A comprehensive genome-wide cross-trait analysis of sexual factors and uterine leiomyoma.

Age at first sexual intercourse (AFS) and lifetime number of sexual partners (NSP) may influence the pathogenesis of uterine leiomyoma (UL) through their associations with hormonal concentrations and uterine infections. Leveraging summary statistics from large-scale genome-wide association studies conducted in European ancestry for each trait (NAFS = 214,547; NNSP = 370,711; NUL = 302,979), we observed a significant negative genomic correlation for UL with AFS (rg = -0.11, P = 7.83×10-4), but not with NSP (rg = 0.01, P = 0.62). Four specific genomic regions were identified as contributing significant local genetic correlations to AFS and UL, including one genomic region further identified for NSP and UL. Partitioning SNP-heritability with cell-type-specific annotations, a close clustering of UL with both AFS and NSP was identified in immune and blood-related components. Cross-trait meta-analysis revealed 15 loci shared between AFS/NSP and UL, including 7 novel SNPs. Univariable two-sample Mendelian randomization (MR) analysis suggested no evidence for a causal association between genetically predicted AFS/NSP and risk of UL, nor vice versa. Multivariable MR adjusting for age at menarche or/and age at natural menopause revealed a significant causal effect of genetically predicted higher AFS on a lower risk of UL. Such effect attenuated to null when age at first birth was further included. Utilizing participant-level data from the UK Biobank, one-sample MR based on genetic risk scores yielded consistent null findings among both pre-menopausal and post-menopausal females. From a genetic perspective, our study demonstrates an intrinsic link underlying sexual factors (AFS and NSP) and UL, highlighting shared biological mechanisms rather than direct causal effects. Future studies are needed to elucidate the specific mechanisms involved in the shared genetic influences and their potential impact on UL development.

[Association of Body Mass Index and Weight Gain With Obesity-Related Breast Cancer Risk Biomarkers in Adult Chinese Women].

Objective: To investigate the associatiojn of body mass index (BMI) at different stages of life and weight gain in adulthood with obesity-related breast cancer risk biomarkers and to provide evidence for formulating policies concerning the prevention and control of breast cancer. Methods: A cross-sectional study was designed based on the follow-up cohort of southwest China community-based breast cancer screening of women. Using sequential sampling, eligible participants were enrolled from the cohort as the subjects of the study. Information on the basic risk factors was collected and the height, weight, and plasma biomarker levels were measured. Multiple linear regression model was applied to analyze the associations of early adulthood BMI (defined as the BMI of the participant at age 20), adulthood BMI (defined as the BMI measured at the time of enrollment), and weight gain in adulthood with the biomarkers. The concentrations of the biomarkers were incorporated in the model after log transformation. Results: The average age of the 442 participants was 49 (45, 54) years old, the average early adulthood BMI and adulthood BMI were 21.47 (19.56, 23.11) and 24.10 (22.59, 25.97) kg/m 2, respectively, and the average weight gain in adulthood was 6.60 (2.00, 11.00) kg. Adulthood BMI was negatively associated with adiponectin level ( ß=-0.026, 95% CI: -0.045--0.008, P=0.006), and positively associated with C-reactive protein level ( ß=0.095, 95% CI: 0.054-0.137, P<0.001) and leptin receptor level ( ß=0.090, 95% CI: 0.063-0.117, P<0.001). No association was found between adulthood BMI and resistin levels or between adulthood BMI and insulin-like growth factor-binding protein-3 levels. BMI in early adulthood was found to be negatively associated with only insulin-like growth factor-binding protein-3 levels ( ß=-0.039, 95% CI: -0.068--0.010, P=0.009). Further analysis of adulthood weight gain after the age of 20 revealed that average annual weight gain in adulthood was negatively associated with adiponectin levels and positively associated with 4 other biomarkers. Furthermore, compared with those of women whose weight remained stable, the adiponectin level of women whose weight gain in adulthood exceeded 5.00 kg was much lower ( ß=-0.185, 95% CI: -0.320--0.049, P=0.008), while their insulin-like growth factor-binding protein-3 ( ß=0.389, 95% CI: 0.183-0.594, P<0.001) and leptin receptor ( ß=0.245, 95% CI: 0.048-0.442, P=0.015) levels were higher. Conclusion: Weight gain in adulthood is strongly associated with the changes in obesity-related breast cancer risk biomarkers. Women should maintain a stable weight throughout adulthood and it is preferred that their weight gain should not exceed 5.00 kg.

