L5: Pharmacogenomics of Hypertension
Presenter: Catrin McDonough.
Topic: Hypertension pharmacogenomics is a field that explores how genetic factors influence the response to medications used to treat high blood pressure (hypertension). It includes examining how different people’s blood pressure (BP) responds to these medications over the long term and how that affects health outcomes.
Primary Goal: The aim is to shift from a "one-size-fits-most" treatment model, where everyone gets the same medication and dose for hypertension, to a precision medicine approach. This means using genetic profiling, which involves understanding an individual's unique genetic makeup, to target specific therapies that are most likely to work for them based on their genetic profile, environment, and lifestyle. This approach hopes to improve treatment effectiveness and reduce side effects.
The Rationale for Pharmacogenomics (PGx)
Standard Dosing Model: Most medications are dosed based on a generic model called "one-size-fits-most". This model is developed during typical drug development through tests and trials but often overlooks individual differences.
High Non-Responder Rates: A significant number of patients do not respond positively to the first medication prescribed. For example, many people do not respond to thiazide diuretics, a common antihypertensive medication. This high rate of non-response led to a search for more personalized treatment options.
Historical Context: The promise of pharmacogenomics isn't new. A 2001 article in Newsweek titled "Made-to-Order Medicine" highlighted the potential of tailoring medical treatments to individual genetic profiles to enhance effectiveness and mitigate side effects.
Precision Medicine Initiative: This term gained popularity after former President Barack Obama's 2015 State of the Union address, which called for an innovative approach to disease prevention and treatment. It emphasizes recognizing individual differences based on genetics, environments, and lifestyles rather than relying on generalized treatments.
The All of Us Research Program: This is a significant project led by the National Institutes of Health (NIH) that is part of the precision medicine initiative. It aims to collect diverse genetic information and Electronic Health Records (EHR) to aid research. Researchers from various institutions, including the University of Florida, have access to this data to study and improve treatment options.
Defining Pharmacogenetics vs. Pharmacogenomics
Both fields are commonly abbreviated as PGx. It is important to understand the differences between them.
Pharmacogenetics: This area studies how genetic differences in a single variation or gene affect how a drug is processed in the body.
Example: Researchers might study specific changes in a gene known as and how these variations impact the effectiveness of the beta-blocker medicine atenolol, which is commonly used to treat high blood pressure.
Pharmacogenomics: This field has a broader scope. It looks across the entire genome to understand how multiple genes and various genetic changes determine how an individual responds to drugs.
Example: A genome-wide association study (GWAS) could be conducted to find out how genes affect an individual's blood pressure response to hydrochlorothiazide (HCTZ), another medication for hypertension.
Relationship Between Drug Concentration and Response
The Ideal Relationship: In theory, as the concentration of a drug in the body increases (shown on a graph with concentration on the x-axis and response on the y-axis), the drug’s effectiveness or response should also increase linearly.
Efficacy Threshold: This is the minimum concentration of a drug needed to produce a noticeable clinical effect or response. It’s essential for doctors to have this knowledge to avoid underdosing or overdosing patients.
Toxicity Threshold: This is the concentration level at which the drug begins to cause harmful side effects or toxic reactions in the body. The goal of treatment is to keep medication doses below this toxicity level.
Variability in Responses: Individuals may show varied responses to medications:
Resistant Individuals/Poor Responders: These individuals might have high drug concentrations in their bodies but experience low or no positive effects.
Sensitive Individuals: Conversely, these patients might get the desired effects with a low concentration of the medication but face a higher risk of severe side effects or toxicity.
PGx Utility: Through genotyping, which is a method to analyze DNA, patients can be categorized into groups based on their likely response to medications:
Responders: These patients typically can take standard doses of conventional drugs successfully.
Non-Responders/Toxic Responders: This group may need alternative medications or dose adjustments to avoid adverse effects or get the desired therapeutic response.
Clinical Landscape of Hypertension
Epidemiology: Currently, more than billion people worldwide are affected by high blood pressure, including nearly half of all American adults. This shows that hypertension is a prevalent health issue that requires effective management.
Empiric Treatment: Managing hypertension often involves a trial-and-error approach. Doctors choose from four first-line classes of medications to treat high blood pressure:
Diuretics: Help eliminate excess fluid by promoting urination.
ACE inhibitors: Help relax blood vessels by blocking the formation of a hormone that constricts them.
Angiotensin Receptor Blockers (ARBs): Similar to ACE inhibitors, they prevent blood vessel constriction.
Calcium Channel Blockers (CCBs): These help lower blood pressure by relaxing the muscles of the heart and blood vessels.
