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Pharmacogenetic Testing

Improving Outcomes and Reducing Healthcare Costs for Diabetes and Its Comorbidities With Pharmacogenetics Guided Medication Therapy

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'Pharmacogenomics, the study of genetic mediators of medication response, has demonstrated success in improving pharmacotherapy outcomes across a range of medical conditions.'Click To Tweet
Volume 5 White Paper – Improving Outcomes and Reducing Healthcare Costs for Diabetes and Its Comorbidities with Pharmacogenetics Guided Medication Therapy

 

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Pharmacogenetics in Practice

Volume 5

 

Improving Outcomes and Reducing Healthcare Costs for Diabetes and Its Comorbidities With Pharmacogenetics Guided Medication Therapy

 

Introduction

 

Diabetes continues to be a growing epidemic in the United States and one of the more costly conditions to treat long-term. Data from the 2017 Centers for Disease Control (CDC) report on diabetes indicates that 30.3 million people (9.4%) in the United States, and over 25% of those aged 65 or older, had diabetes in 2015, with an estimated 1.5 million new cases each year.1 Moreover, an estimated 33.9% of US adults had prediabetes, including nearly half of those aged 65 years or older. The social and economic burden of diabetes is likewise staggering. Diabetes was the seventh leading cause of death in the United States in 2015. Total direct and indirect estimated costs of diagnosed diabetes was $245 billion, accounting for over 20% of health care dollars in the US.2

 

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Care for diabetes patients is complicated by the presence of comorbid conditions. Approximately half of adults with diabetes have at least one comorbid chronic disease and 40% of elderly adults with diabetes have four or more comorbid conditions,3,4 exceeding all other major chronic conditions except ischemic heart disease in extent of comorbidities.3 Hyperlipidemia (77% comorbidity), hypertension (49% comorbidity), and coronary artery disease (11% comorbidity), are among the most common comorbid conditions due to their pathophysiological overlap with diabetes.5,6 Unsuccessful management of these conditions in diabetic patients can result in significantly greater cost burden and reductions in quality of life.7 Indeed, cardiovascular disease is the primary cause of mortality in diabetes.8 Conversely, effective management of cardiovascular conditions can enhance the management of diabetes.9 Other conditions such as depression (19% comorbidity)3,6 also worsen diabetes outcomes by causing poorer adherence to medications and self-management.10 Similar to cardiovascular conditions, effective management of these conditions can reduce economic burden and can improve glycemic outcomes and quality of life.10-14

 

Pharmacogenomics, the study of genetic mediators of medication response, has demonstrated success in improving pharmacotherapy outcomes across a range of medical conditions. Briefly, pharmacogenomic testing evaluates variants in genes known to affect the pharmacokinetics or mechanism of action of a medication. Specifically, much research has focused on the CYP450 genes, which encode enzymes involved in first pass metabolism of many medications. Variation in these genes can increase or reduce clearance of medications from the body, predisposing individuals to a decrease in medication efficacy and an increase in the prevalence of sometimes life-threatening adverse drug reactions. Pharmacogenomic implementation guidelines have been published for medications used to treat a number of common chronic conditions such as depression, cardiovascular disease, and chronic pain, among others.15-20

 

Surprisingly, genetic variation in pharmacogenomic genes is quite common; virtually every individual (90-99%)21-22 carries at least one clinically actionable variant. Pharmacogenomic variation does not typically pose health risks until one is exposed to a drug for which the variant is relevant. However, increased exposure to medications due to medical comorbidities will increase the occurrence of gene-drug interactions. The frequency of comorbidity and polypharmacy in the diabetic population makes this condition a prime target for pharmacogenetic intervention. In this white paper, we will review the evidence supporting the association of genetic variation with medication outcomes for medications used to treat diabetes and its common comorbidities: hypertension, hyperlipidemia, major adverse cardiovascular events, and depression. Given that type 1 diabetes accounts for only 5-10% of all diabetes cases,1 this review will primarily focus on management of type 2 diabetes (T2DM).

 

Pharmacogenomics of Diabetes Management

 

Pharmacotherapy for diabetes mellitus consists of a number of agents that differ in their pharmacokinetics, mechanism of action, efficacy, and side effect profile.

 

Metformin

Metformin is considered first-line monotherapy for type 2 diabetes by both the American Diabetes Association (ADA) and the American Association of Clinical Endocrinologists (AACE).8 Metformin is not metabolized, thus avoiding the polymorphic CYP450 family of enzymes. Some studies have focused on genetic variation in organic cation transporters responsible for metformin uptake into the bloodstream and hepatocytes or secretion into the renal tubular cells, with mixed results.23-28 Another gene, ATM, which encodes a serine/threonine kinase, initially showed promise for predicting metformin effects on HbA1C values,29,30 but failed to replicate in a later large study.31 More research is needed to conclusively demonstrate an effect of these polymorphisms on metformin response.

 

Sulfonylureas

Sulfonylurea medications are generally divided into first-generation medications (including chlorpropamide, tolazamide, and tolbutamide) and second-generation medications (including glipizide, glyburide, and glimepiride). While they remain the second most commonly prescribed oral medications for the treatment of T2DM, their place in treatment algorithms has become more controversial with the approval of newer medications that are less prone to cause hypoglycemia. The ADA recommends sulfonylurea use equally to other second-line agents, while the AACE recommends their use only after lower-risk medications have been tried.8

 

All of the second-generation sulfonylureas (as well as tolbutamide) are metabolized by CYP2C9, and several studies have demonstrated an impact of CYP2C9 genetic variation on serum levels of these medications. For example, in 2010, Zhou et al found that carriers of the CYP2C9*2 and *3 alleles were 3-4 times more likely to achieve target HbA1c after 18 months of initiation of a combination of sulfonylurea and metformin, compared with patients with the normal function genotype.32 Variant allele carriers were also less likely to experience treatment failure with sulfonylurea monotherapy compared to functional allele carriers. Similarly, Becker et al found that CYP2C9*2 and *3 carriers needed a lower tolbutamide dose to achieve optimal outcome.33 Furthermore, a study of Indian patients with T2DM showed that CYP2C9*2 and *3 allele carriers had a better response to glyburide without an increase in risk of hypoglycemia.34 Finally, a small study of glimepiride in Asian patients showed a greater mean change in HbA1c levels at 6 months among CYP2C9*3 carriers.35

 

Thiazolidinediones

Pioglitazone and rosiglitazone are the two thiazolidinedione medications that are FDA-approved for T2DM. While the ADA considers these medications second-line agents, the AACE lists them as fifth line agents due to their risk of causing edema, heart failure, and fractures.8 Both medications are metabolized primarily by CYP2C8 and to a lesser extent by CYP2C9 and CYP3A4.36 These medications are distributed into the hepatocytes by an organic anion transporter encoded by the SLCO1B1 gene, which has genetic polymorphisms known to impact response to statin medications.18 Only one study has examined the impact of these genes on thiazolidinedione outcomes. Dawed et al found that the CYP2C8*3 variant was associated with reduced glycemic response to rosiglitazone, while the SLCO1B1 rs4149056 variant was associated with improved glycemic response.37

 

Newer Classes

Newer classes of oral glucose lowering agents that have come to market in the last 10 years include DPP- 4 inhibitors, SGLT2 inhibitors, and GLP1 agonists. Because of their recent entry to the market, most of these medications have not yet been extensively studied for pharmacogenomic associations.

 

DPP-4 inhibitors include sitagliptin, saxagliptin, linagliptin and alogliptin. They are considered second- line agents by the ADA, but fourth line agents by the AACE.8 Like metformin, most are renally excreted and avoid metabolism by CYP450 enzymes.36 One exception, saxagliptin, is metabolized by CYP3A4/5 but has not yet been evaluated for an association with any of the known polymorphisms in CYP3A4 and CYP3A5. One recent study implicated a single polymorphism near the CTRB1 and CTRB2 genes in response to DPP-4 inhibitors38 but this finding has not yet been replicated.

 

SGLT2 inhibitors include dapagliflozin, empagliflozin and canagliflozin. They are considered second line agents by the ADA and third line medications by the AACE.8 Dapagliflozin and canagliflozin are metabolized by UGT enzymes,39-40 while empagliflozin is primarily excreted unchanged with only minor metabolism by UGT enzymes.41 Only one study has evaluated pharmacogenetic associations with SGLT2 inhibitors, but found no effect of polymorphisms in the SLC5A2 gene on empagliflozin treatment response.42 GLP1 agonists are some of the newest oral glucose lowering agents and include exenatide, liraglutide, lixisenatide, dulaglutide, and semaglutide. They are considered second line agents by the ADA and second or third line medications by the AACE.8/sup> They are metabolized by ubiquitous proteolytic enzymes that are unlikely to be affected by genetic variation. No studies have yet evaluated these medications for pharmacogenetic associations.