The impact of immunoglobulin G N-glycosylation level on COVID-19 outcome: evidence from a Mendelian randomization study.

Background: The coronavirus disease 2019 (COVID-19) pandemic has exerted a profound influence on humans. Increasing evidence shows that immune response is crucial in influencing the risk of infection and disease severity. Observational studies suggest an association between COVID-19 and immunoglobulin G (IgG) N-glycosylation traits, but the causal relevance of these traits in COVID-19 susceptibility and severity remains controversial. Methods: We conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between 77 IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity using summary-level data from genome-wide association studies (GWAS) and applying multiple methods including inverse-variance weighting (IVW), MR Egger, and weighted median. We also used Cochran's Q statistic and leave-one-out analysis to detect heterogeneity across each single nucleotide polymorphism (SNP). Additionally, we used the MR-Egger intercept test, MR-PRESSO global test, and PhenoScanner tool to detect and remove SNPs with horizontal pleiotropy and to ensure the reliability of our results. Results: We found significant causal associations between genetically predicted IgG N-glycosylation traits and COVID-19 susceptibility, hospitalization, and severity. Specifically, we observed reduced risk of COVID-19 with the genetically predicted increased IgG N-glycan trait IGP45 (OR = 0.95, 95% CI = 0.92-0.98; FDR = 0.019). IGP22 and IGP30 were associated with a higher risk of COVID-19 hospitalization and severity. Two (IGP2 and IGP77) and five (IGP10, IGP14, IGP34, IGP36, and IGP50) IgG N-glycosylation traits were causally associated with a decreased risk of COVID-19 hospitalization and severity, respectively. Sensitivity analyses did not identify any horizontal pleiotropy. Conclusions: Our study provides evidence that genetically elevated IgG N-glycosylation traits may have a causal effect on diverse COVID-19 outcomes. Our findings have potential implications for developing targeted interventions to improve COVID-19 outcomes by modulating IgG N-glycosylation levels.

Understanding the relationship between circulating lipids and risk of chronic kidney disease: a prospective cohort study and large-scale genetic analyses.

BACKGROUND: This study aims to comprehensively investigate the phenotypic and genetic relationships between four common lipids (high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; total cholesterol, TC; and triglycerides, TG), chronic kidney disease (CKD), and estimated glomerular filtration rate (eGFR). METHODS: We first investigated the observational association of lipids (exposures) with CKD (primary outcome) and eGFR (secondary outcome) using data from UK Biobank. We then explored the genetic relationship using summary statistics from the largest genome-wide association study of four lipids (N = 1,320,016), CKD (Ncase = 41,395, Ncontrol = 439,303), and eGFR(N = 567,460). RESULTS: There were significant phenotypic associations (HDL-C: hazard ratio (HR) = 0.76, 95%CI = 0.60-0.95; TG: HR = 1.08, 95%CI = 1.02-1.13) and global genetic correlations (HDL-C: [Formula: see text] = - 0.132, P = 1.00 × 10-4; TG: [Formula: see text] = 0.176; P = 2.66 × 10-5) between HDL-C, TG, and CKD risk. Partitioning the whole genome into 2353 LD-independent regions, twelve significant regions were observed for four lipids and CKD. The shared genetic basis was largely explained by 29 pleiotropic loci and 36 shared gene-tissue pairs. Mendelian randomization revealed an independent causal relationship of genetically predicted HDL-C (odds ratio = 0.91, 95%CI = 0.85-0.98), but not for LDL-C, TC, or TG, with the risk of CKD. Regarding eGFR, a similar pattern of correlation and pleiotropy was observed. CONCLUSIONS: Our work demonstrates a putative causal role of HDL-C in CKD and a significant biological pleiotropy underlying lipids and CKD in populations of European ancestry. Management of low HDL-C levels could potentially benefit in reducing the long-term risk of CKD.

Impact of gallstone disease on the risk of stroke and coronary artery disease: evidence from prospective observational studies and genetic analyses.

