Mendelian Randomization for the Identification of Causal Pathways in Atherosclerotic Vascular Disease

Non-high-density to high-density lipoprotein cholesterol ratio and its association with infertility in U.S. women: a cross-sectional study

Objective

To investigate the relationship between Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratio (NHHR) and infertility in US female adults aged 20 to 45.

Methods

Our research team utilized data from the 2013-2018 National Health and Nutrition Examination Survey (NHANES) to conduct a cross-sectional study. Multivariable logistic regression was conducted to examine the association between NHHR and infertility, with trend tests providing additional insight into this relationship. Further, smoothed curve fitting was applied for a more detailed exploration. To ensure the robustness of our results, we conducted subgroup and sensitivity analyses.

Results

Between 2013 and 2018, our study included 2,947 participants, with 342(11.6%) self-reported infertility. A positive association was found between NHHR and infertility (OR=1.17,95%CI:1.07-1.27). Compared with the first trimester, the third trimester of NHHR was associated with an OR of 1.79(95% CI: 1.31-2.44) in model 3. The results of subgroup analyses revealed that the association between NHHR and infertility was nearly consistent.

Conclusion

NHHR demonstrated a positive correlation with infertility among U.S. female adults. Further investigation is needed to explore their association better and the underlying mechanisms.

The relationship between cardiometabolic index and infertility in American adults: a population-based study

Background

Infertility is a fertility disorder caused by various factors, with lipid metabolism playing a crucial role in its development. The cardiometabolic index (CMI), which combines blood lipids (TG/HDL-C) and obesity-related parameters (WHtR), is a new quantitative indicator. This study used NHANES data to investigate the relationship between CMI and the incidence of infertility.

Methods

We utilized data from women who took part in the National Health and Nutrition Examination Survey (NHANES) from 2015 to March 2020 to calculate the CMI index. Subsequently, we used multivariate logistic regression, smooth curve fitting, and subgroup analysis to investigate the relationship between the CMI index and infertility.

Results

The logistic regression model revealed a significant positive correlation between the CMI index and infertility, even after adjusting for all confounding variables (OR=3.23, 95%CI: 1.55-6.73, p=0.0017). This association remained consistent across all subgroups (p>0.05 for all interactions). Smooth curve fitting demonstrated a positive nonlinear relationship between CMI and infertility. However, the CMI index had limited diagnostic power for infertility (AUC=0.60, 95%CI: 0.56-0.65). However, the CMI-BMI index combined with BMI had good predictive performance (AUC=0.722, 95%CI: 0.676-0.767).

Conclusion

The CMI index shows a positive correlation with infertility, but its diagnostic value is restricted. The combination with BMI has good diagnostic value. Further investigation is required to determine the effectiveness of the CMI index as an early indicator of infertility.

The Association between Circulating Lipids and Female Infertility Risk: A Univariable and Multivariable Mendelian Randomization Analysis

BACKGROUND

Although observational studies have demonstrated that blood lipids are associated with female infertility, the causality of this association remains unclear. We performed a univariable and multivariable Mendelian randomization (MR) analysis to evaluate the causal relationship between blood lipids and female infertility.

METHODS

Single-nucleotide polymorphisms associated with lipid traits in univariate analysis were obtained from the Million Veteran Program (MVP) and Global Lipids Genetics Consortium (GLGC), involving up to 215,551 and 188,577 European individuals, respectively. Blood lipids in multivariate analysis were obtained from the latest genome-wide association study meta-analysis with lipid levels in 73 studies encompassing >300,000 participants. Data on female infertility were obtained from the FinnGen Consortium R6 release, which included 6481 samples and 75,450 controls. Subsequently, MR analysis was performed using inverse variance-weighted (IVW), weighted median, weighted-mode, simple-mode and MR-Egger regression to demonstrate the causal relationship between lipids and female infertility.

