The Circadian Imbalance Index captures a polygenic composite susceptibility signal associated with cardiometabolic and mood outcomes, with suggestive evidence of directional relationships.
Abstract
Summary Background Circadian disruption affects multiple aspects of human health, but the genetic architecture of individual susceptibility remains unclear. We examined the genetics of the Circadian Imbalance Index (CII), an additive 0–5 score combining evening chronotype, short/long sleep, high neuroticism, atypical caffeinated coffee intake, and low vitamin D. Methods We ran a genome-wide association study (GWAS) of CII in 312,935 European-ancestry UK Biobank participants, compared signals with component-specific and leave-one-component-out (LOCO) GWASs, and tested sex and shift work interactions. CII polygenic score (PRS) PheWAS analyses were evaluated in Mass General Brigham Biobank (N = 50,908) and All of US (N = 98,182), with component-weighted PRS sensitivity analyses. Replication was assessed in Nurses’ Health Study II women (N = 11,344). We estimated genetic correlations and performed bidirectional two-sample Mendelian randomisation (MR) with MR-Egger, weighted median and LOCO sensitivity analyses. Findings We identified 27 loci mapping to 72 genes, including genes with reported links to circadian regulation or circadian-related pathways, such as CALCA, DHCR7, KDM5A, HAL, and CRX. Five genes (EPHB1, SERPING1, C12orf74, PLEKHG7, and EEA1) were observed in the CII analysis but not in component-specific analyses. LOCO analyses indicated that the CII genetic signal was not reducible to any single component. The CII PRS was associated with metabolic and psychiatric phenotypes. CII was genetically correlated with insomnia, mood swings, body mass index, type 2 diabetes, coronary artery disease, and myocardial infarction. MR analyses provided suggestive directional evidence, strongest for reverse associations of mood swings and coronary artery disease with CII. Interpretation The CII captures a polygenic composite susceptibility signal associated with cardiometabolic and mood outcomes, with suggestive evidence of directional relationships. Funding European Research Council Advanced Grant CLOCKrisk (101053225).
Objectives Circadian rhythms regulate human health, and observational studies have linked their disruption to hypertension; however, confounding factors and reverse causality limit causal interpretation. We aimed to evaluate the existing evidence linking circadian gene sets and hypertension using Mendelian randomization. Methods Two-sample Mendelian randomization was performed using genome-wide association study summary-level data from non-overlapping European ancestry samples. Genetic variants of 1276 circadian genes (CGDB) were instrumental variables; the outcome was hypertension genome-wide association study data from the UK Biobank (ieu-b-5144; 463,010 participants). Single nucleotide polymorphisms were selected at p<5 × 10−8 (mean F-statistic: 276.5). Inverse variance weighting was the primary method used. Benjamini–Hochberg false discovery rate correction was applied across all 1276 genes. Sensitivity analyses were performed using heterogeneity testing, Mendelian randomization–Egger regression, Mendelian Randomization Pleiotropy RESidual Sum and Outlier, Steiger directionality testing, and leave-one-out analyses. Results Mendelian randomization identified 39 nominally significant associations (inverse variance weighting, p < 0.05). After false discovery rate correction, four genes reached statistical significance: PHOSPHO1 (odds ratio = 0.988, 95% confidence interval: 0.983–0.993), BAIAP3 (odds ratio = 1.009, 95% confidence interval: 1.005–1.014), OSGIN2 (odds ratio = 0.990, 95% confidence interval: 0.986–0.995), and ZDHHC18 (odds ratio = 1.012, 95% confidence interval: 1.007–1.018). The remaining nominal associations did not survive false discovery rate correction and were classified as exploratory. Functional enrichment implicated circadian rhythm, apoptosis, and glycosaminoglycan biosynthesis pathways. Sensitivity analyses did not reveal significant heterogeneity or pleiotropy. Conclusions These findings are hypothesis-generating and require experimental validation. PHOSPHO1, BAIAP3, OSGIN2, and ZDHHC18 demonstrated statistically significant associations with hypertension risk after false discovery rate correction and should be prioritized for follow-up. Other nominal findings should be interpreted as exploratory.