BACKGROUND: Despite epidemiological evidence associating gallstone disease (GSD) with cardiovascular disease (CVD), a dilemma remains on the role of cholecystectomy in modifying the risk of CVD. We aimed to characterize the phenotypic and genetic relationships between GSD and two CVD events - stroke and coronary artery disease (CAD). METHODS: We first performed a meta-analysis of cohort studies to quantify an overall phenotypic association between GSD and CVD. We then investigated the genetic relationship leveraging the largest genome-wide genetic summary statistics. We finally examined the phenotypic association using the comprehensive data from UK Biobank (UKB). RESULTS: An overall significant effect of GSD on CVD was found in meta-analysis (relative risk [RR] = 1.26, 95% confidence interval [CI] = 1.19-1.34). Genetically, a positive shared genetic basis was observed for GSD with stroke ([Formula: see text]=0.16, P = 6.00 × 10-4) and CAD ([Formula: see text]=0.27, P = 2.27 × 10-15), corroborated by local signals. The shared genetic architecture was largely explained by the multiple pleiotropic loci identified in cross-phenotype association study and the shared gene-tissue pairs detected by transcriptome-wide association study, but not a causal relationship (GSD to CVD) examined through Mendelian randomization (MR) (GSD-stroke: odds ratio [OR] = 1.00, 95%CI = 0.97-1.03; GSD-CAD: OR = 1.01, 95%CI = 0.98-1.04). After a careful adjustment of confounders or considering lag time using UKB data, no significant phenotypic effect of GSD on CVD was detected (GSD-stroke: hazard ratio [HR] = 0.95, 95%CI = 0.83-1.09; GSD-CAD: HR = 0.98, 95%CI = 0.91-1.06), further supporting MR findings. CONCLUSIONS: Our work demonstrates a phenotypic and genetic relationship between GSD and CVD, highlighting a shared biological mechanism rather than a direct causal effect. These findings may provide insight into clinical and public health applications.

Increases in BMI contribute to worsening inflammatory biomarkers related to breast cancer risk in women: a longitudinal study.

BACKGROUND: Inflammatory adipokines and cytokines play a pivotal role in linking obesity and breast cancer (BC) risk in women. We investigated the longitudinal associations between BMI change and trajectories of inflammatory biomarkers related to BC risk. METHODS: A longitudinal study was conducted among 442 Chinese women with 3-year repeated measures from 2019 to 2021. Plasma circulating inflammatory biomarkers related to BC risk, including adiponectin (ADP), resistin (RETN), soluble leptin receptor (sOB-R), insulin-like growth factor-binding protein-3 (IGFBP-3), and C-reactive protein (CRP), were examined annually. Linear mixed-effect models (LMM) were applied to investigate associations of time-varying BMI with trajectories of biomarkers. We additionally examined the modification effect of baseline BMI groups, menopausal status, and metabolic syndrome. RESULTS: BMI was associated with increased levels of RETN, CRP, sOB-R, and decreased levels of ADP at baseline. An increasing BMI rate was significantly associated with an average 3-year increase in RETN (ß = 0.019, 95% CI 0.004 to 0.034) and sOB-R (ß = 0.022, 95% CI 0.009 to 0.035), as well as a decrease in ADP (ß = - 0.006, 95% CI - 0.012 to 0.001). These associations persisted across different baseline BMI groups. An increasing BMI rate was significantly associated with an average 3-year increase in CRP levels among normal weight (ß = 0.045, 95% CI 0.001 to 0.088) and overweight (ß = 0.060, 95% CI 0.014 to 0.107) women. As BMI increased over time, a more remarkable decrease in ADP was observed among women with metabolic syndrome (ß = - 0.016, 95% CI - 0.029 to - 0.004) than those without metabolic syndrome at baseline. CONCLUSIONS: A higher increase rate of BMI was associated with poorer trajectories of inflammatory biomarkers related to BC risk. Recommendations for BMI reduction may benefit BC prevention in women, particularly for those with metabolic syndrome.

Associations between changes of smartphone pedometer-assessed step counts and levels of obesity-related breast cancer biomarkers in non-cancer women: A population-based observational study.

