Chahal, Anwar

ABSTRACT Background and Purpose White matter hyperintensities (WMH) are a core neuroimaging marker of cerebral small vessel disease (CSVD). Sleep apnoea (SA) is a recognized vascular risk factor, but its associations with regional WMH burden, short‐interval WMH change and cognitive performance in population‐based cohorts remain incompletely defined. We examined these associations in the UK Biobank imaging cohort. Methods We conducted cross‐sectional analyses with an exploratory longitudinal subset in propensity score–matched cohorts excluding major neurologic and cerebrovascular disease before imaging. SA was identified from hospital records and self‐reports prior to brain magnetic resonance imaging (MRI). Head‐size–normalized WMH volumes were analysed on the log1p scale using multivariable linear regression with robust standard errors. Total WMH was the primary outcome; periventricular WMH (PWMH), deep WMH (DWMH) and cognitive measures were secondary outcomes. Mediation analyses evaluated WMH as a mediator of SA–cognition associations. Results In cross‐sectional analyses ( N = 12,890; mean age, 67.4 years; 27.2% women), SA was associated with greater WMH burden. Total WMH volume was 10.7% higher among participants with SA (95% CI, 5.0%–16.6%; p < 0.001). PWMH and DWMH volumes were 10.0% (95% CI, 4.7%–15.7%; q < 0.001) and 15.7% (95% CI, 7.1%–25.1%; q < 0.001) higher, respectively. SA was associated with modestly worse cognitive performance, with effect estimates attenuated after adjustment for WMH burden and cardiometabolic conditions. Mediation analyses indicated that WMH burden, particularly PWMH, mediated associations between SA and cognitive performance. In the longitudinal subset ( N = 698; median follow‐up, 2.26 years), no significant between‐group differences were observed in annualized WMH change. Conclusions In this large population‐based imaging cohort, SA was associated with higher WMH burden, a key neuroimaging marker of CSVD. Cognitive differences were modest, but WMH burden, particularly PWMH, consistently mediated associations between SA and cognitive performance. Longer term studies are needed to clarify temporal relationships and potential treatment effects.

Introduction: LMNA encodes the nuclear envelope proteins lamin A/C that are involved in ageing processes. Mutations in LMNA cause a spectrum of phenotypes which include muscular dystrophy, arrhythmogenic dilated cardiomyopathy, peripheral neuropathy, progeroid syndrome and overlap syndrome. Early diagnosis is crucial to prevent sudden cardiac death. We hypothesized that LMNA mutations result in an ECG biological age older than chronological age. Methods: In this study, we used AI-enabled ECG network to investigate standard digital 12-lead ECGs in genetically characterized LMNA patients. Results: We identified 33 LMNA patients with 331, 12-lead ECG available for analysis. Median age at symptoms onset was 23.5 (range: <1 to 61 years;15 females). Mean follow up time was 86 months (range: <1 to 367 months). Symptoms at onset included muscle weakness (n=10) or cardiac symptoms (n=18) and asymptomatic (n=5). We included a total of 1532 age sex matched controls. We found significant differences in positive age-gap (biologically older than chronological age) comparing LMNA patients (median of 17.5) versus controls (4.9 years; p<0.001, Figure 1 ). AI-ECG age with 10 years or higher age-gap was observed in 73% of LMNA patients compared to 27% in the controls (p<0.001). Consecutive serial analysis for all ECG’s in the study versus predicted age showed faster aging when comparing the rates of age-gap overtime in the LMNA group compared to controls (p<0.0001, Figure 2 ). Moreover, the subset analysis of 23 ECG in the 5 asymptomatic patients versus controls also showed significantly higher AI-ECG age-gap (p=0.004) Conclusions: An AI-ECG algorithm to detect biological age effectively demonstrates accelerated aging in patients with LMNA mutations related to physiological aging. Our findings further validate the role of AI-ECG to detect accelerated aging, expanding previous studies demonstrating higher mortality among individuals with in increased positive age-gap.