Phenotypic and genetic effect of carotid intima-media thickness on the risk of stroke.

While carotid intima-media thickness (cIMT) as a noninvasive surrogate measure of atherosclerosis is widely considered a risk factor for stroke, the intrinsic link underlying cIMT and stroke has not been fully understood. We aimed to evaluate the clinical value of cIMT in stroke through the investigation of phenotypic and genetic relationships between cIMT and stroke. We evaluated phenotypic associations using observational data from UK Biobank (N = 21,526). We then investigated genetic relationships leveraging genomic data conducted in predominantly European ancestry for cIMT (N = 45,185) and any stroke (AS, Ncase/Ncontrol=40,585/406,111). Observational analyses suggested an increased hazard of stroke per one standard deviation increase in cIMT (cIMTmax-AS: hazard ratio (HR) = 1.39, 95%CI = 1.09-1.79; cIMTmean-AS: HR = 1.39, 95%CI = 1.09-1.78; cIMTmin-AS: HR = 1.32, 95%CI = 1.04-1.68). A positive global genetic correlation was observed (cIMTmax-AS: [Formula: see text]=0.23, P=9.44 × 10-5; cIMTmean-AS: [Formula: see text]=0.21, P=3.00 × 10-4; cIMTmin-AS: [Formula: see text]=0.16, P=6.30 × 10-3). This was further substantiated by five shared independent loci and 15 shared expression-trait associations. Mendelian randomization analyses suggested no causal effect of cIMT on stroke (cIMTmax-AS: odds ratio (OR)=1.12, 95%CI=0.97-1.28; cIMTmean-AS: OR=1.09, 95%CI=0.93-1.26; cIMTmin-AS: OR=1.03, 95%CI = 0.90-1.17). A putative association was observed for genetically predicted stroke on cIMT (AS-cIMTmax: beta=0.07, 95%CI = 0.01-0.13; AS-cIMTmean: beta=0.08, 95%CI = 0.01-0.15; AS-cIMTmin: beta = 0.08, 95%CI = 0.01-0.16) in the reverse direction MR, which attenuated to non-significant in sensitivity analysis. Our work does not find evidence supporting causal associations between cIMT and stroke. The pronounced cIMT-stroke association is intrinsic, and mostly attributed to shared genetic components. The clinical value of cIMT as a surrogate marker for stroke risk in the general population is likely limited.

Risk factors for prostate cancer: An umbrella review of prospective observational studies and mendelian randomization analyses.

BACKGROUND: The incidence of prostate cancer is increasing in older males globally. Age, ethnicity, and family history are identified as the well-known risk factors for prostate cancer, but few modifiable factors have been firmly established. The objective of this study was to identify and evaluate various factors modifying the risk of prostate cancer reported in meta-analyses of prospective observational studies and mendelian randomization (MR) analyses. METHODS AND FINDINGS: We searched PubMed, Embase, and Web of Science from the inception to January 10, 2022, updated on September 9, 2023, to identify meta-analyses and MR studies on prostate cancer. Eligibility criteria for meta-analyses were (1) meta-analyses including prospective observational studies or studies that declared outcome-free at baseline; (2) evaluating the factors of any category associated with prostate cancer incidence; and (3) providing effect estimates for further data synthesis. Similar criteria were applied to MR studies. Meta-analysis was repeated using the random-effects inverse-variance model with DerSimonian-Laird method. Quality assessment was then conducted for included meta-analyses using AMSTAR-2 tool and for MR studies using STROBE-MR and assumption evaluation. Subsequent evidence grading criteria for significant associations in meta-analyses contained sample size, P values and 95% confidence intervals, 95% prediction intervals, heterogeneity, and publication bias, assigning 4 evidence grades (convincing, highly suggestive, suggestive, or weak). Significant associations in MR studies were graded as robust, probable, suggestive, or insufficient considering P values and concordance of effect directions. Finally, 92 selected from 411 meta-analyses and 64 selected from 118 MR studies were included after excluding the overlapping and outdated studies which were published earlier and contained fewer participants or fewer instrument variables for the same exposure. In total, 123 observational associations (45 significant and 78 null) and 145 causal associations (55 significant and 90 null) were categorized into lifestyle; diet and nutrition; anthropometric indices; biomarkers; clinical variables, diseases, and treatments; and environmental factors. Concerning evidence grading on significant associations, there were 5 highly suggestive, 36 suggestive, and 4 weak associations in meta-analyses, and 10 robust, 24 probable, 4 suggestive, and 17 insufficient causal associations in MR studies. Twenty-six overlapping factors between meta-analyses and MR studies were identified, with consistent significant effects found for physical activity (PA) (occupational PA in meta: OR = 0.87, 95% CI: 0.80, 0.94; accelerator-measured PA in MR: OR = 0.49, 95% CI: 0.33, 0.72), height (meta: OR = 1.09, 95% CI: 1.06, 1.12; MR: OR = 1.07, 95% CI: 1.01, 1.15, for aggressive prostate cancer), and smoking (current smoking in meta: OR = 0.74, 95% CI: 0.68, 0.80; smoking initiation in MR: OR = 0.91, 95% CI: 0.86, 0.97). Methodological limitation is that the evidence grading criteria could be expanded by considering more indices. CONCLUSIONS: In this large-scale study, we summarized the associations of various factors with prostate cancer risk and provided comparisons between observational associations by meta-analysis and genetically estimated causality by MR analyses. In the absence of convincing overlapping evidence based on the existing literature, no robust associations were identified, but some effects were observed for height, physical activity, and smoking.

