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.

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Objective: To explore the risk factors for developing chronic pulmonary heart disease in patients with pneumoconiosis. Methods: The medical records of pneumoconiosis patients admitted to an occupational disease hospital in Sichuan Province between January 2012 and November 2021 were collected. Kaplan-Meier (K-M) method, or product-limit method, was used to plot the incidence curves of pulmonary heart disease in the pneumoconiosis patients. Cox proportional hazard regression model was used to analyze the influencing factors associated with chronic pulmonary heart disease in patients with pneumoconiosis. Results: A total of 885 pneumoconiosis patients were included in this study. The follow-up time was 12 to 115 months and the median follow-up time was 43 months. A total of 138 patients developed chronic pulmonary heart disease and the incidence density of pulmonary heart disease was 38.50/1000 person-years. Multivariate Cox proportional hazard regression analysis showed that the influencing factors of pneumoconiosis inpatients developing chronic pulmonary heart disease included the following, being 50 and older (hazard ratio [HR]=1.85, 95% confidence interval [CI]: 1.25-2.74), stage Ⅲ pneumoconiosis (HR=2.43, 95% CI: 1.48-4.01), resting heart rate≥100 beats/min (HR=2.62, 95% CI: 1.63-4.21), the complication of chronic obstructive pulmonary disease (COPD) (HR=4.52, 95% CI: 2.12-9.63), underweight (HR=2.40, 95% CI: 1.48-3.87), overweight and obesity (HR=0.54, 95% CI: 0.34-0.86), and triacylglycerol (TG) (HR=0.69, 95% CI: 0.49-0.99). Conclusion: Old age, stage Ⅲ pneumoconiosis, high resting heart rate, low BMI, and the complication of COPD are risk factors for chronic pulmonary heart disease in pneumoconiosis patients, while overweight and obesity and TG are protective factors. Early identification of the risk factors and the adoption of the corresponding prevention measures are the key to preventing chronic pulmonary heart disease in patients with pneumoconiosis.

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.

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.

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.

Design of a high-power collimating optical system based on Fresnel lenses.

In light-emitting diode (LED) illumination (e.g., LED maritime lighting for ships), creating a uniform light environment for optical systems is an important challenge. In this study, we present a high-power collimating system based on Fresnel lenses, which allows high-brightness LED illumination in the earlier-mentioned remote distance. The work presented in this article focuses on improving the power, compacting the optical structure, and promoting the brightness of the spot. To prove the claims, the system with a total power of 1 kW is designed. The system consists of a 27 W LED array, a freeform surface lens array, and a confocal Fresnel lens array. In comparison with the traditional optical system, the optical structure shortens from 390 to 120 mm, and the divergent angle decreases from 3° to 2 ° $$ {}^{{}^{\circ}} $$ . Meanwhile, the illuminance of the system is obtained as high as 230 lx at the near field of 200 m and 3.0 lx at the far field of 1.5 nautical miles. This new method provides a practical and effective way to solve the problem of low power, insufficient illuminance, and long optical structure for LED array illumination, which is suitable for remote illumination and guidance of ships.

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.

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.

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.

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.

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.

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.

Prevalence of suicide ideation, self-harm, and suicide among Chinese patients with schizophrenia: a systematic review and meta-analysis.

Aims: Suicide ideation, self-harm, and suicide are common in patients with schizophrenia, but the reported prevalence vary largely across studies. Improved prevalence estimates and identification of moderators of the above self-directed violence are needed to enhance recognition and care, and to guide future management and research. This systematic review aims to estimate the pooled prevalence and identify moderators of suicide ideation, self-harm, and suicide among patients diagnosed with schizophrenia in China. Methods: Relevant articles published until September 23, 2021, were searched using PubMed, EBSCO, Web of Science, Embase, Science Direct, CNKI, CBM, VIP, and Wanfang databases. Eligible studies published in English or Chinese which reported the prevalence of suicide ideation, self-harm, or suicide among Chinese patients with schizophrenia were collected. All studies passed a quality evaluation. This systematic review was registered with PROSPERO (registration number CRD42020222338). PRISMA guidelines were used in extracting and reporting data. Random-effects meta-analyses were generated using the meta package in R. Results: A total of 40 studies were identified, 20 of which were evaluated as high-quality studies. Based on these studies, the prevalence of lifetime suicide ideation was 19.22% (95% CI: 7.57-34.50%), prevalence of suicide ideation at the time of investigation was 18.06% (95% CI: 6.49-33.67%), prevalence of lifetime self-harm was 15.77% (95% CI: 12.51-19.33%), and prevalence of suicide was 1.49% (95% CI: 0.00-7.95%). Multivariate meta-regression analysis revealed that age (ß = - 0.1517, p = 0.0006) and dependency ratio (ß = 0.0113, p < 0.0001) were associated with the lifetime prevalence of self-harm. Study assessment score (ß = 0.2668, p < 0.0001) and dependency ratio (ß = 0.0050, p = 0.0145) were associated with the lifetime prevalence of suicide ideation. Results of the spatial analysis showed that the prevalence of self-directed violence varied greatly across different provinces. Conclusion: This systematic review provides estimates of the prevalence of self-directed violence among Chinese patients with schizophrenia and explores its moderators and spatial patterns. Findings also have important implications for allocating prevention and intervention resources to targeted high-risk populations in high prevalence areas.