Lu-Jie Wang, Yue-Qi Leng, Weizhong Wang et al.· Journal of International Med...· 0 citations
Chronic low-grade inflammation drives cardiometabolic diseases and has a strong genetic basis. Most genome-wide association studies (GWAS) have focused on European populations, limiting knowledge of the genetic influences on inflammation in admixed populations such as those in Brazil.
This study is part of the cross-sectional ISA Capital Health Survey. It uses data from the 2015 ISA Nutrition cohort, which measured biochemical, genetic, anthropometric, and lifestyle factors in a probabilistic sample of São Paulo residents. Genomic DNA was extracted from 841 individuals. Genotyping was performed using the Axiom 2.0 Precision Medicine Research Array. After quality control and missing data exclusion, 244,338 SNPs from 638 individuals remained for GWAS-based association analysis with eight inflammatory biomarkers. Models were adjusted for sex, age, age
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, overweight, and the first two principal components of ancestry.
Most participants were male (53%) and not overweight (55%). The median age was 49, and 38% were older adults. In the genome-wide analysis of TNF-α, IL-10, IL-1β, monocyte chemoattractant protein-1 (MCP-1), and adiponectin, 12 SNPs were significantly associated, most of which were intronic. Notably, one signal mapped to the missense variant rs16841009 in the olfactory receptor gene OR6K6. This variant was associated with MCP-1, suggesting a possible involvement in inflammatory responses.
We identified new SNPs linked to inflammatory biomarkers in a highly admixed Brazilian population, including a missense variant in an olfactory receptor gene linked to MCP-1. This association may be biologically important for inflammation and could affect the risk of cardiometabolic diseases.
J. Leite, G. F. L. Pascoal, G. B. S. Duarte et al.· Frontiers in Immunology· 0 citations
Sleep-related and chronotype traits have been shown to impact health in observational studies. To identify whether these associations are potentially causal, we conducted phenome-wide Mendelian randomisation analyses of short sleep, insomnia symptoms, total sleep duration, long sleep, snoring, daytime sleepiness and morning chronotype with a broad range of health-related phenotypes. We assessed the association between the genetic predisposition to these traits and the occurrence of 702 health-related phenotypes, using summary statistics of the largest genome-wide association studies in European individuals. Results that were significant (multiple comparisons: False Discovery Rate) and valid (robust genetic instruments, unaffected by horizontal pleiotropy) were validated using data from the second largest European genome-wide association study. Genetically determined short sleep was associated with increased risks of attention-deficit/hyperactivity disorder and neuroticism, musculoskeletal conditions, asthma and gastroesophageal reflux and lower educational attainment. Genetically determined insomnia symptoms showed associations with increased risk of coronary artery disease, major depression and osteoarticular disease. Genetically determined long sleep was linked to higher risk of iron deficiency anaemia and lower bone mineral density. Genetic predisposition to snoring was associated with more falls, greater body mass and higher low-grade inflammation. Genetically determined morning chronotype was related to higher vitamin D levels and lower risk of irritable bowel syndrome. No associations were found for daytime sleepiness. Overall, these findings indicate that genetically determined short sleep duration and insomnia symptoms are associated with mental and neurological problems, cardiovascular disease and musculoskeletal disorders, suggesting a potentially preventive, causal role of healthy sleeping patterns on chronic disease.
Marta H Hernandez, Camille Lassale, A. Camps-Vilaró et al.· Journal of Sleep Research· 0 citations
Abstract Background Increased childhood adiposity contributes to higher type 2 diabetes (T2D) risk, but the underlying mechanisms remain unclear. Furthermore, whether these mechanistic pathways are shared across ethnic groups has not been explored. Methods We conducted a two-step Mendelian randomization (MR) using European-based summary statistics from genome-wide association studies of childhood body mass index (BMI) (n = 61 111), adulthood proteomics (n = 35 559), and later life T2D (cases: 242 283; controls: 1 569 734). We also conducted a recall-by-genotype (RbG) study in a Chinese birth cohort (n = 250) to assess whether childhood BMI was associated with the identified proteomic signals in an East Asian population. Analyses included multi-instrument MR methods (inverse variance weighted and MR-Egger) and, for single-instrument proteins, cis-MR using the Wald ratio, with colocalization validation. Multiple testing was adjusted using false discovery rate (FDR). Results Higher genetically predicted childhood BMI was associated with 1299 proteins (FDR-adjusted P < .05), of which 36 proteins were associated with higher T2D risk. Six proteins were supported by colocalization (PPH4 > 80%). Genetically predicted higher childhood BMI was positively associated with GCKR, RBP1, ENTPD6, and GST A1-1, and inversely associated with PRSS27 and SHBG. The proportion of the BMI-T2D effect mediated by these proteins ranged from 1.87% to 12.92%. However, only SHBG was replicated in Asians in the RbG study. Conclusions Our study identified putative actionable proteins that could reduce the elevated T2D risk attributable to childhood adiposity in Europeans, but their relevance in Asian populations requires further investigation.
