Ethnic-specific associations between body mass index and gastric cancer: a Mendelian randomization study in European and Korean populations

An interracial Mendelian analysis revealed a link between lipid-lowering drugs and renal failure

Lipid-lowering drugs have been used in clinics widely. It is unclear whether the drugs have an effect on renal failure. We chose high-density lipoprotein cholesterol (ieu-b-109), low-density lipoprotein cholesterol (ieu-a-300), triglyceride (ieu-b-111), and total cholesterol (ebi-a-GCST90038690) as exposures. SNPs near drug genes served as instrumental variables. Acute renal failure (ARF) and chronic renal failure (CRF) in Europeans from the GWAS catalog were selected as outcomes. Datasets on renal failure in East Asians and South Asians were used for validation. Inverse variance weighted (IVW) was the primary method for drug-targeted Mendelian randomization. In the Europeans, people who used PPARG reduced ARF risk by 69.3% (OR: 0.307, 95% CI: 0.171-0.553, p = 0.015). NPC1L1 inhibitors increased ARF risk by 2.684 times (OR: 2.684, 95% CI: 2.027-3.341, p = 0.003). APOE increased ARF risk by 1.987 times (OR: 1.987, 95% CI: 1.062-3.716, p = 0.032) but decreased CRF risk by 49.7% (OR: 0.503, 95% CI: 0.283-0.894, p = 0.019). TNFSF12 increased CRF risk by 3.866 times (OR: 3.866, 95% CI: 1.174-12.729, p = 0.026). In the East Asians, PPARG reduced CRF risk by 85.8% (OR: 0.142, 95% CI: 0.054-0.371, p < 0.001). And in the South Asians, APOE decreased ARF risk by 99.8% (OR: 0.002, 95% CI: 2.12e-05-0.179, p = 0.007). We revealed that PPARG could reduce the risk of renal failure in Europeans and Asians. APOE could cause ARF in the Europeans, but it was protective in the South Asians. Clinicians need to consider the characteristics of the local population before administering drugs to patients of different ethnicities.

Elucidating the causal relationship between 486 genetically predicted blood metabolites and the risk of gastric cancer: a comprehensive Mendelian randomization analysis

Background

Previous epidemiological studies have yielded inconclusive results regarding the causality between blood metabolites and the risk of gastric cancer (GC). To address this shortcoming, we conducted a two-sample Mendelian randomization (MR) study, combined with metabolomics techniques, to elucidate the causality between 486 genetically predicted blood metabolites and GC.

Methods

MR analysis and metabolomics techniques such as ultra-high performance liquid chromatography/tandem mass spectrometry (UPLC-MS/MS) and gas chromatography/tandem mass spectrometry (GC-MS/MS) technologies were employed to assess the causality of 486 genetically predicted blood metabolites on the risk of GC. The genome-wide association study (GWAS) summary data for 486 blood metabolites from 7,824 individuals. The GWAS summary data for GC (ebi-a-GCST90018849) were obtained from the IEU Open GWAS project, including 1,029 GC cases and 474,841 controls. Primary causality estimates were obtained using inverse variance weighting (IVW), supplemented with the weighted median, MR-Egger, weighted mode, and simple mode. In addition, we conducted sensitivity analyses (including Cochran's Q, MR-Egger intercept, MR-PRESSO, and leave-one-out tests),Steiger's test, linked disequilibrium score regression, and multivariate MR (MVMR) to improve the assessment of causality between GC and blood metabolite. Finally, we recruited a total of 11 patients diagnosed with gastric cancer from the First Affiliated Hospital of Air Force Military Medical University between September and October 2024. The control group comprised 11 healthy individuals. Serum samples were collected from both groups for the evaluation of blood-related metabolite expression levels using advanced techniques such as ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and gas chromatography-mass spectrometry (GC-MS/MS).

Results

The MVMR analysis revealed a significant association between genetically predicted elevated levels of tryptophan (odds ratio [OR] = 0.523, 95% confidence interval [CI] = 0.313-0.872, p = 0.013), nonadecanoate (19:0) (odds ratio [OR] = 0.460, 95% confidence interval [CI] = 0.225-0.943, p = 0.034), and erythritol (odds ratio [OR] = 0.672, 95% confidence interval [CI] = 0.468-0.930, p = 0.016) with a decreased risk of gastric cancer. Based on metabolomic techniques such as UPLC-MS/MS and GC-MS/MS analyses, it has been demonstrated that the expression levels of tryptophan, nonadecanoate (19:0), and erythritol are reduced in patients with gastric cancer. This finding aligns with the results obtained from our MR analysis and provides further confirmation regarding the protective role of tryptophan, nonadecanoate (19:0), and erythritol against gastric cancer.

Conclusions

These findings indicate that three blood metabolites are causally related to GC and provide new perspectives for combining genomics and metabolomics to study the mechanisms of metabolite-mediated GC development.