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.

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.

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.

Multisite Radiotherapy Combined With Tislelizumab for Metastatic Castration-Resistant Prostate Cancer With Second-Line and Above Therapy Failure: Study Protocol for an Open-Label, Single-Arm, Phase Ib/II Study.

Background: Tislelizumab combined with radiotherapy as a salvage treatment for patients with end-stage metastatic castration-resistant prostate cancer (mCRPC) is not reported. This study aimed to describe a protocol to evaluate the safety and efficacy of multisite radiotherapy combined with tislelizumab as a salvage therapy for mCRPC in patients who had at least one second-line treatment failure. Methods: The study included patients with mCRPC who had at least one lesion suitable for radiotherapy and failed androgen deprivation therapy (ADT), followed by at least one novel second-line endocrine therapy. All patients received tislelizumab monotherapy induction therapy for two cycles, then combined with multisite radiotherapy for one cycle, followed by tislelizumab maintenance therapy, until either disease progressed or the patient developed unacceptable toxicity. Radiation methods and lesions were individually selected according to the specified protocol. Primary endpoints included safety and objective response rate. Secondary endpoints included prostate-specific antigen (PSA) response rate, disease control rate, overall survival, radiographic progression-free survival (rPFS), and biochemical progression-free survival (bPFS). Furthermore, the exploratory endpoints included the identification of the predictive biomarkers and exploration of the correlation between biomarkers and the tumor response to the combined regimen. Discussion: This study included three treatment stages to evaluate the efficacy of immunotherapy and the combination of immunotherapy and radiotherapy for patients with mCRPC who have had at least second-line treatment failure. Additionally, radiation-related and immune-related early and late toxicities were determined, respectively. Furthermore, the study also aimed to identify the predictive biomarkers associated with immunotherapy for treating mCRPC. Trial Registration: https://www.chictr.org.cn/showproj.aspx?proj=126359, identifier ChiCTR2100046212.

Simultaneous and sensitive detection of two pathogenic genes of thrombotic diseases using SPRi sensor with one-step fixation probe by a poly-adenine oligonucleotide approach.

Single-base mutations of Factor V Leiden G1691A and Prothrombin gene G20210A are the main genetic risk factors for inherited thrombotic tendency. The establishment for rapid and efficient detection method is of great significance to the prevention of venous thrombosis. In this work, a multiplexed, highly sensitive and regenerable surface plasmon resonance imaging (SPRi) sensor is described to identify and detect the two pathogenic genes by fixing probes in one-step. The probes are fixed by ployA, which is a simpler, faster and lower cost modification method compared with traditional thiol (-SH). PolyA-DNA-AuNPs is used to amplify the signal to improve sensitivity. The detection limit of the sensor is 8 pM, and it has a wide dynamic range between 8 pM and 100 nM and a good linear relationship between 8 pM to 50 pM. The equilibrium dissociation constant (KD) of 3.0 (± 0.3) pM indicates a high binding capacity. Based on the advantages of high-throughput detection, the SPRi chip can simultaneously identify and detect two genes related to thrombotic Diseases. In addition, more than 90% signal intensity can still be obtained on the surface of the chip after being regenerated of 25 times, indicating that this SPRi sensor has good stability and reproducibility. The established SPRi sensor has the advantages of high-throughput, high-sensitivity, label-free and no need for amplification, which is expected to become an effective technical means for real-time online detection of gene point mutations, and can be extended to detect and quantify a wider range of DNA mutation diseases.

Raman spectrum classification based on transfer learning by a convolutional neural network: Application to pesticide detection.

Pesticide detection is of tremendous importance in agriculture, and Raman spectroscopy/Surface-Enhanced Raman Scattering (SERS) has proven extremely effective as a stand-alone method to detect pesticide residues. Machine learning may be able to automate such detection, but conventional algorithms require a complete database of Raman spectra, which is not feasible. To bypass this problem, the present study describes a transfer learning method that improves the algorithm's accuracy and speed to extract features and classify Raman spectra. The transfer learning model described here was developed through the following steps: (1) the classification model was pre-trained using an open-source Raman spectroscopy database; (2) the feature extraction layer was saved after training; and (3) the training model for the Raman spectroscopy database was re-established while using self-tested pesticides and keeping the feature extraction layer unchanged. Three models were evaluated with or without transfer learning: CNN-1D, Resnet-1D, and Inception-1D, and they have improved the accuracy of spectrum classification by 6%, 2%, and 3%, with reduced training time and increased curve smoothness. These results suggest that transfer learning can improve the feature extraction capability and therefore accuracy of Raman spectroscopy models, expanding the range of Raman-based applications where transfer learning model can be used to identify the spectra of different substances.