Implication of DNA methylation during lifestyle mediated weight loss

Insomnia and Female Reproductive Diseases: A Cross-Sectional and Mendelian Randomization Study

Background

Insomnia is increasingly emerging as a significant concern in public health, with a longstanding emphasis on its relationship with overall well-being. Nevertheless, few research has been devoted to investigating the relationship between insomnia and female reproductive health.

Methods

In our study, we conducted a Mendelian randomization (MR) study to estimate the causal relationship between insomnia and female reproductive diseases. A total of 268 independent genetic variants associated with insomnia at the genome-wide significance level (P < 5×10-8) were used as instrumental variables. Summary-level data were obtained from the UK Biobank and Finn Gen study, including ovarian cysts, polycystic ovarian syndrome (PCOS), endometriosis, premature ovarian insufficiency (POI), ovarian cancer (OC), uterine fibroids, endometrial cancer (EC) and female infertility. We performed logistic regression to assess the associations between insomnia and the risk of OC and EC by using data from the National Health and Nutrition Examination Survey (NHANES) 2013-2014.

Results

Our research reveals that genetic liability to insomnia constitutes a risk factor for ovarian cysts (odds ratio [OR]: 1.44, 95% confidence interval [CI]: 1.21-1.72, P< 0.05), PCOS (OR: 1.67, 95% CI: 1.44-1.94, P< 0.05), and endometriosis (OR: 1.43, 95% CI: 1.16-1.76, P< 0.05). However, we found no statistically significant associations between insomnia and POI, OC, uterine fibroids, EC, or female infertility. Additionally, body mass index (BMI) was found to mediate about 10% of the effect of the insomnia on ovarian cysts and PCOS. Moreover, in cross-sectional study, insomnia was not associated with OC and EC.

Conclusion

Our study provides causal evidence that genetically predicted insomnia increases the risk of ovarian cysts, PCOS, and endometriosis. Accordingly, the potential significance of weight control and good sleep in keeping fit need to be emphasized.

Pre-operative DNA methylation marks as predictors of weight loss outcomes after sleeve gastrectomy

OBJECTIVE

Although DNA methylation has been suggested to be a potential predictor of the progression of obesity and obesity-related diseases, little is known about its potential role as predictive marker of successful weight loss after bariatric surgery.

METHODS

20 patients who underwent sleeve gastrectomy were classified according to the percentage of excess weight loss (%EWL) 1 year after bariatric surgery, using 60% as the cut-off point. Blood DNA methylation was analyzed prior to surgery using the Infinium Methylation EPIC Bead Chip array-based platform.

RESULTS

A total number of 76,559 differentially methylated positions (DMPs) (p < 0.05) were found between <60% EWL and >60% EWL groups. Of them, 59,308 DMPs were annotated to genes. KEGG enrichment analysis showed that pathways involved in the signalling of MAPK, Wnt, mTor, FoxO and AMPK, among others, were involved in weight loss trajectory. A stepwise logistic regression using the DMPs with an absolute Δβ >0.2 showed that higher methylation levels in the CpG sites cg02405213 (mapping to JAK2) (OR: 1.20098, [0.9586, 1.5044]) and cg01702330 (OR: 2.4426, [0.5761, 10.3567]), were shown to be associated with a higher probability of achieving >60 %EWL after sleeve gastrectomy, whereas higher methylation levels in the CpG site cg04863892 (mapping to HOXA5) were associated with lower probability of achieving >60 %EWL after sleeve gastrectomy (OR: 0.7966, [0.5637, 1.1259]).

CONCLUSIONS

Our results show a different pre-surgery methylation pattern according to %EWL. We identified three CpG sites (cg04863892, cg02405213, cg01702330) with potential value as predictor markers of weight loss response to bariatric surgery.

A cross-tissue transcriptome-wide association study identifies WDPCP as a potential susceptibility gene for coronary atherosclerosis

Background

Coronary atherosclerosis (CAS) is a complex chronic inflammatory disease with significant genetic and environmental contributions. While genome-wide association studies (GWAS) have pinpointed many risk loci, over 75 % are in non-coding regions, complicating functional analysis and understanding gene-disease mechanisms.

Methods

We conducted a cross-tissue transcriptome-wide association study (TWAS) using data from the GWAS Catalog (16,041 cases, 440,307 controls) and the Genotype-Tissue Expression (GTEx) v8 eQTL dataset. Initially, we used the Unified Test for Molecular Signatures (UTMOST) for analysis, followed by validation with Functional Summary-based Imputation (FUSION) and conditional and joint (COJO) analyses. Candidate genes were further refined using Multi-marker Analysis of Genomic Annotation (MAGMA). Causal relationships were assessed through Summary Data-Based Mendelian Randomization (SMR), colocalization analysis (COLOC), and Mendelian Randomization (MR). GeneMANIA was used to identify interacting genes, and Phenome-Wide Association Study (PheWAS) was employed to enhance the results.