The association between artificial light at night and gestational diabetes mellitus: A prospective cohort study from China.

BACKGROUND: Emerging evidence suggests that exposure to outdoor artificial light at night (ALAN) may be associated with diabetes. However, limited research explores the relationship between outdoor ALAN and gestational diabetes mellitus (GDM). METHODS: We utilized data from a multilevel infant and early life cohort study conducted in Sichuan Province, China, between February 2018 and April 2021. A total of 9,120 participants were included in the final analysis. Outdoor ALAN exposure at participants' residential locations was estimated using time-varying satellite data, focusing on persistent night-time illumination at a scale of approximately 500x500m. The information about GDM was obtained from medical records. After adjusting for potential confounders, multivariable logistic regression models and restricted cubic splines were employed to estimate the association between ALAN exposure during pregnancy and GDM. RESULTS: Among the total recruitments, 1,484 (16.27%) women were diagnosed with GDM. Compared to women without GDM, those with GDM had a significantly higher mean outdoor ALAN exposure during pregnancy (18.98 nW/cm2/sr1 vs 24.28 nW/cm2/sr1, P < 0.001). Results from multivariable logistic models showed that higher outdoor ALAN exposure during pregnancy could increase the risk of GDM (OR (95% CI) 1st+2nd trimesters ALAN = 1.253 (1.157-1.356)). Meanwhile, results from the restricted cubic spline further indicated a non-linear association between outdoor ALAN exposure during pregnancy and GDM. Generally, with the radiance of the first two trimesters of ALAN increasing to about 17.9 nW/cm2/sr1, outdoor ALAN exposure became a risk factor for GDM. However, when the radiance of ALAN reached about 40.7 nW/cm2/sr1, the continued increasing OR estimation (OR (95% CI) = 1.489 (1.223-1.814)) of outdoor ALAN changed to steady. CONCLUSION: Our findings suggested that high levels of outdoor ALAN exposure during pregnancy can be associated with an increased risk of GDM, and a non-linear relationship pattern might exist. These findings substantially augment existing evidence, positing outdoor ALAN as an emergent, modifiable risk factor for GDM.

Outdoor artificial light at night and male sperm quality: A retrospective cohort study in China.