While a higher level of physical activity (PA) is inversely associated with a higher breast cancer (BC) risk, the health benefits of daily steps on obesity-related BC biomarkers remain unclear. We aimed to understand the associations of changes in step counts with levels of five obesity-related BC biomarkers during a two-year follow-up. In total, 144 non-cancer women (47.96 ± 5.72) were observed on both 2019 and 2021. A structured questionnaire, daily steps and fasting blood samples were collected before (t0, 2019) and after (t1, 2021). Levels of biomarkers (IGF-binding proteins 3, adiponectin, soluble leptin receptor, C-reactive protein, and resistin) were assayed by ELISA. Participants were divided into persistent low steps, decreasing steps, increasing steps, and persistent high steps. Associations of categories on proposed biomarkers were estimated using linear regression models, with persistent low steps as reference. Associations between time-varying step counts with biomarkers were quantified using mixed linear models. Compared with persistent low steps, increasing steps is associated with a reduction in C-reactive protein level (ß=-0.74, 95%CI=-1.23--0.26, P-value = 2.98 × 10-3). An inverse association between time-varying step counts with C-reactive protein level was identified, consistent across different obesity types and baseline step level categories. No association with daily step counts was observed for other proteins.

A large-scale genome-wide cross-trait analysis for the effect of COVID-19 on female-specific cancers.

Little is known regarding the long-term adverse effects of COVID-19 on female-specific cancers, nor the shared genetic influences underlying these conditions. We performed a comprehensive genome-wide cross-trait analysis to investigate the shared genetic architecture between COVID-19 (infection, hospitalization, and critical illness) with three female-specific cancers (breast cancer (BC), epithelial ovarian cancer (EOC), and endometrial cancer (EC)). We identified significant genome-wide genetic correlations with EC for both hospitalization (rg = 0.19, p = 0.01) and critical illness (rg = 0.29, p = 3.00 × 10-4). Mendelian randomization demonstrated no valid association of COVID-19 with any cancer of interest, except for suggestive associations of genetically predicted hospitalization (ORIVW = 1.09, p = 0.04) and critical illness (ORIVW = 1.06, p = 0.04) with EC risk, none withstanding multiple correction. Cross-trait meta-analysis identified 20 SNPs shared between COVID-19 with BC, 15 with EOC, and 5 with EC; and transcriptome-wide association studies revealed multiple shared genes. Findings support intrinsic links underlying these complex traits, highlighting shared mechanisms rather than causal associations.

Temporal relationships between BMI and obesity-related predictors of cardiometabolic and breast cancer risk in a longitudinal cohort.

Prospective inter-relationships among biomarkers were unexplored, which may provide mechanistic insights into diseases. We investigated the longitudinal associations of BMI change with trajectories of biomarkers related to cardiometabolic or breast cancer risk. A longitudinal study was conducted among 444 healthy women between 2019 to 2021. Cross­lagged path analysis was used to examine the temporal relationships among BMI, cardiometabolic risk score (CRS), and obesity­related proteins score (OPS) of breast cancer. Linear mixed-effect models were applied to investigate associations of time-varying BMI with biomarker-based risk score trajectories. Baseline BMI was associated with subsequent change of breast cancer predictors (P = 0.03), and baseline CRS were positively associated with OPS change (P < 0.001) but not vice versa. After fully adjustment of confounders, we found a 0.058 (95%CI = 0.009-0.107, P = 0.020) units increase of CRS and a 1.021 (95%CI = 0.041-1.995, P = 0.040) units increase of OPS as BMI increased 1 kg/m2 per year in postmenopausal women. OPS increased 0.784 (95%CI = 0.053-1.512, P = 0.035) units as CRS increased 1 unit per year. However, among premenopausal women, BMI only significantly affected CRS (ß = 0.057, 95%CI = 0.007 to 0.107, P = 0.025). No significant change of OPS with time-varying CRS was found. Higher increase rates of BMI were associated with worse trajectories of biomarker-based risk of cardiometabolic and breast cancer. The longitudinal impact of CRS on OPS is unidirectional. Recommendations such as weight control for the reduction of cardiometabolic risk factors may benefit breast cancer prevention, especially in postmenopausal women.

Using human genetics to understand the phenotypic association between chronotype and breast cancer.

