Exploring antidiabetic drug targets as potential disease-modifying agents in osteoarthritis.

BACKGROUND: Osteoarthritis is a leading cause of disability, and disease-modifying osteoarthritis drugs (DMOADs) could represent a pivotal advancement in treatment. Identifying the potential of antidiabetic medications as DMOADs could impact patient care significantly. METHODS: We designed a comprehensive analysis pipeline involving two-sample Mendelian Randomization (MR) (genetic proxies for antidiabetic drug targets), summary-based MR (SMR) (for mRNA), and colocalisation (for drug-target genes) to assess their causal relationship with 12 osteoarthritis phenotypes. Summary statistics from the largest genome-wide association meta-analysis (GWAS) of osteoarthritis and gene expression data from the eQTLGen consortium were utilised. FINDINGS: Seven out of eight major types of clinical antidiabetic medications were identified, resulting in fourteen potential drug targets. Sulfonylurea targets ABCC8/KCNJ11 were associated with increased osteoarthritis risk at any site (odds ratio (OR): 2.07, 95% confidence interval (CI): 1.50-2.84, P < 3 × 10-4), while PPARG, influenced by thiazolidinediones (TZDs), was associated with decreased risk of hand (OR: 0.61, 95% CI: 0.48-0.76, P < 3 × 10-4), finger (OR: 0.50, 95% CI: 0.35-0.73, P < 3 × 10-4), and thumb (OR: 0.49, 95% CI: 0.34-0.71, P < 3 × 10-4) osteoarthritis. Metformin and GLP1-RA, targeting GPD1 and GLP1R respectively, were associated with reduced risk of knee and finger osteoarthritis. In the SMR analyses, gene expression of KCNJ11, GANAB, ABCA1, and GSTP1, targeted by antidiabetic drugs, was significantly linked to at least one osteoarthritis phenotype and was replicated across at least two gene expression datasets. Additionally, increased KCNJ11 expression was related to decreased osteoarthritis risk and co-localised with at least one osteoarthritis phenotype. INTERPRETATION: Our findings suggest a potential therapeutic role for antidiabetic drugs in treating osteoarthritis. The results indicate that certain antidiabetic drug targets may modify disease progression, with implications for developing targeted DMOADs. FUNDING: This study was funded by the Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant (2022), the Shanghai Municipal Health Commission Health Industry Clinical Research Project (Grant No. 20224Y0139), Beijing Natural Science Foundation (Grant No. 7244458), and the Postdoctoral Fellowship Program (Grade C) of China Postdoctoral Science Foundation (Grant No. GZC20230130).

Identification of novel therapeutic targets for chronic kidney disease and kidney function by integrating multi-omics proteome with transcriptome.

BACKGROUND: Chronic kidney disease (CKD) is a progressive disease for which there is no effective cure. We aimed to identify potential drug targets for CKD and kidney function by integrating plasma proteome and transcriptome. METHODS: We designed a comprehensive analysis pipeline involving two-sample Mendelian randomization (MR) (for proteins), summary-based MR (SMR) (for mRNA), and colocalization (for coding genes) to identify potential multi-omics biomarkers for CKD and combined the protein-protein interaction, Gene Ontology (GO), and single-cell annotation to explore the potential biological roles. The outcomes included CKD, extensive kidney function phenotypes, and different CKD clinical types (IgA nephropathy, chronic glomerulonephritis, chronic tubulointerstitial nephritis, membranous nephropathy, nephrotic syndrome, and diabetic nephropathy). RESULTS: Leveraging pQTLs of 3032 proteins from 3 large-scale GWASs and corresponding blood- and tissue-specific eQTLs, we identified 32 proteins associated with CKD, which were validated across diverse CKD datasets, kidney function indicators, and clinical types. Notably, 12 proteins with prior MR support, including fibroblast growth factor 5 (FGF5), isopentenyl-diphosphate delta-isomerase 2 (IDI2), inhibin beta C chain (INHBC), butyrophilin subfamily 3 member A2 (BTN3A2), BTN3A3, uromodulin (UMOD), complement component 4A (C4a), C4b, centrosomal protein of 170 kDa (CEP170), serologically defined colon cancer antigen 8 (SDCCAG8), MHC class I polypeptide-related sequence B (MICB), and liver-expressed antimicrobial peptide 2 (LEAP2), were confirmed. To our knowledge, 20 novel causal proteins have not been previously reported. Five novel proteins, namely, GCKR (OR 1.17, 95% CI 1.10-1.24), IGFBP-5 (OR 0.43, 95% CI 0.29-0.62), sRAGE (OR 1.14, 95% CI 1.07-1.22), GNPTG (OR 0.90, 95% CI 0.86-0.95), and YOD1 (OR 1.39, 95% CI 1.18-1.64,) passed the MR, SMR, and colocalization analysis. The other 15 proteins were also candidate targets (GATM, AIF1L, DQA2, PFKFB2, NFATC1, activin AC, Apo A-IV, MFAP4, DJC10, C2CD2L, TCEA2, HLA-E, PLD3, AIF1, and GMPR1). These proteins interact with each other, and their coding genes were mainly enrichment in immunity-related pathways or presented specificity across tissues, kidney-related tissue cells, and kidney single cells. CONCLUSIONS: Our integrated analysis of plasma proteome and transcriptome data identifies 32 potential therapeutic targets for CKD, kidney function, and specific CKD clinical types, offering potential targets for the development of novel immunotherapies, combination therapies, or targeted interventions.