Due to the worldwide increased rate of infertility among reproductive-age couples, there is a growing interest in the relationship between environmental stimuli and human sperm quality. While animal studies have demonstrated the detrimental effects of outdoor artificial light at night (ALAN) on sperm quality, investigations based on human data are lacking. Therefore, we conducted a retrospective cohort study involving 1991 sperm donor candidates and employed multivariate linear regression and restricted cubic spline models to quantify the association between outdoor ALAN and sperm quality. The aim was to determine whether there exists an association between exposure to outdoor ALAN and sperm quality. The study included 1991 sperm donor candidates with the following characteristics: mean [SD] age, 24.98 [4.78] years; mean [SD] BMI, 22.13 [2.60] kg/m2; mean [SD] sleep duration, 7.66 [1.07] hours/day. Outdoor ALAN exposure of study participants ranged from 0 to 100 nW/cm2/sr. Multiple regression analysis on chronic exposure (0-90 days before sperm donation) and human sperm quality revealed the following associations: for CASA primary motion parameters, every 100-unit (nW/cm2/sr) increase in chronic outdoor ALAN was associated with a change of -0.043 [95%CI: 0.073, -0.014] in Linearity (LIN), and -5.523 [95%CI: 9.100, -1.946] in Curvilinear velocity (VCL). For CASA secondary motion parameters, every 100-unit (nW/cm2/sr) increase in chronic outdoor ALAN was associated with a change of -3.873 [95%CI: 4.926, -2.748] in non-progressive motility rate (NP). Furthermore, the primary sperm quality parameter exhibited a decline of -4.740 [95%CI: 8.853, -0.628] in sperm motility rate per 100-unit (nW/cm2/sr) increase in chronic outdoor ALAN. Similar associations were also observed for acute exposure (0-9 days before sperm donation). This retrospective study suggests that poorer sperm quality is more prevalent among adult males residing in areas with higher levels of outdoor ALAN, with a particularly pronounced impact observed in males below the age of 25 years.

Bidirectional relationship between type 2 diabetes mellitus and coronary artery disease: Prospective cohort study and genetic analyses.

BACKGROUND: While type 2 diabetes mellitus (T2DM) is considered a putative causal risk factor for coronary artery disease (CAD), the intrinsic link underlying T2DM and CAD is not fully understood. We aimed to highlight the importance of integrated care targeting both diseases by investigating the phenotypic and genetic relationships between T2DM and CAD. METHODS: We evaluated phenotypic associations using data from the United Kingdom Biobank ( N = 472,050). We investigated genetic relationships by leveraging genomic data conducted in European ancestry for T2DM, with and without adjustment for body mass index (BMI) (T2DM: Ncase / Ncontrol = 74,124/824,006; T2DM adjusted for BMI [T2DM adj BMI]: Ncase / Ncontrol = 50,409/523,897) and for CAD ( Ncase / Ncontrol = 181,522/984,168). We performed additional analyses using genomic data conducted in multiancestry individuals for T2DM ( Ncase / Ncontrol = 180,834/1,159,055). RESULTS: Observational analysis suggested a bidirectional relationship between T2DM and CAD (T2DM→CAD: hazard ratio [HR] = 2.12, 95% confidence interval [CI]: 2.01-2.24; CAD→T2DM: HR = 1.72, 95% CI: 1.63-1.81). A positive overall genetic correlation between T2DM and CAD was observed ( rg = 0.39, P = 1.43 × 10 -75 ), which was largely independent of BMI (T2DM adj BMI-CAD: rg = 0.31, P = 1.20 × 10 -36 ). This was corroborated by six local signals, among which 9p21.3 showed the strongest genetic correlation. Cross-trait meta-analysis replicated 101 previously reported loci and discovered six novel pleiotropic loci. Mendelian randomization analysis supported a bidirectional causal relationship (T2DM→CAD: odds ratio [OR] = 1.13, 95% CI: 1.11-1.16; CAD→T2DM: OR = 1.12, 95% CI: 1.07-1.18), which was confirmed in multiancestry individuals (T2DM→CAD: OR = 1.13, 95% CI: 1.10-1.16; CAD→T2DM: OR = 1.08, 95% CI: 1.04-1.13). This bidirectional relationship was significantly mediated by systolic blood pressure and intake of 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors, with mediation proportions of 54.1% (95% CI: 24.9-83.4%) and 90.4% (95% CI: 29.3-151.5%), respectively. CONCLUSION: Our observational and genetic analyses demonstrated an intrinsic bidirectional relationship between T2DM and CAD and clarified the biological mechanisms underlying this relationship.

Epidemiological and Genetic Analyses of Schizophrenia and Breast Cancer.

