Lipid levels and risk of acute pancreatitis using bidirectional Mendelian randomization.

Previous studies found lipid levels, especially triglycerides (TG), are associated with acute pancreatitis, but their causalities and bi-directions were not fully examined. We determined whether abnormal levels of TG, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) are precursors and/or consequences of acute pancreatitis using bidirectional two-sample Mendelian randomization (MR) with two non-overlapping genome-wide association study (GWAS) summary statistics for lipid levels and acute pancreatitis. We found phenotypic associations that both higher TG levels and lower HDL-C levels contributed to increased risk of acute pancreatitis. Our GWAS meta-analysis of acute pancreatitis identified seven independent signals. Genetically predicted TG was positively associated with acute pancreatitis when using the variants specifically associated with TG using univariable MR [Odds ratio (OR), 95% CI 2.02, 1.22-3.31], but the reversed direction from acute pancreatitis to TG was not observed (mean difference = 0.003, SE = 0.002, P-value = 0.138). However, a bidirectional relationship of HDL-C and acute pancreatitis was observed: A 1-SD increment of genetically predicted HDL-C was associated with lower risk of acute pancreatitis (OR, 95% CI 0.84, 0.76-0.92) and genetically predisposed individuals with acute pancreatitis have, on average, 0.005 SD lower HDL-C (mean difference = - 0.005, SE = 0.002, P-value = 0.004). Our MR analysis confirms the evidence of TG as a risk factor of acute pancreatitis but not a consequence. A potential bidirectional relationship of HDL-C and acute pancreatitis occurs and raises the prospect of HDL-C modulation in the acute pancreatitis prevention and treatment.

Association between high-density lipoprotein cholesterol and type 2 diabetes mellitus: dual evidence from NHANES database and Mendelian randomization analysis.

Background: Low levels of high-density lipoprotein cholesterol (HDL-C) are commonly seen in patients with type 2 diabetes mellitus (T2DM). However, it is unclear whether there is an independent or causal link between HDL-C levels and T2DM. This study aims to address this gap by using the The National Health and Nutrition Examination Survey (NHANES) database and Mendelian randomization (MR) analysis. Materials and methods: Data from the NHANES survey (2007-2018) with 9,420 participants were analyzed using specialized software. Logistic regression models and restricted cubic splines (RCS) were used to assess the relationship between HDL-C and T2DM incidence, while considering covariates. Genetic variants associated with HDL-C and T2DM were obtained from genome-wide association studies (GWAS), and Mendelian randomization (MR) was used to evaluate the causal relationship between HDL-C and T2DM. Various tests were conducted to assess pleiotropy and outliers. Results: In the NHANES study, all groups, except the lowest quartile (Q1: 0.28-1.09 mmol/L], showed a significant association between HDL-C levels and reduced T2DM risk (all P < 0.001). After adjusting for covariates, the Q2 [odds ratio (OR) = 0.67, 95% confidence interval (CI): (0.57, 0.79)], Q3 [OR = 0.51, 95% CI: (0.40, 0.65)], and Q4 [OR = 0.29, 95% CI: (0.23, 0.36)] groups exhibited average reductions in T2DM risk of 23%, 49%, and 71%, respectively. In the sensitivity analysis incorporating other lipid levels, the Q4 group still demonstrates a 57% reduction in the risk of T2DM. The impact of HDL-C levels on T2DM varied with age (P for interaction = 0.006). RCS analysis showed a nonlinear decreasing trend in T2DM risk with increasing HDL-C levels (P = 0.003). In the MR analysis, HDL-C levels were also associated with reduced T2DM risk (OR = 0.69, 95% CI = 0.52-0.82; P = 1.41 × 10-13), and there was no evidence of pleiotropy or outliers. Conclusion: This study provides evidence supporting a causal relationship between higher HDL-C levels and reduced T2DM risk. Further research is needed to explore interventions targeting HDL-C levels for reducing T2DM risk.

HDL levels modulate the impact of type 2 diabetes susceptibility alleles in older adults.

