Personalizing Multiple Sclerosis Management: Application of Genomics and CYP2C9 Testing
Fatigue, pain, and impaired coordination and cognition are symptoms associated with multiple sclerosis (MS), a chronic autoimmune, inflammatory, demyelinating disease of the central nervous system. The condition is characterized by relapsing-remitting episodes, with gradually increasing severity of symptoms and disability over time. Episodes can vary in duration and intensity and can differ from one person to the next such that no 2 cases of the disease are the same.1 The estimated prevalence of MS is estimated to be 362.6 per 100,000 individuals, and women are affected up to 3 times more frequently than men (Figure).1,2
The clinical course of MS is highly heterogeneous but can be broadly classified as relapsing MS (RMS) — which includes clinically isolated syndrome (CIS), relapsing-remitting MS (RRMS), and active secondary progressive MS (SPMS) — or progressive MS (PMS), which includes primary PMS (PPMS) and inactive/worsening secondary PMS (SPMS).3 Approximately 85% of all patients with MS have RRMS and 10% to 15% have PPMS. More than two-thirds of patients with RRMS will develop SPMS within 10 to 15 years of disease onset.4
While the etiology of MS remains unclear, the disease is associated with genetic predisposition. The development of active disease is thought to be triggered by an autoimmune response in the white matter of the brain and spinal cord that causes central nervous system demyelination and axonal degeneration.5 Over the past 2 decades, various classes of disease-modifying therapies (DMTs) have been approved by the US Food and Drug Administration (FDA) for the management of RMS; these therapies include immunomodulators, immunosuppressants, and sphingosine 1-phosphate receptor modulators (S1PRMs).6 The highly heterogeneous clinical manifestations and disease course of RMS suggest a complex and pathophysiologically distinct subset of patients who differ substantially in their response to treatment, even to agents in the same drug class. These differences have been attributed to differences in a patient’s genomic characteristics.7 Deciphering the genetic heterogeneity of RMS and identifying specific disease biomarkers may pave the way for a more targeted and personalized approach to disease management.8 Although clinically actionable pharmacogenomic biomarkers that would enable more personalized treatment of RMS are currently limited, significant progress is being made.
Genomic Characteristics and Personalized MS Disease Management
As MS is a heterogeneous and progressive condition, identifying specific disease biomarkers can help to predict the severity of disease course, facilitate diagnosis, and initiate individualized treatment decision-making. For example, genetic susceptibility to MS disease severity is associated with the human leukocyte antigen (HLA) DRB1*1501 allele.4,9 A DRB1*1501 carrier status predicts disease severity in 4 domains of MS pathology: (1) reduction in the N-acetyl-aspartate concentration within normal-appearing white matter; (2) an increase in the volume of white matter lesions; (3) a reduction in normalized brain parenchymal volume; and (4) impairments in cognitive function. Consistent with MS gender distribution, significantly more women than men are identified as DRB1*1501 carriers (74% vs 63%; P =.009). Furthermore, the expression profiling of CD4+ cells has been shown to predict the future behavior of patients with CIS.9
Evidence suggests a limited window of time to initiate effective treatment to minimize the risk of early brain atrophy and cognitive and physical deficits7; therefore, prompt treatment initiation is essential and starts with an accurate diagnosis. A misdiagnosis of MS is a continuing challenge because several diseases mimic MS symptoms.10 Specific biomarkers have been identified that can distinguish the pathophysiologic features of MS from other neurologic conditions and are used to inform the differential diagnosis. Other biomarkers have been identified to support treatment selection and prognostic assessment.11,12
While several treatment options have been approved by the FDA for RMS, only 30% of patients respond to treatment. Between 30% and 50% of patients do not respond optimally to first-line therapies.4,7 Literature suggests that genetic variability can significantly affect response to treatment in patients with MS.7,13 However, designing treatment that is specific to each patient’s genetic signature is a herculean task, if not impossible. It then becomes necessary to define specific genetic features of the disease that can be used to predict treatment response, anticipate the risk of treatment side effects, or identify patients in whom treatment is contraindicated.7,9,12
Although studies investigating MS biomarkers for disease severity and treatment response currently lack sufficient evidence for clinical application,13 the available information suggests that gene expression signatures may help predict long-term treatment response. Various treatments for RMS — including interferon beta (IFN-β), glatiramer acetate, mitoxantrone, and natalizumab — have been studied to explore the association with several genes. Neutralizing antibodies have also been analyzed as a possible biomarker for treatment nonresponse.7While additional studies are needed to establish a clear association between specific genes and treatment response, the evidence supports the goal of developing meaningful biomarkers for monitoring MS disease course, determining treatment indication, and guiding appropriate treatment selection.