Body Roundness Index Trajectories and the Risk of Cancer: A Cohort Study

BACKGROUND

The body rounds index (BRI), an innovative obesity indicator integrating waist circumference (WC) and height, offers a two-dimensional assessment of obesity. The relationship between BRI trajectories and cancer has been overlooked in previous studies. This study aims to explore the association between BRI trajectories and the incidence of cancer.

METHODS

This study included 42,022 participants with a median age of 48.91 years. Based on the changes in participants' BRI during the period from 2006 to 2010, three BRI trajectory patterns were identified: low-stable, medium-stable, and high-stable. The primary outcome was cancer incidence and the secondary outcome was cancer-specific deaths. The association between BRI trajectories and cancer incidence and death was explored by cox regression analysis in the total, sex-specific and age-specific populations, respectively. Additionally, we further investigated the relationship between BRI and site-specific cancer incidence. Sensitivity analyses were applied to exclude interferences and ensure the stability of the results.

RESULTS

After a median follow-up time of 11.04 years, high-stable BRI trajectory was significantly associated with increased risk of cancer occurrence compared to low-stable BRI trajectory. This association was more pronounced in middle-aged men (men: HR = 1.46, 95% CI = 1.21-1.77, p < 0.001; age < 65: HR = 11.38, 95% CI = 1.15-1.66, p = 0.001). Additionally, high-stable BRI trajectory was significantly associated with a substantial increase in the risk of site-specific uterine cancers (HR = 4.92, 95% CI = 1.69-14.33, p = 0.004). Sensitivity analysis confirmed the stability of the results.

CONCLUSION

Our study identified a significant association between a high-stable BRI trajectory and cancer incidence, with this association being most pronounced in middle-aged men. Moreover, the high-stable BRI trajectory was strongly associated with uterine site-specific cancer development. Our findings underscore the importance of implementing lifestyle modifications and monitoring BRI values and their changes to provide effective health guidance.

An atlas on risk factors for gastrointestinal cancers: A systematic review of Mendelian randomization studies

OBJECTIVE

Gastrointestinal cancers are one of the most frequent cancer types and seriously threaten human life and health. Recent studies attribute the occurrence of gastrointestinal cancers to both genetic and environmental factors, yet the intrinsic etiology remains unclear. Mendelian randomization is a powerful well-established statistical method that is based on genome-wide association study (GWAS) to evaluate the causal relationship between exposures and outcomes. In the present study, we aimed to conduct a systematic review of Mendelian randomization studies investigating any causal risk factors for gastrointestinal cancers.

METHODS

We systematically searched Mendelian randomization studies that addressed the associations of genetically predicted exposures with five main gastrointestinal cancers from September 2014 to March 2024, as well as testing the research quality and validity.

RESULTS

Our findings suggested robust and consistent causal effects of body mass index (BMI), basal metabolic rate, fatty acids, total cholesterol, total bilirubin, insulin like growth factor-1, eosinophil counts, interleukin 2, alcohol consumption, coffee consumption, apolipoprotein B on colorectal cancer risks, BMI, waist circumference, low-density lipoprotein (LDL), total testosterone, smoking on gastric cancer risks, BMI, fasting insulin, LDL, waist circumference, visceral adipose tissue (VAT), immune cells, type 2 diabetes mellitus (T2DM) on pancreatic cancer risks, waist circumference, smoking, T2DM on esophageal adenocarcinoma risks, and VAT, ferritin, transferrin, alcohol consumption, hepatitis B virus infection, rheumatoid arthritis on liver cancer risks, respectively.

CONCLUSION

Larger, well-designed Mendelian randomization studies are practical in determining the causal status of risk factors for diseases.

Risk Prediction Models for Gastric Cancer: A Scoping Review

Background

Gastric cancer is a significant contributor to the global cancer burden. Risk prediction models aim to estimate future risk based on current and past information, and can be utilized for risk stratification in population screening programs for gastric cancer. This review aims to explore the research design of existing models, as well as the methods, variables, and performance of model construction.

Methods

Six databases were searched through to November 4, 2023 to identify appropriate studies. PRISMA extension for scoping reviews and the Arksey and O'Malley framework were followed. Data sources included PubMed, Embase, Web of Science, CNKI, Wanfang, and VIP, focusing on gastric cancer risk prediction model studies.

Results

A total of 29 articles met the inclusion criteria, from which 28 original risk prediction models were identified that met the analysis criteria. The risk prediction model is screened, and the data extracted includes research characteristics, prediction variables selection, model construction methods and evaluation indicators. The area under the curve (AUC) of the models ranged from 0.560 to 0.989, while the C-statistics varied between 0.684 and 0.940. The number of predictor variables is mainly concentrated between 5 to 11. The top 5 most frequently included variables were age, helicobacter pylori (Hp), precancerous lesion, pepsinogen (PG), sex, and smoking. Age and Hp were the most consistently included variables.

Conclusion

This review enhances understanding of current gastric cancer risk prediction research and its future directions. The findings provide a strong scientific basis and technical support for developing more accurate gastric cancer risk models. We expect that these conclusions will point the way for future research and clinical practice in this area to assist in the early prevention and treatment of gastric cancer.