Observational studies have suggested strong associations between sleep duration and many cardiovascular diseases (CVDs), but causal inferences have not been confirmed. We aimed to determine the causal associations between genetically predicted sleep duration and 12 CVDs using both linear and nonlinear Mendelian randomization (MR) designs. Genetic variants associated with continuous, short (≤6 h) and long (≥9 h) sleep durations were used to examine the causal associations with 12 CVDs among 404 044 UK Biobank participants of White British ancestry. Linear MR analyses showed that genetically predicted sleep duration was negatively associated with arterial hypertension, atrial fibrillation, pulmonary embolism, and chronic ischaemic heart disease after correcting for multiple tests (P < 0.001). Nonlinear MR analyses demonstrated nonlinearity (L-shaped associations) between genetically predicted sleep duration and four CVDs, including arterial hypertension, chronic ischaemic heart disease, coronary artery disease, and myocardial infarction. Complementary analyses provided confirmative evidence of the adverse effects of genetically predicted short sleep duration on the risks of 5 out of the 12 CVDs, including arterial hypertension, pulmonary embolism, coronary artery disease, myocardial infarction, and chronic ischaemic heart disease (P < 0.001), and suggestive evidence for atrial fibrillation (P < 0.05). However, genetically predicted long sleep duration was not associated with any CVD. This study suggests that genetically predicted short sleep duration is a potential causal risk factor of several CVDs, while genetically predicted long sleep duration is unlikely to be a causal risk factor for most CVDs. Causal associations of short and long sleep durations with 12 cardiovascular diseases: linear and nonlinear Mendelian randomization analyses in UK Biobank. All associations are significant at a Bonferroni threshold of P < 4.2E-03 (corrected for 12 outcomes). CVD, cardiovascular disease; SNP, single nucleotide polymorphism.

The aim of this study was to test whether current and past night shift work was associated with incident atrial fibrillation (AF) and whether this association was modified by genetic vulnerability. Its associations with coronary heart disease (CHD), stroke, and heart failure (HF) were measured as a secondary aim. This cohort study included 283 657 participants in paid employment or self-employed without AF and 276 009 participants free of CHD, stroke, and HF at baseline in the UK Biobank. Current and lifetime night shift work information was obtained. Cox proportional hazard models were used. Weighted genetic risk score for AF was calculated. During a median follow-up of 10.4 years, 5777 incident AF cases were documented. From ‘day workers’, ‘shift but never/rarely night shifts’, and ‘some night shifts’ to ‘usual/permanent night shifts’, there was a significant increasing trend in the risk of incident AF (P for trend 0.013). Usual or permanent night shifts were associated with the highest risk [hazard ratio (HR) 1.16, 95% confidence interval (CI) 1.02–1.32]. Considering a person’s lifetime work schedule and compared with shift workers never working nights, participants with a duration over 10 years and an average 3–8 nights/month frequency of night shift work exposure possessed higher AF risk (HR 1.18, 95% CI 0.99–1.40 and HR 1.22, 95% CI 1.02–1.45, respectively). These associations between current and lifetime night shifts and AF were not modified by genetic predisposition to AF. Usual/permanent current night shifts, ≥10 years and 3–8 nights/month of lifetime night shifts were significantly associated with a higher risk of incident CHD (HR 1.22, 95% CI 1.11–1.35, HR 1.37, 95% CI 1.20–1.58 and HR 1.35, 95% CI 1.18–1.55, respectively). These associations in stroke and HF were not significant. Both current and lifetime night shift exposures were associated with increased AF risk, regardless of genetic AF risk. Night shift exposure also increased the risk of CHD but not stroke or HF. Whether decreasing night shift work frequency and duration might represent another avenue to improve heart health during working life and beyond warrants further study. This study demonstrates that both current and lifetime night shift exposures were associated with increased risk of atrial fibrillation and coronary heart disease.