RESULTS

After controlling confounding factors including body mass index and age at menarche, two-sample MR demonstrated that genetically predicted LDL-C and TC were causally associated with the risk of female infertility (When the genetic instruments come from the MVP database, LDL-C and female infertility, IVW OR: 1.13, 95% CI: 1.001-1.269, p = 0.047; TC and female infertility, IVW OR: 1.16, 95% CI: 1.018-1.317, p = 0.025, and when the genetic instruments came from the GLGC database, LDL-C and female infertility, IVW OR: 1.10, 95% CI: 1.008-1.210, p = 0.033; TC and female infertility, IVW OR: 1.14, 95% CI: 1.024-1.258, p = 0.015). However, the IVW estimate showed that HDL-C was not significantly associated with the risk of female infertility (when the genetic instruments came from the MVP database, IVW OR: 1.00, 95% CI: 0.887-1.128, p = 0.999; when the genetic instruments came from the GLGC database, IVW OR: 1.00, 95% CI: 0.896-1.111, p = 0.968). The multivariable MR analysis also provided evidence that LDL-C (OR: 1.12, 95% CI: 1.006-1.243, p = 0.042) was significantly associated with the risk of female infertility after considering the correlation of all lipid-related traits.

CONCLUSION

These findings support a causal relationship between increased LDL-cholesterol and increased female infertility risk. Furthermore, the association between lipid-related traits and female infertility risk merits more studies.

Association between periodontitis and COVID-19 infection: a two-sample Mendelian randomization study

Background and Objective

Epidemiological studies report associations between coronavirus disease 2019 (COVID-19) and periodontitis; however, causality has not been proven. The aim of this study is to assess the associations between COVID-19 susceptibility and periodontitis with two-sample Mendelian randomization (MR) analyses.

Methods

A two-sample summary MR analysis was performed using data for outcome and exposure from the OpenGWAS database on people of European descent. Periodontal complex traits (PCTs) were chosen as a proxy for the periodontitis phenotype. The causal association between PCT3 (Aggregatibacter actinomycetemcomitans), PCT5 (Porphyromonas gingivalis), and gingival crevicular fluid (GCF) interleukin-1β (IL-1β) and COVID-19 were considered. Genome-wide association study (GWAS) data with the two largest sample sizes were selected as COVID-19 outcomes (datasets ebi-a-GCST010776 and ebi-a-GCST010777). Single-nucleotide polymorphisms (SNPs) associated with PCT3, PCT5, and GCF IL-1β at statistical significance at genome-wide level (P < 5 × 10^-8) were identified as genetic instruments. We used two-sample summary MR methods and tested the existence of a pleiotropic effect with MR-Egger.

Results

Inverse-variance weighted (IVW) estimates showed that there was a positive association between COVID-19 risk and periodontitis (ebi-a-GCST010776: odds ratio [OR] = 1.02 (95% confidence interval (CI), 1.00-1.05), P = 0.0171; ebi-a-GCST010777: OR = 1.03 (95% CI, 1.00-1.05), P = 0.0397). The weighted median also showed directionally similar estimates. Exploration of the causal associations between other PCTs and COVID-19 identified a slight effect of local inflammatory response (GCF IL-1β) on COVID-19 risk across the two datasets (ebi-a-GCST010776: IVW OR = 1.02 (95% CI, [1.01-1.03]), P < 0.001; ebi-a-GCST010777: IVW OR = 1.03 (95% CI, [1.02-1.04]), P < 0.001). The intercepts of MR-Egger yielded no proof for significant directional pleiotropy for either dataset (ebi-a-GCST010776: P = 0.7660; ebi-a-GCST010777: P = 0.6017).

Conclusions

The findings suggests that periodontitis and the higher GCF IL-1β levels is causally related to increase susceptibility of COVID-19. However, given the limitations of our study, the well-designed randomized controlled trials are needed to confirm its findings, which may represent a new non-pharmaceutical intervention for preventing COVID-19.

Examining the possible causal relationship between lung function, COPD and Alzheimer's disease: a Mendelian randomisation study

Rationale

Large retrospective case-control studies have reported an association between chronic obstructive pulmonary disease (COPD), reduced lung function and an increased risk of Alzheimer’s disease. However, it remains unclear if these diseases are causally linked, or due to shared risk factors. Conventional observational epidemiology suffers from unmeasured confounding and reverse causation. Additional analyses addressing causality are required.

Objectives

To examine a causal relationship between COPD, lung function and Alzheimer’s disease.

