Using genetics to assess the association of commonly used antihypertensive drugs with diabetes, glycaemic traits and lipids: a trans-ancestry Mendelian randomisation study

The role of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (nhhr) in prediabetes progression and the mediating effect of BMI: a longitudinal study in China

BACKGROUND

Diabetes prevalence in China is significant, with a large proportion in the prediabetes stage. Dyslipidemia is associated with abnormal glucose metabolism, and the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) shows potential in diabetes risk assessment, but its role in prediabetes progression is understudied.

METHODS

A longitudinal study from 2011 to 2015 using CHARLS data was conducted. After exclusions, 1408 participants were included. NHHR was calculated from serum TC and HDL - C levels. Diabetes and prediabetes were defined based on standard criteria. Covariates and mediators were assessed, and statistical analyses included logistic regression and mediation analysis, and mediation analysis was conducted to evaluate the involvement of BMI in the association between NHHR and the risk of prediabetes progression.

RESULTS

Among the 1423 people in the cohort analysis, 339 (23.8%) were diagnosed with prediabetes progression. The median NHHR was significantly larger in the progression group (136.99 vs. 124.95, p < 0.05). In the fully adjusted model, NHHR one-unitincrease led to a 10% higher risk. Subgroup analyses showed consistent associations in most subgroups. BMI mediated 33.8% of the NHHR - prediabetes progression association.

CONCLUSION

NHHR is correlated with the risk of prediabetes progressing to diabetes, and BMI may mediate this association. NHHR monitoring could help assess the risk of progression in prediabetes participants.

Systematic review of Mendelian randomization studies on antihypertensive drugs

BACKGROUND

We systematically reviewed Mendelian randomization (MR) studies and summarized evidence on the potential effects of different antihypertensive drugs on health.

METHODS

We searched PubMed and Embase for MR studies evaluating the effects of antihypertensive drug classes on health outcomes until 22 May 2024. We extracted data on study characteristics and findings, assessed study quality, and compared the evidence with that from randomized controlled trials (RCTs).

RESULTS

We identified 2643 studies in the search, of which 37 studies were included. These studies explored a wide range of health outcomes including cardiovascular diseases and their risk factors, psychiatric and neurodegenerative diseases, cancer, immune function and infection, and other outcomes. There is strong evidence supporting the protective effects of genetically proxied antihypertensive drugs on cardiovascular diseases. We found strong protective effects of angiotensin-converting enzyme (ACE) inhibitors on diabetes whereas beta-blockers showed adverse effects. ACE inhibitors might increase the risk of psoriasis, schizophrenia, and Alzheimer's disease but did not affect COVID-19. There is strong evidence that ACE inhibitors and calcium channel blockers (CCBs) are beneficial for kidney and immune function, and CCBs showed a safe profile for disorders of pregnancy. Most studies have high quality. RCT evidence supports the beneficial effects of ACE inhibitors and CCBs on stroke, diabetes, and kidney function. However, there is a lack of reliable RCTs to confirm the associations with other diseases.

CONCLUSIONS

Evidence of the benefits and off-target effects of antihypertensive drugs contribute to clinical decision-making, pharmacovigilance, and the identification of drug repurposing opportunities.

Utilizing genetics and proteomics to assess the role of antihypertensive drugs in human longevity and the underlying pathways: a Mendelian randomization study

BACKGROUND

Antihypertensive drugs are known to lower cardiovascular mortality, but the role of different types of antihypertensive drugs in lifespan has not been clarified. Moreover, the underlying mechanisms remain unclear.

METHODS AND RESULTS

To minimize confounding, we used Mendelian randomization to assess the role of different antihypertensive drug classes in longevity and examined the pathways via proteins. Genetic variants associated with systolic blood pressure (SBP) corresponding to drug-target genes were used as genetic instruments. The genetic associations with lifespan were obtained from a large genome-wide association study including 1 million European participants from UK Biobank and LifeGen. For significant antihypertensive drug classes, we performed sex-specific analysis, drug-target analysis, and colocalization. To examine the mediation pathways, we assessed the associations of 2291 plasma proteins with lifespan, and examined the associations of drug classes with the proteins affecting lifespan. After correcting for multiple testing, genetically proxied beta-blockers (BBs), calcium channel blockers (CCBs), and vasodilators were related to longer life years (BBs: 2.03, 95% CI 0.78-3.28 per 5 mmHg reduction in SBP, CCBs: 3.40, 95% CI 1.47-5.33, and vasodilators: 2.92, 95% CI 1.08-4.77). The beneficial effects of BBs and CCBs were more obvious in men. ADRB1, CACNA2D2, CACNB3, CPT1A, CPT2, and EDNRA genes were related to extended lifespan, with CPT2 further supported by colocalization evidence. Eighty-six proteins were related to lifespan, of which four proteins were affected by CCBs. CDH1 may mediate the association between CCBs and lifespan.