Siyu Chen, Yiwen Liang, Shan Luo et al.· International Journal of Epi...· 0 citations
Metabolomic analyses are increasingly applied in both etiological and predictive research, but frequently report missing values, which are then either imputed or removed from the analyses, and not examined as true missingness due to altered metabolism. We hypothesized that interindividual genetic variation may account for part of this missingness. We perform a logistic GWAS of metabolite missingness from an untargeted mass spectrometry-based platform in the Netherlands Epidemiology of Obesity Study (N = 594) and the Rhineland Study (N = 4,165). We consider metabolites missing in 10%-90% of individuals in both cohorts (N = 224). GWAS meta-analyses of these metabolites’ probability of missingness revealed 55 metabolome-wide significant associations, including 42 novel ones (p < 1.58 × 10–10), involving 28 metabolites and 41 lead SNPs. Despite considerable pleiotropy, the majority of identified SNP- ‘missing metabolite’ associations are biologically plausible, relating to beta-oxidation, bile acids, steroids, and xenobiotics metabolism. These findings suggest that missing values in metabolomics are partially non-random and reflect potential genetic variation.
T. Faquih, M. Imtiaz, V. Talevi et al.· Genome Biology· 0 citations
BACKGROUND
Observational studies have established a strong epidemiological connection between obesity and an increased risk of pre-eclampsia (PE). However, the genetic mechanisms underlying this comorbidity remain largely unexplored. In this study, we conducted a comprehensive cross-trait analysis to elucidate the shared genetic architecture between various adiposity-related traits and PE.
METHODS
Using the genome-wide association study (GWAS) statistics, we first evaluated the overall genetic overlap between adiposity-related traits and PE through multiple approaches, including linkage disequilibrium score regression (LDSC), high-definition likelihood inference (HDL), genetic covariance analysis, and pleiotropy and annotation methods. Causal relationships were then evaluated through bi-directional Generalised Summary-data-based Mendelian Randomisation (GSMR). Candidate pleiotropic loci were identified using a robust suite of analytical tools, including cross-phenotype association analysis, Multi-Trait Analysis of GWAS (MTAG), pleiotropic analysis under a composite null hypothesis, a pleiotropy-informed conditional false discovery rate (pleioFDR) framework, and Functional Mapping and Annotation (FUMA). Bayesian colocalisation (COLOC) was subsequently applied to these loci to pinpoint independent, significant causal single nucleotide polymorphisms (SNPs). To identify and validate shared genes, we performed tissue enrichment analysis, using Multi-marker Analysis of Genomic Annotation, and integrated SPrediXcan with COLOC. Finally, gene functional enrichment was characterised via Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses.
RESULTS
We identified significant positive genetic correlations and robust causal associations between adiposity-related traits and PE-related diseases. Our analyses revealed 35 independent significant causal SNPs, 32 enriched tissues, and 7 shared high-confidence genes supported by COLOC analysis.
CONCLUSIONS
Collectively, our study indicates a genetic correlation and common risk genes, linking adiposity-related traits to PE-related diseases. These findings offer novel insights into the biological mechanisms underlying this comorbidity, highlighting promising targets for future mechanistic studies and stratified preventative strategies.
Yuping Shan, Hong Hu, Chong Liu et al.· Journal of Obstetrics and Gy...· 0 citations