Results

UTMOST identified 33 susceptibility genes for CAS. Out of these, 17 met stringent criteria in both UTMOST and FUSION analyses. Combining results from UTMOST, FUSION, and MAGMA, we identified four critical candidate genes. WDPCP was the only gene to pass SMR, COLOC, and MR analyses, confirming its causal role in CAS. GeneMANIA revealed additional interacting genes, and PheWAS validated WDPCP's role as a susceptibility gene.

Conclusion

WDPCP is a potential novel susceptibility gene for CAS, influencing endothelial function, lipid metabolism, and coronary artery development. This study extends GWAS findings, highlighting WDPCP's potential as a therapeutic target and its consistent expression across different tissues. Further validation studies are warranted.

Comprehensive Genetic Analysis of Associations between Obesity-Related Parameters and Physical Activity: A Scoping Review

Genetic epidemiological studies have shown that numerous genetic variants cumulatively increase obesity risk. Although genetically predisposed individuals are more prone to developing obesity, it has been shown that physical activity can modify the genetic predisposition to obesity. Therefore, genetic data obtained from earlier studies, including 30 polymorphisms located in 18 genes, were analyzed using novel methods such as the total genetic score and Biofilter 2.4 software to combine genotypic and phenotypic information for nine obesity-related traits measured before and after the realization of the 12-week training program. The results revealed six genes whose genotypes were most important for post-training changes-LEP, LEPR, ADIPOQ, ADRA2A, ADRB3, and DRD2. Five noteworthy pairwise interactions, LEP × LEPR, ADRB2 × ADRB3, ADRA2A × ADRB3, ADRA2A × ADRB2, ADRA2A × DRD2, and three specific interactions demonstrating significant associations with key parameters crucial for health, total cholesterol (TC), high-density lipoprotein (HDL), and fat-free mass (FFM), were also identified. The molecular basis of training adaptation described in this study would have an enormous impact on the individualization of training programs, which, designed according to a given person's genetic profile, will be effective and safe intervention strategies for preventing obesity and improving health.

Genetics of posttraumatic stress disorder and cardiovascular conditions using Life's Essential 8, Electronic Health Records, and Heart Imaging

BACKGROUND

Patients with post-traumatic stress disorder (PTSD) experience higher risk of adverse cardiovascular (CV) outcomes. This study explores shared loci, and genes between PTSD and CV conditions from three major domains: CV diagnoses from electronic health records (CV-EHR), cardiac and aortic imaging, and CV health behaviors defined in Life's Essential 8 (LE8).

METHODS

We used genome-wide association study (GWAS) of PTSD (N=1,222,882), 246 CV diagnoses based on EHR data from Million Veteran Program (MVP; N=458,061), UK Biobank (UKBB; N=420,531), 82 cardiac and aortic imaging traits (N=26,893), and GWAS of traits defined in the LE8 (N = 282,271 ~ 1,320,016). Shared loci between PTSD and CV conditions were identified using local genetic correlations (rg), and colocalization (shared causal variants). Overlapping genes between PTSD and CV conditions were identified from genetically regulated proteome expression in brain and blood tissues, and subsequently tested to identify functional pathways and gene-drug targets. Epidemiological replication of EHR-CV diagnoses was performed in AllofUS cohort (AoU; N=249,906).

RESULTS

Among the 76 PTSD-susceptibility risk loci, 33 loci exhibited local rg with 45 CV-EHR traits (|rg|≥0.4), four loci with eight heart imaging traits(|rg|≥0.5), and 44 loci with LE8 factors (|rg|≥0.36) in MVP. Among significantly correlated loci, we found shared causal variants (colocalization probability > 80%) between PTSD and 17 CV-EHR (in MVP) at 11 loci in MVP, that also replicated in UKBB and/or other cohorts. Of the 17 traits, the observational analysis in the AoU showed PTSD was associated with 13 CV-EHR traits after accounting for socioeconomic factors and depression diagnosis. PTSD colocalized with eight heart imaging traits on 2 loci and with LE8 factors on 31 loci. Leveraging blood and brain proteome expression, we found 33 and 122 genes, respectively, shared between PTSD and CVD. Blood proteome genes were related to neuronal and immune processes, while the brain proteome genes converged on metabolic and calcium-modulating pathways (FDR p <0.05). Drug repurposing analysis highlighted DRD2, NOS1, GFAP, and POR as common targets of psychiatric and CV drugs.

CONCLUSION

PTSD-CV comorbidities exhibit shared risk loci, and genes involved in tissue-specific regulatory mechanisms.