 

Summary

The pharmacogenomics of oral glucose lowering agents continues to be an emerging field of inquiry. Research into predictors of metformin response continues to expand, and it is likely that research efforts will begin focusing on some of the newer classes of medications. While more research is needed to support the use of pharmacogenomics to predict patient outcomes with other classes of diabetes medications, there are sufficient data to support the use of pharmacogenomics with sulfonylureas and, to a less extent, thiazolidinediones.

 

Pharmacogenomics of Cardiovascular Medications

 

Hyperlipidemia and hypertension are two of the most common diabetes comorbidities. Together with hyperglycemia, these conditions constitute the “three H’s” of metabolic syndrome. These two conditions are significant predictors of overall cardiovascular health in diabetics and ADA guidelines emphasize both hyperlipidemia and hypertension management as a key component of effective diabetes treatment.43

 

Hyperlipidemia is the most common diabetes comorbidity and is a more important risk factor for cardiovascular disease than hyperglycemia.44 While the prevalence of LDL-C levels is similar in diabetics and non-diabetics, diabetic patients have a 2-3 fold increased risk of elevated triglycerides and low HDL-C compared to the general population.44 Moreover, for the same serum lipid levels, individuals with diabetes have a greater risk of cardiovascular disease than non-diabetic individuals.45 Similarly, the risk of coronary artery disease in patients with comorbid diabetes and hypertension is three-fold higher than in patients with either diabetes or hypertension alone46 and the risk of stroke, nephropathy, and retinopathy is also increased.47

 

Treatment of these underlying risk factors reduces the risk of cardiovascular disease in diabetic individuals. Statin treatment reduced the risk of CVD-related mortality by 19-25% in two studies.45 Likewise, the UKPDS 36 study showed that for each 10 mm Hg decrease in systolic blood pressure (SBP), there was a corresponding decrease in deaths related to diabetes (15% decrease), myocardial infarction (11% decrease), microvascular complications (13% decrease), and any complication (12% decrease).48 Improving efficacy and adherence to statin and antihypertensive therapy via pharmacogenetic-guided treatment would be expected to result in further decreases in major adverse cardiovascular events.

 

Statins

Statins are the preferred treatment for hyperlipidemia and are effective at lowering lipid levels and consequent risk of cardiovascular disease in individuals with diabetes.44 Medications in the statin class include atorvastatin, fluvastatin, lovastatin, pravastatin, rosuvastatin, and simvastatin. Like many medication classes, statins are not uniformly metabolized in the same fashion. Fluvastatin is primarily metabolized by CYP2C9, while atorvastatin, lovastatin, and simvastatin are metabolized by CYP3A4/5. Pravastatin and rosuvastatin do not undergo CYP-mediated metabolism.49

Cytochrome P450 variation has been shown to have an impact on statin efficacy and safety profiles. Carriers of the CYP3A4*22 variant, which reduces activity of the CYP3A4/5 enzyme system, have higher plasma concentrations of simvastatin and was associated with reduced dose requirement and greater reductions in total cholesterol and LDL-c levels.49 Carriers of the CYP3A5*1 allele, which increases activity of the CYP3A4/5 enzyme system, had reduced response to simvastatin, lovastatin, and atorvastatin.50 Genetic variation in CYP2C9 has been shown to increase serum levels of fluvastatin,51,52 and has been shown to increase adverse event rates by over 6-fold.53

 

Another well-known example of hyperlipidemia pharmacogenomics is the SLCO1B1 gene, which encodes a protein that transports statins into the hepatocyte. As the hepatocyte is both the site of action and the site of metabolism for most statin medications, this protein plays a critical role in their clinical effect.49 Individuals who carry two copies of the SLCO1B1 rs4149056 variant, which reduces transport of statin into the hepatocyte, have shown a 120-221% increase in simvastatin AUC compared with wild-type patients.54 Moreover, these individuals have a nearly 17-fold increase in likelihood of statin-induced myopathy compared to individuals with the normal genotype.55 This increase in myopathy risk may explain the two-fold increase in discontinuation rates among variant carriers.56 These data have led the Clinical Pharmacogenetic Implementation Consortium (CPIC) to establish clinical guidelines for the use of SLCO1B1 genotyping to inform simvastatin prescribing.18

 

SLCO1B1 variation has also been found to impact efficacy of some statins. Carriers of the rs4149056 allele have shown reduced total cholesterol and LDL-c response with pravastatin and atorvastatin, while SLCO1B1*14 carriers showed improved response to fluvastatin.49 Pharmacokinetic variability, though not necessarily clinical outcomes, has been observed as a function of SLCO1B1 genotype with all of the statins except lovastatin.49

 

Angiotensin Converting Enzyme Inhibitors

Angiotensin converting enzyme (ACE) inhibitors, along with angiotensin II receptor blockers (ARBs), are considered first line therapy for hypertension in diabetes due to their nephroprotective effects.8 ACE facilitates the conversion of angiotensin I to angiotensin II, which limits the production of aldosterone, thereby reducing sodium and water reabsorption in the kidney. While some studies have evaluated associations between ACE inhibitor efficacy and genetic variants in the ACE gene (in particular, rs1799572), the results have been conflicting.57,58 As a class, ACE inhibitors largely avoid CYP-mediated metabolism, reducing the impact of metabolism-related pharmacogenomic variants. However, studies have found that SLCO1B1 variation can increase enalapril serum levels59 and may increase risk of enalapril-induced cough by as much as 7-fold.60 Though more research is needed, SLCO1B1 is an intriguing target as a pharmacogenetic predictor of enalapril tolerability.

 

Angiotensin II Receptor Blockers

Angiotensin II receptor blockers (ARBs) target the angiotensin II receptor. However, studies have failed to show a consistent association between genetic variation in angiotensin receptor genes and ARB response577 Unlike ACE inhibitors, many ARBs are metabolized by the CYP450 enzyme system. In particular, losartan, azilsartan, candesartan, valsartan, and irbesartan are all metabolized to greater or lesser degrees by CYP2C9 and CYP3A4/5.61 Pharmacogenomic variation in these genes has been shown to impact the clinical profile of these medications. For example, data shows that variants in CYP2C9 can impact losartan pharmacokinetics, reducing its conversion to its pharmacologically active form.57 Corresponding reductions in losartan efficacy have also been observed.62-64 In particular, one study looked at the impact of CYP2C9 variation on losartan response in type I diabetic patients with nephropathy, finding that individuals carrying the CYP2C9*3 variant showed less improvement after 4 months of losartan therapy. CYP2C9 variation has also been shown to impact irbesartan response65-66 and changes in pharmacokinetic parameters as a function of CYP2C9 genotype have been reported with candesartan67,68 and valsartan.69 Thus, CYP2C9 genotype may be an important predictor of response to ARBs in hypertensive diabetics.

 

β-Blockers

β-blockers are extensively prescribed for heart failure and continue to be prescribed as an effective therapy for the treatment of hypertension in diabetes, especially as an adjunctive medication.8 β-blockers that have been evaluated for pharmacogenomic associations include carvedilol, metoprolol, and propranolol. A considerable amount of data has shown significant impacts of CYP450 variation on β-blocker pharmacokinetics and outcomes. The FDA-approved drug label for metoprolol notes the impact of CYP2D6 poor metabolism on pharmacokinetics and cardioselectivity of metoprolol, while the Dutch Pharmacogenetics Working Group has published metoprolol dosing guidelines as a function of CYP2D6 metabolizer status.70 The impact of CYP2D6 genotype on carvedilol pharmacokinetics and clinical response has also been extensively demonstrated.57,71 While CYP2D6 variation has been shown to impact propranolol pharmacokinetics, its effect on response is still somewhat controversial.72-74 Several well- studied pharmacogenomic variants have been shown to impact β-blocker pharmacodynamics, including variants in genes encoding the β-adrenergic receptors themselves (ADRB1 and ADRB2).57,75,76

 

Anticoagulant/Antiplatelet Medications

When diabetes-related cardiovascular disease progresses to the point where intervention is required, anticoagulant and antiplatelet medications are often prescribed to manage risk of thrombosis and stroke, particularly after procedures such as heart valve replacement and stent placement. Clopidogrel and warfarin are some of the most commonly prescribed medications in these situations and both are among the best-known examples of pharmacogenomics.