The effects of Mediterranean diet on cardiovascular risk factors, glycemic control and weight loss in patients with type 2 diabetes: a meta-analysis.

To explore the impact of the Mediterranean diet on cardiovascular risk factors, glycemic control and weight loss in patients with type 2 diabetes(T2D) by a meta-analysis of randomized controlled trials (RCTs). We systematically searched PubMed, Cochrance Library, EMBASE and four Chinese databases to identify RCTs that compared the Mediterranean diet with control diets in patients with T2D up to December 2021. The Risk of Bias of the included studies was assessed using the version 2 of the Cochrane risk-of-bias tools for randomized trials (ROB 2). Seven RCTs with 1371 patients met the eligibility criteria and entered into the meta-analysis. Compared to control diets, the beneficial effects of Mediterranean diet were not statistically significant in high-density lipoprotein (MD = 2.33; 95% CI: -0.27 to 4.92), low-density lipoprotein (MD = -2.34; 95% CI -5.67 to 0.99) and total cholesterol (MD = 2.60; 95% CI: -0.95 to 6.15). But Mediterranean diet led to reduce the level of diastolic blood pressure (MD = -1.20; 95% CI: -2.21 to -0.19) and systolic blood pressure (MD = -4.17; 95% CI: -7.12 to -1.22). Meanwhile, Mediterranean diet showed beneficial effects in glycemic control (HbA1[%]: MD = -0.39, 95% CI: -0.58 to -0.20; fasting plasma glucose: MD = -15.12, 95% CI: -24.69 to -5.55) and weight loss (BMI: MD = -0.71, 95% CI: -1.30 to -0.78; WC: MD = -1.69; 95% CI: -3.35 to -0.02) compared to the control diets. The meta-analysis presented evidence supporting the beneficial effects of the Mediterranean diet on blood pressure, glycemic control, and weight loss. However, the impact of the Mediterranean diet on the lipid profile was not found to be significant, warranting further verification. This Meta-analysis was registered on the INPLASY website (Registration number: INPLASY 202160096).

Association between type 1 diabetes and systemic lupus erythematosus: a Mendelian randomization study.

OBJECTIVES: Observational studies have shown that there is a bidirectional relationship between type 1 diabetes (T1D) and systemic lupus erythematosus (SLE); the causality of this association remains elusive and may be affected by confusion and reverse causality. There is also a lack of large-scale randomized controlled trials to verify. Therefore, this Mendelian randomization (MR) study aimed to investigate the causal association between T1D and SLE. METHODS: We aggregated data using publicly available genome-wide association studies (GWAS), all from European populations. Select independent (R2 < 0.001) and closely related to exposure (P < 5 × 10-8) as instrumental variables (IVs). The inverse-variance weighted (IVW) method was used as the primary method. We also used MR-Egger, the weighted median method, MR-Robust, MR-Lasso, and other methods leveraged as supplements. RESULTS: T1D had a positive causal association with SLE (IVW, odds ratio [OR] = 1.358, 95% confidence interval [CI], 1.205 - 1.530; P < 0.001). The causal association was verified in an independent validation set (IVW, OR = 1.137, 95% CI, 1.033 - 1.251; P = 0.001). SLE had a positive causal association with T1D (IVW, OR = 1.108, 95% CI, 1.074 - 1.144; P < 0.001). The causal association was verified in an independent validation set (IVW, OR = 1.085, 95% CI, 1.046 - 1.127; P < 0.001). These results have also been verified by sensitivity analysis. CONCLUSION: The MR analysis results indicated a causal association between T1D and SLE. Therefore, further research is needed to clarify the potential biological mechanism between T1D and SLE. Key Points • Observational studies have shown that there is a bidirectional relationship between T1D and SLE. • We evaluated causal effects between T1D and SLE by Mendelian randomization analyses. • The MR analysis results indicated a causal association between T1D and SLE.

