Somers, Virend K.

Background Disruption in rest‐activity rhythm (RAR) is an emerging risk factor for cardiovascular disease (CVD) and mortality, but the strength of evidence is unclear. Therefore, we conducted a systematic review and meta‐analysis to assess associations between RAR characteristics and cardiovascular disease incidence or prevalence, cardiovascular mortality, and all‐cause mortality. Methods A systematic search was conducted in PubMed, Web of Science, Cochrane Library, and Embase for cohort or cross‐sectional studies published up to August 2025. The exposure variables were nonparametric RAR parameters, including interdaily stability (describing day‐to‐day stability of the RAR), intradaily variability (a measure of RAR fragmentation), and relative amplitude (indicating robustness or strength of the RAR). The primary outcomes were cardiovascular mortality and all‐cause mortality. The secondary outcomes included cardiovascular disease prevalence and incidence. Results Seven studies involving 109 365 participants were included. Pooled results showed that higher intradaily variability was associated with a significantly increased risk of all‐cause mortality (hazard ratio [HR], 1.05 [95% CI, 1.02–1.09]) and cardiovascular disease prevalence (odds ratio, 1.73 [95% CI, 1.21–2.47]). Lower relative amplitude was significantly associated with higher cardiovascular mortality (HR, 1.50 [95% CI, 1.13–1.98]) and all‐cause mortality (HR, 1.46 [95% CI, 1.27–1.68]). Interdaily stability showed no significant associations with any outcome. Conclusions Measures of disrupted rest‐activity rhythms were associated with increased cardiovascular mortality, and all‐cause mortality. These findings support using RAR metrics as early, noninvasive risk indicators. Future work should investigate whether appropriately timed physical activity and sleep, as well as other interventions targeting RAR can mitigate cardiovascular risk.

The advent of high-throughput sequencing technologies has revolutionized cardiovascular genetics, generating vast amounts of data. A major challenge in the genomic era is the efficient and accurate identification of causative genetic variants associated with cardiovascular disease. Artificial intelligence (AI)-driven computational approaches offer a powerful solution by enabling the automation of variant classification, improving consistency and reproducibility, and enhancing predictive accuracy. These methods may guide not only variant classification, variant effect prediction, and clinical prioritization, but also open the door to data-driven precision medicine, enabling more accurate and individualized diagnoses and targeted therapeutic strategies tailored to each patient’s unique genetic and clinical profile. This state-of-the-art review provides a structured overview of AI methodologies applied to cardiovascular genomics, beginning with rule-based expert systems that encode standardized guidelines for consistent variant interpretation. Next, we examine machine learning approaches capable of identifying complex patterns in annotated multimodal clinical and multi-omic datasets. The role of deep learning algorithms is highlighted for their ability to extract features from high-dimensional, unstructured data relevant to cardiovascular disease. In addition, the potential of generative AI is explored, including applications in synthetic data generation, variant impact prediction, and automated summarization of biomedical literature. Despite advances, several challenges remain, including data heterogeneity, the need for explainable AI models to elucidate the decision mechanisms, and the complexity linked to the integration of AI-based tools into clinical workflows. Addressing these issues requires interdisciplinary collaboration among clinicians, geneticists, data scientists, and bioinformaticians to ensure the effective translation of AI-generated insights into clinical practice. This review aims to provide a comprehensive perspective on the evolving role of AI in cardiovascular genomics and its implications for advancing precision medicine.

Sleep is an active period of profound autonomic fluctuation, cycling between the parasympathetic dominance of nonrapid eye movement sleep and the sympathetic/parasympathetic volatility of rapid eye movement sleep. Sleep-disordered breathing, a spectrum of disorders marked by recurrent ventilatory instability and intermittent hypoxia during sleep, particularly obstructive sleep apnea, pathologically amplifies this volatility, transforming sleep into a nightly cascade of severe autonomic and hemodynamic stress. The cardinal features of sleep-disordered breathing, intermittent hypoxia, recurrent arousals, and marked intrathoracic pressure swings, act synergistically to drive chronic, 24-hour sympathetic overactivity, chemoreflex sensitization, and maladaptive neuroplasticity. These effects are mediated at a cellular level by oxidative stress, systemic inflammation, endothelial dysfunction, and neuroendocrine dysregulation. This persistent autonomic reset provides a direct mechanistic link to cardiovascular consequences. It is likely a primary driver of hypertension, blunting the nocturnal blood pressure dip and promoting sustained 24-hour sympathoexcitation. It fosters a proarrhythmic substrate for atrial fibrillation through mechanical stress, which drives atrial remodeling and autonomic conflict. Furthermore, sleep-disordered breathing contributes to myocardial ischemia by increasing myocardial oxygen demand and promoting a prothrombotic state. Beyond chronic disease, sleep-related autonomic shifts can act as acute triggers for malignant arrhythmias in individuals with vulnerable substrates, such as inherited channelopathies, a risk that may be significantly amplified by comorbid sleep-disordered breathing. This review delineates the critical neural and cellular pathways connecting sleep, autonomic dysregulation, and cardiovascular risk.