CONCLUSIONS

Beta-blockers, CCBs, and vasodilators may prolong lifespan, with potential sex differences for BBs and CCBs. The role of CCBs in lifespan is partly mediated by CDH1. Prioritizing the potential protein targets can provide new insights into healthy aging.

The causal relationship between antihypertensive drugs and depression: a Mendelian randomization study of drug targets

Background

Depression ranks as a leading contributor to the global disease burden. The potential causal relationship between the use of antihypertensive medications and depression has garnered significant interest. Despite extensive investigation, the nature of this relationship remains a subject of ongoing debate. Therefore, this study aims to evaluate the influence of antihypertensive medications on depression by conducting a Mendelian randomization study focused on drug targets.

Method

We focused on the targets of five antihypertensive drug categories: ACE Inhibitors (ACEIs), Angiotensin II Receptor Antagonists (ARBs), Calcium Channel Blockers (CCBs), Beta-Blockers (BBs), and Thiazide Diuretics (TDs). We collected single-nucleotide polymorphisms (SNPs) associated with these drug targets from genome-wide association study (GWAS) statistics, using them as proxies for the drugs. Subsequently, we conducted a Mendelian randomization (MR) analysis targeting these drugs to explore their potential impact on depression.

Results

Our findings revealed that genetic proxies for Beta-Blockers (BBs) were associated with an elevated risk of depression (OR [95%CI] = 1.027 [1.013, 1.040], p < 0.001). Similarly, genetic proxies for Calcium Channel Blockers (CCBs) were linked to an increased risk of depression (OR [95%CI] = 1.030 [1.009, 1.051], p = 0.006). No significant associations were identified between the genetic markers of other antihypertensive medications and depression risk.

Conclusion

The study suggests that genetic proxies associated with Beta-Blockers (BBs) and Calcium Channel Blockers (CCBs) could potentially elevate the risk of depression among patients. These findings underscore the importance of considering genetic predispositions when prescribing these medications, offering a strategic approach to preventing depression in susceptible individuals.

Prostate cancer genotyping for risk stratification and precision treatment

Prostate cancer (PC) is the most frequently diagnosed cancer and second leading cause of cancer-related deaths in men. It is heterogeneous, as is evident from the wide spectrum of therapeutic approaches. Most patients with PC are initially responsive to androgen deprivation therapy; however, the majority of cases are either hormone-sensitive PC or castration-resistant PC. Current therapeutic protocols follow the evolution of PC, a continuously progressive process involving a combination of widespread genomic alterations. These genomic alterations are either hereditary germline mutations, such as mutations in BRCA2, or specific only to tumor cells (somatic). Tumor-specific genomic spectra include genomic structural rearrangements, canonical androgen response genes, and many other specific genes such as TMPRSS2-ERG fusion, SPOP/FOXA1, TP53/RB1/PTEN, and BRCA2. New evidence indicates the involvement of signaling pathways including PI3K, WNT/β-catenin, SRC, and IL-6/STAT, which have been shown to promote epithelial-mesenchymal transition cancer stem cell-like features/stemness, and neuroendocrine differentiation in PC. Over the last decade, our understanding of the genotype-phenotype relationships has been enhanced considerably. The genetic background of PC related to canonical genetic alterations and signaling pathway activation genes has shed more insight into the molecular subtype and disease landscape, resulting in a more flexible role of individual therapies targeting diverse genotypes and phenotypes.

Association of genetic variants related to combined lipid-lowering and antihypertensive therapies with risk of cardiovascular disease: 2 × 2 factorial Mendelian randomization analyses

BACKGROUND

Lipid-lowering drugs and antihypertensive drugs are commonly combined for cardiovascular disease (CVD). However, the relationship of combined medications with CVD remains controversial. We aimed to explore the associations of genetically proxied medications of lipid-lowering and antihypertensive drugs, either alone or both, with risk of CVD, other clinical and safety outcomes.