BACKGROUND: Type 2 Diabetes (T2D) is influenced by genetic, environmental, and ageing factors. Ageing pathways exacerbate metabolic diseases. This study aimed to examine both clinical and genetic factors of T2D in older adults. METHODS: A total of 2,909 genotyped patients were enrolled in this study. Genome Wide Association Study was conducted, comparing T2D patients to non-diabetic older adults aged ≥ 60, ≥ 65, or ≥ 70 years, respectively. Binomial logistic regressions were applied to examine the association between T2D and various risk factors. Stepwise logistic regression was conducted to explore the impact of low HDL (HDL < 40 mg/dl) on the relationship between the genetic variants and T2D. A further validation step using data from the UK Biobank with 53,779 subjects was performed. RESULTS: The association of T2D with both low HDL and family history of T2D increased with the age of control groups. T2D susceptibility variants (rs7756992, rs4712523 and rs10946403) were associated with T2D, more significantly with increased age of the control group. These variants had stronger effects on T2D risk when combined with low HDL cholesterol levels, especially in older control groups. CONCLUSIONS: The findings highlight a critical role of age, genetic predisposition, and HDL levels in T2D risk. The findings suggest that individuals over 70 years who have high HDL levels without the T2D susceptibility alleles may be at the lowest risk of developing T2D. These insights can inform tailored preventive strategies for older adults, enhancing personalized T2D risk assessments and interventions.

A regulatory element associated to NAFLD in the promoter of DIO1 controls LDL-C, HDL-C and triglycerides in hepatic cells.

BACKGROUND: Genome-wide association studies (GWAS) have identified genetic variants linked to fat metabolism and related traits, but rarely pinpoint causative variants. This limitation arises from GWAS not considering functional implications of noncoding variants that can affect transcription factor binding and potentially regulate gene expression. The aim of this study is to investigate a candidate noncoding functional variant within a genetic locus flagged by a GWAS SNP associated with non-alcoholic fatty liver disease (NAFLD), a condition characterized by liver fat accumulation in non-alcohol consumers. METHODS: CRISPR-Cas9 gene editing in HepG2 cells was used to modify the regulatory element containing the candidate functional variant linked to NAFLD. Global gene expression in mutant cells was assessed through RT-qPCR and targeted transcriptomics. A phenotypic assay measured lipid droplet accumulation in the CRISPR-Cas9 mutants. RESULTS: The candidate functional variant, rs2294510, closely linked to the NAFLD-associated GWAS SNP rs11206226, resided in a regulatory element within the DIO1 gene's promoter region. Altering this element resulted in changes in transcription factor binding sites and differential expression of candidate target genes like DIO1, TMEM59, DHCR24, and LDLRAD1, potentially influencing the NAFLD phenotype. Mutant HepG2 cells exhibited increased lipid accumulation, a hallmark of NAFLD, along with reduced LDL-C, HDL-C and elevated triglycerides. CONCLUSIONS: This comprehensive approach, that combines genome editing, transcriptomics, and phenotypic assays identified the DIO1 promoter region as a potential enhancer. Its activity could regulate multiple genes involved in the NAFLD phenotype or contribute to defining a polygenic risk score for enhanced risk assessment in NAFLD patients.

Genome-wide analysis reveals extensive genetic overlap between childhood phenotypes and later-life type 2 diabetes.

Observational studies have indicated a potential influence of childhood phenotypes on the later development of type 2 diabetes (T2D). However, the underlying biological mechanisms remain unclear. In this study, we conducted a comprehensive genome-wide analysis to investigate the shared genetic architecture and genetic loci between nine childhood phenotypes (N = 4202-620,26) and later-life T2D (N = 80,154) using genetic correlation, mendelian randomization (MR), and conjunctional false discovery rate (conjFDR) statistical frameworks. Our findings demonstrated substantial genetic correlations and pleiotropic enrichment between childhood obesity, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and later-life T2D. Childhood obesity exhibited a significant association with increased later-life T2D risk through 10 mediators, 6 of which were adulthood obesity-related phenotypes. Additionally, we identified 69, 83, 3, 5, 10, 5, 3, and 7 loci shared between childhood obesity, BMI, SBP, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), apolipoprotein A-I (ApoA-I), apolipoprotein B (ApoB), and T2D at conjFDR <0.05, with the majority of these loci being novel discoveries. Overall, our study reveals extensive genetic overlap between childhood obesity-related phenotypes and T2D with concordant effect directions, shedding new light on variants and phenotypes with lifelong effects.

Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank.

Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence IR-associated loci using 51,550 European individuals in the Michigan Genomics Initiative. We identified associations with diabetes, hyperglyceridemia, hypertension, nonalcoholic fatty liver disease and ischemic heart disease. Collectively, this study provides insight into the genes, pathways, tissues and subtypes critical in IR.

Causal role of lipid metabolism in pulmonary alveolar proteinosis: an observational and mendelian randomisation study.

BACKGROUND: Pulmonary alveolar proteinosis (PAP) is a rare interstitial lung disease characterised by the accumulation of lipoprotein material in the alveoli. Although dyslipidaemia is a prominet feature, the causal effect of lipid traits on PAP remains unclear. This study aimed to explore the role of lipid traits in PAP and evaluate the potential of lipid-lowering drug targets in PAP. METHODS: Clinical outcomes, lipid profiles and lung function tests were analysed in a clinical cohort of diagnosed PAP patients and propensity score-matched healthy controls. Genome-wide association study data on PAP, lipid metabolism, blood cells and variants of genes encoding potential lipid-lowering drug targets were obtained for Mendelian randomisation (MR) and mediation analyses. FINDINGS: Observational results showed that higher levels of total cholesterol (TC), triglycerides and low-density lipoprotein (LDL) were associated with increased risks of PAP. Higher levels of TC and LDL were also associated with worse PAP severity. In MR analysis, elevated LDL was associated with an increased risk of PAP (OR: 4.32, 95% CI: 1.63 to 11.61, p=0.018). Elevated monocytes were associated with a lower risk of PAP (OR 0.34, 95% CI: 0.18 to 0.66, p=0.002) and mediated the risk impact of LDL on PAP. Genetic mimicry of PCSK9 inhibition was associated with a reduced risk of PAP (OR 0.03, p=0.007). INTERPRETATION: Our results support the crucial role of lipid and metabolism-related traits in PAP risk, emphasising the monocyte-mediated, causal effect of elevated LDL in PAP genetics. PCSK9 mediates the development of PAP by raising LDL. These finding provide evidence for lipid-related mechanisms and promising lipid-lowering drug target for PAP.

Genetic Insights into the Risk of Metabolic Syndrome and Its Components on Dementia: A Mendelian Randomization.

BACKGROUND: The role of metabolic syndrome (MetS) on dementia is disputed. OBJECTIVE: We conducted a Mendelian randomization to clarify whether the genetically predicted MetS and its components are casually associated with the risk of different dementia types. METHODS: The genetic predictors of MetS and its five components (waist circumference, hypertension, fasting blood glucose, triglycerides, and high-density lipoprotein cholesterol [HDL-C]) come from comprehensive public genome-wide association studies (GWAS). Different dementia types are collected from the GWAS in the European population. Inverse variance weighting is utilized as the main method, complemented by several sensitivity approaches to verify the robustness of the results. RESULTS: Genetically predicted MetS and its five components are not causally associated with the increasing risk of dementia (all p > 0.05). In addition, no significant association between MetS and its components and Alzheimer's disease, vascular dementia, frontotemporal dementia, dementia with Lewy bodies, and dementia due to Parkinson's disease (all p > 0.05), except the association between HDL-C and dementia with Lewy bodies. HDL-C may play a protective role in dementia with Lewy bodies (OR: 0.81, 95% CI: 0.72-0.92, p = 0.0010). CONCLUSIONS: From the perspective of genetic variants, our study provides novel evidence that MetS and its components are not associated with different dementia types.