Personalized prediction for multiple chronic diseases by developing the multi-task Cox learning model.

Personalized prediction of chronic diseases is crucial for reducing the disease burden. However, previous studies on chronic diseases have not adequately considered the relationship between chronic diseases. To explore the patient-wise risk of multiple chronic diseases, we developed a multitask learning Cox (MTL-Cox) model for personalized prediction of nine typical chronic diseases on the UK Biobank dataset. MTL-Cox employs a multitask learning framework to train semiparametric multivariable Cox models. To comprehensively estimate the performance of the MTL-Cox model, we measured it via five commonly used survival analysis metrics: concordance index, area under the curve (AUC), specificity, sensitivity, and Youden index. In addition, we verified the validity of the MTL-Cox model framework in the Weihai physical examination dataset, from Shandong province, China. The MTL-Cox model achieved a statistically significant (p<0.05) improvement in results compared with competing methods in the evaluation metrics of the concordance index, AUC, sensitivity, and Youden index using the paired-sample Wilcoxon signed-rank test. In particular, the MTL-Cox model improved prediction accuracy by up to 12% compared to other models. We also applied the MTL-Cox model to rank the absolute risk of nine chronic diseases in patients on the UK Biobank dataset. This was the first known study to use the multitask learning-based Cox model to predict the personalized risk of the nine chronic diseases. The study can contribute to early screening, personalized risk ranking, and diagnosing of chronic diseases.

Quantifying substantial carcinogenesis of genetic and environmental factors from measurement error in the number of stem cell divisions.

BACKGROUND: The relative contributions of genetic and environmental factors versus unavoidable stochastic risk factors to the variation in cancer risk among tissues have become a widely-discussed topic. Some claim that the stochastic effects of DNA replication are mainly responsible, others believe that cancer risk is heavily affected by environmental and hereditary factors. Some of these studies made evidence from the correlation analysis between the lifetime number of stem cell divisions within each tissue and tissue-specific lifetime cancer risk. However, they did not consider the measurement error in the estimated number of stem cell divisions, which is caused by the exposure to different levels of genetic and environmental factors. This will obscure the authentic contribution of environmental or inherited factors. METHODS: In this study, we proposed two distinct modeling strategies, which integrate the measurement error model with the prevailing model of carcinogenesis to quantitatively evaluate the contribution of hereditary and environmental factors to cancer development. Then, we applied the proposed strategies to cancer data from 423 registries in 68 different countries (global-wide), 125 registries across China (national-wide of China), and 139 counties in Shandong province (Shandong provincial, China), respectively. RESULTS: The results suggest that the contribution of genetic and environmental factors is at least 92% to the variation in cancer risk among 17 tissues. Moreover, mutations occurring in progenitor cells and differentiated cells are less likely to be accumulated enough for cancer to occur, and the carcinogenesis is more likely to originate from stem cells. Except for medulloblastoma, the contribution of genetic and environmental factors to the risk of other 16 organ-specific cancers are all more than 60%. CONCLUSIONS: This work provides additional evidence that genetic and environmental factors play leading roles in cancer development. Therefore, the identification of modifiable environmental and hereditary risk factors for each cancer is highly recommended, and primary prevention in early life-course should be the major focus of cancer prevention.

Causal relationship between type 1 diabetes and hypothyroidism: A Mendelian randomization study.