Maternal Malnutrition and Elevated Disease Risk in Offspring

US populations have seen dramatic increases in the prevalence of chronic disease over the past three generations. Rapid increases in type 2 diabetes and obesity have occurred in all the states but have been particularly striking in the Deep South. These increases have contributed to decreases in life expectancy and to painful elevations in health care costs. The causes of worsening population health are complex and incompletely understood. However, there is strong evidence that vulnerability to chronic conditions is determined in early life. Most chronic diseases are developmentally driven. There are specific stressors experienced in early life that influence epigenetic and structural changes during development. These include malnutrition, severe levels of social stress, toxic chemicals, and low oxygen levels. Most US populations have experienced a decrease in the quality of the food they consume as industrial foods have replaced garden-grown foods. Thus, the consumption of too few nutrients before and during pregnancy and during lactation influences the growth of the placenta and fetal organs and their level of resilience when faced with stresses in postnatal life and particularly as adults. Animal studies have shown that the effects of poor nutrition can be passed on to future generations. The most powerful way that the current epidemics of obesity and insulin resistance can be reversed is by providing key nutrients to prospective mothers and those already pregnant.

Blood methylation pattern reflects epigenetic remodelling in adipose tissue after bariatric surgery

BACKGROUND

Studies on DNA methylation following bariatric surgery have primarily focused on blood cells, while it is unclear to which extend it may reflect DNA methylation profiles in specific metabolically relevant organs such as adipose tissue. Here, we investigated whether adipose tissue depots specific methylation changes after bariatric surgery are mirrored in blood.

METHODS

Using Illumina 850K EPIC technology, we analysed genome-wide DNA methylation in paired blood, subcutaneous and omental visceral AT (SAT/OVAT) samples from nine individuals (N = 6 female) with severe obesity pre- and post-surgery.

FINDINGS

The numbers and effect sizes of differentially methylated regions (DMRs) post-bariatric surgery were more pronounced in AT (SAT: 12,865 DMRs from -11.5 to 10.8%; OVAT: 14,632 DMRs from -13.7 to 12.8%) than in blood (9267 DMRs from -8.8 to 7.7%). Cross-tissue DMRs implicated immune-related genes. Among them, 49 regions could be validated with similar methylation changes in blood from independent individuals. Fourteen DMRs correlated with differentially expressed genes in AT post bariatric surgery, including downregulation of PIK3AP1 in both SAT and OVAT. DNA methylation age acceleration was significantly higher in AT compared to blood, but remained unaffected after surgery.

INTERPRETATION

Concurrent methylation pattern changes in blood and AT, particularly in immune-related genes, suggest blood DNA methylation mirrors AT's inflammatory state post-bariatric surgery.

FUNDING

The funding sources are listed in the Acknowledgments section.

Epigenetic/circadian clocks and PCOS

Polycystic ovary syndrome (PCOS) affects 6-20% of reproductive-aged women. It is associated with increased risks of metabolic syndrome, Type 2 diabetes, cardiovascular diseases, mood disorders, endometrial cancer and non-alcoholic fatty liver disease. Although various susceptibility loci have been identified through genetic studies, they account for ∼10% of PCOS heritability. Therefore, the etiology of PCOS remains unclear. This review explores the role of epigenetic changes and modifications in circadian clock genes as potential contributors to PCOS pathogenesis. Epigenetic alterations, such as DNA methylation, histone modifications, and non-coding RNA changes, have been described in diseases related to PCOS, such as diabetes, cardiovascular diseases, and obesity. Furthermore, several animal models have illustrated a link between prenatal exposure to androgens or anti-Müllerian hormone and PCOS-like phenotypes in subsequent generations, illustrating an epigenetic programming in PCOS. In humans, epigenetic changes have been reported in peripheral blood mononuclear cells (PBMC), adipose tissue, granulosa cells (GC), and liver from women with PCOS. The genome of women with PCOS is globally hypomethylated compared to healthy controls. However, specific hypomethylated or hypermethylated genes have been reported in the different tissues of these women. They are mainly involved in hormonal regulation and inflammatory pathways, as well as lipid and glucose metabolism. Additionally, sleep disorders are present in women with PCOS and disruptions in clock genes' expression patterns have been observed in their PBMC or GCs. While epigenetic changes hold promise as diagnostic biomarkers, the current challenge lies in distinguishing whether these changes are causes or consequences of PCOS. Targeting epigenetic modifications potentially opens avenues for precision medicine in PCOS, including lifestyle interventions and drug therapies. However, data are still lacking in large cohorts of well-characterized PCOS phenotypes. In conclusion, understanding the interplay between genetics, epigenetics, and circadian rhythms may provide valuable insights for early diagnosis and therapeutic strategies in PCOS in the future.