BACKGROUND AND HYPOTHESIS: While the phenotypic association between schizophrenia and breast cancer has been observed, the underlying intrinsic link is not adequately understood. We aim to conduct a comprehensive interrogation on both phenotypic and genetic relationships between schizophrenia and breast cancer. STUDY DESIGN: We first used data from UK Biobank to evaluate a phenotypic association and performed an updated meta-analysis incorporating existing cohort studies. We then leveraged genomic data to explore the shared genetic architecture through a genome-wide cross-trait design. STUDY RESULTS: Incorporating results of our observational analysis, meta-analysis of cohort studies suggested a significantly increased incidence of breast cancer among women with schizophrenia (RR = 1.30, 95% CIs = 1.14-1.48). A positive genomic correlation between schizophrenia and overall breast cancer was observed (rg = 0.12, P = 1.80 × 10-10), consistent across ER+ (rg  = 0.10, P = 5.74 × 10-7) and ER- subtypes (rg = 0.09, P = .003). This was further corroborated by four local signals. Cross-trait meta-analysis identified 23 pleiotropic loci between schizophrenia and breast cancer, including five novel loci. Gene-based analysis revealed 27 shared genes. Mendelian randomization demonstrated a significantly increased risk of overall breast cancer (OR = 1.07, P = 4.81 × 10-10) for genetically predisposed schizophrenia, which remained robust in subgroup analysis (ER+: OR = 1.10, P = 7.26 × 10-12; ER-: OR = 1.08, P = 3.50 × 10-6). No mediation effect and reverse causality was found. CONCLUSIONS: Our study demonstrates an intrinsic link underlying schizophrenia and breast cancer, which may inform tailored screening and management of breast cancer in schizophrenia.

Observational and genetic analyses of the bidirectional relationship between depression and hypertension.

BACKGROUND: While the association between depression and hypertension has been extensively investigated, the pattern and nature of such association remain inconclusive. We sought to investigate the bidirectional relationship between depression and hypertension and its causal. METHODS: We first performed observational analyses using longitudinal data from the UK Biobank. We then performed genetic analyses leveraging summary statistics from large-scale genome-wide association studies (GWASs) conducted in European ancestry for depression and hypertension. RESULTS: Observational analysis suggested a significant bidirectional phenotypic association between depression and hypertension (Depression â†’ Hypertension: HR = 1.27, 95 % CI: 1.19, 1.36; Hypertension â†’ Depression: HR = 1.65, 95 % CI: 1.58, 1.72). Linkage disequilibrium score regression demonstrated a positive genetic correlation between the two conditions (rg=0.15, P = 5.75 × 10-10). Bidirectional two-sample Mendelian randomization (MR) suggested that genetic liability to depression was significantly associated with an increased risk of hypertension (OR = 1.27, 95 % CI: 1.12, 1.43), while the genetic liability to hypertension was not associated with the risk of depression (OR = 1.01, 95 % CI: 0.99, 1.03). Multivariate MR, after adjusting for smoking, drinking, and body mass index, further supported an independent causal effect of genetic liability to depression on hypertension risk (OR = 1.10, 95 % CI: 1.02, 1.18). LIMITATIONS: (1) interference of confounders, (2) absence of adequate statistical power, and (3) limitation to European populations. CONCLUSION: Our study indicates depression is a causal risk factor for hypertension, whereas the reverse maybe not. Findings support that prevention of depression might help in decreasing hypertension incidence.

Maternal Prenatal Depressive Symptoms and Fetal Growth During the Critical Rapid Growth Stage.