Genetic and Environmental Influences on Blood Pressure and Serum Lipids Across Age-Groups.

Aging plays a crucial role in the mechanisms of the impacts of genetic and environmental factors on blood pressure and serum lipids. However, to our knowledge, how the influence of genetic and environmental factors on the correlation between blood pressure and serum lipids changes with age remains to be determined. In this study, data from the Chinese National Twin Registry (CNTR) were used. Resting blood pressure, including systolic and diastolic blood pressure (SBP and DBP), and fasting serum lipids, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglycerides (TGs) were measured in 2378 participants (1189 twin pairs). Univariate and bivariate structural equation models examined the genetic and environmental influences on blood pressure and serum lipids among three age groups. All phenotypes showed moderate to high heritability (0.37-0.59) and moderate unique environmental variance (0.30-0.44). The heritability of all phenotypes showed a decreasing trend with age. Among all phenotypes, SBP and DBP showed a significant monotonic decreasing trend. For phenotype-phenotype pairs, the phenotypic correlation (Rph) of each pair ranged from -0.04 to 0.23, and the additive genetic correlation (Ra) ranged from 0.00 to 0.36. For TC&SBP, TC&DBP, TG&SBP and TGs&DBP, both the Rph and Ra declined with age, and the Ra difference between the young group and the older adult group is statistically significant (p < .05). The unique environmental correlation (Re) of each pair did not follow any pattern with age and remained relatively stable with age. In summary, we observed that the heritability of blood pressure was affected by age. Moreover, blood pressure and serum lipids shared common genetic backgrounds, and age had an impact on the phenotypic correlation and genetic correlations.

Low-density lipoprotein cholesterol and risk of hepatocellular carcinoma: a Mendelian randomization and mediation analysis.

BACKGROUND: A previous study demonstrated that low-density lipoprotein cholesterol (LDL-C) is associated with hepatocellular carcinoma (HCC); however, the causality between them has not been proven due to conflicting research results and the interference of confounders. This study utilized Mendelian randomization (MR) to investigate the causal relationship between LDL-C and HCC and identify the mediating factors. METHODS: LDL-C, HCC, and coronary artery disease (CAD) genome-wide association study (GWAS) data were obtained from a public database. To investigate causality, inverse variance weighting (IVW) was the main analysis approach. MR‒Egger, simple mode, weighted median (WM), and weighted mode were employed as supplementary analytic methods. In addition, horizontal pleiotropy and heterogeneity were tested. To evaluate the stability of the MR results, a "leave-one-out" approach was used. Multivariate MR (MVMR) was utilized to correct the confounders that might affect causality, and mediation analysis was used to investigate the potential mediating effects. Finally, we used HCC risk to infer the reverse causality with LDL-C level. RESULTS: Random effects IVW results were (LDL-C-HCC: odds ratio (OR) = 0.703, 95% confidence interval (CI) = [0.508, 0.973], P = 0.034; CAD-HCC: OR = 0.722, 95% CI = [0.645, 0.808], P = 1.50 × 10-8; LDL-C-CAD: OR = 2.103, 95% CI = [1.862, 2.376], P = 5.65 × 10-33), demonstrating a causal link between LDL-C levels and a lower risk of HCC. Through MVMR, after mutual correction, the causal effect of LDL-C and CAD on HCC remained significant (P < 0.05). Through mediation analysis, it was proven that CAD mediated the causative connection between LDL-C and HCC, and the proportion of mediating effect on HCC was 58.52%. Reverse MR showed that HCC could affect LDL-C levels with a negative correlation (ORIVW = 0.979, 95% CI = [0.961, 0.997], P = 0.025). CONCLUSION: This MR study confirmed the causal effect between LDL-C levels and HCC risk, with CAD playing a mediating role. It may provide a new view on HCC occurrence and development mechanisms, as well as new metabolic intervention targets for treatment.