Little is known regarding the shared genetic influences underlying the observed phenotypic association between chronotype and breast cancer in women. Leveraging summary statistics from the hitherto largest genome-wide association study conducted in each trait, we investigated the genetic correlation, pleiotropic loci, and causal relationship of chronotype with overall breast cancer, and with its subtypes defined by the status of oestrogen receptor. We identified a negative genomic correlation between chronotype and overall breast cancer ( r g $$ {r}_g $$ = -0.06, p = 3.00 × 10-4 ), consistent across oestrogen receptor-positive ( r g $$ {r}_g $$ = -0.05, p = 3.30 × 10-3 ) and oestrogen receptor-negative subtypes ( r g $$ {r}_g $$ = -0.05, p = 1.11 × 10-2 ). Five specific genomic regions were further identified as contributing a significant local genetic correlation. Cross-trait meta-analysis identified 78 loci shared between chronotype and breast cancer, of which 23 were novel. Transcriptome-wide association study revealed 13 shared genes, targeting tissues of the nervous, cardiovascular, digestive, and exocrine/endocrine systems. Mendelian randomisation demonstrated a significantly reduced risk of overall breast cancer (odds ratio 0.89, 95% confidence interval 0.83-0.94; p = 1.30 × 10-4 ) for genetically predicted morning chronotype. No reverse causality was found. Our work demonstrates an intrinsic link underlying chronotype and breast cancer, which may provide clues to inform management of sleep habits to improve female health.

Nuclear magnetic resonance-determined lipoprotein profile and risk of breast cancer: a Mendelian randomization study.

PURPOSE: While crudely quantified lipoproteins have been reported to affect the risk of breast cancer, the effects of subclass lipoproteins characterized by particle size, particle number, and lipidomes remain unknown. METHODS: Utilizing nuclear magnetic resonance-based GWAS of 85 lipoprotein traits, we performed two-sample univariable Mendelian randomization (MR) to evaluate the causal relationship between each trait with breast cancer (Ncase/control = 133,384/113,789) and with its estrogen receptor (ER) subtypes. Then, we applied multivariable MR to investigate the independent effects considering both general and central obesity. RESULTS: In univariable MR, a heterogeneous effect of subclass high-density lipoproteins (HDL) was observed, in which small HDL traits (ORs ranged from 0.89 to 0.94) were associated with a decreased risk of breast cancer while non-small HDLs traits (OR ranged from 1.04 to 1.08) were associated with an increased risk of breast cancer. Very-low-density lipoproteins (VLDL) traits and serum total triglycerides (TG) were associated with a decreased risk of breast cancer (ORs ranged from 0.88 to 0.94). Similar association patterns were found for ER + subtype. In multivariable MR, only the protective effects of small HDL, VLDL and TG on ER + subtype remained significant. CONCLUSION: We identified a heterogeneous effect of subclass HDLs and a consistent protective effect of VLDL on breast cancer. Only the effects of small HDL and VLDL on ER + subtype remained robust after controlling for obesity. These findings provide new insight into the causal pathway underlying lipoproteins and breast cancer.

[Effect of Interactions Among Obesity-Related Proteins on Breast Cancer Risk: A Preliminary Study].

Objective: To explore the potential interactions among obesity-related proteins in the pathogenic process of breast cancer (BC) in women. Methods: We conducted a case-control study, enrolling 279 primary breast cancer cases and 260 age-frequency-matched healthy women between April 2014 and May 2015. Based on the evidence of previous published literature on obesity-related proteins and BC risks, we selected proteins that received more attention and measured the plasma levels of these proteins by enzyme-linked immunosorbent assay (ELISA). After stratification of the subjects according to their menopausal status, an analytic strategy combining multivariate logistic regression and generalized multifactor dimensionality reduction (GMDR) was used to explore the effect of the possible interactions of these proteins on BC risk. Results: There were marginal high-order interactions among insulin-like growth factor 1 (IGF-1), insulin-like growth factor binding protein 3 (IGFBP-3), C-reactive protein (CRP), resistin (RETN), soluble leptin receptor (sOB-R), and adiponectin (ADP) in premenopausal women (with the balanced accuracy for the testing set being 59.01%, cross-validation consistency being 10/10, and permutation test P=0.05). There were high-order interactions among leptin (LEP), sOB-R, ADP, CRP, IGFBP3 and visfatin (VF) in postmenopausal women (with the balanced accuracy for the testing set being 67.31%, cross-validation consistency being 10/10, and permutation test P=0.01). Along with an increase in the number of obesity-related proteins to which the subjects were exposed, the risk of developing breast cancer gradually increased in both pre- and postmenopausal women ( OR pre =2.18, 95% CI: 1.69-2.82; OR post =2.41, 95% CI: 1.75-3.32). Conclusions: This preliminary study suggested high-order interactions among obesity-related proteins on BC risk in both pre- and postmenopausal women. In future studies, close attention should be given to these potential interactions when these proteins are used jointly as predictors, as well as in developing a comprehensive risk scoring system for BC.

