Multiple Sclerosis: Advances in Clinical Trial Design, Treatment and Future Perspectives

Clinical trials in progressive multiple sclerosis: Lessons learned and future perspectives

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Robustness considerations in Bayesian analysis.

Statistical Methods in Medical Research , 5, pp. Smoking and middle ear disease. Otolaryngol Head Neck Surg , , pp. Statistical and design considerations for multiple sclerosis clinical trials. Surveillance of clustering near point sources. Statistics in Medicine , 15, pp. Time series models with univariate margins in the convolution-closed infinitely divisible class. Journal of Applied Probability , 33, pp. Zidovudine absorption and small intestinal function in HIV seropositive patients. Approximations to multivariate normal rectangle probabilities based on conditional expectations.

Journal of the American Statistical Association , 90, pp. An assessment of pNEM: A Bayesian analysis of bivariate survival data from a multicentre cancer clinical trial. Statistics in medicine , 14, pp. Bayesian multivariate spatial interpolation: A bootstrap based on the estimating equations of the linear model. Biometrika , 82, pp. Freezing influences the healing of rabbit medial collateral ligament autografts. None have been validated for use in clinical practice.

This review covers pharmacogenetic markers in clinical practice in other diseases and then reviews the current status of MS DMT markers interferon , glatiramer acetate, and mitoxantrone. For a complex disease such as MS, multiple biomarkers may need to be evaluated simultaneously to identify potential responders. These will require extensive validation in large patient groups before they can be used in clinical practice.

Multiple sclerosis MS is a chronic, immune-mediated, inflammatory, neurodegenerative disorder. The diagnosis is three times more common in women than in men [ 1 , 2 ]. The precise etiology of MS is unknown; however, there is strong evidence that it arises from complex interactions between environmental and genetic factors. With regard to genetic factors, genome-wide association studies GWAS have identified almost genetic variants associated with MS susceptibility, most of which are involved in the immune response and are often associated with other immune-mediated diseases [ 3 — 6 ].

A strong association has been found between the major histocompatibility complex MHC region and MS susceptibility, with human leukocyte antigen- HLA- showing the strongest effect [ 7 ]. Other contributors include the interleukin-2 receptor and interleukin-7 receptor alleles [ 8 ].

Environmental factors associated with MS include exposure to infectious organisms, for example, Epstein-Barr virus, vitamin D levels and sunlight exposure, tobacco use, geographical latitude, and possibly antigenic determinants in the gut microbiome [ 9 — 12 ]. Although there are currently no therapies recognized to reverse the neurodegenerative process of MS, significant progress has been made over the last two decades in the treatment of relapsing forms of MS RMS with the introduction of disease-modifying therapies DMTs that decrease the frequency of relapses and slow development of disability.

Responses to these treatments, as defined by reduced relapse rates, improved magnetic resonance imaging outcomes, and preservation of neurological function, vary between patients, and there are notable differences in adverse effect profiles [ 14 ]. Glatiramer acetate treatment can cause localized lipoatrophy that can be distressing to patients. Natalizumab treatment, and to a much lesser extent dimethyl fumarate and fingolimod treatments, is associated with a rare but potentially fatal demyelinating disorder known as progressive multifocal leukoencephalopathy. Mitoxantrone treatment can cause cardiotoxicity and acute leukemia.

Clinical trials in progressive multiple sclerosis: lessons learned and future perspectives.

Fingolimod has been associated with herpes infections, macular edema, and cardiac conduction issues. Although attempts are underway to identify biomarkers that can be used to monitor response to therapy during treatment [ 15 , 16 ] and patients are monitored for the occurrence of adverse effects, it would clearly be beneficial if biomarkers could be used before initiating treatment to identify patients who are likely to respond. It would also be helpful to identify those who are more likely to experience a serious adverse effect [ 14 ].

Such approaches would avoid unnecessary costs and negative effects on quality of life resulting from treating patients with drugs to which they will not respond and which may be associated with unacceptable adverse events.

Drug response is affected by pharmacokinetic, pharmacodynamic, physiological, pathological, and environmental factors; drug mechanism of action, formulation, and route of administration; and patient characteristics Table 1. Genetic polymorphisms that influence the activity of proteins regulating the pharmacodynamic and pharmacokinetic properties of drugs are key contributors to the variability in response to drugs between individuals. For example, cytochrome P CYP enzymes are the major enzymes involved in drug metabolism.