METHODS

We divided 423,821 individuals in the UK Biobank into 4 groups via median genetic scores for targets of lipid-lowering drugs and antihypertensive drugs: lower low-density lipoprotein cholesterol (LDL-C) mediated by targets of statins or proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, lower systolic blood pressure (SBP) mediated by targets of β-blockers (BBs) or calcium channel blockers (CCBs), combined genetically lower LDL-C and SBP, and reference (genetically both higher LDL-C and SBP). Associations with risk of CVD and other clinical outcomes were explored among each group in factorial Mendelian randomization.

RESULTS

Independent and additive effects were observed between genetically proxied medications of lipid-lowering and antihypertensive drugs with CVD (including coronary artery disease, stroke, and peripheral artery diseases) and other clinical outcomes (ischemic stroke, hemorrhagic stroke, heart failure, diabetes mellitus, chronic kidney disease, and dementia) (P > 0.05 for interaction in all outcomes). Take the effect of PCSK9 inhibitors and BBs on CVD for instance: compared with the reference, PCSK9 group had a 4% lower risk of CVD (odds ratio [OR], 0.96; 95%CI, 0.94-0.99), and a 3% lower risk was observed in BBs group (OR, 0.97; 95%CI, 0.94-0.99), while combined both were associated with a 6% additively lower risk (OR, 0.94; 95%CI, 0.92-0.97; P = 0.87 for interaction).

CONCLUSIONS

Genetically proxied medications of combined lipid-lowering and antihypertensive drugs have an independent and additive effects on CVD, other clinical and safety outcomes, with implications for CVD clinical practice, subsequent trials as well as drug development of polypills.

The risk of common hypoglycemic and antihypertensive medications and COVID-19: A 2-sample Mendelian randomization study

BACKGROUND

It has been reported that diabetes and hypertension increase the adverse outcomes of coronavirus disease 2019 (COVID-19). Aside from the inherent factors of diabetes and hypertension, it remains unclear whether antidiabetic or antihypertensive medications contribute to the increased adverse outcomes of COVID-19. The effect of commonly used antidiabetic and antihypertensive medications on COVID-19 outcomes has been inconsistently concluded in existing observational studies. Conducting a systematic study on the causal relationship between these medications and COVID-19 would be beneficial in guiding their use during the COVID-19 pandemic.

METHODS

We employed the 2-sample Mendelian randomization approach to assess the causal relationship between 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and 3 commonly used antihypertensive medications (calcium channel blockers [CCB], ACE inhibitors, β-receptor blockers [BB]), and COVID-19 susceptibility, hospitalization, and severe outcomes. The genetic variations in the drug targets of the 5 antidiabetic medications and 3 antihypertensive medications were utilized as instrumental variables. European population-specific genome-wide association analysis (GWAS) data on COVID-19 from the Host Genetics Initiative meta-analyses were obtained, including COVID-19 susceptibility (n = 2597,856), COVID-19 hospitalization (n = 2095,324), and COVID-19 severity (n = 1086,211). The random-effects inverse variance-weighted estimation method was employed as the primary assessment technique, with various sensitivity analyses conducted to evaluate heterogeneity and pleiotropy.

RESULTS

There were no potential associations between the genetic variations in the drug targets of the 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and the 3 commonly used antihypertensive medications (CCBs, ACE inhibitors, BBs) with COVID-19 susceptibility, hospitalization, and severity (all P > .016).

CONCLUSION

The findings from this comprehensive Mendelian randomization analysis suggest that there may be no causal relationship between the 5 commonly used antidiabetic medications (SGLT-2 inhibitors, Sulfonylureas, Insulin analogues, Thiazolidinediones, GLP-1 analogues) and the 3 commonly used antihypertensive medications (CCBs, ACE inhibitors, BBs) with COVID-19 susceptibility, hospitalization, and severity.

The landscape of the methodology in drug repurposing using human genomic data: a systematic review

The process of drug development is expensive and time-consuming. In contrast, drug repurposing can be introduced to clinical practice more quickly and at a reduced cost. Over the last decade, there has been a significant expansion of large biobanks that link genomic data to electronic health record data, public availability of various databases containing biological and clinical information and rapid development of novel methodologies and algorithms in integrating different sources of data. This review aims to provide a thorough summary of different strategies that utilize genomic data to seek drug-repositioning opportunities. We searched MEDLINE and EMBASE databases to identify eligible studies up until 1 May 2023, with a total of 102 studies finally included after two-step parallel screening. We summarized commonly used strategies for drug repurposing, including Mendelian randomization, multi-omic-based and network-based studies and illustrated each strategy with examples, as well as the data sources implemented. By leveraging existing knowledge and infrastructure to expedite the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic uses for approved drugs in a more efficient and targeted manner. However, technical challenges when integrating different types of data and biased or incomplete understanding of drug interactions are important hindrances that cannot be disregarded in the pursuit of identifying novel therapeutic applications. This review offers an overview of drug repurposing methodologies, providing valuable insights and guiding future directions for advancing drug repurposing studies.