OBJECTIVES: Although an association between type 1 diabetes (T1D) and hypothyroidism has been found in multiple observational studies, whether T1D plays a causal role in the development of hypothyroidism remains uncertain. Therefore, this Mendelian randomization (MR) study aimed to investigate the causal association between T1D and hypothyroidism. METHODS: Independent single-nucleotide polymorphisms associated with T1D with genome-wide significance were selected as instrumental variables from a large genome-wide association study (GWAS) of T1D. Hypothyroidism GWAS summary statistics were obtained from the Thyroidomics Consortium. The inverse-variance weighted (IVW) method was used as the primary analysis for estimating the effect of the exposure on the outcome. We also used MR-Egger, the weighted median method, MR-Robust, and other methods to confirm the results. RESULTS: T1D had a positive causal association with hypothyroidism [IVW, odds ratio (OR) = 1.083, 95% confidence interval (CI), 1.046-1.122; p < .001]. MR-Egger regression indicated that directional pleiotropy did not bias the result (intercept = 0.006; p = .295). The causal association was verified in an independent validation set (IVW, OR = 1.099, 95% CI, 1.018-1.186; p = .017). The results were robust according to various MR methods, and the results of the reverse MR analysis did not support reverse causation (p > .05). CONCLUSIONS: The MR analysis results indicated a causal association between T1D and hypothyroidism. Therefore, it is recommended that patients with T1D undergo thyroid function tests regularly to minimize the risk of undiagnosed hypothyroidism among young patients with T1D.

Identification of novel proteins associated with movement-related adverse antipsychotic effects by integrating GWAS data and human brain proteomes.

Genome-wide association studies (GWAS) have identified some variants for movement-related adverse antipsychotic effects (MAAE), while how these variants confer MAAE remains unclear. We used the probabilistic Mendelian randomization (PMR) method to identify candidate proteins for MAAE by integrating MAAE GWASs and protein quantitative trait loci (pQTL) data. An independent pQTL data from the Banner project and brain-derived eQTL data were used to perform confirmatory PMR. A total of 56 proteins were identified as candidate targets for MAAE after false discovery rates (FDR) correction, such as GRIN2B, ADRA1A, and PED4B. 12 genes were replicated in the confirmatory PMR, and 18 genes had consistent evidence at the transcript level. Furthermore, we investigated the associations between candidate proteins and the motor symptoms of Parkinson's disease (PD). There were 24, 38, and 10 candidate proteins that were significantly associated with PD, PD motor subtypes, and PD motor progression, respectively. Enrichment analysis identified 34 GO terms and 17 pathways that may be involved in MAAE, such as glutamatergic synapse, glutamate receptor complex, and GABAergic synapse. Our study identified multiple candidate genes and pathways that were associated with MAAE, providing new insights into the biological mechanism of MAAE and targets for further mechanistic and therapeutic studies.

Exposure to various ambient air pollutants increases the risk of venous thromboembolism: A cohort study in UK Biobank.

Epidemiological evidence for the association between air pollutants exposure and venous thromboembolism (VTE) remains controversial. In this study, a total of 389,659 participants from the UK Biobank who were free of VTE in 2010 were included, and the annual mean concentrations of air pollutants near where participants lived were collected. During a median follow-up period of 8.25 years, 4986 VTEs were determined from the hospital admission records. The Cox proportional hazard model was used to examine the association between air pollutants and VTE. We firstly investigated the associations between air pollutants concentration and VTE and found only NO2 and NO increased VTE risk (P < 0.05). We further calculated the product of air pollutant concentrations and outdoor time to measure personal daily cumulative exposure and found that the hazard rates (HRs) of VTE for a 50-µg/m3∗day increase in daily cumulative exposure to PM10, PM2.5, PM2.5-10, NO, and NO2 were 1.08 (1.05-1.12), 1.16 (1.09-1.24), 1.23 (1.11-1.37), 1.04 (1.01-1.06), and 1.05 (1.03-1.08), respectively. To measure joint exposure to various air pollutants and its effect on VTE, we created a weighted air pollutants exposure score (APES) and found a dose-response relationship between APES and VTE risk (P < 0.001 for trend). Compared with participants in the lowest quintile of APES, the HRs of VTE were 1.19 (1.08-1.30) for those within the highest quintile groups. Furthermore, we also found the effect of air pollutants on VTE was statistically significant only in individuals with low-middle VTE genetic risk score (GRS) (P < 0.05), but not in the high VTE GRS groups (P > 0.05). Our findings suggest that exposure to various air pollutants including PM2.5, PM2.5-10, PM10, NO, and NO2, either individually or jointly, were associated with an increased risk of VTE in a dose-response pattern. Our study highlights the importance of a comprehensive assessment of various air pollutants in VTE prevention.

Effects of antipsychotics on triglyceride trajectories and its implications in CVD: A longitudinal cohort study.