 

Clopidogrel is one of several medications to have a black box warning in the FDA-approved drug label that explicitly calls out differential risk as a function of patient genotype, noting that “effectiveness of Plavix depends on conversion to an active metabolite by the cytochrome P450 (CYP) system, principally CYP2C19.” The black box warning further notes that clinical tests are available to identify CYP2C19 poor metabolizers and recommends that practitioners “consider use of another platelet P2Y12 inhibitor in patients identified as CYP2C19 poor metabolizers.”77 CYP2C19 genotype may also interact with diabetes status to further reduce antiplatelet response to clopidogrel.78

 

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In late 2017, a landmark study was published by Cavallari et al that assessed clinical outcomes following clinical implementation of CYP2C19 testing in 1,815 patients who underwent percutaneous coronary intervention (PCI).79 Those with a normal genotype received standard therapy (approximately 85% received clopidogrel, with the rest receiving an alternative antiplatelet medication). However, if a patient carried a loss-of-function (LOF) allele, their provider was alerted and alternative anti-platelet therapy was suggested (approximately 61% received alternative antiplatelet therapy, with the rest receiving clopidogrel). After 12 months, patients with a LOF allele who received clopidogrel were 2.3 times more likely to experience a major adverse cardiovascular event than patients with a LOF allele who received alternative therapy (p = 0.013). Patients with an LOF allele who received alternative therapy had similar outcomes to those without an LOF allele.

 

These data indicate that CYP2C19 testing is an effective predictor of post-PCI clopidogrel outcomes. Prospective use of CYP2C19 genotyping can reduce risk of major adverse cardiovascular risk post-PCI and can also be used to triage individuals to the most appropriate and cost-effective therapy. For example, CYP2C19 normal metabolizers taking alternative therapies may be able to be triaged to the less expensive clopidogrel, reserving the more expensive alternative medications for individuals carrying LOF alleles.

 

The case of warfarin has been somewhat more controversial. FDA labeling has included CYP2C9 genotype-guided dosing information since 2007.80 CPIC guidelines were published in 2011 and updated in 2017.20 However, trials examining clinical utility of warfarin have produced mixed results. Early studies failed to meet the primary endpoint of time in therapeutic range,81-82 although these studies have also been criticized for failing to mirror standard clinical practice.83 The COAG trial did show a trend toward fewer adverse events in the genotype-guided arm81 and the GIFT trial was launched to further explore these clinical outcomes.84 This study, which enrolled 1,650 patients randomized to either CYP2C9-guided dosing or standard clinical dosing, demonstrated a 27% reduction in the composite endpoint of venous thromboembolism, major bleeding, INR ≥ 4, or death in the genotype-guided arm compared to the clinical dosing arm. These data argue powerfully for the clinical implementation of warfarin despite earlier failures with less clinically relevant endpoints.

 

Economic Outcomes

To date, cost-effectiveness analyses for cardiovascular medications have been limited to clopidogrel and warfarin only. These analyses generally follow a similar pattern of comparing pharmacogenomic-guided therapy with one or more alternative approaches that do not require pharmacogenomic testing.

 

In the case of clopidogrel, one cost-effectiveness analysis compared pharmacogenomic-guided therapy antiplatelet selection (with normal allele carriers receiving clopidogrel and LOF allele carriers receiving alternative antiplatelet therapy) with universal clopidogrel therapy, universal alternative antiplatelet therapy, and platelet-reactivity guided therapy.85 The analysis evaluated costs over the lifetime of a 60-year-old patient undergoing a PCI and found that pharmacogenomic-
guided testing resulted in the lowest overall cost over a lifetime and with the highest number of quality-adjusted life years gained. Another study evaluated the cost-effectiveness of genotype-guided antiplatelet therapy over a 30-day and 1-year window, finding that genotype-guided treatment was cost effective over 30 days and 1 year in 62 and 70% of simulations, respectively.86 A 2015 review of CYP2C19-guided antiplatelet therapy found that genotype-guided therapy was cost-effective in all seven studies that were reviewed, not including the two studies described previously.87

 

Analyses of warfarin cost-effectiveness have produced largely, though not universally, positive results. Seven cost-effectiveness analyses have demonstrated genotype-guided anticoagulant therapy to be cost- effective relative to standard warfarin treatment and/or universal use of direct oral anticoagulant therapy,88-94 with two analyses finding standard warfarin dosing to be superior95-96 and one analysis finding standard warfarin dosing and genotype-guided dosing to be essentially equivalent.97

 

Summary

Pharmacogenomics has a significant role to play in the management of cardiovascular risk factors in diabetes. Pharmacogenomic testing for clopidogrel and warfarin is now well established, with recent trials providing definitive evidence for clinical utility of genotyping prior to prescription of these medications. Pharmacogenomic testing for CYP3A4, CYP3A5 and SLCO1B1 can also be used to optimize the selection and dosing of statin medications for hyperlipidemia. In particular, SLCO1B1 already has published guidelines on its clinical implementation and routine testing is occurring at many major medical centers. Similarly, testing for SLCO1B1, CYP2D6, and CYP2C9 for the individualization of ACE inhibitors, beta-blockers, and ARBs, respectively, may reduce the time to effective dose (thus improving efficacy), while decreasing the risk of side effects (thus increasing adherence), resulting in better hypertension outcomes. Thus, adoption of pharmacogenomics is likely to result in significant improvements in cardiovascular health and quality of life among individuals with type 2 diabetes, with a reduced overall cost to the healthcare system. Moreover, by targeting a high-cardiovascular-risk population such as patients with type 2 diabetes, cost-effectiveness of pharmacogenomic testing is likely to exceed universal testing of the general population.

 

Pharmacogenomics of Antidepressant Medications

 

Few conditions have a greater impact on global functioning and quality of life than depression. In diabetes, comorbid depression is associated with poorer cognitive functioning, worsened glycemic outcomes, decreased adherence to behavioral and pharmacotherapeutic interventions, greater frequency and severity of diabetes complications (such as lower extremity amputation), and decreased quality of life.10,98-100 The prevalence of depression in type 2 diabetes is nearly twice as high (19.1%) compared to those without diabetes (10.7%).101 The relationship between depression and diabetes is likely bidirectional, with depression as both a risk factor for and a consequence of diabetes102 and the two conditions share neurobiological pathways.98

 

Depression is primarily treated through pharmacotherapy and/or psychotherapy. Overall efficacy of antidepressants in both diabetics and the general population is poor, with only 50% of individuals responding to their first trial of an antidepressant, while intolerability and nonadherence to medications are quite common.103-104 Antidepressant use has been shown to be effective in reducing depressive symptoms, improving glycemic control, and improving quality of life for diabetic patients.14,105,106

 

Clinical Outcomes

Pharmacogenomic testing in psychiatry is supported by an abundance of data. CPIC guidelines exist for tricyclic antidepressants (TCAs)15 and selective serotonin reuptake inhibitors (SSRIs)16 and over 30 neuropsychiatric medications contain pharmacogenomic information in their FDA-approved package inserts.107 Psychiatric pharmacogenomic testing has been evaluated in multiple published double-blind randomized controlled trials, with all showing statistically significant108-110 or trending111 improvements in depressive symptomatology in the genotype-guided arm relative to the treatment-as-usual arm. Naturalistic studies have likewise shown that genotype-guided treatment can improve antidepressant response by as much as 56% over treatment-as-usual.112-115 Studies have also demonstrated improved antidepressant adherence with genotype-guided treatment relative to standard treatment.108,116,117 Outside of depression, evidence also exists for the use of pharmacogenomics to predict antidepressant outcomes in diabetic neuropathy.118

 

Economic Outcomes

Psychiatric pharmacogenomic testing has been demonstrated to reduce healthcare medication costs. One large study that compared 2,168 genotype-guided patients to 10,880 matched controls demonstrated savings of over $1,000 USD per person in medication expenditures over a one year timeframe.116 Interestingly, diabetes and cardiovascular medications made up ~28% and ~16% of these savings, respectively. This is likely due to the aforementioned effect of improved mental wellbeing on physical health.14,105,106

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Pharmacogenomic testing has also been demonstrated to positively impact and lower healthcare utilization costs. One study found that patients taking genetically inappropriate medications accrued an additional ~$5,200 in healthcare utilization costs relative to patients on genetically appropriate medications,119 while another study found that CYP2D6 abnormal metabolizers had longer hospitalization stays and more adverse events, resulting in increased healthcare costs.120 Additionally, prospective use of psychiatric pharmacogenomic testing reduced healthcare utilization in two studies.117,121

 

Summary

Psychiatric pharmacogenomic testing can improve patient outcomes in depression, leading to increased medication adherence and reduced healthcare costs. Psychiatric pharmacogenomic testing has shown a direct impact on medication costs associated with diabetes and cardiovascular disease and is likely to produce similar benefits in healthcare utilization and patient quality of life. The evidence supporting the clinical utility of pharmacogenomic testing for psychiatric medications may be the most extensive of any disease state.

