Pharmacogenomics in antipsychotics 2.pptx

Pharmacogenomics in antipsychotics

1. Pharmacogenomic Variations and CNS Medications 11. Explore how pharmacogenomics variations can influence individual responses to CNS medications targeting neurotransmiter systems. Provide examples of how genetic polymorphisms may affect drug metabolism and efficacy. by NKALUBO ISAAC

2. Introduction

3. Influence on Drug Metabolism Genetic polymorphisms in cytochrome P450 (CYP) enzymes are among the most studied, as many CNS drugs are substrates for these liver enzymes. Individuals are classified as poor, intermediate, extensive (normal), or ultra-rapid metabolizers based on their genotypes, which can drastically alter drug plasma concentrations and thus clinical outcomes.

4. CYP2D6 Polymorphisms This enzyme metabolizes numerous antidepressants and antipsychotics. Poor metabolizers (e.g., due to *3, *4, *5, or *6 alleles) experience reduced clearance, leading to higher drug levels and increased risk of side effects like sedation or cardiovascular issues. For example, with the antidepressant paroxetine (an SSRI targeting serotonin reuptake), poor CYP2D6 metabolizers may require lower doses to avoid toxicity, while ultra-rapid metabolizers might need higher doses for efficacy. Similarly, for venlafaxine (an SNRI affecting serotonin and norepinephrine), poor metabolizers show elevated active metabolite levels, enhancing efficacy but raising side effect risks. In antipsychotics like risperidone (which modulates dopamine and serotonin receptors), CYP2D6 poor metabolizers have higher exposure to the active form, increasing the likelihood of extrapyramidal symptoms. 10

5. CYP2C19 Polymorphisms

6. Other CYP Enzymes CYP1A2 variations influence clozapine (an atypical antipsychotic for dopamine and serotonin systems), where poor metabolizers risk agranulocytosis due to accumulation, while inducers like smoking can reduce efficacy in certain genotypes. CYP3A4 polymorphisms can affect metabolism of drugs like quetiapine.

7. Influence on Drug Efficacy Polymorphisms in genes directly involved in neurotransmitter systems can modulate how well a drug engages its target, independent of or in addition to metabolism effects.

8. Serotonin Transporter (SLC6A4/5-HTTLPR) The promoter region has long (L) and short (S) alleles. Individuals with the S/S genotype often show reduced transporter expression, leading to poorer response to SSRIs like fluvoxamine in treating depression or delusional states, as the drug’s ability to increase synaptic serotonin is blunted. This can result in treatment resistance, requiring alternative therapies.

9. Dopamine Receptors The DRD2 Taq I polymorphism is linked to better response to nemonapride (a dopamine antagonist) in schizophrenia but higher risk of tardive dyskinesia with long-term antipsychotics. DRD3 Ser9Gly variants show marginal associations with clozapine efficacy and drug-induced movement disorders. DRD4 polymorphisms have mixed effects on typical antipsychotics.

10. Catechol-O-Methyltransferase (COMT) The Val158Met polymorphism affects dopamine breakdown in the prefrontal cortex. Met/Met individuals have lower enzyme activity, leading to higher dopamine levels, which can enhance response to dopamine-modulating drugs like antipsychotics or levodopa in Parkinson’s but increase pain sensitivity in chronic conditions.

11. Opioid Receptor (OPRM1) The A118G SNP reduces mu-opioid receptor binding, diminishing efficacy of opioids like morphine (targeting endogenous opioid neurotransmitters) for pain, while increasing addiction risk in some populations. Combined with CYP2D6, this affects codeine conversion to morphine, where poor metabolizers get minimal analgesia.

12. Other Examples Alpha-7 nicotinic receptor variations alter response to cholinergic drugs in Alzheimer’s or schizophrenia. 5-HT2A/2C polymorphisms influence clozapine’s antipsychotic effects. BDNF(brain derived neurotropic Factor) and IL-6 variants modulate pain and antidepressant responses in neuropathic conditions.

13. Conclusion Overall, these variations underscore the need for pharmacogenetic testing (e.g., via CPIC guidelines) to personalize dosing and drug selection, potentially improving outcomes in psychiatric and neurological disorders while reducing adverse events. However, responses are often polygenic, involving interactions between multiple variants and environmental factors.

14. Refrences List of sources (e.g., from prior discussion: CPIC guidelines, studies on CYP enzymes, receptor polymorphisms). Additional Reading: Reviews from NCBI, FDA pharmacogenomics labels.