BACKGROUND: Although the association between short-term antipsychotics exposure and triglycerides (TG) levels has been confirmed, the effects of long-term antipsychotics exposure on TG trajectories and its implications in cardiovascular disease (CVD) remains largely unknown. METHODS: A total of 39,988 participants with at least 3 TG measurements between January 2014 and February 2021 were included in this longitudinal study, with a median follow-up was 4.48 years. A latent class growth mixed model (LCGMM) was used to identify TG trajectories. Based on the LCGMM parameters, we calculated the area under the curve (AUC) and estimated the effect of antipsychotics on AUC and TG trajectory slopes. The primary outcome was CVD events. We also investigated and compared the association between antipsychotics and CVD in subgroups stratified by TG trajectory and TG levels. FINDINGS: A total of 11,543 CVD events were documented and the incidence density was 64.64 per 1000 person-years. We identified two TG trajectories labeled as inverse-U shape (30.77%, n=12306) and low-decreasing (69.23%, n=27682). The antipsychotic exposure increased total AUC by 13% and increased the slopes of TG trajectories before age 48 years. In the inverse-U and low-decreasing group, the adjusted hazard ratios (HRs) and 95% confidence intervals (CI) for antipsychotics associated with CVD were 1.40 (1.21-1.62) and 1.29 (1.14-1.45), respectively, and the difference between the two trajectory groups become larger with the increase of the antipsychotic exposure. The association of antipsychotics with CVD (HR=1.72, 95%CI: 1.36-2.19) in inverse-U trajectory and high TG group was stronger than that in other subgroups. INTERPRETATION: Long-term antipsychotic exposure increased the TG burden and TG increase rate early in life. The strength of the association between antipsychotics and CVD risk in the inverse-U group was stronger than that in the low-decreasing group. FUNDING: The National Key Research and Development Program of China, Shandong Province Major Science and Technology Innovation Project, and National Natural Science Foundation of China.

Relationships of sleep traits with prostate cancer risk: A prospective study of 213,999 UK Biobank participants.

BACKGROUND: The effect of sleep on the occurrence of prostate cancer (PCa) remains unclear. This study explored the influence of sleep traits on the incidence of PCa using a UK Biobank cohort study. METHODS: In this prospective cohort study, 213,999 individuals free of PCa at recruitment from UK Biobank were included. Missing data were imputed using multiple imputation by chained equations. Cox proportional hazards models were used to calculate the adjusted hazard ratios and 95% confidence intervals for PCa (6747 incident cases) across seven sleep traits (sleep duration, chronotype, insomnia, snoring, nap, difficulty to get up in the morning, and daytime sleepiness). In addition, we newly created a healthy sleep quality score according to sleep traits to assess the impact of the overall status of night and daytime sleep on PCa development. E values were used to assess unmeasured confounding. RESULTS: We identified 6747 incident cases, of which 344 died from PCa. Participants who usually suffered from insomnia had a higher risk of PCa (hazard ratio [HR]: 1.11; 95% confidence interval [CI]: 1.04-1.19, E value: 1.46). Finding it fairly easy to get up in the morning was also positively associated with PCa (HR: 1.09; 95% CI: 1.04-1.15, E value: 1.40). Usually having a nap was associated with a lower risk of PCa (HR: 0.91; 95% CI: 0.83-0.99, E value: 1.42). CONCLUSIONS: Fairly easy to get up in the morning and usually experiencing insomnia were associated with an increased incidence of PCa. Moreover, usually having a nap was associated with a lower risk of PCa. Therefore, sleep behaviors are modifiable risk factors that may have a potential impact on PCa risk.

The TARGET Nurses' health cohort study protocol: Towards a revolution in getting nurses' health ticked.

AIM: To evaluate the health status of nurses in China and explore the impact of work-related stress, work environment and lifestyle factors on their health outcomes. DESIGN: The Chinese Nurses' Health Study is a multicentred, prospective cohort study. METHODS: We plan to recruit approximately 80,000 registered nurses aged between 18 and 65 years. Eligible nurses will be introduced to complete a series of web-based questionnaires after obtaining their informed consent. Follow-up questionnaires will be completed at 2-year interval to continuously track subsequent exposures. Health-related indicators will be obtained through self-reporting by nurses and the provincial and national registry platforms such as National Central Cancer Registry. The funding was approved in July 2020 and Research Ethics Committee approval was granted in February 2021. DISCUSSION: The study is the first multicentred prospective cohort study that aims to assess the impact of work-related stress, work environment and lifestyle factors on the health of Chinese nurses. The results of the Chinese Nurses' Health Cohort Study will potentially draw a picture of the current situation of general health and well-being among nurses in China and their health risks. This will be critical in recommending locally tailored strategic preventive measures and policies to reduce health and well-being threats for nurses and potentially general public, thereby promoting the quality of healthcare in China and globally. IMPACT: This study will help to understand the health status and working environment characteristics of Chinese nurses, and provide valuable epidemiological evidence for improving working environment and promoting well-being. The results of this study are potentially of great significance for formulating targeted nursing strategies to promote the nurses' health, nursing quality and patient safety in China and even around the world. CLINICAL TRIAL REGISTRATION NUMBER AND NAME OF TRIAL REGISTER: ChiCTR.org (ID:ChiCTR2100043202), The Nurses' Health Cohort Study of Shandong.