 

Future Directions: Genetic Predictors of Diabetes Risk

 

While not directly related to pharmacogenomics, a brief discussion of genetic predictors of diabetes diagnosis is warranted. Monogenic forms of diabetes (i.e. inherited forms of diabetes caused by single genes) may represent one underutilized area of genetic testing in diabetes. The most well characterized form of monogenic diabetes is maturity-onset-diabetes of the young (MODY), a term encompassing 13 subtypes of the condition, each characterized by a single gene causing the illness presentation. As the clinical presentation of MODY is similar to both type 1 and type 2 diabetes, it is often misdiagnosed and may make up 1-2% of all diabetes cases.122 Neonatal diabetes mellitus, which usually presents in the first six months of life, is also caused by known, detectable mutations.122

 

Type 2 diabetes mellitus, on the other hand, is multifactorial and is the result of a complex interplay between environment and numerous, largely uncharacterized genetic variants. Indeed, the NHGRI-EBI Catalog of published genome-wide association studies lists well over 1500 statistically significant associations, including variants in TCF7L2, KCNJ11, PPAR-γ, and FTO. However, each of these variants confers a very small increase in absolute risk for type 2 diabetes, making them presently useless as diagnostic markers. However, as the field advances, polygenic risk scores may be developed that, when validated, can assist in the prediction and early detection of type 2 diabetes so that interventions can occur before the disease progresses.

 

Conclusion

The treatment of type 2 diabetes mellitus, with its myriad of risk factors, treatment options, complications, and comorbidities is incredibly complex, resulting in significant social and economic burden in the United States. Pharmacogenomic testing has been demonstrated to significantly improve the treatment of cardiovascular and psychiatric conditions associated with diabetes, and data on the pharmacogenomics of glycemic agents themselves continue to accumulate. As clinicians adopt the use of pharmacogenomic testing for the management of pharmacotherapy in diabetic patients, it is likely that significant gains will be seen in medication efficacy, tolerability, and adherence, resulting in overall improved outcomes and reduced healthcare costs for the patient and healthcare system.

 

References

 

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Rxight Is Now An Affiliate In The IGNITE Network

By | Announcements, Pharmacogenetic Testing, Pharmacogenomics, Precision Medicine | No Comments

Rxight Pharmacogenetics has become an affiliate member of the NIH-funded effort, IGNITE (Implementing GeNomics In pracTicE). IGNITE is a network dedicated to supporting and advancing the use of genetic information across clinical and diverse healthcare settings. It is comprised of a series of projects aiming to enhance translation of validated actionable genomic information into clinical settings and decision making, and includes educational initiatives for patients and providers. IGNITE is poised to have a significant impact on the acceleration of genomic information into medical practice, and Rxight Pharmacogenetics is proud to be a member of this step forward in clinical care.

The Pharmacogenetics of Antiplatelet Agent: Meta-Analyses of Aspirin and Clopidogrel Loss-of-Function Alleles

By | Anticoagulants, Pharmacogenetic Testing, Provider | No Comments

Antiplatelet agents combined with aspirin have been shown to play a significant role in mitigating the effects of coronary disease, and ample research has found that distinct genetic determine patients’ response to clinically significant antiplatelet agents.
 
Platelets play a decisive role during the formation of an initial hemostatic plug through their intricate response to injury. When inappropriately activated, platelets contribute to pathological thrombus formation. Arterial thrombus formation can then lead to tissue ischemia causing potentially fatal coronary and cerebrovascular events.
 

Interindividual Genetic Variation Impacts Aspirin Antiplatelet Efficacy

 
Aspirin is regarded as “the cornerstone for secondary cardiovascular prevention,” the efficacy of which has long been established. as noted in Current Pharmaceutical Design, “Pharmacogenetics of the Antiplatelet Effect of Aspirin” (2012).
 
The researchers aver that there is considerable interindividual variation in response to aspirin, thus reducing its efficacy in treating heart disease in some patients.
 

P1A2 and P2Y1 Association with Decreased Aspirin Antiplatelet Efficacy

 
Specifically, the review conducted by Current Pharmaceutical Design examined polymorphisms of genes that contributed highly to antiplatelet responses. These were P1A2 from glycoprotein GP IIb/IIIa, and the P2Y1 polymorphism from AD receptor (ADP) genes.
 
P1A2 was characterized as having an association with coronary thrombus formation. One study showed P1A2 allele was related with a shorter baseline bleeding time in comparison to a wild type allele. After measuring bleeding after aspirin ingestion, there was a a reduced antiplatelet effect.
 
Another study supported this finding by discovering an enhanced thrombin formation in P1A2 carriers compared to P1A1/A1 homozygotes before and after aspirin ingestion. The review concluded that P1/A2 polymorphism is a prothrombotic platelet phenotype responding inadequately to aspirin.
 
Polymorphism P2Y1 was utilized in an arachidonic acid-induced optical platelet aggregometry to assess its antiplatelet effect of aspirin. The results showed that the T allele of the C893T P2Y1 polymorphism was substantially linked with a decreased antiplatelet effect of aspirin.
 

CYP2C19 Mediates Clopidogrel Non-Response

 
Evidence for association of CYP2C19 with clopidogrel response was investigated in the Journal of Human Genetics “Pharmacogenomics of Anti-Platelet Therapy: How Much Evidence is Enough for Clinical Implementation?” (June 2013).
 
The study established CYP2C19 as a genetic factor contributing to the creation of the active metabolite of clopidogrel. A corresponding analysis detailing the associations of CYP2C19 alleles and increasing residual on-treatment platelet reactivity corroborated this finding. The study concluded that patients with even one reduced function of CYP2C19 and taking clopidogrel as treatment for percutaneous coronary intervention may be “associated with increased risk of major adverse cardiovascular events as a consequence of aspirin antiplatelet inefficacy.
 
The International Journal of Environmental Research and Public Health “Pharmacokinetic and Pharmacodynamics Responses to Clopidogrel” (February 2017) also reviewed the connection between CYP2C19 and clopidogrel. The review was based on the authors’ argument that genetic polymorphisms impact the absorbtion and metabolism of clopidogrel and that the P2Y12 receptor may interfere with its antiplatelet activity.
 
In one meta-analysis, it was found there was a critical relation between CYPC219 loss-of-function in diverse patients with frequent cardiovascular events. In another meta-analysis, CYPC219 was identified as having a having a crucial part in reducing the active metabolite of clopidogrel.
 

CYP3A4/5 Mediates Clopidogrel Non-Response

 
In addition to analyzing clopidogrel, the review also analyzed CYP3A4/5. The authors found that the CYP3A5*3 allele has an influence on clopidogrel metabolism because of its possible dependence on CYP2C19 and CYP3A4 inhibitors. In the study, the patients with a CYP3A5*3/3 genotype displayed enhanced platelet reactivity compared to those with a CYP3A5*1 allele in CYP2C19 poor metabolizers. An additional study reported CYP3A5*3 on clopidogrel response is prominently in patients with the CYP2C19 loss-of-function.
 

Benefits of Individualizing Antiplatelet Therapy with Pharmacogenetic Testing

 
Research has been conclusive in identifying potential antiplatelet pharmacogenetic applications pointing to effective individualized treatments, according to the studies.
 
The review by the International Journal of Environmental Research and Public Health asserted there is an “inter-individual variability” in clopidogrel’s antiplatelet effects. They concluded inadequate platelet responsiveness to clopidogrel has a role in accumulating the risk of cardiovascular events, and therefore increasing drug dosage or switching to alternative drug medications may be more beneficial for patients. Similarly, the review published in Current Pharmaceutical Design concludes by recommending utilization of antiplatelet pharmacogenetics in clinical practice. “The promise of pharmacogenetics lies in the prospect of improving treatment efficacy and safety.”

The Prospect of Pharmacogenetics in Pediatrics

By | Opioids, Other, Pharmacogenetic Testing, Provider | No Comments

Pharmacogenetics of Opioids as a Potential Alternative in Pediatric Pain Management

 
Opioid and codeine treatment in pain management for children has been a primary concern in clinical settings, specifically for surgical pain management. The concerns are the adverse reactions caused by the opioids, such as respiratory depression. Current Opinion in Anesthesiology, “Codeine and Opioid Metabolism: Implications and Alternatives for Pediatric Pain Management” (2017), reviews how important clinical factors and genetic polymorphisms affect the metabolism of opioids after surgical operations.

