Lack of structural brain alterations associated with insomnia: findings from the ENIGMA-Sleep Working Group

• Published in: Journal of sleep research Vol. 32; no. 5; p. e13884
• Main Authors: Weihs, Antoine, Frenzel, Stefan, Bi, Hanwen, Schiel, Julian E, Afshani, Mortaza, Bülow, Robin, Ewert, Ralf, Fietze, Ingo, Hoffstaedter, Felix, Jahanshad, Neda, Khazaie, Habibolah, Riemann, Dieter, Rostampour, Masoumeh, Stubbe, Beate, Thomopoulos, Sophia I, Thompson, Paul M, Valk, Sofie L, Völzke, Henry, Zarei, Mojtaba, Eickhoff, Simon B, Grabe, Hans J, Patil, Kaustubh R, Spiegelhalder, Kai, Tahmasian, Masoud
• Format: Journal Article
• Language: English
• Published: England 01.10.2023
• Subjects: meta-analysis; Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA)-sleep; brain volume; insomnia
• ISSN: 0962-1105; 1365-2869
• DOI: 10.1111/jsr.13884

Existing neuroimaging studies have reported divergent structural alterations in insomnia disorder (ID). In the present study, we performed a large-scale coordinated meta-analysis by pooling structural brain measures from 1085 subjects (mean [SD] age 50.5 [13.9] years, 50.2% female, 17.4% with insomnia) across three international Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA)-Sleep cohorts. Two sites recruited patients with ID/controls: Freiburg (University of Freiburg Medical Center, Freiburg, Germany) 42/43 and KUMS (Kermanshah University of Medical Sciences, Kermanshah, Iran) 42/49, while the Study of Health in Pomerania (SHIP-Trend, University Medicine Greifswald, Greifswald, Germany) recruited population-based individuals with/without insomnia symptoms 75/662. The influence of insomnia on magnetic resonance imaging-based brain morphometry using an insomnia brain score was then assessed. Within each cohort, we used an ordinary least-squares linear regression to investigate the link between the individual regional cortical and subcortical volumes and the presence of insomnia symptoms. Then, we performed a fixed-effects meta-analysis across cohorts based on the first-level results. For the insomnia brain score, weighted logistic ridge regression was performed on one sample (Freiburg), which separated patients with ID from controls to train a model based on the segmentation measurements. Afterward, the insomnia brain scores were validated using the other two samples. The model was used to predict the log-odds of the subjects with insomnia given individual insomnia-related brain atrophy. After adjusting for multiple comparisons, we did not detect any significant associations between insomnia symptoms and cortical or subcortical volumes, nor could we identify a global insomnia-related brain atrophy pattern. Thus, we observed inconsistent brain morphology differences between individuals with and without insomnia across three independent cohorts. Further large-scale cross-sectional/longitudinal studies using both structural and functional neuroimaging are warranted to decipher the neurobiology of insomnia.