Coronary artery disease (CAD) is characterized by atherosclerotic plaque formation in the arterial wall. CAD progression involves complex interactions and phenotypic plasticity among vascular and immune cell lineages. Single-cell RNA-seq (scRNA-seq) studies have highlighted lineage-specific transcriptomic signatures, but human cell phenotypes remain controversial. Here, we perform an integrated meta-analysis of 22 scRNA-seq libraries to generate a comprehensive map of human atherosclerosis with 118,578 cells. Besides characterizing granular cell-type diversity and communication, we leverage this atlas to provide insights into smooth muscle cell (SMC) modulation. We integrate genome-wide association study data and uncover a critical role for modulated SMC phenotypes in CAD, myocardial infarction, and coronary calcification. Finally, we identify fibromyocyte/fibrochondrogenic SMC markers (LTBP1 and CRTAC1) as proxies of atherosclerosis progression and validate these through omics and spatial imaging analyses. Altogether, we create a unified atlas of human atherosclerosis informing cell state-specific mechanistic and translational studies of cardiovascular diseases.

Aims: The underlying mechanisms of atrial fibrillation (AF) are largely unknown. Inflammation may underlie atrial remodelling. Autoimmune diseases, related to increased systemic inflammation, may therefore be associated with new-onset AF.Methods and results: Participants from the population-based UK Biobank were screened for rheumatic fever, gastrointestinal autoimmune diseases, autoimmune diseases targeting the musculoskeletal system and connective tissues, and neurological autoimmune diseases. Between 2006 and 2022, participants were followed for incident AF. Cox proportional hazards regression analyses were performed to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) to quantify associations. 494 072 participants free from AF were included (median age 58.0 years, 54.8% women). After a median of 12.8 years, 27 194 (5.5%) participants were diagnosed with new-onset AF. Rheumatic fever without heart involvement (HR, 95% CI: 1.47, 1.26–1.72), Crohn’s disease (1.23, 1.05–1.45), ulcerative colitis (1.17, 1.06–1.31), rheumatoid arthritis (1.39, 1.28–1.51), polyarteritis nodosa (1.82, 1.04–3.09), systemic lupus erythematosus (1.82, 1.41–2.35), and systemic sclerosis (2.32, 1.57–3.44) were associated with a larger AF risk. In sex-stratified analyses, rheumatic fever without heart involvement, multiple sclerosis, Crohn’s disease, seropositive rheumatoid arthritis, psoriatic and enteropathic arthropathies, systemic sclerosis and ankylosing spondylitis were associated with larger AF risk in women, whereas only men showed a larger AF risk associated with ulcerative colitis.Conclusions: Various autoimmune diseases are associated with new-onset AF, more distinct in women. Our findings elaborate on the pathophysiological differences in autoimmunity and AF risk between men and women.

Atrial fibrillation (AF) is the most common cardiac arrhythmia worldwide and carries a large morbidity and mortality risk.¹ Evidence suggests differences in the pathophysiological processes of AF between men and women and an association of AF with a poor prognosis among women.^1,2 Such findings warrant additional research into the sex-specific risk factors in the development of AF.

Short and long sleep duration and poor sleep quality may affect serum and hepatic lipid content, but available evidence is inconsistent. Therefore, we aimed to investigate the associations of sleep duration and quality with serum and hepatic lipid content in a large population‐based cohort of middle‐aged individuals. The present cross‐sectional study was embedded in the Netherlands Epidemiology of Obesity (NEO) study and consisted of 4260 participants (mean age, 55 years; proportion men, 46%) not using lipid‐lowering agents. Self‐reported sleep duration and quality were assessed using the Pittsburgh Sleep Quality Index questionnaire (PSQI). Outcomes of this study were fasting lipid profile (total cholesterol, low‐density lipoprotein [LDL]‐cholesterol, high‐density lipoprotein [HDL]‐cholesterol and triglycerides), postprandial triglyceride (response) levels, and hepatic triglyceride content (HTGC) as measured with magnetic resonance spectroscopy. We performed multivariable linear regression analyses, adjusted for confounders and additionally for measures that link to adiposity (e.g. body mass index [BMI] and sleep apnea). We observed that relative to the group with median sleep duration (≈7.0 hr of sleep), the group with shortest sleep (≈5.0 hr of sleep) had 1.5‐fold higher HTGC (95% confidence interval [CI]: 1.0‐2.2). The group with PSQI score ≥ 10 had a 1.1‐fold (95% CI: 1.0‐1.2) higher serum triglyceride level compared with the group with PSQI ≤ 5. However, these associations disappeared after adjustment for BMI and sleep apnea. Therefore, we concluded that previously observed associations of shorter sleep duration and poorer sleep quality with an adverse lipid profile, may be explained by BMI and sleep apnea, rather than by a direct effect of sleep on the lipid profile.

The APOE ε4 genotype has a higher risk for developing coronary artery disease (CAD), but there is preliminary evidence that antioxidative lifestyle factors interact with APOE genotype on CAD risk. Here, we assessed the effect modification of physical activity, oily fish and polyunsaturated fatty acid (PUFA) intake with APOE genotype on risk of incident CAD. The present study comprised 345,659 white European participants from UK Biobank (mean age: 56.5 years, 45.7% men) without a history of CAD. Information regarding physical activity, oily fish intake and PUFA intake was collected through questionnaires, and information on incident CAD through linkage with hospital admission records. Analyses were performed using Cox proportional hazard models adjusted for age and sex. Higher physical activity level and oily fish intake were both associated with a lower incidence of CAD. However, these associations were similar across the different APOE genotypes (p-values for interaction > 0.05). Most notable, higher PUFA intake was associated with a lower CAD risk in APOE ε4 genotype carriers (hazard ratio: 0.76, 95% confidence interval: 0.63-0.92), and not in APOE ε3/ε3 genotype carriers (0.90; 0.79, 1.02), but without statistical evidence for effect modification (p-valueinteraction = 0.137). While higher physical activity and high fish and PUFA intake were associated with a lower risk of incident CAD, no evidence for interaction of these lifestyle factors with APOE genotype was observed in UK Biobank participants. Interventions intended to reduce cardiovascular risk might therefore be similarly effective across the APOE genotype carriers.

Evidence on whether habitual sleep duration and sleep quality are associated with increased insulin resistance is inconsistent. Here, we investigated the associations between different measures of habitual sleep with glycemic traits through cross-sectional and Mendelian randomization (MR) analyses. We assessed the associations of sleep duration and sleep quality with glycemic traits using multivariable linear regression models adjusted for potential confounders in 4672 middle-aged (45–65 years; 48% men) nondiabetic participants of the Netherlands Epidemiology of Obesity (NEO) study. Genetic variants for total, short, and long sleep duration were used as instrumental variables in MR analyses using summary-level data of glycemic traits in nondiabetic individuals (MAGIC; n = 58,074). In cross-sectional analyses, shortest sleepers (median 5.0 h of sleep per night) had 14.5% (95% confidence interval (CI): 2.0; 28.6%) higher fasting insulin level and 16.3% (95% CI: 2.7; 31.7%) higher HOMA-β. Bad sleep quality was associated with higher insulin resistance (e.g., 14.3% (95% CI: 4.7; 24.9%) higher HOMA-IR). All these associations disappeared after adjustment for BMI and the risk of sleep apnea. MR analyses did not indicate a causal association between total, short or long sleep duration and glycemic traits. Therefore, our used measures of habitual sleep duration and sleep quality are unlikely to directly associate with insulin resistance.