Identification of appropriate biochemical parameters and cut points to detect Maturity Onset Diabetes of Young (MODY) in Asian Indians in a clinic setting.

Maturity Onset Diabetes of the Young (MODY) is a monogenic form of diabetes which is detected by genetic testing. We looked at clinical and biochemcial variables that could help detect possible MODY among Asian Indians with youth-onset diabetes. From the diabetes electronic medical records of a diabetes care centre in Chennai in southern India, demographic, anthropometric, and biochemical details of 34 genetically confirmed MODY participants were extracted. They were compared with patients with type 1 diabetes (T1D) (n = 1011) and type 2 diabetes (T2D) (n = 1605), diagnosed below 30 years of age. Clinical and biochemical variables including body mass index (BMI), glycated hemoglobin, HDL cholesterol, and C-peptide (fasting and stimulated) were analyzed to determine whether cut points could be derived to identify individuals who could be sent for genetic testing to diagnose or rule out MODY in this ethnic group. The age at diagnosis was higher for T2D (26.5 ± 4.0 years) compared to T1D (18.2 ± 6.1 years) and MODY (17.8 ± 6.0 years). Individuals with MODY had BMI, glycated hemoglobin, total cholesterol, triglycerides, HDL cholesterol, and C-peptide levels which were intermediate between T1D and T2D. The identified probable parameters and their cut points to identify cases for MODY genetic screening were BMI 21.2-22.7 kg/m2, glycated hemoglobin 7.2-10%, HDL cholesterol 43-45 mg/dl, fasting C -peptide, 1.2-2.1 ng/ml and stimulated C-peptide, 2.1-4.5 ng/ml. Asian Indians with MODY have clinical features that are intermediate between T1D and T2D and selected biochemical parameters, especially stimulated C peptide cut points were the most useful to diagnose MODY.

Serum il-18 and rs187238 single nucleotide polymorphism are associated with high-density lipoprotein changes in covid-19 outpatients.

AIM: COVID-19 is an inflammatory disease and its prognosis is associated with cardiovascular risk, which can be associated with changes in lipoprotein metabolism. The single nucleotide polymorphism (SNP) rs187238 of Interleukin (IL)-18 is extensively reported in association with worsening inflammatory and cardiovascular disease (CVD). This study evaluated the association of IL-18 levels and its SNP rs187238 with lipoprotein profile changes in COVID-19 outpatients. METHODS: Observational, analytical, cross-sectional study that evaluated 250 patients with respiratory syndrome, 36% (n = 90) with COVID-19. Serum total cholesterol (TC), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), triglycerides (TG), apolipoproteins A-I and B (Apo A-I and Apo B) and IL-18 levels were determined. Polymorphism genotyping was done by real-time polymerase chain reaction (qPCR). The significance level was p < 0.05. RESULTS: Patients with COVID-19 showed a reduction in TC and HDL-c, without difference in IL-18. HDL-c and LDL-c had a high frequency outside the reference values. There was a negative correlation of IL-18 with HDL-c and a positive correlation with Apo B/Apo A-I ratio. The frequencies of the C (wild) and G (polymorphic) alleles between patients with and without COVID-19 followed the Hardy-Weinberg equilibrium. However, COVID-19 was associated with reduced HDL-c and Apo A-I values in patients with the CC genotype. CONCLUSION: IL-18 levels and its SNP rs187238 were associated with decreased HDL-c and Apo A-I in COVID-19 outpatients.

LDLR gene's promoter region hypermethylation in patients with familial hypercholesterolemia.