Investigating the relationship between depression and breast cancer: observational and genetic analyses.

BACKGROUND: Both depression and breast cancer (BC) contribute to a substantial global burden of morbidity and mortality among women, and previous studies have observed a potential depression-BC link. We aimed to comprehensively characterize the phenotypic and genetic relationships between depression and BC. METHODS: We first evaluated phenotypic association using longitudinal follow-up data from the UK Biobank (N = 250,294). We then investigated genetic relationships leveraging summary statistics from the hitherto largest genome-wide association study of European individuals conducted for depression (N = 500,199), BC (N = 247,173), and its subtypes based on the status of estrogen receptor (ER + : N = 175,475; ER - : N = 127,442). RESULTS: Observational analysis suggested an increased hazard of BC in depression patients (HR = 1.10, 95%CIs = 0.95-1.26). A positive genetic correlation between depression and overall BC was observed ([Formula: see text] = 0.08, P = 3.00 × 10-4), consistent across ER + ([Formula: see text] = 0.06, P = 6.30 × 10-3) and ER - subtypes ([Formula: see text] = 0.08, P = 7.20 × 10-3). Several specific genomic regions showed evidence of local genetic correlation, including one locus at 9q31.2, and four loci at, or close, to 6p22.1. Cross-trait meta-analysis identified 17 pleiotropic loci shared between depression and BC. TWAS analysis revealed five shared genes. Bi-directional Mendelian randomization suggested risk of depression was causally associated with risk of overall BC (OR = 1.12, 95%Cis = 1.04-1.19), but risk of BC was not causally associated with risk of depression. CONCLUSIONS: Our work demonstrates a shared genetic basis, pleiotropic loci, and a putative causal relationship between depression and BC, highlighting a biological link underlying the observed phenotypic relationship; these findings may provide important implications for future studies aimed reducing BC risk.

Reassessing the causal role of obesity in breast cancer susceptibility: a comprehensive multivariable Mendelian randomization investigating the distribution and timing of exposure.

BACKGROUND: Previous Mendelian randomization (MR) studies on obesity and risk of breast cancer adopted a small number of instrumental variables and focused mainly on the crude total effect. We aim to investigate the independent causal effect of obesity on breast cancer susceptibility, considering the distribution of fat, covering both early and late life. METHODS: Using an enlarged set of female-specific genetic variants associated with adult general [body mass index (BMI)] and abdominal obesity [waist-to-hip ratio (WHR) with and without adjustment for BMI, WHR and WHRadjBMI] as well as using sex-combined genetic variants of childhood obesity (childhood BMI), we performed a two-sample univariable MR to re-evaluate the total effect of each obesity-related exposure on overall breast cancer (Ncase = 133 384, Ncontrol = 113 789). We further looked into its oestrogen receptor (ER)-defined subtypes (NER+ = 69 501, NER- = 21 468, Ncontrol = 105 974). Multivariable MR was applied to estimate the independent causal effect of each obesity-related exposure on breast cancer taking into account confounders as well as to investigate the independent effect of adult and childhood obesity considering their inter-correlation. RESULTS: In univariable MR, the protective effects of both adult BMI [odds ratio (OR) = 0.89, 95% CI = 0.83-0.96, P = 2.06 × 10-3] and childhood BMI (OR = 0.78, 95% CI = 0.70-0.87, P = 4.58 × 10-6) were observed for breast cancer overall. Comparable effects were found in ER+ and ER- subtypes. Similarly, genetically predicted adult WHR was also associated with a decreased risk of breast cancer overall (OR = 0.87, 95% CI = 0.80-0.96, P = 3.77 × 10-3), restricting to ER+ subtype (OR = 0.88, 95% CI = 0.80-0.98, P = 1.84 × 10-2). Conditional on childhood BMI, the effect of adult general obesity on breast cancer overall attenuated to null (BMI: OR = 1.00, 95% CI = 0.90-1.10, P = 0.96), whereas the effect of adult abdominal obesity attenuated to some extent (WHR: OR = 0.90, 95% CI = 0.82-0.98, P = 1.49 × 10-2; WHRadjBMI: OR = 0.92, 95% CI = 0.86-0.99, P = 1.98 × 10-2). On the contrary, an independent protective effect of childhood BMI was observed in breast cancer overall, irrespective of adult measures (adjusted for adult BMI: OR = 0.84, 95% CI = 0.77-0.93, P = 3.93 × 10-4; adjusted for adult WHR: OR = 0.84, 95% CI = 0.76-0.91, P = 6.57 × 10-5; adjusted for adult WHRadjBMI: OR = 0.80, 95% CI = 0.74-0.87, P = 1.24 × 10-7). CONCLUSION: Although successfully replicating the inverse causal relationship between adult obesity-related exposures and risk of breast cancer, our study demonstrated such effects to be largely (adult BMI) or partly (adult WHR or WHRadjBMI) attributed to childhood obesity. Our findings highlighted an independent role of childhood obesity in affecting the risk of breast cancer as well as the importance of taking into account the complex interplay underlying correlated exposures.