Augmented cardiovascular responses to spontaneous nocturnal arousals were previously shown in chronic short-sleeping adults, without known sex differences. Sustained 4-h sleep restriction produced a sex-dependent alteration in heart rate responses to arousals and resulted in a prolonged reduction in postarousal pulse transit time in females only. These findings yield the first sex-specific characterization of nocturnal cardiovascular responses to spontaneous arousals following sleep restriction, and may place females at greater sleep truncation-related cardiovascular disease risk.

Establishes a robust long-term human adipocyte organoid culture system maintained for over 90 days. Recapitulates key features of OSA-related intermittent hypoxia in human adipocytes in vitro. Demonstrates IH-induced adipocyte aging, including ultrastructural damage and epigenetic reprogramming. Identifies impaired adipogenesis and insulin signaling under intermittent hypoxia. Provides a physiologically relevant platform for mechanistic studies and drug screening.

Abstract Aims Glucagon-like peptide-1 receptor agonists (GLP-1RA) reduce cardiovascular risk in patients with Type 2 diabetes (T2D) and established atherosclerotic cardiovascular disease and are recommended in guidelines. We evaluated the real-world effectiveness of GLP-1RA therapy on cardiovascular outcomes in patients with T2D after myocardial infarction (MI) or ischaemic stroke and examined trends and disparities. Methods and results Using nationwide Czech registry data (2015–24), we identified patients with incident nonfatal MI or ischaemic stroke and confirmed T2D. GLP-1RA users—initiating therapy within 12 months post-event—were propensity score matched to non-users. The primary outcome was major adverse cardiovascular events (MACE: nonfatal MI, nonfatal stroke, cardiovascular death); secondary outcomes included individual components and all-cause mortality. GLP-1RA therapy was initiated in only ∼2% of MI and stroke survivors with T2D. Among 126 845 MI survivors, 28 206 had T2D; the matched cohort comprised 2271 patients (401 GLP-1RA; median follow-up 35 months). GLP-1RA use was associated with lower risk of MACE (HR 0.7; 95% CI, 0.52–0.93), all-cause (HR 0.61; 95% CI, 0.47–0.80), and cardiovascular death (HR 0.54; 95% CI, 0.36–0.80). Among 177 115 stroke survivors, 73 750 had T2D; the matched cohort comprised 2235 patients (385 GLP-1RA; median follow-up 27 months). GLP-1RA use was associated with lower risk of MACE (HR 0.71; 95% CI, 0.54–0.94), all-cause (HR 0.59; 95% CI, 0.46–0.76), and cardiovascular death (HR 0.55; 95% CI, 0.37–0.81). Conclusion GLP-1RA therapy after MI or stroke in T2D was associated with substantially lower risks of MACE, cardiovascular, and all-cause death in real-world practice. Utilization remained low, particularly among women and older adults, underscoring the need for broader and more equitable implementation in secondary prevention.

Abstract Study Objectives Respiratory events during sleep induce immediate cardiac alterations, including increased RR intervals during events and decreased RR intervals after events. However, the extent to which related desaturations and arousals modulate these responses remains underexplored. We hypothesized that desaturations and arousals are the main contributors to respiratory event-related cardiac response, with greatest cardiac alterations expected when both are present. Methods We analyzed RR, QT, and heart rate-corrected QT (QTc) intervals before, during, and after 4310 respiratory events from 129 obstructive sleep apnea patients. Mixed-effect statistical models were utilized to assess the influence of the presence and severity of desaturations and arousals on the cardiac electrical response to respiratory events. Results There were no significant differences between pre- and post-respiratory event RR and QTc intervals in the absence of desaturation or arousal. Arousal (RR estimate = −23.9 ms; QTc estimate = 5.7 ms) or simultaneous desaturation and arousal (RR estimate = −32.8 ms; QTc estimate = 8.4 ms) modulated significantly (p < .05) mean RR and QTc intervals after respiratory events. Desaturation alone affected only RR intervals (estimate = −9.3 ms, p<.05). Greater desaturation depth (RR estimate = −0.09 ms; QTc estimate = 0.56 ms) and longer arousal duration (RR estimate = −3.52 ms; QTc estimate = 0.84 ms) were significant (p < .05) predictors of RR and QTc magnitude alterations after respiratory events. Conclusions Not all respiratory events have the same effects on cardiac electrophysiology; they are associated with acute alterations after events if they cause desaturations and/or arousal, with longer arousal and deeper desaturations increasing the magnitude of cardiac responses. Statement of Significance This study provides a detailed analysis of the temporal dynamics of cardiac response to respiratory events in obstructive sleep apnea patients, with a focus on the potential modulators of this response. Our observations present that not all respiratory events have the same effects on cardiac electrophysiology; they are associated with significant cardiac response if they cause desaturations and/or arousals, with longer arousal and deeper desaturations increasing the magnitude of cardiac response. Our results present evidence of possible modulators of post-event cardiac function, providing a deeper understanding of obstructive sleep apnea’s impact on health as potential underlying mechanisms leading to adverse cardiovascular events.