An epigenome-wide association study of waist circumference in Chinese monozygotic twins.

OBJECTIVES: Central obesity poses significant health risks because it increases susceptibility to multiple chronic diseases. Epigenetic features such as DNA methylation may be associated with specific obesity traits, which could help us understand how genetic and environmental factors interact to influence the development of obesity. This study aims to identify DNA methylation sites associated with the waist circumference (WC) in Northern Han Chinese population, and to elucidate potential causal relationships. METHODS: A total of 59 pairs of WC discordant monozygotic twins (ΔWC >0) were selected from the Qingdao Twin Registry in China. Generalized estimated equation model was employed to estimate the methylation levels of CpG sites on WC. Causal relationships between methylation and WC were assessed through the examination of family confounding factors using FAmiliaL CONfounding (ICE FALCON). Additionally, the findings of the epigenome-wide analysis were corroborated in the validation stage. RESULTS: We identified 26 CpG sites with differential methylation reached false discovery rate (FDR) < 0.05 and 22 differentially methylated regions (slk-corrected p < 0.05) strongly linked to WC. These findings provided annotations for 26 genes, with notable emphasis on MMP17, ITGA11, COL23A1, TFPI, A2ML1-AS1, MRGPRE, C2orf82, and NINJ2. ICE FALCON analysis indicated the DNA methylation of ITGA11 and TFPI had a causal effect on WC and vice versa (p < 0.05). Subsequent validation analysis successfully replicated 10 (p < 0.05) out of the 26 identified sites. CONCLUSIONS: Our research has ascertained an association between specific epigenetic variations and WC in the Northern Han Chinese population. These DNA methylation features can offer fresh insights into the epigenetic regulation of obesity and WC as well as hints to plausible biological mechanisms.

Association of Abnormal Sleep Duration and Sleep Disturbance with Physical Activity in Older Adults: Between- and within-Person Effects.

OBJECTIVES: Sleep is associated with physical activity (PA), yet the nature and directions of this association are less understood. This study aimed to disentangle the long-term temporal sequences between sleep duration/disturbance and PA in older adults, distinguishing between- and within-person effects. DESIGN: Longitudinal panel study. SETTING AND PARTICIPANTS: We conducted a longitudinal study using 3 waves of data collected in 2008/09 (T1), 2012/13 (T2), and 2016/17(T3) from adults aged ≥50 years in the English Longitudinal Study of Ageing (N = 10,749 individuals). MEASURES: Sleep duration, sleep disturbance, and PA were assessed by self-reported questionnaires. We used cross-lagged panel models (CLPMs) to examine between-person effects and random intercept cross-lagged panel models (RI-CLPMs) to examine within-person effects. RESULTS: Our analyses revealed a reciprocal relationship between abnormal sleep duration and low PA levels at between-person level (abnormal sleep duration to PA: ßT1-T2 = -0.053, ßT2-T3 = -0.058, all P < .001; PA to abnormal sleep duration: ßT1-T2 = -0.040, ßT2-T3 = -0.045, all P < .05), with abnormal sleep duration being the driving force in the dynamic association. In addition, there was a unidirectional effect of more severe sleep disturbance on lower levels of PA at both between- and within-person levels (between-person level: ßT1-T2 = -0.032, ßT2-T3 = -0.028, all P < .001; within-person level: ßT1-T2 and T2-T3 = -0.031, all P = .011). CONCLUSIONS AND IMPLICATIONS: This study adds novel insights into the temporal directionality of sleep and PA among community-dwelling older adults and highlights poor sleep as a potential risk factor for PA. Intervention strategies should aim to improve sleep to promote PA levels and successful aging.

Liver Iron Overload Drives COVID-19 Mortality: a Two-Sample Mendelian Randomization Study.

Iron overload has been associated with an increased risk of COVID-19 severity and mortality in observational studies, but it remains unclear whether these associations represent causal effects. We performed a two-sample Mendelian randomization (MR) to determine associations between genetic liability to iron overload and the risk of COVID-19 severity and mortality. From genome-wide association studies of European ancestry, single-nucleotide polymorphisms associated with liver iron (n = 32,858) and ferritin (n = 23,986) were selected as exposure instruments, and summary statistics of the hospitalization (n = 16,551) and mortality (n = 15,815) of COVID-19 were utilized as the outcome. We used the inverse-variance weighted (IVW) method as the primary analysis to estimate causal effects, and other alternative approaches as well as comprehensive sensitivity analysis were conducted for estimating the robustness of identified associations. Genetically predicted high liver iron levels were associated with an increased risk of COVID-19 mortality based on the results of IVW analysis (OR = 1.38, 95% CI: 1.05-1.82, P = 0.02). Likewise, sensitivity analyses showed consistent and robust results in general (all P > 0.05). A higher risk of COVID-19 hospitalization trend was also observed in patients with high liver iron levels without statistical significance. This study suggests that COVID-19 mortality might be partially driven by the iron accumulation in the liver, supporting the classification of iron overload as one of the independent death risk factors. Therefore, avoiding iron overload and maintaining normal iron levels may be a powerful measure to reduce COVID-19 mortality.

Genome-wide DNA methylation analysis of body composition in Chinese monozygotic twins.

BACKGROUND: Little is currently known about epigenetic alterations associated with body composition in obesity. Thus, we aimed to explore epigenetic relationships between genome-wide DNA methylation levels and three common traits of body composition as measured by body fat percentage (BF%), fat mass (FM) and lean body mass (LBM) among Chinese monozygotic twins. METHODS: Generalized estimated equation model was used to regress the methylation level of CpG sites on body composition. Inference about Causation Through Examination Of Familial Confounding was used to explore the evidence of a causal relationship. Gene expression analysis was further performed to validate the results of differentially methylated genes. RESULTS: We identified 32, 22 and 28 differentially methylated CpG sites (p < 10-5 ) as well as 20, 17 and eight differentially methylated regions (slk-corrected p < 0.05) significantly associated with BF%, FM and LBM which were annotated to 65 genes, showing partially overlapping. Causal inference demonstrated bidirectional causality between DNA methylation and body composition (p < 0.05). Gene expression analysis revealed significant correlations between expression levels of five differentially methylated genes and body composition (p < 0.05). CONCLUSIONS: These DNA methylation signatures will contribute to increased knowledge about the epigenetic basis of body composition and provide new strategies for early prevention and treatment of obesity and its related diseases.