Importance: Fetal growth in the critical rapid growth stage (CRGS) before delivery, approximately between 30 to 37 gestational weeks, carries significant implications for subsequent overweight, obesity, and arterial health. Previous evidence has demonstrated the association between maternal depressive symptoms and fetal growth trajectories from early to late pregnancy, but there remains limited understanding of the association of these symptoms with the longitudinal fetal growth change within the CRGS. Objective: To investigate the association between maternal depressive symptoms and fetal growth during the CRGS before delivery. Design, Setting, and Participants: This prospective birth cohort study was conducted from January 2018 to December 2020. Volunteer pregnant women were enrolled in their first trimester of prenatal visits. Women with severe disease before pregnancy and multiple births, fetuses with congenital anomalies, and preterm or postterm births were excluded. This multicenter study was based in 13 hospitals covering 81 counties across 12 cities in Sichuan Province, China. Follow-up visits were performed at the second trimester, the third trimester, and 24 hours after delivery. The analysis was conducted from January to May 2023. Exposures: Maternal depressive symptoms, as a continuous variable, measured by the Edinburgh Postpartum Depression Scale (EPDS) at a median gestational week of 24 (range, 14 to 27) weeks of gestation. A higher score on the EPDS indicates worse depressive symptoms. Main Outcomes and Measures: The main outcomes included ultrasonography-measured biparietal diameter (BPD), femur length (FL), and abdominal circumference (AC), along with calculated estimated fetal weight (EFW). These parameters were evaluated longitudinally at a median gestational week of 30 (range, 28 to 32) and 37 (range, 35 to 39) weeks. Linear mixed models were used to estimate the associations between maternal depressive symptoms and fetal growth parameters. Results: A total of 2676 mother-offspring dyads were included, in which the mean (SD) age of mothers was 28.0 (4.4) years, and 1294 (48.4%) of the offspring were female. The median (IQR) maternal EPDS score was 5.0 (4.0 to 9.0). After adjustment for confounders, a significant correlation was found between a higher score of depressive symptoms in mothers and a slower rate of fetal growth across FL (ß = -0.40; 95% CI, -0.58 to -0.22), AC (ß = -1.97; 95% CI, -2.90 to -1.03), and EFW (ß = -50.11; 95% CI, -68.46 to -31.75). These associations were stronger in female fetuses or those with better family socioeconomic conditions. Conclusions and Relevance: In this prospective cohort study, maternal depressive symptoms were associated with slower fetal growth rate in the CRGS before delivery. Early screening for depressive disorders in pregnant women appears to be essential for fetal growth and later health.

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.

Additional Evidence for the Relationship Between Type 2 Diabetes and Stroke Through Observational and Genetic Analyses.

While type 2 diabetes mellitus (T2DM) is commonly considered a putative causal risk factor for stroke, the effect of stroke on T2DM remains unclear. The intrinsic link underlying T2DM and stroke has not been thoroughly examined. We aimed to evaluate the phenotypic and genetic relationships underlying T2DM and stroke. We evaluated phenotypic associations using data from the UK Biobank (N = 472,050). We then investigated genetic relationships by leveraging genomic data in European ancestry for T2DM, with and without adjusting (adj) for BMI (T2DM: n = 74,124 case subjects/824,006 control subjects; T2DMadjBMI: n = 50,409 case subjects/523,897 control subjects), and for stroke (n = 73,652 case subjects/1,234,808 control subjects). We performed additional analyses using genomic data in East Asian ancestry for T2DM (n = 77,418 case subjects/356,122 control subjects) and for stroke (n = 27,413 case subjects/237,242 control subjects). Observational analyses suggested a significantly increased hazard of stroke among individuals with T2DM (hazard ratio 2.28 [95% CI 1.97-2.64]), but a slightly increased hazard of T2DM among individuals with stroke (1.22 [1.03-1.45]) which attenuated to 1.14 (0.96-1.36) in sensitivity analysis. A positive global T2DM-stroke genetic correlation was observed (rg = 0.35; P = 1.46 × 10-27), largely independent of BMI (T2DMadjBMI-stroke: rg = 0.27; P = 3.59 × 10-13). This was further corroborated by 38 shared independent loci and 161 shared expression-trait associations. Mendelian randomization analyses suggested a putative causal effect of T2DM on stroke in Europeans (odds ratio 1.07 [95% CI 1.06-1.09]), which remained significant in East Asians (1.03 [1.01-1.06]). Conversely, despite a putative causal effect of stroke on T2DM also observed in Europeans (1.21 [1.07-1.37]), it attenuated to 1.04 (0.91-1.19) in East Asians. Our study provides additional evidence to underscore the significant relationship between T2DM and stroke.

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.

Migraine, chronic kidney disease and kidney function: observational and genetic analyses.