Nonlinear relationship between untraditional lipid parameters and the risk of prediabetes: a large retrospective study based on Chinese adults

BACKGROUND

Abnormal lipid metabolism poses a risk for prediabetes. However, research on lipid parameters used to predict the risk of prediabetes is scarce, and the significance of traditional and untraditional lipid parameters remains unexplored in prediabetes. This study aimed to comprehensively evaluate the association between 12 lipid parameters and prediabetes and their diagnostic value.

METHODS

This cross-sectional study included data from 100,309 Chinese adults with normal baseline blood glucose levels. New onset of prediabetes was the outcome of concern. Untraditional lipid parameters were derived from traditional lipid parameters. Multivariate logistic regression and smooth curve fitting were used to examine the nonlinear relationship between lipid parameters and prediabetes. A two-piecewise linear regression model was used to identify the critical points of lipid parameters influencing the risk of prediabetes. The areas under the receiver operating characteristic curve estimated the predictive value of the lipid parameters.

RESULTS

A total of 12,352 participants (12.31%) were newly diagnosed with prediabetes. Following adjustments for confounding covariables, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol were negatively correlated with prediabetes risk. Conversely, total cholesterol, triglyceride (TG), lipoprotein combine index (LCI), atherogenic index of plasma (AIP), non-HDL-C, atherogenic coefficient, Castelli's index-I, remnant cholesterol (RC), and RC/HDL-C ratio displayed positive correlations. In younger adults, females, individuals with a family history of diabetes, and non-obese individuals, LCI, TG, and AIP exhibited higher predictive values for the onset of prediabetes compared to other lipid profiles.

CONCLUSION

Nonlinear associations were observed between untraditional lipid parameters and the risk of prediabetes. The predictive value of untraditional lipid parameters for prediabetes surpassed that of traditional lipid parameters, with LCI emerging as the most effective predictor for prediabetes.

Genetic proxies for antihypertensive drugs and mental disorders: Mendelian randomization study in European and East Asian populations

BACKGROUND

Mental disorders are among the top causes of disease burden worldwide. Existing evidence regarding the repurposing of antihypertensives for mental disorders treatment is conflicting and cannot establish causation.

METHODS

We used Mendelian randomization to assess the effects of angiotensin-converting-enzyme inhibitors (ACEIs), beta blockers (BBs), and calcium channel blockers (CCBs) on risk of bipolar disorder (BD), major depression disorder (MDD), and schizophrenia (SCZ). We used published genetic variants which are in antihypertensive drugs target genes and correspond to systolic blood pressure (SBP) in Europeans and East Asians, and applied them to summary statistics of BD (cases = 41,917; controls = 371,549 in Europeans), MDD (cases = 170,756; controls = 329,443 in Europeans and cases = 15,771; controls = 178,777 in East Asians), and SCZ (cases = 53,386; controls = 77,258 in Europeans and cases = 22,778; controls = 35,362 in East Asians) from the Psychiatric Genomics Consortium. We used inverse variance weighting with MR-Egger, weighted median, weighted mode, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier. We performed gene-specific analysis and utilized various methods to address potential pleiotropy.

RESULTS

After multiple testing correction, genetically proxied ACEIs were associated with an increased risk of SCZ in Europeans (odds ratio (OR) per 5 mmHg lower in SBP 2.10, 95% CI 1.54 to 2.87) and East Asians (OR per 5 mmHg lower in SBP 2.51, 95% CI 1.38 to 4.58). Genetically proxied BBs were not associated with any mental disorders in both populations. Genetically proxied CCBs showed no benefits on mental disorders.

CONCLUSIONS

Antihypertensive drugs have no protection for mental disorders but potential harm. Their long-term use among hypertensive patients with, or with high susceptibility to, psychiatric illness needs careful evaluation.

Unraveling Potential Sex-Specific Effects of Cardiovascular Medications on Longevity Using Mendelian Randomization

BACKGROUND

Establishing the sex-specific efficacy of cardiovascular medications is pivotal to evidence-based clinical practice, potentially closing the gender gap in longevity. Trials large enough to establish sex differences are unavailable. This study evaluated sex-specific effects of commonly prescribed cardiovascular medications on lifespan.