Familial hypercholesterolemia (FH) is characterized by high low-density lipoprotein cholesterol (LDL-C) levels and a high risk of early coronary heart disease. Structural alterations in the LDLR, APOB, and PCSK9 genes were not found in 20-40% of patients diagnosed using the Dutch Lipid Clinic Network (DCLN) criteria. We hypothesized that methylation in canonical genes could explain the origin of the phenotype in these patients. This study included 62 DNA samples from patients with a clinical diagnosis of FH according to the DCLN criteria, who previously tested negative for structural alterations in the canonical genes, and 47 DNA samples from patients with normal blood lipids (control group). All DNA samples were tested for methylation in the CpG islands of the three genes. The prevalence of FH relative to each gene was determined in both groups and the respective prevalence ratios (PRs) were calculated. The methylation analysis of APOB and PCSK9 was negative in both groups, showing no relationship between methylation in these genes and the FH phenotype. As the LDLR gene has two CpG islands, we analyzed each island separately. The analysis of LDLR-island1 showed PR = 0.982 (CI 0.33-2.95; χ2 = 0.001; p = 0.973), also suggesting no relationship between methylation and the FH phenotype. Analysis of LDLR-island2 showed a PR of 4.12 (CI 1.43-11.88; χ2 = 13,921; p = 0.00019), indicating a possible association between methylation on this island and the FH phenotype.

ABO gene polymorphisms are associated with acute coronary syndrome and with plasma concentration of HDL-cholesterol and triglycerides.

The role of ABO gene polymorphisms in acute coronary syndrome (ACS) and lipid metabolism is increasingly recognized. We investigated whether ABO gene polymorphisms are significantly associated with ACS and the plasma lipid profile. Six ABO gene polymorphisms (rs651007 T/C, rs579459 T/C, rs495928 T/C, rs8176746 T/G, rs8176740 A/T, and rs512770 T/C) were determined by 5'exonuclease TaqMan assays in 611 patients with ACS and 676 healthy controls. The results demonstrated that the rs8176746 T allele was associated with a lower risk of ACS under the co-dominant, dominant, recessive, over-dominant, and additive models (P = 0.0004, P = 0.0002, P = 0.039,  P = 0.0009, and P = 0.0001, respectively). Furthermore, under co-dominant, dominant, and additive models, the rs8176740 A allele was associated with a lower risk of ACS (P = 0.041, P = 0.022, and P = 0.039, respectively). On the other hand, the rs579459 C allele was associated with a lower risk of ACS under the dominant, over-dominant, and additive models (P = 0.025, P = 0.035, and P = 0.037, respectively). In a subanalysis performed with the control group, rs8176746 T and rs8176740 A alleles were associated with low systolic blood pressure and with both high high-density lipoprotein-cholesterol (HDL-C) and low triglyceride plasma concentrations, respectively. In conclusion, ABO gene polymorphisms were associated with a lower risk of ACS, and lower systolic blood pressure and plasma lipid levels, suggesting a causal relationship between ABO blood groups and the incidence of ACS.

A Polynesian-specific missense CETP variant alters the lipid profile.

Identifying population-specific genetic variants associated with disease and disease-predisposing traits is important to provide insights into the genetic determinants of health and disease between populations, as well as furthering genomic justice. Various common pan-population polymorphisms at CETP associate with serum lipid profiles and cardiovascular disease. Here, sequencing of CETP identified a missense variant rs1597000001 (p.Pro177Leu) specific to Maori and Pacific people that associates with higher HDL-C and lower LDL-C levels. Each copy of the minor allele associated with higher HDL-C by 0.236 mmol/L and lower LDL-C by 0.133 mmol/L. The rs1597000001 effect on HDL-C is comparable with CETP Mendelian loss-of-function mutations that result in CETP deficiency, consistent with our data, which shows that rs1597000001 lowers CETP activity by 27.9%. This study highlights the potential of population-specific genetic analyses for improving equity in genomics and health outcomes for population groups underrepresented in genomic studies.

Falsification of the instrumental variable conditions in Mendelian randomization studies in the UK Biobank.