Methods

Using two-sample Mendelian randomisation, we used single nucleotide polymorphisms (SNPs) identified in a genome wide association study (GWAS) for lung function as instrumental variables (exposure). Additionally, we used SNPs discovered in a GWAS for COPD in those with moderate to very severe obstruction. The effect of these SNPs on Alzheimer’s disease (outcome) was taken from a GWAS based on a sample of 24 807 patients and 55 058 controls.

Results

We found minimal evidence for an effect of either lung function (OR: 1.02 per SD; 95% CI 0.91 to 1.13; p value 0.68) or liability for COPD on Alzheimer’s disease (OR: 0.97 per SD; 95% CI 0.92 to 1.03; p value 0.40).

Conclusion

Neither reduced lung function nor liability COPD are likely to be causally associated with an increased risk of Alzheimer’s, any observed association is likely due to unmeasured confounding. Scientific attention and health prevention policy may be better focused on overlapping risk factors, rather than attempts to reduce risk of Alzheimer’s disease by targeting impaired lung function or COPD directly.

Mendelian randomization analysis to assess a causal effect of haptoglobin on macroangiopathy in Chinese type 2 diabetes patients

Background

Haptoglobin (Hp) functions as an antioxidant by binding with haemoglobin. We investigated whether serum Hp has a causal effect on macroangiopathy via Mendelian randomization (MR) analysis with common variants of the Hp gene in Chinese patients with type 2 diabetes.

Methods

A total of 5687 type 2 diabetes patients were recruited and genotyped for the Hp gene. Clinical features and vascular imaging tests were applied to diagnose macroangiopathy. The association between common Hp genotypes and macroangiopathy was analyzed in the whole population. Serum Hp levels were measured by enzyme-linked immunosorbent assay in a subset of 935 patients. We individually analyzed the correlations among Hp levels, Hp genotypes and macroangiopathy. Further, 8-hydroxy-2′-deoxyguanosine (8-OHdG), an oxidative marker of DNA damage, was examined to evaluate the levels of oxidative stress.

Results

Common Hp genotypes were correlated with macroangiopathy (OR = 1.140 [95% CI 1.005–1.293], P = 0.0410 for the Hp 1 allele). Serum Hp levels were associated with both common Hp genotypes (P = 3.55 × 10⁻³¹) and macroangiopathy (OR = 2.123 [95% CI 1.098–4.102], P = 0.0252) in the subset of 935 patients. In the MR analysis, the directional trends of the observed and predicted relationships between common Hp genotypes and macroangiopathy were the same (OR 1.357 and 1.130, respectively). Furthermore, common Hp genotypes and Hp levels were associated with serum 8-OHdG levels (P = 0.0001 and 0.0084, respectively).

Conclusions

Our study provides evidence for a causal relationship between serum Hp levels and macroangiopathy in Chinese type 2 diabetes patients by MR analysis.

Electronic supplementary material

The online version of this article (10.1186/s12933-018-0662-7) contains supplementary material, which is available to authorized users.

The Genetic Architecture of Coronary Artery Disease: Current Knowledge and Future Opportunities

PURPOSE OF REVIEW

We provide an overview of our current understanding of the genetic architecture of coronary artery disease (CAD) and discuss areas of research that provide excellent opportunities for further exploration.

RECENT FINDINGS

Large-scale studies in human populations, coupled with rapid advances in genetic technologies over the last decade, have clearly established the association of common genetic variation with risk of CAD. However, the effect sizes of the susceptibility alleles are for the most part modest and collectively explain only a small fraction of the overall heritability. By comparison, evidence that rare variants make a substantial contribution to risk of CAD has been somewhat disappointing thus far, suggesting that other biological mechanisms have yet to be discovered. Emerging data suggests that novel pathways involved in the development of CAD can be identified through complementary and integrative systems genetics strategies in mice or humans. There is also convincing evidence that gut bacteria play a previously unrecognized role in the development of CAD, particularly through metabolism of certain dietary nutrients that lead to proatherogenic metabolites in the circulation. A major effort is now underway to functionally understand the newly discovered genetic and biological associations for CAD, which could lead to the development of potentially novel therapeutic strategies. Other important areas of investigation for understanding the pathophysiology of CAD, including epistatic interactions between genes or with either sex and environmental factors, have not been studied on a broad scope and represent additional opportunities for future studies.