 

Adverse Side Effects of Codeine

 
Codeine’s efficacy has been questioned in the pain management of children. Current Opinion in Anesthesiology identifies the adverse reactions of it. The prominent ones are respiratory depression, anoxic brain injuries, and even death occurring in children. With reported doses of codeine, significant respiratory depression was found in newborns in a report by Canadian Pharmacists Journal “Pain Management in Children: A Transition from Codeine to Morphine for Moderate to Severe Pain in Children” (2012).

 
Opioids in Pain Management

 
Opioids are the cornerstone of pain and chronic pain management. “Successful pain management provides adequate analgesia without excessive adverse reactions affirms Clinical Biochemistry “Pharmacogenetics of Chronic Pain Management” (2014). Drug metabolism and responses are influenced by numerous factors, including pharmacogenetics. Genetic variations contribute to the distinct inter individual responses to pain medications.

 
Involvement of CYP2D6 in Codeine

 
Those with two nonfunctional alleles of CYP2D6 are considered poor metabolizers. Extensive metabolizers have one or two effective CYP2D6 alleles and those with duplicated CYP2D6 alleles are ultra rapid metabolizers. Canadian Pharmacists Journal indicates the functions of CYP2D6 are similar in both children and adults.

 
The review also acknowledges the safety concerns of CYP2D6 ultra rapid metabolizers from several studies. One study demonstrated how a breastfed newborn infant died after his mother consumed Tylenol #3 for postpartum pain. Toxicology testing found the mother had abnormally high concentration levels of morphine in her breast milk. Genotype testing found the mother was an ultra rapid metabolizer of codeine. The study concluded since the mother was an ultra rapid metabolizer, higher than normal morphine levels crossed into the breast milk and resulted in the infant dying from morphine intoxication.

 
Another study found a two-year-old child who also died of morphine intoxication. The child was prescribed codeine in recommended dosages after having his tonsils removed. Genotype testing revealed the child was an ultra rapid metabolizer of codeine. However, there were also other contributing factors; the child had bronchopneumonia and sleep apnea. The study concluded these factors “may have increased his risk of hypoxemia, leading to alterations in opioid receptors and increased sensitivity to morphine.”

 
Canadian Pharmacists Journal concludes these studies show ultra rapid metabolizers of codeine are correlated with a higher risk of morphine intoxication among children.

 

Alternatives to Prevent Adverse Drug Reactions

 
Canadian Pharmacists Journal argues morphine as a safer alternative compared to codeine. They argue morphine has “demonstrated efficacy and relative safety when used appropriately in pain management in both adults and children.” A study they analyzed found morphine treatment more effective than a placebo for children in postoperative pain.

 
Current Opinion in Anesthesiology also outlines the possible alternatives to prevent the risks of opioids, such as pharmacogenetics. They indicate personalized opioid therapy for pain management is “distant from reality”, but current CYP2D6 pharmacogenetic research on codeine is hopeful. The review summarizes, “pharmacogenetics has the potential to guide anesthesia providers on perioperative opioid selection and dosing to maximize efficacy and safety.”

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Pharmacogenetics Emerging as a Method to Guide Medication Therapy

By | Gene Panel, Opioids, Other, Pharmacogenetic Testing, Provider | No Comments

According to a recent article published in American Family Physician “Pharmacogenetics: Using Genetic Data to Guide Drug Therapy (2015), pharmacogenetics is being more widely used by family physicians and the number of patients who are interested in acquiring genetic information is growing.

 

The Components of Pharmacogenetics Testing

 
Pharmacogenetics involves genetic variations that code for drug metabolizing enzymes. It also involves how a medication breaks down in the body and how the body responds to the medication. The most common forms of genetic variations are single nucleotide polymorphisms.

 
The differences in single nucleotide polymorphisms or other polymorphisms result in diverse types of genes or alleles, the American Family Physician explains. Individuals inherit these alleles that “govern expression of the gene and the cor¬responding enzyme or protein.” As a result, these genetic differences influence how the drug reacts in the body and how the body metabolizes the drug.

 

Genetic Variability Can Alter the Effects of Drugs

 
Studies have demonstrated there is a connection between genetic variations and changes in drug levels and effects.

 
CYP2D6 and Opioids

 
The enzyme activity of CYP2D6 is volatile because of single nucleotide polymorphisms and other variations of CYP2D6. American Family Physician indicates codeine metabolism occurs in 90% of patients and results in normal morphine formation. However, 1% to 2% of people are ultra rapid metabolizers of codeine signifying they have an increased risk of morphine toxicity.

 
American Family Physician analyzed a study involving the death of a breastfed infant and a mother who was an ultra rapid metabolizer of codeine. The study demonstrated the infant died of morphine intoxication. There was opioid toxicity in the breast milk, which passed onto the infant.

 
They recommend pharmacogenetic testing for patients who are possible poor or ultra rapid metabolizers of opioids.

 

CYP2C19 and Clopidrogrel

 
Clopidogrel is primarily metabolized in the enzyme CYP2C19. CYP2C19 is highly polymorphic and 80% of individuals metabolize clopidogrel normally. However, 18% to 45% of people have intermediate enzyme activity and 2% to 15% have poor enzyme activity.

 
American Family Physician presents meta-analyses of CYP2C19 poor metabolizers. Poor CYP2C19 metabolizers taking clopidogrel treatment and undergoing percutaneous coronary intervention have a higher risk of cardiovascular death, myocardial infraction, stroke, and stent thrombosis.

 
These results lead to the recommendation that clinicians should consider alternative treatments, such as pharmacogenetic testing of CYP2C19 to guide antiplatelet therapy.

 

The Benefits of Pharmacogenetics

 
American Family Physician examined the clinical implications of pharmacogenetic testing and the various resources available and developing to support the usage of pharmacogenetics in clinical settings. They conclude “pharmacogenetic testing can be a practical tool to optimize drug therapy and avoid medication adverse effects.”

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The Pharmacogenetics of Antiplatelet Agents: Meta-Analyses of Aspirin and Clopidogrel Loss-of-Function Alleles

By | Gene Panel, Other, Pharmacogenetic Testing | No Comments

 
Antiplatelet agents combined with aspirin have been shown to play a significant role in mitigating the effects of coronary disease, and ample research has found that distinct genetics determine patients’ response to clinically significant antiplatelet agents.

 

Platelets play a decisive role during the formation of an initial hemostatic plug through their intricate response to injury. When inappropriately activated, platelets contribute to pathological thrombus formation. Arterial thrombus formation can then lead to tissue ischemia causing potentially fatal coronary and cerebrovascular events.

 

Interindividual Genetic Variation Impacts Aspirin Antiplatelet Efficacy

 

Aspirin is regarded as “the cornerstone for secondary cardiovascular prevention,” the efficacy of it, which has long been established, as noted in Current Pharmaceutical Design, “Pharmacogenetics of the Antiplatelet Effect of Aspirin” (2012).

 

The researchers avert that there is considerable interindividual variation in response to aspirin, thus reducing its efficacy in treating heart disease in some patients.

 

P1A2 and P2Y1 Association with Decreased Aspirin Antiplatelet Efficacy

 

Specifically, the review conducted by Current Pharmaceutical Design examined polymorphisms of genes that contributed highly to antiplatelet responses. These were P1A2 from glycoprotein GP IIb/IIIa, and the P2Y1 polymorphism from AD receptor (ADP) genes.

 

P1A2 was characterized as having an association with coronary thrombus formation. One study showed P1A2 allele was related with a shorter baseline bleeding time in comparison to a wild type allele. After measuring bleeding after aspirin ingestion, there was a reduced antiplatelet effect.

 

Another study supported this finding by discovering an enhanced thrombin formation in P1A2 carriers compared to P1A1/A1 homozygotes before and after aspirin ingestion. The review concluded that P1/A2 polymorphism is a prothrombotic platelet phenotype responding inadequately to aspirin.

 

Polymorphism P2Y1 was utilized in an arachidonic acid-induced optical platelet aggregometry to assess its antiplatelet effect of aspirin. The results showed that the T allele of the C893T P2Y1 polymorphism was substantially linked with a decreased antiplatelet effect of aspirin.

 

CYP2C19 Mediates Clopidogrel Non-Response

 

Evidence for association of CYP2C19 with clopidogrel response was investigated in the Journal of Human Genetics “Pharmacogenomics of Anti-Platelet Therapy: How Much Evidence is Enough for Clinical Implementation?” (June 2013).

 

The study established CYP2C19 as a genetic factor contributing to the creation of the active metabolite of clopidogrel. A corresponding analysis detailing the associations of CYP2C19 alleles and increasing residual on-treatment platelet reactivity corroborated this finding. The study concluded that patients with even one reduced function of CYP2C19 and taking clopidogrel as treatment for percutaneous coronary intervention may be “associated with increased risk of major adverse cardiovascular events as a consequence of aspirin antiplatelet inefficacy.”