Exploring the Causal Roles of Circulating Remnant Lipid Profile on Cardiovascular and Cerebrovascular Diseases: Mendelian Randomization Study.

BACKGROUND: Causal evidence of circulating lipids especially the remnant cholesterol with cardiovascular and cerebrovascular disease (CVD) is lacking. This research aimed to explore the causal roles of extensive lipid traits especially the remnant lipids in CVD. METHODS: Two-sample Mendelian randomization (TSMR) analysis was performed based on large-scale meta-analysis datasets in European ancestry. The causal effect of 15 circulating lipid profiles including 6 conventional lipids and 9 remnant lipids on coronary heart disease (CHD) and ischemic stroke (IS), as well as the subtypes, was assessed. RESULTS: Apolipoprotein B (Apo B), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were still important risk factors for CHD and myocardial infarction (MI) but not for IS. Apo B is the strongest which increased the CHD and MI risk by 44% and 41%, respectively. The odds ratios (ORs) of total TG on CHD and MI were 1.25 (95% confidence interval [CI], 1.13-1.38) and 1.24 (95% CI, 1.11-1.38), respectively. A one standard deviation difference increased TG in medium very-low-density lipoproteins (M.VLDL.TG), TG in small VLDL (S.VLDL.TG), TG in very small VLDL (XS.VLDL.TG), TG in intermediate-density lipoproteins (IDL.TG), TG in very large HDL (XL.HDL.TG), and TG in small HDL (S.HDL.TG) particles also robustly increased the risk of CHD and MI by 9-28% and 9-27%, respectively. TG in very/extremely large VLDL (XXL.VLDL.TG and XL.VLDL.TG) were insignificant or even negatively associated with CHD (in multivariable TSMR), and negatively associated with IS as well. CONCLUSION: The remnant lipids presented heterogeneity and two-sided effects for the risk of CHD and IS that may partially rely on the particle size. The findings suggested that the remnant lipids were required to be intervened according to specific components. This research confirms the importance of remnant lipids and provides causal evidence for potential targets for intervention.

Integration analysis of GWAS and expression quantitative trait loci to identify candidate genes and pathways for clozapine-related neutropaenia.

AIMS: Little is known about the genetic basis of clozapine-related neutropaenia. This study aims to explore candidate genes and pathways involved in clozapine-related neutropaenia. METHODS: This study conducted a two-stage integrative analysis of the summary statistics from the genome-wide association study (GWAS, n = 552) of the lowest absolute neutrophil count (ANC) during clozapine treatment and the summary data of the expressed quantitative trait locus (eQTL). First, we use the probabilistic Mendelian randomization (PMR-Egger) to identify genes whose expression is causally related to ANC, and then use Bayesian co-localization analysis to investigate whether there are shared causal variants between them [posterior probability for hypotheses 4 (PP.H4) > 0.80]. Finally, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted to explore the pathways that may be associated with ANC during clozapine treatment. RESULTS: PMR-Egger analysis identified 146 genes that may be causally associated with ANC after Bonferroni correction (P-value < 3.25e-6). Bayesian co-localization analysis identified six further genes whose gene expression shared common variants with ANC, including NT5E (PP.H4 = 0.96), GLDC (PP.H4 = 0.82), NUDT17 (PP.H4 = 0.88), MSH4 (PP.H4 = 0.88), PTER (PP.H4 = 0.89) and SERPINB6 (PP.H4 = 0.83). Enrichment analysis identified 52 GO terms and seven pathways associated with ANC, such as NAD metabolic process, drug catabolic process and glyoxylate and dicarboxylate metabolism. CONCLUSION: This study identified multiple candidate genes and pathways that may be involved in clozapine-related neutropaenia, providing novel clues for the mechanism of clozapine-related neutropaenia.

