Chronic Inflammation, Dyslipidemias, Hypertension, Inflammatory Cytokines, Inflammatory Response
Conditions
Keywords
Antihypertensive Drugs, Lipid-Lowering Drugs, Mendelian Randomization, ACE Inhibitors, ARBs, HMG-CoA Reductase Inhibitors, PCSK9 Inhibitors, NPC1L1 Inhibitors, IL-1β, TNF-α, CRP, MCP-1, Inflammatory Pathways, Genetic Association Studies, Causal Inference
Brief summary
This study investigates the causal relationships between antihypertensive and lipid-lowering drugs and inflammatory cytokines using a drug-targeted Mendelian randomization approach. By leveraging genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) data, the study evaluates the effects of angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), HMG-CoA reductase inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors on key inflammatory cytokines such as IL-1β, TNF-α, CRP, and MCP-1. The findings aim to provide insights into the prevention and control of excessive inflammatory responses, particularly in patients with hypertension and dyslipidemia, by assessing the causal effects of these therapies.
Detailed description
This observational study focuses on elucidating the causal relationships between commonly prescribed antihypertensive drugs (ACEIs and ARBs) and lipid-lowering drugs (HMG-CoA reductase inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors) with various inflammatory cytokines, including IL-1β, TNF-α, CRP, MCP-1, and IFN-γ, using a drug-targeted Mendelian randomization (MR) framework. The study employs large-scale genetic data from European populations, drawing from genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) datasets, to construct instrumental variables that mimic the effects of drug exposure. The primary aim is to explore how these pharmaceutical interventions influence inflammatory pathways at the molecular level. The use of MR methods enables causal inference by utilizing genetic variants within or near drug-target genes, allowing for the estimation of downstream effects similar to those produced by actual drug interventions. Key statistical methods, including inverse variance weighting and sensitivity analyses, are applied to ensure robustness and validity of the results. This research provides critical evidence for the selection of antihypertensive and lipid-lowering therapies that not only manage cardiovascular risk factors but also modulate inflammation, contributing to personalized medicine strategies for patients with chronic inflammatory conditions. Furthermore, the findings have broader implications for drug repurposing and the development of new therapeutic targets aimed at mitigating inflammatory processes that underlie various chronic diseases.
Interventions
None listed
Sponsors
Shanghai Guanghua Hospital of Integrated Traditional Chinese and Western Medicine
Guangzhou Institute of Respiratory Disease
Study design
Observational model
COHORT
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Participants aged 18 years or older. * Diagnosed with hypertension, coronary artery disease, or dyslipidemia. * Availability of complete genome-wide data and inflammatory cytokine levels. * Willingness to participate in the study and provide the required clinical data.
Exclusion criteria
* Participants under the age of 18. * Individuals with severe chronic diseases or other conditions that may significantly influence inflammatory responses. * Individuals unwilling or unable to provide necessary clinical or genomic data. * Pregnant or breastfeeding women.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Reduction in IL-6 Levels Due to PCSK9 Inhibitors | Baseline to 12 months | The primary outcome is the reduction in plasma levels of IL-6 in individuals exposed to PCSK9 inhibitors.（Unit: pg/m） |
| Reduction in CRP Levels Due to ACE Inhibitors | Baseline to 12 months | The primary outcome is the reduction in plasma levels of CRP due to exposure to ACE inhibitors (ACEIs). The study evaluates the causal relationship between ACEIs and CRP levels using Mendelian randomization.（Unit: mg/L） |
| Modulation of MCP-1 Levels Due to Statin Therapy | Baseline to 12 months | The primary outcome is the modulation of plasma levels of MCP-1 in patients treated with statins (HMG-CoA reductase inhibitors). The study investigates the effect of statins on MCP-1 levels.（Unit: pg/mL） |
| Modulation of MIP-1α Levels Due to Statin Therapy | Baseline to 12 months | The primary outcome is the modulation of plasma levels of MIP-1α in patients treated with statins (HMG-CoA reductase inhibitors).（Unit: pg/mL） |
| Modulation of MIP-1β Levels Due to Statin Therapy | Baseline to 12 months | The primary outcome is the modulation of plasma levels of MIP-1β in patients treated with statins (HMG-CoA reductase inhibitors).（Unit: pg/mL） |
| Reduction in IL-1β Levels Due to PCSK9 Inhibitors | Baseline to 12 months | The primary outcome is the reduction in plasma levels of IL-1β in individuals exposed to PCSK9 inhibitors.（Unit: pg/mL） |
| Reduction in IL-1β Levels Due to ACE Inhibitors | Baseline to 12 months | The primary outcome is the reduction in plasma levels of IL-1β due to exposure to ACE inhibitors (ACEIs). The study evaluates the causal relationship between ACEIs and IL-1β levels using Mendelian randomization.（Unit: pg/mL） |
| Reduction in TNF-α Levels Due to ACE Inhibitors | Baseline to 12 months | The primary outcome is the reduction in plasma levels of TNF-α due to exposure to ACE inhibitors (ACEIs). The study evaluates the causal relationship between ACEIs and TNF-α levels using Mendelian randomization.（Unit: pg/mL） |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Changes in LDL-C Levels Due to Statin Therapy | Baseline to 24 months | This outcome examines changes in LDL cholesterol (LDL-C) levels due to statin therapy. |
| Changes in HDL-C Levels Due to Statin Therapy | Baseline to 24 months | This outcome examines changes in HDL cholesterol (HDL-C) levels due to statin therapy. |
| Reduction in IL-1β Levels Due to PCSK9 Inhibitors | Baseline to 24 months | The secondary outcome measures the reduction in IL-1β levels linked to PCSK9 inhibitors. |
| Changes in Cardiometabolic Outcomes Due to PCSK9 Inhibitors | Baseline to 24 months | This secondary outcome measures changes in cardiometabolic outcomes, including changes in lipid levels and inflammatory cytokine profiles. |
| Reduction in Cardiovascular Events Due to Antihypertensive Therapy | Baseline to 24 months | The secondary outcome evaluates the reduction in cardiovascular events (e.g., myocardial infarction, stroke) linked to antihypertensive therapies such as ACEIs and ARBs. |
Countries
China
Outcome results
None listed