Convergent connectivity of sleep disorders and its neurotransmitter and cell enrichment correlates
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Sleep disorders are highly prevalent and impose a substantial public health burden, yet the neurobiological mechanisms underlying shared and disorder-specific abnormalities remain incompletely understood. We conducted a pre-registered transdiagnostic study to identify shared and distinct normative macroscale connectivity patterns associated with reported brain abnormalities across insomnia disorder, obstructive sleep apnea, narcolepsy, and rapid eye movement sleep behavior disorder, and to characterize their microscale neurotransmitter and cellular correlates. We obtained peak coordinates from 80 experiments reporting meta-analytic brain abnormalities across these four sleep disorders. Convergent connectivity mapping was then applied to these coordinates using dense connectivity matrices derived from 100 unrelated participants from the Human Connectome Project, with connectivity patterns evaluated relative to a null distribution generated from randomly selected foci. We subsequently examined the spatial correspondence of the identified connectivity maps with 19 neurotransmitter systems using curated positron emission tomography-derived density maps and assessed cellular enrichment across 24 cell-type systems using regional gene-expression profiles from the Allen Human Brain Atlas. Statistical significance was assessed using spin-based permutation testing and false discovery rate correction (pFDR < 0.05). Shared convergent connectivity patterns were identified within the default mode network (zmean = 1.103, pspin,FDR = 0.019), as well as the dorsal attention (zmean = −0.674, pspin,FDR = 0.014) and frontoparietal (zmean = −0.239, pspin,FDR = 0.019) resting-state networks. Disorder-specific analyses revealed broadly overlapping connectivity patterns, with some disorder-related variability. Both transdiagnostic and disorder-specific connectivity patterns showed selective spatial correspondence with multiple neurotransmitter systems, including serotonin, dopamine, norepinephrine, and glutamate, and were enriched for excitatory, inhibitory, and non-neuronal cell types (pFDR < 0.05). These findings indicate that sleep disorders share convergent macroscale connectivity architecture while also exhibiting disorder-specific variations, with the identified network patterns linked to distinct neurotransmitter and cellular profiles. Together, the results provide a normative systems-level framework for understanding shared and distinct neurobiological mechanisms across sleep disorders.