Triglyceride-Glucose Index Is Not Associated With Lung Cancer Risk: A Prospective Cohort Study in the UK Biobank.

BACKGROUND: The triglyceride-glucose (TyG) index is a practical substitute measure for insulin resistance (IR). The relationship between IR and lung cancer has been examined in previous studies; however, the findings have been controversial. In addition, previous studies had small sample sizes. Thus, we systematically examined the association between IR and lung cancer risk based on the UK Biobank with IR measured by the TyG index and further examined the interactions and joint effects for lung cancer. METHODS: A total of 324,334 individuals free from any type of cancer at recruitment from the UK Biobank prospective cohort were included. The participants were predominantly between 40 and 70 years old. After adjusting for relevant confounders, multivariable Cox regression models were constructed to examine the relationship between the TyG index and the risk of lung cancer. We also checked the interactions and joint effects using a polygenic risk score (PRS) for lung cancer. RESULTS: During a median follow-up of 9 years, 1,593 individuals were diagnosed with lung cancer. No association was found between the TyG index and lung cancer risk after multivariate Cox regression analysis adjusted for risk factors (hazard ratio: 0.91; 95% confidence interval: 0.64-1.18). No interaction or joint effects for genetic risk and the TyG index were observed. CONCLUSION: The TyG index was not associated with the risk of lung cancer. Our results provide limited evidence that IR is not correlated with the risk of lung cancer.

Identifying causality, genetic correlation, priority and pathways of large-scale complex exposures of breast and ovarian cancers.

BACKGROUND: Genetic correlations, causalities and pathways between large-scale complex exposures and ovarian and breast cancers need systematic exploration. METHODS: Mendelian randomisation (MR) and genetic correlation (GC) were used to identify causal biomarkers from 95 cancer-related exposures for risk of breast cancer [BC: oestrogen receptor-positive (ER + BC) and oestrogen receptor-negative (ER - BC) subtypes] and ovarian cancer [OC: high-grade serous (HGSOC), low-grade serous, invasive mucinous (IMOC), endometrioid (EOC) and clear cell (CCOC) subtypes]. RESULTS: Of 31 identified robust risk factors, 16 were new causal biomarkers for BC and OC. Body mass index (BMI), body fat mass (BFM), comparative body size at age 10 (CBS-10), waist circumference (WC) and education attainment were shared risk factors for overall BC and OC. Childhood obesity, BMI, CBS-10, WC, schizophrenia and age at menopause were significantly associated with ER + BC and ER - BC. Omega-6:omega-3 fatty acids, body fat-free mass and basal metabolic rate were positively associated with CCOC and EOC; BFM, linoleic acid, omega-6 fatty acids, CBS-10 and birth weight were significantly associated with IMOC; and body fat percentage, BFM and adiponectin were significantly associated with HGSOC. Both GC and MR identified 13 shared factors. Factors were stratified into five priority levels, and visual causal networks were constructed for future interventions. CONCLUSIONS: With analysis of large-scale exposures for breast and ovarian cancers, causalities, genetic correlations, shared or specific factors, risk factor priority and causal pathways and networks were identified.

BrcuHAC1 is a histone acetyltransferase that affects bolting development in Chinese flowering cabbage.

Histone acetylation is an important posttranslational modification associated with gene activation. In Arabidopsis, histone acetyltransferase 1 (HAC1) can promote flowering by regulating the transcription of FLOWERING LOCUS C (FLC), a major floral repressor. The size of the full-length cDNA and genomic DNA sequences of the histone acetyltransferase 1 gene (BrcuHAC1) in Chinese flowering cabbage (Brassica rapa syn. campestris ssp. chinensis var. utilis) were 5846 bp and 7376 bp, with an open reading frame (ORF) coding for a peptide with 1689 amino acids. The expression levels of BrcuHAC1 in different tissues and different developmental stages were as follows: flower>leaf>stem>root, and completed bolting and flowering stage>5th true leaf-stage>4th true leaf-stage>3rd true leaf-stage>2nd true leaf-stage>1st true leaf-stage. Silencing of BrcuHAC1 resulted in slow growth, and delayed bolting and flowering time in Chinese flowering cabbage. Molecular analysis showed that the mRNA level of FLC was increased, indicating that the delayed flowering phenomenon was mediated by FLC in the silenced group. In contrast, the expression levels of the autonomous-pathway genes were not significantly affected in the silenced group. In addition, the histone modification of FLC chromatin was also not affected in the silenced group. FLC is not the direct target gene of BrcuHAC1. However, BrcuHAC1 may affect the bolting and flowering time of Chinese flowering cabbage through the epigenetic modification of upstream factors of FLC.