Observational and genetic analyses clarify the relationship between type 2 diabetes mellitus and gallstone disease.

Background: The relationship between type 2 diabetes mellitus (T2DM) and gallstone disease (GSD) have been incompletely understood. We aimed to investigate their phenotypic and genetic associations and evaluate the biological mechanisms underlying these associations. Methods: We first evaluated the phenotypic association between T2DM and GSD using data from the UK Biobank (n>450,000) using a prospective observational design. We then conducted genetic analyses using summary statistics from a meta-analysis of genome-wide association studies of T2DM, with and without adjusting for body mass index (BMI) (Ncase=74,124, Ncontrol=824,006; T2DMadjBMI: Ncase=50,409, Ncontrol=523,897) and GSD (Ncase=43,639, Ncontrol=506,798). Results: A unidirectional phenotypic association was observed, where individuals with T2DM exhibited a higher GSD risk (hazard ratio (HR)=1.39, P<0.001), but not in the reverse direction (GSD→T2DM: HR=1.00, P=0.912). The positive T2DM-GSD genetic correlation (rg=0.35, P=7.71×10-23) remained even after adjusting for BMI (T2DMadjBMI: rg=0.22, P=4.48×10-10). Mendelian randomization analyses provided evidence of a unidirectional causal relationship (T2DM→GSD: odds ratio (OR)=1.08, P=4.6×10-8; GSD→T2DM: OR=1.02, P=0.48), even after adjusting for important metabolic confounders (OR=1.02, P=0.02). This association was further corroborated through a comprehensive functional analysis reflected by 23 pleiotropic single nucleotide polymorphisms, as well as multiple neural and motor-enriched tissues. Conclusion: Through comprehensive observational and genetic analyses, our study clarified the causal relationship between T2DM and GSD, but not in the reverse direction. These findings might provide new insights into prevention and treatment strategies for T2DM and GSD.

Investigating the shared genetic architecture of uterine leiomyoma and breast cancer: A genome-wide cross-trait analysis.

Little is known regarding the shared genetic architecture or causality underlying the phenotypic association observed for uterine leiomyoma (UL) and breast cancer (BC). Leveraging summary statistics from the hitherto largest genome-wide association study (GWAS) conducted in each trait, we investigated the genetic overlap and causal associations of UL with BC overall, as well as with its subtypes defined by the status of estrogen receptor (ER). We observed a positive genetic correlation between UL and BC overall (rg = 0.09, p = 6.00 × 10-3), which was consistent in ER+ subtype (rg = 0.06, p = 0.01) but not in ER- subtype (rg = 0.06, p = 0.08). Partitioning the whole genome into 1,703 independent regions, local genetic correlation was identified at 22q13.1 for UL with BC overall and with ER+ subtype. Significant genetic correlation was further discovered in 9 out of 14 functional categories, with the highest estimates observed in coding, H3K9ac, and repressed regions. Cross-trait meta-analysis identified 9 novel loci shared between UL and BC. Mendelian randomization demonstrated a significantly increased risk of BC overall (OR = 1.09, 95% CI = 1.01-1.18) and ER+ subtype (OR = 1.09, 95% CI = 1.01-1.17) for genetic liability to UL. No reverse causality was found. Our comprehensive genome-wide cross-trait analysis demonstrates a shared genetic basis, pleiotropic loci, as well as a putative causal relationship between UL and BC, highlighting an intrinsic link underlying these two complex female diseases.