Epidemiological studies demonstrate an association between migraine and chronic kidney disease (CKD), while the genetic basis underlying the phenotypic association has not been investigated. We aimed to help avoid unnecessary interventions in individuals with migraine through the investigation of phenotypic and genetic relationships underlying migraine, CKD, and kidney function. We first evaluated phenotypic associations using observational data from UK Biobank (N = 255,896). We then investigated genetic relationships leveraging genomic data in European ancestry for migraine (Ncase/Ncontrol = 48,975/540,381), CKD (Ncase/Ncontrol = 41,395/439,303), and two traits of kidney function (estimated glomerular filtration rate [eGFR, N = 567,460] and urinary albumin-to-creatinine ratio [UACR, N = 547,361]). Observational analyses suggested no significant association of migraine with the risk of CKD (HR = 1.13, 95% CI = 0.85-1.50). While we did not find any global genetic correlation in general, we identified four specific genomic regions showing significant for migraine with eGFR. Cross-trait meta-analysis identified one candidate causal variant (rs1047891) underlying migraine, CKD, and kidney function. Transcriptome-wide association study detected 28 shared expression-trait associations between migraine and kidney function. Mendelian randomization analysis suggested no causal effect of migraine on CKD (OR = 1.03, 95% CI = 0.98-1.09; P = 0.28). Despite a putative causal effect of migraine on an increased level of UACR (log-scale-beta = 0.02, 95% CI = 0.01-0.04; P = 1.92 × 10-3), it attenuated to null when accounting for both correlated and uncorrelated pleiotropy. Our work does not find evidence supporting a causal association between migraine and CKD. However, our study highlights significant biological pleiotropy between migraine and kidney function. The value of a migraine prophylactic treatment for reducing future CKD in people with migraine is likely limited.

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.

Epidemiological and genetic evidence for the relationship between ABO blood group and human cancer.

To comprehensively evaluate the etiological role of ABO blood group in human cancer, we conducted a large-scale meta-analysis of 127 publications totaling 20 million participants including 231 737 patients of 20 cancers, supplemented by genetic evidence. Effects of A, AB and B groups on cancer risk were investigated by respectively comparing with O group and their combined counterparts, and subgroup analysis by ethnicity was conducted for O-referent models. For cancer categories, A group increased risk of cancers of oral cavity and nasopharynx, digestive and female genital organs, while both AB and B groups showed associations with cancers of digestive and female genital organs. For individual cancers, A group significantly increased the risk of nine cancers including oral cavity (OR = 1.17, P = .013), stomach (OR = 1.19, P = 3.90 × 10-15 ), pancreas (OR = 1.33, P = 9.89 × 10-33 ), colorectum (OR = 1.09, P = .001), liver (OR = 1.23, P = .011), ovary (OR = 1.13, P = .001), cervix (OR = 1.17, P = .025), bladder (OR = 1.12, P = .025) and breast (OR = 1.06, P = .043). AB group showed associations with only three cancers: stomach (OR = 1.10, P = .007), pancreas (OR = 1.21, P = .001) and ovary (OR = 1.28, P = .006). B group, except for shared associations with A group on pancreas (OR = 1.20, P = 2.27 × 10-5 ) and cervix cancers (OR = 1.13, P = .011), had two distinct associations with esophagus (OR = 1.17, P = .002) and nonmelanoma skin cancers (OR = 0.96, P = .017). Ethnicity-specific analyses revealed the notable effects of non-O groups on pancreatic cancer both in Caucasians and Asians. In genetic analysis, four SNPs were associated with the risk of pancreatic cancer, with rs505922 corresponding to O group showing the strongest protective effect (P = 1.16 × 10-23 ). Our study provided comprehensive evidence of ABO blood group associated with cancers and highlighted its carcinogenic role.

Temporal relationship between sleep duration and obesity among Chinese Han people and ethnic minorities.