Genetically Determined Chronic Low-Grade Inflammation and Hundreds of Health Outcomes in the UK Biobank and the FinnGen Population: A Phenome-Wide Mendelian Randomization Study.

Background: C-reactive protein (CRP) has been used as a biomarker of chronic low-grade inflammation in observational studies. We aimed to determine whether genetically determined CRP was associated with hundreds of human phenotypes to guide anti-inflammatory interventions. Methods: We used individual data from the UK Biobank to perform a phenome-wide two-stage least squares (2SLS) Mendelian randomization (MR) analysis for CRP with 879 diseases. Summary-level data from the FinnGen consortium were utilized to perform phenome-wide two-sample MR analysis on 821 phenotypes. Systematic two-sample MR methods included MR-IVW, MR-WME, MR-Mod, and MR-PRESSO as sensitivity analyses combined with multivariable MR to identify robust associations. Genetic correlation analysis was applied to identify shared genetic risks. Results: We found genetically determined CRP was robustly associated with 15 diseases in the UK Biobank and 11 diseases in the FinnGen population (P < 0.05 for all MR analyses). CRP was positively associated with tongue cancer, bronchitis, hydronephrosis, and acute pancreatitis and negatively associated with colorectal cancer, colon cancer, cerebral ischemia, electrolyte imbalance, Parkinson's disease, epilepsy, anemia of chronic disease, encephalitis, psychophysical visual disturbances, and aseptic necrosis of bone in the UK Biobank. There were positive associations with impetigo, vascular dementia, bipolar disorders, hypercholesterolemia, vertigo, and neurological diseases, and negative correlations with degenerative macular diseases, metatarsalgia, interstitial lung disease, and idiopathic pulmonary fibrosis, and others. in the FinnGen population. The electrolyte imbalance and anemia of chronic disease in UK Biobank and hypercholesterolemia and neurological diseases in FinnGen pass the FDR corrections. Neurological diseases and bipolar disorders also presented positive genetic correlations with CRP. We found no overlapping causal associations between the populations. Previous causal evidence also failed to support these associations (except for bipolar disorders). Conclusions: Genetically determined CRP was robustly associated with several diseases in the UK Biobank and the FinnGen population, but could not be replicated, suggesting heterogeneous and non-repeatable effects of CRP across populations. This implies that interventions at CRP are unlikely to result in decreased risk for most human diseases in the general population but may benefit specific high-risk populations. The limited causal evidence and potential double-sided effects remind us to be cautious about CRP interventions.

Genetically Predicted Insomnia in Relation to 14 Cardiovascular Conditions and 17 Cardiometabolic Risk Factors: A Mendelian Randomization Study.

Background This Mendelian randomization study aims to investigate causal associations between genetically predicted insomnia and 14 cardiovascular diseases (CVDs) as well as the potential mediator role of 17 cardiometabolic risk factors. Methods and Results Using genetic association estimates from large genome-wide association studies and UK Biobank, we performed a 2-sample Mendelian randomization analysis to estimate the associations of insomnia with 14 CVD conditions in the primary analysis. Then mediation analysis was conducted to explore the potential mediator role of 17 cardiometabolic risk factors using a network Mendelian randomization design. After correcting for multiple testing, genetically predicted insomnia was consistent significantly positively associated with 9 of 14 CVDs, those odds ratios ranged from 1.13 (95% CI, 1.08-1.18) for atrial fibrillation to 1.24 (95% CI, 1.16-1.32) for heart failure. Moreover, genetically predicted insomnia was consistently associated with higher body mass index, triglycerides, and lower high-density lipoprotein cholesterol, each of which may act as a mediator in the causal pathway from insomnia to several CVD outcomes. Additionally, we found very little evidence to support a causal link between insomnia with abdominal aortic aneurysm, thoracic aortic aneurysm, total cholesterol, low-density lipoprotein cholesterol, glycemic traits, renal function, and heart rate increase during exercise. Finally, we found no evidence of causal associations of genetically predicted body mass index, high-density lipoprotein cholesterol, or triglycerides on insomnia. Conclusions This study provides evidence that insomnia is associated with 9 of 14 CVD outcomes, some of which may be partially mediated by 1 or more of higher body mass index, triglycerides, and lower high-density lipoprotein cholesterol.