Mendelian randomization (MR) is an increasingly popular approach to estimating causal effects. Although the assumptions underlying MR cannot be verified, they imply certain constraints, the instrumental inequalities, which can be used to falsify the MR conditions. However, the instrumental inequalities are rarely applied in MR. We aimed to explore whether the instrumental inequalities could detect violations of the MR conditions in case studies analyzing the effect of commonly studied exposures on coronary artery disease risk.Using 1077 single nucleotide polymorphisms (SNPs), we applied the instrumental inequalities to MR models for the effects of vitamin D concentration, alcohol consumption, C-reactive protein (CRP), triglycerides, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol on coronary artery disease in the UK Biobank. For their relevant exposure, we applied the instrumental inequalities to MR models proposing each SNP as an instrument individually, and to MR models proposing unweighted allele scores as an instrument. We did not identify any violations of the MR assumptions when proposing each SNP as an instrument individually. When proposing allele scores as instruments, we detected violations of the MR assumptions for 5 of 6 exposures.Within our setting, this suggests the instrumental inequalities can be useful for identifying violations of the MR conditions when proposing multiple SNPs as instruments, but may be less useful in determining which SNPs are not instruments. This work demonstrates how incorporating the instrumental inequalities into MR analyses can help researchers to identify and mitigate potential bias.

[HDL - Quo vadis]. / HDL ­ Quo vadis.

Many epidemiological studies found low plasma levels of high-density lipoprotein (HDL) cholesterol (HDL-C) associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD). In cell culture and animal models, HDL particles show many anti-atherogenic actions. However, until now, clinical trials did not find any prevention of ASCVD events by drugs elevating HDL-C levels, at least not beyond statins. Also, genetic studies show no associations of HDL-C levels altering variants with cardiovascular risk. Therefore, the causal role and clinical benefit of HDL-C elevation in ASCVD are questioned. However, the interpretation of previous data has important limitations: First, the inverse relationship of HDL-C with the risk of ASCVD is limited to concentrations < 60 mg/dl (< 1.5 mmol/l). Higher concentrations do not reduce the risk of ASCVD events and are even associated with increased mortality. Therefore, neither the higher-the-better strategies of earlier drug developments nor the assumption of linear cause-and-effect relationships in Mendelian randomization trials are justified. Second, most of the drugs tested so far do not act specifically on HDL metabolism. Therefore, the futile endpoint studies question the clinical benefit of the investigated drugs, but not the importance of HDL in ASCVD. Third, the vascular functions of HDL are not exerted by its cholesterol content (i.e. HDL-C), but by a variety of other molecules. Comprehensive knowledge of the structure-function-disease relationships of HDL particles and their molecules is a prerequisite for testing their physiological and pathogenic relevance and possibly for optimizing the diagnosis and treatment of persons with HDL-associated risk of ASCVD, but also for other diseases, such as diabetes, chronic kidney disease, infections, autoimmune and neurodegenerative diseases.

Robust multivariable Mendelian randomization based on constrained maximum likelihood.

Mendelian randomization (MR) is a powerful tool for causal inference with observational genome-wide association study (GWAS) summary data. Compared to the more commonly used univariable MR (UVMR), multivariable MR (MVMR) not only is more robust to the notorious problem of genetic (horizontal) pleiotropy but also estimates the direct effect of each exposure on the outcome after accounting for possible mediating effects of other exposures. Despite promising applications, there is a lack of studies on MVMR's theoretical properties and robustness in applications. In this work, we propose an efficient and robust MVMR method based on constrained maximum likelihood (cML), called MVMR-cML, with strong theoretical support. Extensive simulations demonstrate that MVMR-cML performs better than other existing MVMR methods while possessing the above two advantages over its univariable counterpart. An application to several large-scale GWAS summary datasets to infer causal relationships between eight cardiometabolic risk factors and coronary artery disease (CAD) highlights the usefulness and some advantages of the proposed method. For example, after accounting for possible pleiotropic and mediating effects, triglyceride (TG), low-density lipoprotein cholesterol (LDL), and systolic blood pressure (SBP) had direct effects on CAD; in contrast, the effects of high-density lipoprotein cholesterol (HDL), diastolic blood pressure (DBP), and body height diminished after accounting for other risk factors.

Causal effects of circulating lipids and lipid-lowering drugs on the risk of epilepsy: a two-sample Mendelian randomization study.