For the last two decades research has revealed an alarming association between short sleep duration and metabolic disorders. In tandem, the hormonal, behavioral, and genetic mechanisms underlying this relationship have been extensively investigated and reviewed. However, emerging evidence is revealing that excessive sleep duration has remarkably similar deleterious effects. Unfortunately, to date there has been little attention to what drives this connection. This narrative review therefore aims to summarize existing epidemiological findings, experimental work, and most importantly putative molecular and behavioral mechanisms connecting excessive sleep duration with both obesity and type 2 diabetes mellitus. It will also address recent findings suggesting a worrisome bidirectional effect such that metabolic disorders create a positive feedback loop which further perpetuates excessive sleep.

The study aimed to assess whether aerobic exercise (AEx) training and a fibre-enriched diet can reduce hepatic fat content (HFC) and increase glycaemic control in pre-diabetic patients with non-alcoholic fatty liver disease (NAFLD). Six-hundred-and-three patients from seven clinics in Yangpu district, Shanghai, China were recruited. Of them 115 individuals aged 50–65-year fulfilled the inclusion criteria (NAFLD with impaired fasting glucose or impaired glucose tolerance) and were randomly assigned into exercise (AEx n = 29), diet (Diet n = 28), exercise plus diet (AED n = 29), or no-intervention (NI n = 29) groups. Progressive supervised AEx training (60–75% VO2max intensity) was given 2-3 times/week in 30–60 min/sessions, and the diet intervention was provided as lunch with 38% carbohydrate and diet fibre of 12 g/day for 8.6-month. HFC was assessed by ¹H MRS. We found that HFC was significantly reduced in the AEx (−24.4%), diet (−23.2%), and AED (−47.9%) groups by contrast to the 20.9% increase in the NI group (p = 0.001 for all) after intervention. However, only AED group significantly decreased HbA_1c (−4.4%, p = 0.01) compared with the NI group (−0.6%). Aerobic exercise training combined with fibre-enriched diet can reduce HFC more effectively than either exercise or increased fibre-intake alone in pre-diabetic patients with NAFLD.

Atrial fibrillation (AF) is the most common sustained arrhythmia in adults. Investigations of risk factor profiles for AF according to age and genetic risk groups are essential to promote individualized strategies for the prevention and control of AF. A total of 409 661 participants (mean age, 56 years; 46% men) free of AF at baseline and with complete information about risk factors were included from the UK Biobank cohort. The hazard ratios and population-attributable risk (PAR) percentages of incident AF associated with 23 risk factors were examined, including 3 social factors, 7 health behaviours, 6 cardiometabolic factors, 6 clinical comorbidities, and the genetic risk score (GRS), across 3 age groups (40–49, 50–59, and 60–69 years) and 3 genetic risk groups (low, moderate, and high GRS). After a follow-up of 5 027 587 person-years, 23 847 participants developed AF. Most cardiometabolic factors and clinical comorbidities showed a significant interaction with age, whereby the associations were generally strengthened in younger groups (P_interaction < .002). However, only low LDL cholesterol, renal dysfunction, and cardiovascular disease showed a significant interaction with genetic risk, and the associations with these factors were stronger in lower genetic risk groups (P_interaction < .002). Cardiometabolic factors consistently accounted for the largest number of incident AF cases across all age groups (PAR: 36.2%–38.9%) and genetic risk groups (34.0%–41.9%), with hypertension and overweight/obesity being the two leading modifiable factors. Health behaviours (PAR: 11.5% vs. 8.7%) and genetic risk factors (19.1% vs. 14.3%) contributed to more AF cases in the 40–49 years group than in the 60–69 years group, while the contribution of clinical comorbidities remained relatively stable across different age groups. The AF risk attributable to overall cardiometabolic factors (PAR: 41.9% in the low genetic risk group and 34.0% in the high genetic risk group) and clinical comorbidities (24.7% and 15.9%) decreased with increasing genetic risk. The impact of social factors on AF was relatively low across the groups by age and genetic risk. This study provided comprehensive information about age- and genetic predisposition-related risk factor profiles for AF in a cohort of UK adults. Prioritizing risk factors according to age and genetic risk stratifications may help to achieve precise and efficient prevention of AF. Age-specific and genetic predisposition-specific associations of risk factor profiles with atrial fibrillation (AF). Population-attributable risk percentages of AF risk factors were presented for different age and genetic risk population groups.