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.

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.

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.

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.

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.

Leisure-Time Physical Activity and Cardiovascular Disease Risk Among Hypertensive Patients: A Longitudinal Cohort Study.

Objective: Few studies estimated the effect of leisure-time physical activity (LTPA) on cardiovascular disease (CVD) risk among hypertensive patients in a longitudinal cohort. This study aims to evaluate the association between LTPA and CVD in a longitudinal management cohort of hypertensive patients. Methods: A total of 58,167 hypertensive patients without baseline CVD from a longitudinal cohort were included in this study. LTPA and other covariates were measured at the follow-up four times annually. The primary outcome was CVD events. The association between LTPA and CVD was assessed by the marginal structure model (MSM) and Cox model with adjustment for age, gender, body mass index (BMI), smoking, drinking, diabetes, hyperlipidemia, and antihypertensive medication. The restricted cubic spline and segmented regression were used to assess the dose-response relationship between LTPA and CVD. Results: We recorded 16,332 CVD events; crude incidence of CVD were 89.68, 80.39, 62.64, and 44.04 per 1,000 person-years for baseline 0, 1-150, 151-300, and >300 min/week LTPA, respectively. Compared with inactive LTPA, the adjusted hazard ratios (HRs) estimated by Cox model and MSM-Cox model for CVD associated with 1-150,151-300, and 300 min/week LTPA were 0.85 (95% CI, 0.83-0.88), 0.67 (95% CI, 0.64-0.71), 0.47 (95% CI, 0.44-0.51), and 0.83 (95% CI, 0.76-0.91), 0.58 (95% CI, 0.52-0.63), and 0.39 (95% CI, 0.35-0.44), respectively. Per 60 min/week increase in LTPA was associated with a 13% reduction in CVD risk. LTPA breakpoint was 417 min/week for CVD. Before and after the break-point, the slopes of the piecewise-linear relationship between LTPA and CVD risk were -0.0017 and -0.0003, respectively. Conclusion: LTPA was more strongly associated with the CVD risk than that estimated by conventional analyses based on baseline LTPA; 417 min/week is a breakpoint, after which the incremental health benefits on CVD prevention obtained from the increase in LTPA are much less than before.

Development and validation of a Super learner-based model for predicting survival in Chinese Han patients with resected colorectal cancer.

OBJECTIVE: Improved prognostic prediction for patients with colorectal cancer stays an important challenge. This study aimed to develop an effective prognostic model for predicting survival in resected colorectal cancer patients through the implementation of the Super learner. METHODS: A total of 2333 patients who met the inclusion criteria were enrolled in the cohort. We used multivariate Cox regression analysis to identify significant prognostic factors and Super learner to construct prognostic models. Prediction models were internally validated by 10-fold cross-validation and externally validated with a dataset from The Cancer Genome Atlas. Discrimination and calibration were evaluated by Harrell concordence index (C-index) and calibration plots, respectively. RESULTS: Age, T stage, N stage, histological type, tumor location, lymph-vascular invasion, preoperative carcinoembryonic antigen and sample lymph nodes were integrated into prediction models. The concordance index of Super learner-based prediction model (SLM) was 0.792 (95% confidence interval: 0.767-0.818), which is higher than that of the seventh edition American Joint Committee on Cancer TNM staging system 0.689 (95% confidence interval: 0.672-0.703) for predicting overall survival (P < 0.05). In the external validation, the concordance index of the SLM for predicting overall survival was also higher than that of tumor-node-metastasis (TNM) stage system (0.764 vs. 0.682, respectively; P < 0.001). In addition, the SLM showed good calibration properties. CONCLUSIONS: We developed and externally validated an effective prognosis prediction model based on Super learner, which offered more reliable and accurate prognosis prediction and may be used to more accurately identify high-risk patients who need more active surveillance in patients with resected colorectal cancer.

Body surface area, height, and body fat percentage as more sensitive risk factors of cancer and cardiovascular disease.

BACKGROUND: Limited studies have compared the association between various physical measurements and the risk of cancer or cardiovascular disease (CVD). We aim to explore the best-individualized indicators of cancer and CVD risk assessment. METHODS: From May 2004 to December 2017, a community-based cohort in China involving 100 280 participants were enrolled. BMI, height, body surface area (BSA), and body fat percentage (BFP) were compared in parallel about cancer and CVD risk with the multivariable-adjusted Cox proportional hazard regression model. RESULTS: Within the follow-up period, 3107 (3.10%) were diagnosed with cancer and 3721 (3.71%) had CVD. Per-level increased (in tertile: T1, T2, and T3 level) BSA, height, and BFP was positively associated with the risk of overall cancer [HR (95% CI): 1.10 (1.05-1.15), 1.12 (1.07-1.18), and 1.10 (1.03-1.16), respectively], whereas BMI was insignificant. Compared with the reference group (T2), the highest BSA level (T3) was positively associated with overall cancer incidence for both male [HR (95% CI): 1.28 (1.13-1.45)] and female [HR (95% CI): 1.13 (1.00-1.28)]. The BSA, height, and BFP also significantly associated with some site-specific cancers including thyroid, stomach, breast, urinary system, and skin cancer. Meanwhile, BFP presented a strong positive association with overall CVD [HR (95% CI): 1.22 (1.15-1.30) in trend] in both gender and associated with nearly all CVD subtypes especially the myocardial infarction and heart failure. CONCLUSION: BSA, height, and BFP have more sensitivity in assessing cancer risk and BFP shows the largest hazard ratios for CVD incident. We provided valuable evidence for the application of height, BSA, and BFP in routine healthcare practice. These encouraging findings should be tested in more well-defined studies for risk prediction.