BACKGROUND: Previous studies have reported inconsistent results on the association between circulating lipids and lipid-lowering drugs with the risk of epilepsy. AIM: To assess whether genetically predicted circulating lipids and lipid-lowering drugs are causally associated with the risk of epilepsy outcome. METHODS: We performed a two-sample Mendelian randomization (MR) analysis model to genetically predict the causal effects of circulating lipids (apolipoprotein A [APOA], apolipoprotein B [APOB], cholesterol, high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], lipoprotein A and triglycerides) and lipid-lowering drugs (HMG-CoA reductase [HMGCR] and proprotein convertase subtilisin/kexin type 9 [PCSK9] inhibitors) on epilepsy. Nine MR analysis methods were conducted to analyze the final results. The inverse-variance weighted (IVW) method was used as the primary outcome. The other MR analysis methods (simple mode, weighted mode, simple median, weighted median, penalized weighted median, MR Egger and MR-Egger [bootstrap]) were conducted as the complement to IVW. In addition, the robustness of the MR analysis results was assessed by leave-one-out analysis. RESULTS: The IVW analysis method demonstrated that there is no causal association between circulating lipids (APOA: odds ratio [OR], 0.958, 95% confidence interval (CI), 0.728-1.261, P = 0.760; APOB: OR, 1.092; 95% CI, 0.979-1.219, P = 0.115; cholesterol: OR, 1.210; 95% CI, 0.981-1.494, P = 0.077; HDL-C: OR, 0.964; 95% CI, 0.767-1.212, P = 0.753; LDL-C: OR, 1.100; 95% CI, 0.970-1.248, P = 0.137; lipoprotein A: OR, 1.082; 95% CI, 0.849-1.379, P = 0.528; triglycerides: OR, 1.126; 95% CI, 0.932-1.360, P = 0.221) and lipid-lowering drugs (HMGCR inhibitors: OR, 0.221; 95% CI, 0.006-8.408, P = 0.878; PCSK9 inhibitors: OR, 1.112; 95% CI, 0.215-5.761, P = 0.902) with risk of epilepsy. The other MR analysis methods and further leave-one-out sensitivity analysis confirmed the robustness of final results. CONCLUSION: This MR study demonstrated that there were no genetically predicted causal relationships between circulating lipids and lipid-lowering drugs with the risk of epilepsy.

Leveraging Genetics to Address the Role of GALNT2 on Atherogenic Dyslipidemia.

Several studies have shown that downregulation of GALNT2 (Polypeptide N-Acetylgalactosaminyltransferase 2), encoding polypeptide N-acetylgalactosaminyltransferase 2, decreases high-density lipoprotein cholesterol (HDL-C) and increases triglycerides levels by glycosylating key enzymes of lipid metabolism, such as angiopoietin like 3, apolipoprotein C-III, and phospholipid transfer protein. GALNT2 is also a positive modulator of insulin signaling and action, associated with in vivo insulin sensitivity and during adipogenesis strongly upregulates adiponectin. Thus, the hypothesis that GALNT2 affects HDL-C and triglycerides levels also through insulin sensitivity and/or circulating adiponectin, is tested. In 881 normoglycemic individuals the G allele of rs4846914 SNP at the GALNT2 locus, known to associate with GALNT2 downregulation, is associated with low HDL-C and high values of triglycerides, triglycerides/HDL-C ratio, and theHomeostatic Model Assessment of insulin resistance HOMAIR (p-values = 0.01, 0.027, 0.002, and 0.016, respectively). Conversely, no association is observed with serum adiponectin levels (p = 0.091). Importantly, HOMAIR significantly mediates a proportion of the genetic association with HDL-C (21%, 95% CI: 7-35%, p = 0.004) and triglyceride levels (32%, 95% CI: 4-59%, p = 0.023). The results are compatible with the hypothesis that, besides the effect on key lipid metabolism enzymes, GALNT2 alters HDL-C and triglyceride levels also indirectly through a positive effect on insulin sensitivity.