The waking and working times of night shift workers are displaced relative to the natural light/dark cycle, putting behavioral patterns in misalignment with the circadian regulation of biological processes. This state of circadian misalignment constitutes a circadian health problem, with widespread negative consequences for metabolic, cardiovascular, and mental health, as well as elevated risk of cancer. Scientific advances over the past decade have shed light on key aspects of the underlying biological mechanisms. With a focus on recent human studies, this paper reviews novel insights into what drives the adverse health consequences of circadian misalignment due to night shift work. Misalignment between the central circadian pacemaker and externally driven behavioral patterns during night shift work produces a rapid uncoupling of peripheral rhythms, reflected in the cargo of exosomes and other signaling mechanisms, and causes conflict between central and peripheral regulatory mechanisms. This endogenous internal desynchrony has been shown to be linked to shifted meal timing and, in part, may be mediated by the gut microbiome. Endogenous internal desynchrony leads to insulin resistance – a manifestation of metabolic dysfunction. It perturbs the cardiometabolic and immune systems, and also erodes mental health. At the cellular level, mistimed DNA repair mechanisms leave residual DNA damage after exposure to a night shift schedule – which, over time, may result in genomic instability and ultimately carcinogenesis. A systems biology perspective serves to elucidate how the effects of endogenous circadian disruption from night shift work increase the risk of acute and chronic illnesses. Internal desynchrony, endogenous in nature, is a common underlying cause. Time-restricted eating may help to address metabolic dysfunction due to night shift work; countermeasures for other negative health outcomes, including cancer and mental health disorders, remain to be developed.
This review covers the pathophysiology of central sleep apnea (CSA) as well as summarizes the recently updated clinical practice guidelines from the American Academy of Sleep Medicine (AASM), published in 2025, on the treatment of CSA and their supporting evidence. Central sleep apnea is a group of sleep-related breathing disorders caused by unstable or depressed ventilatory drive. Updated clinical practice guidelines from the AASM offer conditional recommendations for six treatment options: continuous positive airway pressure (CPAP), bilevel positive airway pressure with a backup rate (BiPAP-BUR), adaptive servo-ventilation (ASV), supplemental oxygen, acetazolamide, and transvenous phrenic nerve stimulation (TPNS). However, the guidelines do not specify a preferred order or algorithm for choosing among these therapies. We provide a practical approach of how to utilize the new AASM CSA guidelines in everyday practice. Special attention is given to the changing role of ASV in heart failure and the emergence of TPNS.
Sleep disruptions, particularly insomnia, are highly prevalent across mental health disorders. While the bidirectional relationship between sleep and psychiatric conditions is well-established, the mechanisms are not fully understood. Genomic-driven precision medicine offers a promising avenue to personalize treatment to improve overall outcomes, yet few studies have focused on identifying clinically actionable, pleiotropic genes that link many of these conditions. This study utilized a pleiotropic prioritization pipeline to identify shared genetic loci between insomnia and eight mental health disorders using GWAS summary statistics. Recent Findings. Using FUMA for functional mapping (positional, ChIP-seq, and eQTL) we prioritized results using the Pharos database for drug-target relevance and ClinPGx for known pharmacogenomic (PGx) variants. We identified 2,567 genes associated with both insomnia and at least one mental health disorder. Two genes, APOB and PSMG3, overlapped across all the conditions investigated. Further filtering revealed six actionable PGx genes with clinical evidence: CYP2D6, DPYD, ALDH2, SLC19A1, CFTR, and F2. Our findings suggest that sleep disturbances and psychiatric disorders are linked through shared biological mechanisms rather than appearing as secondary symptoms. Limitations exist regarding ancestral diversity in genetic data and the reliance on self-reported sleep measures, however these prioritized genes provide a foundation for preemptive genotyping. Integrating pharmacogenomic insights into clinical practice holds potential to reduce trial-and-error prescribing, minimize adverse drug reactions, and improve overall patient outcomes through genotype-guided therapeutic interventions.
This review synthesizes the current evidence base for digital cognitive behavioural therapy for insomnia (dCBT-I) delivered to specific clinical and demographic populations, examining both tailored and non-tailored implementations to evaluate their effectiveness, acceptability, and feasibility across diverse groups. dCBT-I demonstrates efficacy across adolescents and young adults, perinatal populations, older adults, cancer survivors and those with other comorbidities, as well as shift workers. Cultural adaptations improve engagement and completion. Across populations, effect sizes are clinically meaningful, though protocol modifications often improve outcomes. dCBT-I is a scalable, evidence-based treatment that retains meaningful efficacy across a wide range of populations when appropriately adapted. Key adaptation strategies include tailoring sleep restriction parameters, incorporating population-specific psychoeducation, providing additional support, and embedding cultural and occupational relevance. Future research should prioritize adequately powered RCTs, longer follow-up, and head-to-head comparisons of adapted versus unadapted protocols in underserved groups.
Obstructive sleep apnea (OSA) is a common nocturnal breathing disorder characterized by recurrent upper airway obstruction during sleep, leading to sleep fragmentation and intermittent hypoxemia. The apnea-hypopnea index (AHI) is the most widely used clinical metric to assess OSA severity; however, the AHI fails to capture the full physiological burden caused by recurrent oxygen desaturations. Consequently, quantifying hypoxemia, the cumulative burden of oxygen desaturations, has become crucial for assessing the physiological impact of OSA more comprehensively. Furthermore, studies have illustrated that hypoxemia is associated with cardiovascular morbidity, metabolic dysfunction, and neurocognitive impairment in OSA patients. This narrative review aims to explore various methods used to quantify nocturnal hypoxemia from sleep recordings and discuss the different approaches, and their association with OSA-related comorbidities. The discussed metrics include traditional measures and newer parameters that provide a more detailed quantification of oxygen desaturation, including separate characterization of desaturation and re-saturation dynamics as well as integrated measures of the overall hypoxic load. Additionally, this review discusses how these more detailed metrics have provided further insight into the associations between OSA-related hypoxemia and clinically relevant outcomes, including cardiometabolic comorbidities and impaired daytime functioning. This narrative review emphasizes the need for diagnostic modifications and advocates for the integration of metrics quantifying hypoxemia into routine clinical practice to enable early recognition of the health risks associated with OSA.