 

The International Journal of Environmental Research and Public Health “Pharmacokinetic and Pharmacodynamics Responses to Clopidogrel” (February 2017) also reviewed the connection between CYP2C19 and clopidogrel. The review was based on the authors’ argument that genetic polymorphisms impact the absorbtion and metabolism of clopidogrel and that the P2Y12 receptor may interfere with its antiplatelet activity.

 

In one meta-analysis, it was found there was a critical relation between CYPC219 loss-of-function in diverse patients with frequent cardiovascular events. In another meta-analysis, CYPC219 was identified as having a having a crucial part in reducing the active metabolite of clopidogrel.

 

CYP3A4/5 Mediates Clopidogrel Non-Response

 

In addition to analyzing clopidogrel, the review also analyzed CYP3A4/5. The authors found that the CYP3A5*3 allele has an influence on clopidogrel metabolism because of its possible dependence on CYP2C19 and CYP3A4 inhibitors. In the study, the patients with a CYP3A5*3/3 genotype displayed enhanced platelet reactivity compared to those with a CYP3A5*1 allele in CYP2C19 poor metabolizers. An additional study reported CYP3A5*3 on clopidogrel response is prominently in patients with the CYP2C19 loss-of-function.

 

 

Benefits of Individualizing Antiplatelet Therapy with Pharmacogenetic Testing

 

Research has been conclusive in identifying potential antiplatelet pharmacogenetic applications pointing to effective individualized treatments, according to the studies.

 
The review by the International Journal of Environmental Research and Public Health asserted there is an “inter-individual variability” in clopidogrel’s antiplatelet effects. They concluded inadequate platelet responsiveness to clopidogrel has a role in accumulating the risk of cardiovascular events, and therefore increasing drug dosage or switching to alternative drug medications may be more beneficial for patients.

 
Similarly, the review published in Current Pharmaceutical Design concludes by recommending utilization of antiplatelet pharmacogenetics in clinical practice. “The promise of pharmacogenetics lies in the prospect of improving treatment efficacy and safety.”

 

 

 

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Antipsychotic Medications in Schizophrenia

By | Antipsychotics, Pharmacogenetic Testing, Pharmacogenomics, Precision Medicine, Psychiatric Medications | No Comments

Medications are central to the treatment of schizophrenia and a number of drugs are used to treat this serious mental condition. Schizophrenia is a long-term mental disorder marked by psychosis- a breakdown in the relation between thought, emotion, and behavior, leading to errors in perception, inappropriate actions and feelings, withdrawal from reality, and a sense of mental fragmentation.

 

Most patients are now treated with antipsychotics that are thought to control symptoms through the brain chemical, dopamine. There are two types of antipsychotics used: first generation and second generation.

 

First Generation Antipsychotics

 
The first generation antipsychotics have more serious side effects and are used only when necessary. They include haloperidol (Haldol), chlorpromazine (Thorazine), and Fluphenazine (Prolixin). Side effects of first-generation antipsychotics include extrapyramidal side effects which is marked by rigidity, bradykinesia, dystonias, tremor, and akathisia. Tardive dyskinesia (TD)— a disorder marked by permanent involuntary movements in the limbs and face such as grimacing and lip-smacking – is another adverse effect that can occur with first-generation antipsychotics. Additionally. first-generation antipsychotics are known to cause cardiac rhythm abnormalities.

 

Second Generation Antipsychotics and Side Effects

 
The newer second generation antipsychotics have less side effects than the older drugs, and are preferred for treatment of schizophrenia. They include: aripiprazole (Abilify), asenapine (Saphris), brexipiprazole (Rexulti), clozapine (Clozaril), Iloperidone (Fanapt), Lurasidone (Latuda), Olanzapine (Zyprexa), Paliperidone (Invega), quetiapine (Seroquel), risperidone (Risperdal), and ziprasidone (Geodon).

 
Abilify side effects include akathisia (agitation), restlessness, insomnia, constipation, fatigue and blurred vision. Most of the second-generation antipsychotics have similar side effects, as they are similar chemically. Geodon is one of the newer antipsychotics with extra-pyramidal side effects reported (drug induced movement disorders).

 
During initial phases of treatment with the second generation antipsychotics patients may experience side effects such as dry mouth, drowsiness, restlessness, muscle spasms, tremor or blurring of vision. The second generation antipsychotics have a much lower risk of tardive dyskinesia, a serious side effect of the older antipsychotics. It is possible to lessen side effects by either lowering the dose or by changing medications.

 

Antipsychotic Pharmacogenetics

 
Patients and physicians often work together to find a dose that results in the fewest side effects. Patients will often change medications if the side effects are severe and side effects lessen over time. One way to potentially avoid side effects for new medications and for newly prescribed schizophrenia medications is to have your drug metabolism genes tested. After the human genome was sequenced back in 2003, genome wide association studies showed that there is variation among the population in the genes that process medications. As a result, if there’s a drug-processing gene with variation, it may have trouble processing medications that are metabolized by that gene product.

 

Know Your Risks with the Rxight® DNA Test

 
The most state-of-the-art way to determine genetic variations is with the Rxight® pharmacogenetics test from MD Labs. This advance in pharmacogenetics means that a physician can determine beforehand what drugs may be safe to take and what drugs to avoid or require different doses than recommended. All that is required is a prescription from a physician and a cheek swab at a participating pharmacy.

 
You could benefit from this advance in precision medicine with the knowledge of your gene variations with your physician or other healthcare services. The Rxight® pharmacogenetics test determines your genetic susceptibilities for over 200 drugs on the market. You could also benefit from knowing how you might respond to drugs you may have to take in the future. Most importantly, you could get information that may change your current dosing and medication for fewer harmful side effects from your antipsychotic medication.

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Overview of the Dangers and Side Effects of Psychotropic Medications

By | ADHD Medications, Antianxiety Medications, Antidepressants, Antipsychotics, Pharmacogenetic Testing, Precision Medicine, Psychiatric Medications | No Comments

Get the Rxight® Genetic Test to Know Your Risks

Psychiatric medications (often called “psychotropics”) are routinely used to treat a variety of psychiatric disorders – ranging from ADHD (attention deficit hyperactive disorder) and depression to bipolar disorder and anxiety to schizophrenia – Psychiatric medications are generally jused as an adjunct to psychotherapy.

 
It is estimated that 17 percent (some 80 million people) in the United States are taking some form of psychiatric medication (Scientific American, “1 in 6 Americans Takes a Psychiatric Drug,”  Dec 13 2016) According to the article, an earlier government report, from 2011, found that just over 10% of adults are taking prescription drugs for “problems with emotions, nerves or mental health,” published in the journal JAMA Internal Medicine.

 
While the potential benefits of psychotropic medications have been demonstrated in research and clinical practice for decades, patients are cautioned to remain vigilant of the many side effects of psychiatric medications.

 
This article presents a detailed summary of the major types of mental health medications and their associated risks for side effects as reported by the U.S. Food and Drug Administration (FDA) and the National Institute of Mental Health (NIMH) and an overview of the benefits of the Rxight® genetic test for psychiatric medications in identifying your unique genetically determined risk for developing side effects or non-response to dozens of these psychiatric medications along with hundreds of other medications across 50 pharmacological classes.

Antidepressant Side Effects

What are antidepressants?
Antidepressants are commonly used to treat depressive disorders. They also are used for other conditions, such as pain, anxiety and insomnia. Although antidepressants are not FDA-approved specifically to treat ADHD, they are sometimes used “off-label” for ADHD treatment.

The most commonly prescribed types of antidepressants today are called . Examples of SSRIs include:

Other types of antidepressants are serotonin and norepinephrine reuptake inhibitors (SNRIs) .These are chemically similar to SSRIs and include and duloxetine (Cymbalta)  and venlafaxine (Effexor).

 
Another antidepressant that is commonly used is bupropion – a third sub-class of antidepressant which acts differently than either SSRIs or SNRIs.  Bupropion is also used to treat seasonal affective disorder (SAD) and for smoking cessation treatment.

SSRIs, SNRIs, and bupropion are commonly used today because they do not cause as many side effects as the older (“first generation”) classes of antidepressants, and moreover are effective in treating a broader range of depressive and anxiety disorders.

 
Older antidepressant medications include tricyclic antidepressants, tetracyclic antidepressants, and monoamine oxidase inhibitors (MAOIs).  These are less commonly prescribed since the development of the newer generation antidepressants.
 