Factors influencing parents' willingness to vaccinate their preschool children against COVID-19: Results from the mixed-method study in China.

During the COVID-19 pandemic, little is known about parental hesitancy to receive the COVID-19 vaccine for preschool children who are the potential vaccinated population in the future. The purpose of this mixed-method study was to explore the factors influencing Chinese parents' decision to vaccinate their children aged 3-6 years old against COVID-19. In July 2021, we conducted semi-structured interviews (n = 19) and a cross-sectional survey (n = 2605) with parents of kindergarten children in an urban-rural combination pilot area in China. According to the qualitative study, most parents were hesitant to vaccinate their children with the COVID-19 vaccine. In the quantitative study, we found that three-fifths of 2605 participants were unwilling to vaccinate their children against COVID-19. Furthermore, the main predictors of parents' intention to vaccinate their children were fathers, lower level of education, and positive attitudes toward vaccination. Based on our findings, targeted health education techniques may be able to boost childhood COVID-19 immunization rates.

Obesity-related proteins score as a potential marker of breast cancer risk.

There is strong evidence to suggest that obesity-related proteins play a key role in pathways that are related to breast cancer. In this study, we aimed to establish a robust obesity-related protein score (ORPS) that could be used to assess breast cancer risk. Based on evidence from high-quality systematic reviews and population studies, we selected nine such proteins that are stable in vitro, and measured their circulating concentrations by ELISA in a case-control study conducted in Chengdu, Sichuan, China, with 279 breast cancer cases and 260 healthy controls. Two obesity-related protein scores (ORPS) were calculated using a three-step method, with linear-weighted summation, and the one with a larger area under the curve was chosen for further evaluation. As a result, ORPS (PS5pre or PS4post) was positively correlated with breast cancer risk (premenopausal: OR≤63 VS >63 3.696, 95% CI 2.025-6.747; postmenopausal: OR≤38 VS >38 7.100, 95% CI 3.134-16.084), and represented a better risk predictor among obese women compared to non-obese in pre- and postmenopausal women. Among different molecular subtypes, ORPS was positively correlated with Luminal breast cancer, with additionally positive association with triple-negative breast cancer in premenopausal women. The ORPS might be a potential marker of breast cancer risk among Chinese women.

A network meta-analysis of secondary attack rates of COVID-19 in different contact environments.

As the corona virus disease 2019 (COVID-19) pandemic continues around the world, understanding the transmission characteristics of COVID-19 is vital for prevention and control. We conducted the first study aiming to estimate and compare the relative risk of secondary attack rates (SARs) of COVID-19 in different contact environments. Until 26 July 2021, epidemiological studies and cluster epidemic reports of COVID-19 were retrieved from SCI, Embase, PubMed, CNKI, Wanfang and CBM in English and Chinese, respectively. Relative risks (RRs) were estimated in pairwise comparisons of SARs between different contact environments using the frequentist NMA framework, and the ranking of risks in these environments was calculated using the surface under the cumulative ranking curve (SUCRA). Subgroup analysis was performed by regions. Thirty-two studies with 68 260 participants were identified. Compared with meal or gathering, transportation (RR 10.55, 95% confidence interval (CI) 1.43-77.85), medical care (RR 11.68, 95% CI 1.58-86.61) and work or study places (RR 10.15, 95% CI 1.40-73.38) had lower risk ratios for SARs. Overall, the SUCRA rankings from the highest to the lowest were household (95.3%), meal or gathering (81.4%), public places (58.9%), daily conversation (50.1%), transportation (30.8%), medical care (18.2%) and work or study places (15.3%). Household SARs were significantly higher than other environments in the subgroup of mainland China and sensitive analysis without small sample studies (<100). In light of the risks, stratified personal protection and public health measures need to be in place accordingly, so as close contacts categorising and management.