Insomnia and short/long sleep duration increase the risk of AMI, but their interaction with each other or with chronotype is not well known. We investigated the prospective joint associations of any two of these sleep traits on risk of AMI. We included 302 456 and 31 091 participants without past AMI episodes from UK Biobank (UKBB; 2006–10) and the Trøndelag Health Study (HUNT2; 1995–97), respectively. A total of 6 833 and 2 540 incident AMIs were identified during an average 11.7 and 21.0 years follow-up, in UKBB and HUNT2, respectively. Compared to those who reported normal sleep duration (7–8 h) without insomnia symptoms, the Cox proportional hazard ratios (HRs) for incident AMI in UKBB among participants who reported normal, short and long sleep duration with insomnia symptoms were 1.07 (95% CI 0.99, 1.15), 1.16 (95% CI 1.07, 1.25) and 1.40 (95% CI 1.21, 1.63), respectively. The corresponding HRs in HUNT2 were 1.09 (95% CI 0.95, 1.25), 1.17 (95% CI 0.87, 1.58) and 1.02 (95% CI 0.85, 1.23). The HRs for incident AMI in UKBB among evening chronotypes were 1.19 (95% CI 1.10, 1.29) for those who had insomnia symptoms, 1.18 (95% CI 1.08, 1.29) for those with short sleep duration, and 1.21 (95% CI 1.07, 1.37) for those with long sleep duration, compared to morning chronotypes without another sleep symptom. The relative excess risk for incident AMI in UKBB due to interaction between insomnia symptoms and long sleep duration was 0.25 (95% CI 0.01, 0.48). Insomnia symptoms with long sleep duration may contribute more than just an additive effect of these sleep traits on the risk of AMI.

Background: Few studies have investigated the joint effects of sleep traits on the risk of acute myocardial infarction (AMI). No previous study has used factorial Mendelian randomization (MR) which may reduce confounding, reverse causation, and measurement error. Thus, it is prudent to study joint effects using robust methods to propose sleep-targeted interventions which lower the risk of AMI. Methods: The causal interplay between combinations of two sleep traits (including insomnia symptoms, sleep duration, or chronotype) on the risk of AMI was investigated using factorial MR. Genetic risk scores for each sleep trait were dichotomized at their median in UK Biobank (UKBB) and the second survey of the Trøndelag Health Study (HUNT2). A combination of two sleep traits constituting 4 groups were analyzed to estimate the risk of AMI in each group using a 2×2 factorial MR design. Results: In UKBB, participants with high genetic risk for both insomnia symptoms and short sleep had the highest risk of AMI (hazard ratio (HR) 1.10; 95% confidence interval (CI) 1.03, 1.18), although there was no evidence of interaction (relative excess risk due to interaction (RERI) 0.03; 95% CI −0.07, 0.12). These estimates were less precise in HUNT2 (HR 1.02; 95% CI 0.93, 1.13), possibly due to weak instruments and/or small sample size. Participants with high genetic risk for both a morning chronotype and insomnia symptoms (HR 1.09; 95% CI 1.03, 1.17) and a morning chronotype and short sleep (HR 1.11; 95% CI 1.04, 1.19) had the highest risk of AMI in UKBB, although there was no evidence of interaction (RERI 0.03; 95% CI −0.06, 0.12; and RERI 0.05; 95% CI –0.05, 0.14, respectively). Chronotype was not available in HUNT2. Conclusions: This study reveals no interaction effects between sleep traits on the risk of AMI, but all combinations of sleep traits increased the risk of AMI except those with long sleep. This indicates that the main effects of sleep traits on AMI are likely to be independent of each other.

Cysteine is a semi-essential amino acid that has been positively associated with growth in children. However, transgenerational effects remain unclear. The aim of this analysis was to assess whether maternal plasma total cysteine (tCys) concentration is associated with various growth indicators in infants living in peri-urban settings in Bhaktapur, Nepal. We used data from the 561 mothers enrolled in an ongoing randomized controlled trial. We built linear regression models to evaluate the associations between maternal tCys and birth weight, length-for-age Z-scores (LAZ) and weight-for-length Z-scores (WLZ) at birth and six months of age. Maternal tCys was inversely associated with birth weight among boys after adjusting for confounders (p < 0.05). In addition, there was a negative association between maternal tCys and LAZ at birth (p < 0.01). No associations between maternal tCys and the other anthropometric indicators were found significant, although there was a tendency for maternal tCys to be associated positively with WLZ at birth among girls (p < 0.10). This is a first study evaluating transgenerational relation of tCys on growth in infants. Further, larger and more comprehensive studies are needed to determine if and how maternal tCys alters child growth.