What are the possible side effects of antidepressants?
Some antidepressants may cause more side effects than others. The most common side effects listed by the FDA include:

  • Sexual problems (impotence or inability to orgasm)
  • Nausea and vomiting
  • Weight gain
  • Sleepiness or fatigue
  • Diarrhea

In 2004, the FDA ordered a “black box” label – the most serious warning it issues – on all antidepressants to caution of psychiatric drugs’ increasing suicide risk in children and adolescents. In 2006, the FDA increased the age to include young adults up to age of 25. (FDA, Revision to Product Labeling, 2004)

 
Call your doctor immediately if you have any of the following symptoms, especially if they are new, worsening, or worry you (U.S. Food and Drug Administration, 2011):

  • Suicidal thoughts or actions
  • New or worsening depression
  • New or worsening anxiety
  • Feeling restless or agitated or
  • Panic attacks
  • Insomnia
  • New or worsening irritability
  • Acting aggressively, being angry, or violent
  • Acting on dangerous impulses
  • An increase in activity and talking (mania)

Additionally, drug interactions can occur.  Specifically, combining the newer SSRI or SNRI antidepressants with one of the commonly-used “triptan” medications for treating migraines can cause a life-threatening condition called “serotonin syndrome.” Serotonin syndrome is marked by agitation, hallucinations, high temperature, or unusual blood pressure changes. Serotonin syndrome is usually associated with the older antidepressants called MAOIs, but it can happen with the newer antidepressants as well.

 
Antidepressants may cause other side effects that were not included in this list, as determined by individual genetics and ability to metabolize the drug in the liver.

 
How do patients respond to antidepressants?
Some people respond better to some antidepressant medications than to others.  It is critical to know that some people may not feel better with the first medicine they try. Additionally, sometimes people taking antidepressants feel better and stop taking the medication too soon, and the depression may return.

 
These inter-individual differences are based in genetics, and the Rxight® genetic test will indicate which antidepressants may not work for you right from the start instead of having to go through trial and error with your doctor  With Rxight results, you your doctor can work together to find the best and most effective antidepressant treatment tailored to your unique genetics.

 

Antipsychotic Side Effects

What are antipsychotics?
Antipsychotic medicines are primarily used to manage psychosis, a condition that affects the mind. Psychosis is characterized by some loss of contact with reality, often including or hallucinations (hearing or seeing things that are not really there), or delusions (false, fixed beliefs). It can also be a symptom of a physical condition such as drug abuse or a mental disorder such as schizophrenia, very severe depression (also known as “psychotic depression”), or bipolar disorder.

 
Antipsychotic medications are frequently used in combination with other drugs to treat delirium, dementia, and mental health conditions, including:

The older antipsychotic medications are conventionally referred to as “typical” antipsychotics or “neuroleptics”. Some of the common typical antipsychotics include:

Second generation antipsychotic medications are also called “atypical” antipsychotics. Some of the most common atypical antipsychotics are:

According to a 2013 research review by the Agency for Healthcare Research and Quality , typical and atypical antipsychotics both work to treat of bipolar disorder (preventing mania) and symptoms of schizophrenia Additionally, some atypical antipsychotics have wider applications and are used for treating bipolar depression or general depression.

 
What are the possible side effects of antipsychotics?

Antipsychotics are known to have a large number of side effects (also called adverse events) and risks, including potentially fatal complications.

 
The FDA lists the following side effects of antipsychotic medicines:

  • Constipation
  • Nausea
  • Vomiting
  • Uncontrollable movements, such as tics and tremors (the risk is higher with typical antipsychotic medicines)
  • Seizures Drowsiness
  • Blurred vision
  • Low blood pressure
  • Dizziness
  • Restlessness
  • Weight gain (the risk is higher with some atypical antipsychotic medicines)
  • Dry mouth
  • A low number of white blood cells, which fight infections

Typical antipsychotic medications can also cause additional side effects related to physical movement, such as:

  • Tremors
  • Restlessness
  • Rigidity
  • Muscle spasms

Long-term use of antipsychotic medications may lead to a condition called tardive dyskinesia (TD). Tardive dyskinesia causes uncontrolled muscle movements, commonly around the mouth. TD can range from mild to very severe, and in some people, the problem cannot be cured and becomes disfiguring.

 
Avoid the Risk of Antipsychotic Side Effects with Rxight®

The Rxight® medication panel includes 18 popular antipsychotics on the market. Because the potential side effects of both typical and atypical antipsychotics can be very serious and potentially fatal, knowing your risks ahead of time with Rxight® can be an invaluable test for you and your prescriber.

 

Mood Stabilizer Side Effects

What are mood stabilizers?
Mood stabilizers work by decreasing abnormal brain activity. They are used mainly to treat bipolar disorder and the mood swings associated with other mental conditions including:

  • Depression (usually in conjunction with an antidepressant)
  • Disorders of impulse control
  • Schizoaffective Disorder

Anticonvulsant (anti-seizure) medications are most frequently used as mood stabilizers. They were originally developed for treatment of seizures, but they were found to help control mood swings as well. One anticonvulsant commonly used as a mood stabilizer especially in patients with symptoms of both mania and depression, or those with rapid-cycling bipolar disorder, is valproic acid (sold as Depakote). Anticonvulsants used as mood stabilizers include:

Lithium is a non-anticonvulsant mood stabilizer approved for the treatment of mania and the maintenance treatment of bipolar disorder.

 
What are the potential side effects of mood stabilizers?

Mood stabilizers can cause several side effects, some of which may be serious, especially at high dosages. These side effects include:

  • Potentially fatal rash (Stevens-Johnson Syndrome)
  • Itching
  • Extreme thirst
  • Tremor
  • Nausea and vomiting
  • Fast, slow, or irregular heartbeat
  • Slurred speech
  • Blackouts
  • Changes in vision
  • Hallucinations
  • Loss of coordination
  • Swelling

Mood stabilizers may cause other side effects that are not included in this list. Your unique reaction to anticonvulsants is based in genetics, and the Rxight® genetic test will indicate which mood stabilizer not work for you may right from the start instead of having to go through trial and error with your doctor – a process which can be expensive, lengthy and dangerous.  With Rxight® results, you your doctor can work together to find the best and most effective antidepressant treatment tailored to your genotype, preferably before treatment begins.

 

Anti-Anxiety Medication Side Effects

What are anti-anxiety medications?
Anti-anxiety medications (also called “anxiolytics”) work by reducing the symptoms of anxiety, such as that seen in panic attacks, or extreme worry and fear. The most commonly prescribed anti-anxiety medications are called “benzodiazepines.” Benzodiazepines are most frequently used to treat a condition called generalized anxiety disorder, while in cases of social phobia (social anxiety disorder) or panic disorder (panic attacks). Benzodiazepines are usually second-line treatments, behind antidepressants such as SSRIS.

Benzodiazepines used to treat anxiety disorders – all of which are tested in the Rxight® panel – include:

Short-acting benzodiazepines such as Lorazepam and another class of medication known as beta-blockers are used to treat non-persistent symptoms of anxiety. Beta-blockers are used primarily to manage physical symptoms of anxiety (e.g., shaking, rapid heartrate, and sweating).

 
Buspirone  (which is chemically unrelated to the benzodiazepine family) is sometimes indicated for the long-term treatment of chronic anxiety. It is not effective to use on an “as-needed” basis like the benzodiazepines.

 
How common is addiction to benzodiazepines?
One of the serious risks of anti-anxiety medications is that you can build up a tolerance to benzodiazepines if they are taken over a long period of time and may need increasingly higher doses to get the same effect. There is a serious risk of addiction and dependence. To avoid these problems, doctors usually prescribe benzodiazepines for short periods, particularly in the elderly (NIMH, “Despite Risks, Benzodiazepine Use Highest in Older People”), and people with addiction tendencies. If people suddenly stop taking benzodiazepines, they may have withdrawal symptoms or their anxiety may return.

 
What are the possible side effects of anti-anxiety medications?
Like other medications, anti-anxiety medications may cause side effects, many of which are serious. The most common side effects of benzodiazepines are sleepiness and dizziness. Other possible side effects include:

  • Headache
  • Confusion
  • Tiredness
  • Nausea
  • Blurred vision
  • Nightmares

Tell your doctor immediately if any of these symptoms are severe or do not go away:

  • Drowsiness
  • Difficulty thinking or remembering
  • Increased saliva
  • Dizziness
  • Unsteadiness
  • Problems with coordination
  • Blurred vision

If you experience any of the symptoms below, call your doctor immediately:

  • Swelling of the eyes, face, lips, tongue, or throat
  • Difficulty breathing or swallowing
  • Rash
  • Hives
  • Hoarseness
  • Seizures
  • Yellowing of the skin or eyes (jaundice)
  • Depression
  • Difficulty speaking
  • Difficulty breathing

Common side effects of beta-blockers include:

  • Fatigue
  • Dizziness
  • Weakness
  • Cold hands

 

Stimulant Side Effects

What are Stimulants?
Stimulants increase alertness, attention, and energy, as well as elevate blood pressure, heart rate, and respiration. Stimulant medications are generally prescribed to treat individuals diagnosed with ADHD (attention-deficit hyperactivity disorder). People with ADHD who take prescription stimulants describe a calming and “focusing” effect from the medication.  This is due to its effects on the brain chemical dopamine.