METHODS AND RESULTS

In a two-sample Mendelian randomization study, established genetic variants mimicking effects of lipid-lowering drugs, antihypertensives, and diabetes drugs were applied to genetic associations with lifespan proxied by UK Biobank maternal (n=412 937) and paternal (n=415 311) attained age. Estimates were obtained using inverse variance weighting, with sensitivity analyses where possible. For lipid-lowering drugs, genetically mimicked PCSK9 (proprotein convertase subtilisin/kexin type 9) inhibitors were associated with longer lifespan, particularly in men (2.39 years per SD low-density lipoprotein cholesterol reduction [95% CI, 0.42-4.36], P for interaction=0.14). Genetically mimicked treatments targeting APOC3, LPL, or possibly LDLR were associated with longer lifespan in both sexes. For antihypertensives, genetically mimicked β-blockers and calcium channel blockers were associated with longer lifespan, particularly in men (P for interaction=0.17 for β-blockers and 0.31 for calcium channel blockers). For diabetes drugs, genetically mimicked metformin was associated with longer lifespan in both sexes. No associations were found for genetically mimicked statins, ezetimibe, or angiotensin-converting enzyme inhibitors.

CONCLUSIONS

PCSK9 inhibitors, β-blockers, and calcium channel blockers may prolong lifespan in the general population, particularly men. Treatments targeting APOC3, LPL, or LDLR and metformin may be relevant to both sexes. Whether other null findings are attributable to lack of efficacy requires investigation. Further investigation of repurposing should be conducted.

Association between blood pressure and different antihypertensive drugs with outcome after ischemic stroke: A Mendelian randomization study

BACKGROUND

Observational studies suggest an association between blood pressure (BP) and functional outcomes in ischemic stroke patients but whether this is causal or due to confounding is uncertain. We used Mendelian randomization (MR) to assess causality, and also explore whether particular classes of anti-hypertensives were associated with a better outcome after ischemic stroke.

METHODS

We selected genetic variants associated with systolic and diastolic BP and BP-lowering variants in genes encoding antihypertensive drugs from genome-wide association studies (GWAS) on 757,601 individuals. The primary outcome was 3-month dependence or death defined as a modified Rankin Scale (mRS) of 3-6. The secondary outcome was disability or death after 90 days defined as mRS 2-6. Cochran's Q statistic in the inverse variance weighted (IVW) model, the weighted median, MR-Egger regression, leave-one-single-nucleotide polymorphism (SNP)-out analysis, MR-Pleiotropy Residual Sum and Outlier methods were adopted as sensitivity analyses. To validate our primary results, we performed independent repeat analyses and Bi-directional MR analyses.

RESULTS

Genetic predisposition to higher systolic and diastolic BP was associated with disability or death after ischemic stroke in univariable IVW MR analysis (odds ratio (OR) 1.29, 95% confidence interval (CI): 1.05-1.59, p = 0.014; OR 1.27, 95% CI: 1.07-1.51, p = 0.006, respectively). Pulse pressure was associated with both dependence or death and disability or death after ischemic stroke (OR = 1.05, 95% CI: 1.02-1.08, p = 0.002; OR = 1.04, 95% CI = 1.01-1.07, p = 0.009, respectively). Angiotensin-converting enzyme inhibitor (ACEI) and calcium channel blocker (CCB) were significantly associated with improved functional outcomes (dependence or death, OR 0.76, 95% CI: 0.62-0.94, p = 0.009; OR 0.89, 95% CI: 0.83-0.97, p = 0.005). Proxies for β-blockers, angiotensin receptor blockers (ARB), and thiazides failed to show associations with functional outcomes (p > 0.05).

CONCLUSION

We provide evidence for an association of genetic predisposition to higher BP with a higher risk of 3-month functional dependence after ischemic stroke. Our findings support ACEI and CCB as promising antihypertensive drugs for improving functional outcomes in ischemic stroke.

Effects of blood pressure and antihypertensive drugs on osteoarthritis: a mendelian randomized study

BACKGROUND

Previous studies have suggested that antihypertensive drugs may play a role in the treatment of osteoarthritis, but these studies may be limited by confounding factors and lead to biased results. Therefore, we conducted a Mendelian randomization study to investigate the effects of blood pressure and antihypertensive drugs on osteoarthritis.