Pharmacogenomics is increasingly available in clinical settings. Known molecular biomarkers to diagnose MS include oligoclonal bands, the immunoglobulin G (IgG) index, and presence of anti-aquaporin (AQP)-4 antibodies, neutralizing antibodies against IFN-β and natalizumab, anti-JCV antibodies, and antivaricella zoster virus (VZV) antibodies.12 These pharmacogenomic assessments can be used in conjunction with standard imaging modalities to enable a faster and more accurate diagnosis and precise management strategies.11,12 With a growing number of approved treatment options for MS (Table),6,14 more specific biomarkers are needed to select patients and more precisely predict treatment response, thus providing the opportunity to personalize and optimize treatment for patients with RMS.
Application of Genomics to Guide Treatment of RMS: Illustration With S1PRMs
Optimal treatment of RMS remains challenging, and several new therapeutic targets have been explored. One such target is S1P, a bioactive lysophospholipid signaling molecule found in several organs — including the central nervous system — that is involved in a wide range of physiologic and pathophysiologic processes. Elevated S1P levels in the cerebrospinal fluid and brain parenchyma of patients with MS have been associated with disease progression.15,16 There are 5 recognized S1PR subtypes, and their expression pattern and effects vary depending on the receptor that is targeted. S1PRMs are a newer class of therapies for RMS, and currently 4 of the S1PRMs — fingolimod,17 siponimod,18 ozanimod,19 and ponesimod20 — are approved by the FDA.
Fingolimod, the first S1PRM approved for RRMS, targets 4 of the receptor subtypes: S1PR 1, 3, 4, and 5. Fingolimod is a lipophilic molecule that can readily cross the blood-brain barrier, where it is phosphorylated by sphingosine kinases into its active form, fingolimod-P. It is approved by the FDA for the treatment of CIS, RRMS, and active SPMS. However, fingolimod-P bioavailability is relatively low, and first-dose adverse events (AEs) include bradycardia, liver enzyme elevations, and lymphopenia.16,17
Second-generation S1PRMs were designed to improve S1PR specificity, increase bioavailability, and reduce AEs; these agents include ponesimod, ozanimod, and siponimod. Ponesimod is a selective S1PRM that does not require phosphorylation for activation and is approved by the FDA for the treatment of CIS, RRMS, and active SPMS.16,21 It is rapidly absorbed and reaches maximal availability within 2 to 4 hours. Bradycardia and atrioventricular block are common AEs reported after the first dose, although optimized up-titration can mitigate the first-dose effect on heart rate.20
Ozanimod is a selective S1PR 1 and 5 modulator that does not require phosphorylation for activation and is approved by the FDA for the treatment of CIS, RRMS, and active SPMS.19,21 Despite its higher volume of distribution, ozanimod absorption is slow, reaching maximum concentrations after 6 to 8 hours, which could account for its increased tolerability in terms of reduced first-dose effects on heart rate.22
Like ozanimod, siponimod is selective for S1PR 1 and 5, does not require phosphorylation for activation, is highly bioavailable, and binds with high affinity. The time to reach maximum plasma concentrations is 3 to 8 hours. Siponimod is approved by the FDA for the treatment of CIS, RRMS, and active SPMS.16,18,21
First-dose cardiovascular AEs are common with S1PRMs; however, specific cardiovascular risk varies between the modulators. In addition, dose adjustments are needed based on a patient’s the genetic profile for cytochrome P450 (CYP) 2C9 and CYP3A4.