Stimulants used to treat ADHD – all of which are analyzed in the Rxight® DNA test – include:

In 2002, the FDA approved non-stimulant medication atomoxetine (Strattera) for use as a treatment for ADHD. Additional non-stimulant antihypertensive medications, clonidine  and guanfacine, are also approved for treatment of ADHD.

In addition to treating ADHD, stimulants are prescribed to treat other health conditions, including narcolepsy, and occasionally depression.

 
What are the possible side effects of stimulants?
Stimulants may cause side effects, most of which are relatively minor and disappear when dosage levels are lowered. The most common side effects include:

  • Loss of appetite
  • Insomnia
  • Stomach pain
  • Headache

Less common side effects include:

  • Motor tics or verbal tics
  • Personality changes

What are serious side effects of stimulant medications?
While side effects of stimulant medications tend to be minimal, patients and parents of patients are cautioned that serious adverse effects may occur, as reported by the FDA Drug Safety Communication in 2013. Also see
FDA Warns of Psychiatric Adverse Events from ADHD Medications
.

 
Heart-related problems:

  • Sudden death in patients who have heart problems or heart defects
  • Stroke
  • Myocardial infarction (heart attack)
  • Increased blood pressure and heart rate

Mental (Psychiatric) problems:

  • Behavior and thought problems
  • New or worse aggressive behavior or hostility
  • New or worse bipolar illness
  • New psychotic symptoms (or new manic symptoms)
  • Physical or psychological dependence

For additional details on the FDA warnings and manufacturer labeling for medications covered in the Rxight® panel, please refer to our list of medications covered.

 

About Rxight® Pharmacogenetic Testing

The Rxight® genetic test analyzes your risks based on your unique genetic makeup through a process called “SNP genotyping.” The report which will be shared with you in a personal consultation with a pharmacist. The report “red-flags” medications which may cause you to have issues, or conversely highlight medications which may not be effective for you.

 
Rxight® is based on pharmacogenetics — the study of how genes affect a person’s response to medicines. Our panel of over 200 clinically significant medications includes dozens of commonly prescribed psychiatric medications, including antidepressants across five sub-classes, mood stabilizers used in bipolar disorder and schizoaffective disorder, antipsychotics, ADHD medications (stimulant and non-stimulant), and anti-anxiety medications.

 
Based on how well you metabolize those particular medications, which is determined by your genes that encode liver enzymes that break down drugs, you will be at risk for developing side effects or the medication not working well or at all. With the results of the Rxight® test you and your prescriber can find the right medication for you, preferably before treatment begins.

 
Contact us today by phone 1 (888) 888-1932 or email to learn more about how Rxight® pharmacogenetic testing can help you find the right medication, right from the start.

statins side effects

Statin Side Effects in Women

By | Drug Metabolism, Pharmacogenetic Testing, Pharmacogenomics, Precision Medicine, Statins | No Comments

Statin treatment in women without cardiovascular disease is controversial. Research has found that for women with elevated LDL levels as their only cardiovascular risk factor, the benefit of lowering LDL cholesterol with a statin drug might not outweigh the risks.
 
According to an article in Circulation “Statins for the primary prevention of cardiovascular events in women with elevated high-sensitivity C-reactive protein or dyslipidemia” (March 2010) many women take statins and suffer side effects similar to those experienced by men. Statin side effects range from mild to severe and include liver damage, myopathy, and behavioral and cognitive problems.
 

Revised Treatment Guidelines Push for Increasing Statin Use

 
Treatment guidelines issued in 2014 in the New England Journal of Medicine suggest that up to 13 million more adults should be taking statins. The revised guidelines changed the focus from specific cholesterol levels to a wider assessment of heart attack and stroke risk.
 

Opponents Claim Too Many Women Prescribed Statins

 
Not everyone agrees with these new treatment guidelines, as reported in the New York Times, also in 2014: “Among men 60 to 75, the percentage would jump to 87 percent from 30 percent; among older women, it would increase to 54 percent from 21 percent.” In that New York Times article, the chief of cardiovascular medicine at the Cleveland Clinic said the report confirmed his concerns that the new guidelines “don’t target the right patients for treatment.” He faulted the study for not taking into account the family history of cardiovascular disease: “Should so many women be taking statins? Far too many healthy women are taking statins, they say, though some research indicates the drugs will do them little good and may be more likely to cause serious side effects in women.”
 

Women Found to Suffer More Side Effects from Statins Than Men

 
These studies highlight the fact that fewer women take statins than men, and that women suffer more side effects from statins than men. Although women represent about half the population, they are enormously under-represented in clinical trials of statins. It follows that the evidence on the benefits and risks for women is scarce. In one of the studies American Journal of Cardiology “Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER)” (Jan 2006), there was no significant reduction in heart attacks, strokes and deaths among the women while the male participants on statins had fewer heart attacks and strokes.
 

Weigh the Risks and Benefits with Genetic Testing

 
Some side effects of statins and other drugs may be reduced by either altering the dose or by changing the particular statin prescribed. Side effects in general may be reduced by taking into account the variation in your drug metabolism genes. The study of variation in the drug metabolism genes defines the field of Pharmacogenetics. This advanced genomics field emerged after the human genome was sequenced and has become an important field of its own.
 

Rxight® Pharmacogenetic Testing for Statin Side Effects

 
Pharmacogenetics research showed there is variation in the genes that are responsible for processing drugs. That means that if a particular gene has variations it may result in a gene product (protein or enzyme) that is non-functional or has reduced function. This altered function, which can sometimes mean an inability to process a medication or a reduced ability to process a medication, may result in adverse side effects. Side effects may be lessened by avoiding those drugs that you don’t have the ability to process normally.

 
Once you and your physSician have these results you can use them for your lifetime. The results allow your physician to interpret your ability to metabolize over 200 drugs on the market. Your physician will then have at hand the predictive ability to prescribe drugs that are safer for you and to possibly avoid side effects with any new medication. With the Rxight® pharmacogenetic test from MD Labs you can bring precision medicine home to your personalized medical care.

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Research Shows Ultrarapid Metabolizers of CYP2D6 Face Increased Risk of Hospitalization

By | Adverse Drug Reactions, Pharmacogenetic Testing, Pharmacogenomics, Precision Medicine, Provider | No Comments

The cytochrome P450 2D6 (CYP2D6) hepatic enzyme is responsible for the metabolism a wide range of medications and other substances. For example, opioids such as codeine, morphine and tramadol are activated by CYP2D6, while several classes of antidepressants and antipsychotics are in made inactive by the CYP2D6 enzyme. While it has been shown extensively that variation within the genes controlling drug metabolism has been associated with toxicity/adverse drug reactions or conversely drug inefficacy, there is a dearth of data on the adverse health outcomes of the potential impact of extreme metabolism phenotypes (ultrarapid / poor metabolism of CYP2D6) on hospitalization and emergency department (ER) visits.
 
A recent study published in Pharmacogenomics and Personalized Medicine “Increased risk of hospitalization for ultrarapid metabolizers of cytochrome P450 2D6” (Jun 2016) found a patient’s CYP2D6 phenotype has a statistically significant impact on the rate of hospitalization from adverse drug effects for ultra-rapid metabolizers in comparison to extensive metabolizers. The hypothesis was that participants with ultra-rapid and poor metabolism would have higher rates of hospitalization.
 
The investigators examined hospital records over a 9-year period, employed data from the Mayo Clinic Biobank on patients enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT) protocol, which sequenced 86 pharmacogenomics genes for clinical use. For the study, a cohort of 929 adult patients underwent CYP2D6 testing. CYP2D6 clinical phenotypes ranged from ultrarapid to poor metabolizer, with extensive metabolizer being the reference group. There was no statistically significant difference between other CYP2D6 phenotypes and controls.
“Precision medicine within pharmacogenomics can be used to predict adverse health outcomes such as hospitalization,” the study’s authors concluded. “There may be clinical utility in pre-emptively genotyping patients to decrease health care use.”

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