First-Line Exceptions: Beta-blockers, which lower heart rate and blood pressure, are no longer considered a universal first-line treatment. They are now recommended primarily for patients with specific health issues alongside hypertension.
Efficiency Problems: Each medication type is effective in only about 50\text{\text{%}} of patients. This trial-and-error method often leads to patients needing more visits to doctors for adjustments, known as titration or switching of medications. Alarmingly, only about half of those with hypertension manage to lower their blood pressure effectively. This is a significant issue, leading to higher instances of polypharmacy, which is the practice of adding extra medications when one might not be working instead of finding the right medication initially.
Heritability and Pathophysiology
Hypertension Heritability: It is estimated that between 30-60\text{\text{%}} of cases of hypertension are genetically inherited. Researchers typically identify heritability through studies examining family patterns and histories of high blood pressure.
Pharmacogenomic Heritability: Determining pharmacogenomic heritability is more complex since it requires both a parent and a child to be taking the same medication at the same time in their lives with similar health conditions. Presently, studies often rely on polygenic models looking at unrelated individuals.
Ancestry-Based Differences in Pathophysiology: Genetic ancestry can influence how hypertension develops and how individuals respond to treatment:
European Ancestry (Self-Identifying as White): Predominantly, hypertension is linked to the Renin-Angiotensin-Aldosterone System (RAAS), which regulates blood pressure. These individuals tend to respond better to beta-blockers.
African Ancestry (Self-Identifying as Black): Often, hypertension is influenced by salt sensitivity, and these individuals may see improvement more quickly with dietary changes, particularly a low-salt diet or thiazide diuretics.
Genetic Study Designs in PGx
Family-Based Studies (Linkage Design): This type of study focuses on tracking genomic regions that are linked with particular traits within families. It is most useful for studying conditions caused by a single gene, known as Mendelian diseases.
Association Studies (Unrelated Individuals): These studies are designed for complex diseases like hypertension, where many genes subtly contribute to the condition.
Advantage of PGx Association Studies: Pharmacogenomic traits often show larger effects than general disease genetics. For instance, examining how blood pressure responds to a drug is usually more direct than the broader study of hypertension itself, allowing researchers to work with smaller sample sizes.
Experimental Approaches to Discovery
Candidate Gene Approach: Researchers target specific genes they know are connected to drug targets and metabolism.
Examples: The gene is relevant for beta-blockers, and relates to calcium channel blockers.
Genome-Wide Association Studies (GWAS): This more expansive approach searches the entire genome for common variants that are associated with specific traits.
Advances in genomic technologies, like the Human Genome Project, have made these studies possible.
It utilizes Linkage Disequilibrium (LD): The human genome is inherited in blocks, so researchers can study representative variations (SNPs) for each block instead of analyzing every single variant.
Limitation: Often, results show associations with SNPs that are correlated with the functional variant, meaning side effects. More studies are then needed to definitively identify impacts on gene expression or other biological factors.
Detailed Phenotypes in Hypertension PGx
Long-Term Cardiovascular (CV) Outcomes: These studies track significant health events like all-cause death, non-fatal strokes, and heart attacks by using data from large clinical trials such as the INVEST study.
Blood Pressure (BP) Lowering: This metric serves as an outcome indicator to gauge the effectiveness of treatment after a specific period, often monitored within weeks (as seen in the PEAR study).
Adverse Metabolic Responses: Researchers focus on side effects related to blood pressure medications, including changes in glucose levels, the risk of developing diabetes, or lipid level changes, which can have broader health implications.
Key Study: PEAR (Pharmacogenomic Evaluation of Antihypertensive Responses)
Design: This key study involved multiple sub-studies (PEAR and PEAR2) concentrating on patients diagnosed with mild-to-moderate, uncomplicated hypertension.
Methodology: Participants were assigned to medication treatment groups, prioritized through randomization to ensure unbiased results. Some patients received monotherapy (one drug) while others underwent combination therapy after a washout period (when medications are paused). Two drug types studied included beta-blockers (atenolol/metoprolol) and thiazide diuretics (HCTZ/chlorthalidone).
Scale: Clinical sites involved in the study included the University of Florida, Emory University, and the Mayo Clinic. Over patients were enrolled; roughly were randomized and more than completed all aspects of the study, attending between clinic visits over a month period for thorough evaluations.
Specific Gene Examples: ADRB1, PRKCA, and CACNA1C
ADRB1 (Beta-One Adrenergic Receptor)
Variants: Two notable genetic variants of this receptor are Ser49Gly (found in the extracellular part of the receptor) and Gly389Arg (located in the cytoplasm).
