampus was segmented into anterior (L1), middle (L2), and posterior (L3) subregions. The right hippocampus was segmented into top anterior (R1), second top anterior (R2), middle (R3), posterior (R4), and last posterior (R5) subregions. Multivariate Logistic regression was used to evaluate the associations of hippocampal volume of each subfield with the risk of development of insomnia. Mediation analyses were performed to evaluate mediated associations among post-insomnia negative emotion, insomnia severity and hippocampal volume atrophy. A visual easy-to-deploy risk nomogram was used for individual prediction of risk of development of insomnia.
Results: Hippocampal volume atrophy was identified in the L1, R1, and R2 subregions. L1 and R2 volume atrophy each predisposed to an approximate 3-fold higher risk of insomnia (L1, odds ratio: 2.90, 95% confidence intervals: [1.24, 6.76], p = 0.014; R2, 2.72 [1.19, 6.20], p = 0.018). Anxiety fully mediates the causal path of insomnia severity leading to R1 volume atrophy with a positive affect. We developed a practical and visual competing risk-nomogram tool for individual prediction of insomnia risk, which stratifies individuals into different levels of insomnia risk with the highest prediction accuracy of 97.4% and average C-statistic of 0.83.
Conclusions: Hippocampal atrophy in specific neurofunctional subfields was not only found to be associated with insomnia but also a significant risk factor predicting development of insomnia. Insomnia