Mitigating the Cardiovascular Risk of S1PRMs and Adjusting Dose Based on Genotype Testing for CYP2C9 and CYP3A4
As they are generally associated with some first-dose cardiovascular AEs, S1PRMs require close patient monitoring, particularly for patients with pre-existing cardiac diseases. In a pooled analysis of 17 randomized trials (12 for fingolimod, 3 for ozanimod, and 2 for siponimod) involving 13,295 patients, the risk of cardiovascular AEs was 1.21 times higher with S1PRM use compared with placebo or other DMTs; specifically, patients treated with S1PRMs were at 2.92- and 2.00-fold increased risk for bradyarrhythmia and hypertension, respectively. However, subgroup analysis found that ozanimod was associated with a higher risk of hypertension compared with siponimod (risk ratio [RR], 1.76; 95% CI, 1.10-2.82 vs 1.39; 95% CI, 0.99-1.96). Siponimod was associated with a higher risk of bradyarrhythmia than ozanimod (RR, 2.75; 95% CI, 1.75- 4.31 vs 1.05; 95% CI, 0.31-3.59).23
Although siponimod does not undergo phosphorylation for activation, it undergoes hepatic biotransformation mediated by enzymes encoded by the CYP2C9/CYP3A4 gene before excretion in the feces.21,24 The CYP2C9/CYP3A4 enzymes metabolize compounds, including steroid hormones and fatty acids, for excretion. Siponimod is the only S1PRM that needs genotyping for CYP2C9/CYP3A4 with dose adjustment based on genetic status. In CYP2C9/CYP3A4, inhibitors increase the siponimod dose, and inducers reduce the dose. Use of siponimod is not recommended with moderate CYP2C9 and moderate or strong CYP3A4 inhibitors. Siponimod use is also not recommended with moderate CYP2C9 and strong CYP3A4 inducers.18
Expansion of RMS treatment options can make treatment selection challenging. Therefore, what are the key considerations and approaches to treatment selection?
Escalation vs Induction Strategy and Key Considerations for Selecting Treatment
Treating a patient with RMS generally follows an escalation or induction strategy. The escalation strategy involves a stepwise increase in treatment, starting with a first-line DMT and, when there are signs of breakthrough disease activity, advancing to a second-line agent.25 The induction strategy, considered more aggressive, involves the initial use of second-line therapies.
A study involving 2700 patients from the Swedish MS registry and 2161 patients from the Danish MS registry found that outcomes of patients who were treated with an escalation strategy were inferior to those who were treated with an induction strategy.25
The selection of S1PRMs requires key considerations, among which is the half-life, which differs substantially with potential implications for therapy adherence, risk of rebound, and sequencing of medication. Fingolimod has a half-life of 6 to 9 days, siponimod 22 to 38 hours, ozanimod 19 to 22 hours, and ponesimod 32 hours. A risk of rebound has been reported for fingolimod and siponimod.21 As the risk of skin cancer has been reported with S1PRMs, patients should undergo dermatologic monitoring.26 Given the risk of first-dose cardiovascular AEs, a comprehensive assessment is necessary prior to starting patients on treatment with an S1PRM.23
- Clinicians should consider avoiding S1PRMs in patients with a history of unstable angina, heart attack, stroke, transient ischemic attack, decompensated heart failure, class III or IV heart failure, second- or third-degree atrioventricular block, sinoatrial block, or sick sinus syndrome (except for patients with a pacemaker).
- During treatment, monitor heart rate, electrical conduction events, and blood pressure via active electrocardiography recording for at least 6 hours after the first dose and then prolonged according to patient situation.
- If unintentional first-dose effects occur after treatment interruptions, reinstate treatment with dose titration.
- Long-term follow-up of 1.5 to 3 years is advised, focusing on heart rate and blood pressure.
Summary
MS is a chronic progressive autoimmune inflammatory demyelinating disease of the central nervous system. Most cases are RMS, which are the most challenging to diagnose. In addition, the significantly heterogeneous disease presentation and treatment response are genetically linked. Therefore, specific genomic biomarkers can be used to predict the severity of disease course, facilitate differential diagnosis, and initiate individualized treatment decision-making to optimize patient outcomes. The application of a genomic biomarker has been demonstrated with S1PRMs, a newer class of therapies for RMS. Siponimod is the only S1PRM that undergoes hepatic biotransformation mediated by enzymes encoded by the CYP2C9/CYP3A4 gene. Therefore, before administration, CYP2C9/CYP3A4 status must be determined for patient selection and appropriate dose adjustment. Appropriate patient selection is also essential for minimizing the risk of cardiovascular events associated with S1PRMs.
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Reviewed September 2022