BACKGROUND: No studies have assessed the association between sleep duration and obesity in Chinese ethnic minorities. Whether the relationship between sleep duration and obesity is different between Chinese Han people and Chinese ethnic minorities remains unclear. The study aimed to explore the relationship between sleep duration and obesity among Chinese Han people and Chinese ethnic minorities. METHODS: We applied data from the Guizhou Population Health Cohort Study (GPHCS), which 9,280 participants were recruited in the baseline survey from 2010 to 2012, and 8,163 completed the follow-up survey from 2016 to 2020. A total of 5,096 participants (3,188 Han Chinese and 1,908 ethnic minorities) were included in the ultimate analysis. Information on sleep duration (total 24-hour sleep time), body mass index (BMI), and waist circumference (WC) was collected at the baseline and follow-up survey, respectively. Cross-lagged panel analyses were conducted to explore the temporal relationship between sleep duration and obesity for Han people and ethnic minorities. RESULTS: For Han people, the results from cross-lagged panel analyses indicated that baseline sleep duration was significantly associated with follow-up BMI (ßBMI = -0.041, 95% CIBMI: -0.072 ~ -0.009) and follow-up WC (ßWC = -0.070, 95%CIWC: -0.103 ~ -0.038), but baseline BMI (ßBMI = -0.016, 95% CIBMI: -0.050 ~ 0.018) and baseline WC (ßWC = -0.019, 95% CIWC: -0.053 ~ 0.016) were not associated with follow-up sleep duration. In addition, the relationship between baseline sleep duration and follow-up BMI was gender-specific and significant only in the Han people female (ßBMI = -0.047, 95% CIBMI: -0.090 ~ -0.003) but not in the Han people male (ßBMI = -0.029, 95% CIBMI: -0.075 ~ 0.016). For ethnic minorities, the results indicated that there was no relationship between sleep duration and obesity at all, either from sleep duration to obesity (ßBMI = 0.028, 95%CIBMI: -0.012 ~ 0.068; ßWC = 0.020, 95%CIWC: -0.022 ~ 0.062), or from obesity to sleep duration (ßBMI = -0.022, 95%CIBMI: -0.067 ~ 0.022; ßWC = -0.042, 95%CIWC: -0.087 ~ 0.003). CONCLUSION: The relationship pattern between sleep duration and obesity across Han people and ethnic minorities is different. Future sleep-aimed overweight and obesity intervention should be conducted according to population characteristics.

Using human genetics to understand the epidemiological association between obesity, serum urate, and gout.

OBJECTIVES: We aimed to clarify the genetic overlaps underlying obesity-related traits, serum urate, and gout. METHODS: We conducted a comprehensive genome-wide cross-trait analysis to identify genetic correlation, pleiotropic loci, and causal relationships between obesity (the exposure variable), gout (the primary outcome) and serum urate (the secondary outcome). Summary statistics were collected from the hitherto largest genome-wide association studies conducted for BMI (N = 806 834), waist-to-hip ratio (WHR; N = 697 734), WHR adjusted for BMI (WHRadjBMI; N = 694 649), serum urate (N = 288 649), and gout (Ncases = 13 179 and Ncontrols = 750 634). RESULTS: Positive overall genetic correlations were observed for BMI (rg = 0.27, P = 6.62 × 10-7), WHR (rg = 0.22, P = 6.26 × 10-7) and WHRadjBMI (rg = 0.07, P = 6.08 × 10-3) with gout. Partitioning the whole genome into 1703 LD (linkage disequilibrium)-independent regions, a significant local signal at 4q22 was identified for BMI and gout. The global and local shared genetic basis was further strengthened by the multiple pleiotropic loci identified in the cross-phenotype association study, multiple shared gene-tissue pairs observed by Transcriptome-wide association studies, as well as causal relationships demonstrated by Mendelian randomization [BMI-gout: OR (odds ratio) = 1.66, 95% CI = 1.45, 1.88; WHR-gout: OR = 1.57, 95% CI = 1.37, 1.81]. Replacing the binary disease status of gout with its latent pathological measure, serum urate, a similar pattern of correlation, pleiotropy and causality was observed with even more pronounced magnitude and significance. CONCLUSION: Our comprehensive genome-wide cross-trait analysis demonstrates a shared genetic basis and pleiotropic loci, as well as a causal relationship between obesity, serum urate, and gout, highlighting an intrinsic link underlying these complex traits.