SR Haplotype: Individuals carry a specific combination of the Serine 49 and Arginine 389 mutations.
Findings: Those homozygous for the SR/SR haplotype responded best to beta-blocker treatments, showing the most significant drop in diastolic blood pressure. Notably, individuals who did not identify as Black and had zero copies of the glycine allele at position experienced significantly higher blood pressure responses.
PRKCA (Protein Kinase C Alpha)
Discovery: This gene was identified through a GWAS that focused on responses to HCTZ in the PEAR and GARA studies.
Significance: The most prominent SNP associated with this gene reached a significant level of statistical importance (with P < 3.3 \times 10^{-8}).
Genotype Impact: Patients with the AA or AG alleles had a more substantial blood pressure reduction in response to HCTZ compared to those with the GG genotype.
Functional Validation: Individuals with the GG genotype displayed significantly lower levels of gene expression, indicating its role in crucial processes like calcium signaling, which is essential for blood vessel contraction and sodium reabsorption.
INVEST Study and CACNA1C
Scale: Conducted on over patients with existing coronary artery disease and hypertension, including about genetic samples for analysis.
Treatment: Examined two therapeutic strategies: one using the drug verapamil and another using atenolol.
ADRB1 Finding in INVEST: Carriers of the SR haplotype taking atenolol showed lower mortality risks compared to those on verapamil, which suggested that atenolol could mitigate genetic risks associated with hypertension.
CACNA1C (L-type Calcium Channel Alpha-1C Subunit): Notably, the study revealed that individuals with the AA genotype did better on a calcium channel blocker strategy, while those with the GG genotype showed better outcomes with beta-blockers.
The International Consortium for Antihypertensive Pharmacogenomics (ICAPs)
Purpose: This group's goal is to promote research discoveries using meta-analyses across diverse populations from different continents, allowing for a broader understanding of pharmacogenomic responses.
HCTZ Meta-Analysis: This research successfully identified and confirmed significant genes and linked to hypertension treatment responses among individuals of both European and African ancestry.
Beta-Blocker Meta-Analysis: A particular genetic variation (missense SNP) located in the gene was found to be associated with the response to systolic blood pressure in patients taking beta-blockers.
NMT Gene: Identified through a genome-wide interaction meta-analysis, where a specific SNP suggested that beta-blocker treatment raised the chance of primary outcomes (negative responses) for certain genotypes, whereas non-beta-blocker treatments led to reduced risks for those same genetic profiles.
Emerging Methods and Biobanks
Polygenic Risk Scores (PRS): This innovative method involves incorporating vast amounts of SNPs, each weighed by their effect size, to assess an individual’s overall genetic risk or likely response to specific medications.
Mendelian Randomization: This technique employs genetic variations as instruments to determine if there is a cause-and-effect relationship between specific risk factors and health outcomes.
Multi-omics: A new trend involves combining various biological data layers, like genomic data with transcriptomics, which studies RNA levels and gene expression to provide a holistic view of biological processes.
Biobanks/EHR Data: Large repositories of data play a critical role in advancing pharmacogenomics:
UK Biobank: Collects extensive health-related data from thousands of patients.
All of Us: A project designed to gather comprehensive health data from a diverse population.
Million Veterans Program: Focuses on understanding health conditions among veteran patients.
BioVue (Vanderbilt): A biobank that aids in pharmacogenomic research.
OneFlorida / UF IDR: Employed for important epidemiological studies linked to pharmacogenomics.
Clinical Implementation Resources
CPIC (Clinical Pharmacogenetics Implementation Consortium): Created in 2009, this organization offers evidence-based guidelines that help healthcare providers integrate pharmacogenomics into clinical settings effectively.
IGNITE (Implementing Genomics in Practice): A network funded by the NIH that carried out practical clinical trials involving approximately patients, focusing specifically on therapeutic areas related to blood pressure.
UF Health Precision Medicine Program: This program leads in clinical implementation efforts, advocating for applying genetic insights to patient care to improve outcomes.
Summary of the PGx Pipeline
Discovery: Researchers use linkage or association studies to identify genetic traits associated with drug response.
Validation: These findings are replicated and further studied to prove their reliability.
Translation: Involves drug repurposing, identifying new drug targets, and stratifying patient risk levels based on genetics.
Clinical Trials: Pragmatic tests are conducted to check the real-world effectiveness of employing these findings.
Implementation: Finally, the findings are integrated into routine clinical practice to enhance patient care and treatment outcomes.