METHODS

We used published large-scale genome-wide association data and applied univariate and multivariate Mendelian randomization methods. The main analysis model was inverse variance weighting, and the reliability of the results was tested using MR-Egger intercept analysis, Cochran's Q test, and leave-one-out analysis. We comprehensively evaluated the relationship between systolic blood pressure, diastolic blood pressure, 12 antihypertensive drugs, and osteoarthritis. We also conducted verification in the independent queue of UK Biobank and built a simple linear regression model to obtain an independent comparison.

RESULTS

We found no evidence that systolic and diastolic blood pressure significantly affected osteoarthritis. However, among antihypertensive drugs, we observed a significant positive correlation between potassium-preserving diuretics and aldosterone antagonists and all osteoarthritis (OR: 0.560, 95% CI 0.406-0.772, P = 0.0004). Sensitivity analysis showed no horizontal pleiotropy or heterogeneity, and the leave-one-out analysis demonstrated the reliability of the results. This result was replicated with nominally statistical significance in the validation cohort and exhibited significant correlation in the linear regression analysis.

CONCLUSIONS

Our study suggested that controlling the protein targets of potassium-sparing diuretics and aldosterone antagonists may have beneficial results for osteoarthritis. These findings provide valuable medication strategies for the control of hypertension in patients with osteoarthritis.

Insights into Causal Cardiovascular Risk Factors from Mendelian Randomization

PURPOSE OF THE REVIEW

This review summarizes major insights into causal risk factors for cardiovascular disease (CVD) by using Mendelian randomization (MR) to obtain unconfounded estimates, contextualized within its strengths and weaknesses.

RECENT FINDINGS

MR studies have confirmed the role of major CVD risk factors, including alcohol, smoking, adiposity, blood pressure, type 2 diabetes, lipids, and possibly inflammation, but added that the relation with alcohol is likely linear, confirmed the role of diastolic blood pressure, identified apolipoprotein B as the major target lipid, and foreshadowed results of some trials concerning anti-inflammatories. Identifying a healthy diet and the role of early life influences, such as birth weight, has proved more difficult. Use of MR has winnowed empirically driven hypotheses about CVD into a set of genetically validated targets of intervention. Greater inclusion of global diversity in genetic studies and the use of an overarching framework would enable even more informative MR studies.

Correlation between the triglyceride-to-high-density lipoprotein cholesterol ratio and other unconventional lipid parameters with the risk of prediabetes and Type 2 diabetes in patients with coronary heart disease: a RCSCD-TCM study in China

Objective

Type 2 diabetes mellitus (T2DM) is often accompanied by undiagnosed dyslipidemia. Research on the association of unconventional lipid markers with prediabetes (pre-DM) and T2DM simultaneously is limited in coronary heart disease (CHD) patients.

Methods

This study included 28,476 patients diagnosed with CHD. Their lipid levels, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), were measured, and non-traditional lipid parameters were calculated. The patients were divided into three groups based on the diabetic status including normoglycemic (NG), pre-DM, and T2DM. Multiple logistic regression was used to compare the association of TG/HDL-C and other non-traditional lipid parameters with pre-DM and T2DM. The tertiles of TG/HDL-C included T1 (TG/HDL-C < 1.10), T2 (1.10 ≤ TG/HDL-C ≤ 1.89) and T3 (TG/HDL-C > 1.89). Low and high TG/HDL-C was defined with sex-specific cutoff points.

Results

Multiple logistic regression results showed that the non-traditional lipid parameters, including non-HDL-C, LDL-C/HDL-C, TC/HDL-C, non-HDL-C/HDL-C and TG/HDL-C, were all correlated with the risk of pre-DM and T2DM. Meanwhile TG/HDL-C showed the strongest correlation (odds ratio [OR]: 1.19; 95% confidence interval [CI] 1.16–1.23), (OR: 1.36; 95% CI 1.33–1.39). When dividing TG/HDL-C into tertiles, using T1 as a reference, T3 was observed to have the highest association with both pre-DM and T2DM (OR: 1.60; 95% CI 1.48–1.74), (OR: 2.79; 95% CI 2.60–3.00). High TG/HDL-C was significantly associated with pre-DM and T2DM (OR: 1.69; 95% CI 1.52–1.88), (OR: 2.85; 95% CI 2.60–3.12). The association of TG/HDL-C with T2DM and pre-DM existed across different sex, age, smoking, and drinking statuses.

Conclusion

Elevated non-traditional lipid parameters were significantly associated with pre-DM and T2DM in CHD patients, especially TG/HDL-C. High TG/HDL-C was the risk factor with a strong correlation with the risk of pre-DM and T2DM.