Aims: Sleep disturbances can induce alterations in functional and electrical properties of the heart, thereby increasing susceptibility to atrial fibrillation (AF). We aimed to test the causal role of different sleep traits and their joint effects on the risk of AF. Methods and results: We used an observational cohort study design along with one-sample and factorial Mendelian randomization (MR) approaches to test for individual and joint associations of sleep traits (i.e. insomnia symptoms, sleep duration, and chronotype) on the risk of AF using UK Biobank and the second survey of the Trøndelag Health Study (HUNT2). One-sample MR analysis showed that genetic predisposition to insomnia symptoms [hazard ratio (HR) 1.14; 95% confidence interval (CI) 1.07, 1.21] and short (≤6 h vs. 7–8 h) sleep duration (HR 1.14; 95% CI 1.04, 1.26) increased the risk of AF in UK Biobank. However, these findings (HR 0.95; 95% CI 0.81, 1.11 for insomnia symptoms and HR 1.41; 95% CI 0.57, 3.46 for short sleep duration) were not consistent in HUNT2. Factorial MR analysis showed that participants with genetic predisposition to both insomnia symptoms and short sleep duration (HR 1.08; 95% CI 1.03, 1.12) had the highest risk of AF, although there was no evidence of interaction [relative excess risk due to interaction (RERI) 0.03; 95% CI −0.03, 0.09]. However, this finding (HR 0.96; 95% CI 0.89, 1.04) was not consistent in HUNT2. Participants with genetic predisposition to both a morning chronotype and insomnia symptoms (HR 1.08; 95% CI 1.04, 1.13) and a morning chronotype and short sleep (HR 1.06; 95% CI 1.02, 1.10) had the highest risk of AF in UK Biobank, although there was no evidence of interaction (RERI −0.01; 95% CI −0.07, 0.04 and RERI 0.06; 95% CI −0.01, 0.12, respectively). Conclusion: Our study indicates that insomnia symptoms and short sleep duration are causal risk factors for AF. However, having two sleep traits in combination does not increase risk beyond the additive risk of each individual trait. This reinforces clinical and public health efforts to effectively manage insomnia symptoms and short sleep, in order to mitigate the risk of AF and improve overall cardiovascular health.

Mendelian randomization (MR) studies show that higher body mass index (BMI) and lower 25-hydroxyvitamin D (25[OH]D) increase psoriasis risk. The combined effect of these factors has not been explored using factorial MR. Using cross-sectional data from UK Biobank (n = 398,404) and The Trøndelag Health Study (n = 86,648), we calculated polygenic risk scores for BMI and 25(OH)D to estimate ORs for psoriasis using 2 × 2 and continuous factorial MR. We quantified additive interaction by estimating relative excess risk due to interaction. We also performed traditional observational analyses in UK Biobank. There were 12,207 (3.1%) participants with psoriasis in UK Biobank and 7794 (9.0%) in The Trøndelag Health Study. In 2 × 2 factorial MR, we found no evidence of relative excess risk for psoriasis due to interaction between genetically predicted higher BMI and lower 25(OH)D, neither in UK Biobank (relative excess risk due to interaction = −0.01, 95% confidence interval = −0.08 to 0.07) nor in The Trøndelag Health Study (relative excess risk due to interaction = −0.04, 95% confidence interval = −0.14 to 0.06). The same was observed in the continuous factorial MR and observational analyses. In conclusion, this study did not find evidence of interaction between BMI and 25(OH)D on the risk of psoriasis. Given minor differences in measured BMI and 25(OH)D between the factorial groups, small effects may have been undetected.

Background: Mitral valve prolapse (MVP) is a leading cause of mitral regurgitation in high-income countries. Although the course of MVP is often benign, a subset of patients progresses to significant valvular insufficiency, and a smaller subset develops ventricular arrhythmias or sudden cardiac death. This study aimed to identify genetic variants associated with MVP and/or mitral annulus disjunction (MAD) using whole-genome sequencing (WGS) in a Norwegian cohort. Methods: WGS was performed in 93 individuals diagnosed with MVP and/or MAD, of whom 92 passed genomic quality control criteria. Variants were called using Genome Analysis ToolKit (GATK) Best Practices and compared with non-Finnish European reference data from gnomAD (n = 34 029). Analyses were restricted to curated gene panels comprising: (i) non-syndromic MVP and cardiomyopathy genes, (ii) syndromic/connective tissue disorder genes, and (iii) arrhythmia-related genes. Enriched or underrepresented variants were identified using Fisher’s exact test with Bonferroni correction for multiple testing. Independent variants were derived through linkage disequilibrium pruning. A sensitivity analysis was conducted using low-coverage WGS data from an independent large Norwegian cohort – the Trøndelag Health Study (HUNT). Results: Across predefined gene panels, several coding and regulatory variants were significantly associated with MVP and/or MAD. A missense variant in FLNA and regulatory variants in TBX5 and SMAD4 were enriched in these patients. Additional significant associations involved regulatory variants in XYLT1, HS3ST4, SH3PXD2B , and a synonymous variant in COL1A2 . Furthermore, several regulatory variants in arrhythmia-related genes ( KCNK3, CACNA1D, NR2F1, KCNJ4 and others) were identified. Sensitivity analyses revealed population-level differences, underscoring the need of cautious interpretation of these findings. Conclusion: This targeted WGS study expands the genetic landscape of MVP and/or MAD, identifying several coding and regulatory variants across extracellular matrix, developmental, and electrophysiological pathways. These results support a multifactorial genetic architecture of MVP. Graphical Whole-genome sequencing of 92 Norwegian patients with mitral valve prolapse (MVP) and/or mitral annulus disjunction (MAD) identified coding and regulatory genetic variants across three curated gene categories: (i) non-syndromic MVP/cardiomyopathy genes, (ii) syndromic MVP/connective tissue disorder genes, and (iii) arrhythmia-related genes. Key associations included variants in FLNA, TBX5, COL1A2, SMAD4 , and several electrophysiological genes including KCNK3, CACNA1D, NR2F1 , and KCNJ4 . The findings implicate extracellular matrix (ECM) remodeling, transforming growth factor-β (TGF-β) signaling, cardiac developmental pathways, cytoskeletal integrity, and electrophysiological mechanisms, supporting a multifactorial genetic architecture of MVP/MAD.