Aims: To quantify the association of combined sleep behaviours and genetic susceptibility with the incidence of cardiovascular disease (CVD). Methods and results: This study included 385 292 participants initially free of CVD from UK Biobank. We newly created a healthy sleep score according to five sleep factors and defined the low-risk groups as follows: early chronotype, sleep 7–8 h per day, never/rarely insomnia, no snoring, and no frequent excessive daytime sleepiness. Weighted genetic risk scores of coronary heart disease (CHD) or stroke were calculated. During a median of 8.5 years of follow-up, we documented 7280 incident CVD cases including 4667 CHD and 2650 stroke cases. Compared to those with a sleep score of 0–1, participants with a score of 5 had a 35% (19–48%), 34% (22–44%), and 34% (25–42%) reduced risk of CVD, CHD, and stroke, respectively. Nearly 10% of cardiovascular events in this cohort could be attributed to poor sleep pattern. Participants with poor sleep pattern and high genetic risk showed the highest risk of CHD and stroke. Conclusion: In this large prospective study, a healthy sleep pattern was associated with reduced risks of CVD, CHD, and stroke among participants with low, intermediate, or high genetic risk.

Proteomics offers unique insights into human biology and drug development, but few studies have directly compared the utility of different proteomics platforms. We measured plasma levels of 2168 proteins in 3976 Chinese adults using both Olink Explore and SomaScan platforms. The correlation of protein levels between platforms was modest (median rho = 0.29), with protein abundance and data quality parameters being key factors influencing correlation. For 1694 proteins with one-to-one matched reagents, 765 Olink and 513 SomaScan proteins had cis-pQTLs, including 400 with colocalising cis-pQTLs. Moreover, 1096 Olink and 1429 SomaScan proteins were associated with BMI, while 279 and 154 proteins were associated with risk of ischaemic heart disease, respectively. Addition of Olink and SomaScan proteins to conventional risk factors for ischaemic heart disease improved C-statistics from 0.845 to 0.862 (NRI: 12.2%) and 0.863 (NRI: 16.4%), respectively. These results demonstrate the utility of these platforms and could inform the design and interpretation of future studies.

Little is known about the contribution of genetic variation to food timing, and breakfast has been determined to exhibit the most heritable meal timing. As breakfast timing and skipping are not routinely measured in large cohort studies, alternative approaches include analyses of correlated traits. The aim of this study was to elucidate breakfast skipping genetic variants through a proxy-phenotype genome-wide association study (GWAS) for breakfast cereal skipping, a commonly assessed correlated trait. We leveraged the statistical power of the UK Biobank (n = 193,860) to identify genetic variants related to breakfast cereal skipping as a proxy-phenotype for breakfast skipping and applied several in silico approaches to investigate mechanistic functions and links to traits/diseases. Next, we attempted validation of our approach in smaller breakfast skipping GWAS from the TwinUK (n = 2,006) and the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (n = 11,963). In the UK Biobank, we identified 6 independent GWAS variants, including those implicated for caffeine (ARID3B/CYP1A1), carbohydrate metabolism (FGF21), schizophrenia (ZNF804A), and encoding enzymes important for N6-methyladenosine RNA transmethylation (METTL4, YWHAB, and YTHDF3), which regulates the pace of the circadian clock. Expression of identified genes was enriched in the cerebellum. Genome-wide correlation analyses indicated positive correlations with anthropometric traits. Through Mendelian randomization (MR), we observed causal links between genetically determined breakfast skipping and higher body mass index, more depressive symptoms, and smoking. In bidirectional MR, we demonstrated a causal link between being an evening person and skipping breakfast, but not vice versa. We observed association of our signals in an independent breakfast skipping GWAS in another British cohort (P = 0.032), TwinUK, but not in a meta-analysis of non-British cohorts from the CHARGE consortium (P = 0.095). Our proxy-phenotype GWAS identified 6 genetic variants for breakfast skipping, linking clock regulation with food timing and suggesting a possible beneficial role of regular breakfast intake as part of a healthy lifestyle.

Plant-based dietary patterns may be related to better cardiovascular profiles. Whether a healthy plant-based dietary index is predictive of future cardiovascular disease (CVD) across people with different genetic susceptibility remains uncertain. We investigated associations of adherence to healthy plant-based diets with the incidence of CVD considering the genetic susceptibility. This prospective cohort study included a total of 156,148 adults initially free of CVD and cancer. We calculated a healthful plant-based diet index (healthful-PDI) in which healthy plant foods received positive scores, and less healthy plant foods and animal foods received reverse scores. Genetic risk scores (GRSs) for myocardial infarction (MI) and stroke were calculated to assess interactions between healthful-PDI and GRSs. During 5 y of follow-up, we observed 1812 incident cases of CVD. Higher healthful-PDI was associated with a lower CVD risk [HR per 10-unit increment: 0.87 (95% CI: 0.81, 0.93) after adjusting for demographic, lifestyle, and other dietary factors (model 1); HR 0.90 (0.84, 0.97) after further adjusting for obesity and metabolic factors (model 2)]. The risk of CVD was gradually decreased in association with higher adherence to healthful-PDI, regardless of genetic susceptibility. The inverse associations of healthful-PDI with CVD were consistently observed in people with low GRS-MI [HR 0.85 (95% CI: 0.76, 0.94) in model 1; HR 0.88 (0.79, 0.97) in model 2] and those with high GRS-MI [HR 0.91 (0.82, 0.99) in model 1; HR 0.94 (0.86, 1.04) in model 2], without significant interactions (Pinteraction = 0.59 in model 1; Pinteraction = 0.66 in model 2). Similarly, higher healthful-PDI was related to a lower risk of CVD, regardless of low/high GRS-stroke. Adherence to healthy plant-based diets may be associated with a decreased incidence of CVD in the entire population, suggesting that plant-based dietary patterns may modify the risk of CVD, regardless of genetic susceptibility.

Background: The association of incident cardiometabolic multimorbidity (CMM) with mortality risk is rarely studied, and neither are the durations of cardiometabolic diseases (CMDs). Whether the association patterns of CMD durations with mortality change as individuals progress from one CMD to CMM is unclear. Methods: Data from China Kadoorie Biobank of 512,720 participants aged 30–79 was used. CMM was defined as the simultaneous presence of two or more CMDs of interest, including diabetes, ischemic heart disease, and stroke. Cox regression was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the duration-dependent associations of CMDs and CMM with all-cause and cause-specific mortality. All information on exposures of interest was updated during follow-up. Results: During a median follow-up of 12.1 years, 99,770 participants experienced at least one incident CMD, and 56,549 deaths were documented. Among 463,178 participants free of three CMDs at baseline, compared with no CMD during follow-up, the adjusted HRs (95% CIs) between CMM and all-cause mortality, mortality from circulatory system diseases, respiratory system diseases, cancer, and other causes were 2.93 (2.80–3.07), 5.05 (4.74–5.37), 2.72 (2.35–3.14), 1.30 (1.16–1.45), and 2.30 (2.02–2.61), respectively. All CMDs exhibited a high mortality risk in the first year of diagnosis. Subsequently, with prolonged disease duration, mortality risk increased for diabetes, decreased for IHD, and sustained at a high level for stroke. With the presence of CMM, the above association estimates inflated, but the pattern of which remained. Conclusion: Among Chinese adults, mortality risk increased with the number of the CMDs and changed with prolonged disease duration, the patterns of which varied among the three CMDs.