Polymorphisms in these enzymes can result in either ultrafast metabolism of therapeutic drugs, thereby limiting their efficacy, or poor metabolism, thereby increasing the risk of toxicity [ 17 ]. Identification of genetic differences associated with variability in drug response would allow better-informed decisions regarding choice of treatment. The aim of this article is to review basic definitions of genetic biomarkers and how they are being used in other disorders and then to review their current status in MS.

Pharmacogenomics is the study of how genes affect drug response. Both inherited and acquired genetic variations may be involved. A genomic biomarker could, for example, be the degree of expression of a gene, the function of a gene, or the regulation of a gene [ 18 ]. Pharmacogenetics is a subset of pharmacogenomics. It involves variations in DNA sequences as they relate to drug metabolism and response [ 18 ].

A genetic variation may range from a single nucleotide polymorphism SNP to loss of part of a chromosome. Key applications for pharmacogenetic biomarkers are the identification of responders and nonresponders to medications, avoidance of adverse events, and optimization of drug dose. Almost all therapeutic areas have at least one drug for which pharmacogenomic guidance exists, including psychiatry, rheumatology, gastroenterology, endocrinology, and dermatology; however, by far, the best represented therapeutic area is oncology Table 2. The vast majority of drugs have guidance concerning variations in DNA sequence which relate to drug response, which are therefore classed as pharmacogenetic biomarkers.

Examples of drugs with pharmacogenetic guidance are presented in Table 3. Pharmacogenetic information may pertain to many aspects of drug use, including definition of specific patient populations for which a drug is indicated or contraindicated, for which dose adjustments could be necessary, and also in which potentially serious adverse events could occur. For the majority of oncology drugs, the inclusion of biomarkers in drug labels generally corresponds to a requirement or recommendation for genetic testing; however, in other therapeutic areas, there is no specific guidance on what actions should be taken based on biomarker information.

In the area of infectious diseases, there are at least 17 drugs with pharmacogenetic information in their labeling [ 19 ]. For the majority of these, the guidance relates to the presence of a pharmacogenetic marker and the increased likelihood of adverse effects associated with treatment. Abacavir is a synthetic carbocyclic nucleoside analog with inhibitory activity against human immunodeficiency virus.

The labeling of abacavir states that all patients should be screened for the presence of the allele before initiating or reinitiating abacavir therapy, unless the patient has a previously documented allele assessment [ 20 ].

Abacavir is contraindicated in patients who are positive for the allele because of the high risk of experiencing a hypersensitivity reaction [ 20 ]. Systematic analysis has indicated that testing for before initiating abacavir is cost-effective [ 21 ], and companion diagnostic tests are available for this allele, although no specific test is recommended in the drug label [ 22 ].

In oncology, there are at least 54 drugs with pharmacogenetic information in their labeling [ 19 ]. For over half, the pharmacogenetic information relates to a specific indication or usage [ 19 ]. It is not recommended for use in patients with wild-type BRAF melanoma, as safety and efficacy have not been demonstrated in this population. Accordingly, the requirement for the presence of this mutation is specified in the indications for vemurafenib within the drug label [ 23 ]. Despite the codevelopment and coapproval of the drug and diagnostic test, the label does allow for another FDA-approved test to be used if desired [ 23 ].

Only a handful of hematology drugs have pharmacogenetic information in their labeling, mostly relating to warnings and precautions [ 19 ]. Lenalidomide is one of the few drugs with pharmacogenetic information pertaining to its indication. In an initial study involving patients with myelodysplastic syndromes who did not respond to treatment with recombinant erythropoietin, a greater proportion of patients with a 5q deletion no longer needed red cell transfusions after being treated with lenalidomide compared with patients with other karyotypes [ 24 ].

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This observation was confirmed in further studies, leading to a defined indication for lenalidomide for the treatment of transfusion-dependent anemia due to International Prognostic Scoring System low- or intermediate-1 risk myelodysplastic syndromes associated with a 5q deletion abnormality with or without additional cytogenetic abnormalities [ 25 ]. No specific guidance is provided regarding testing for 5q deletion.

Some drugs used to treat heritable genetic diseases, such as cystic fibrosis and certain inborn errors of metabolism, also have pharmacogenetic information in their labeling. Specific guidelines are available to facilitate the interpretation of genotype tests to guide ivacaftor therapy [ 27 ].

In the field of schizophrenia, aripiprazole, an atypical antipsychotic, has pharmacogenetic information in its label relating to its use in patients with poor CYP2D6 metabolism. In endocrinology, glimepiride, a sulfonylurea indicated as an adjunct to diet and exercise to improve glycemic control in adults with type 2 diabetes mellitus, has guidance in its label relating to its use in individuals who are glucosephosphate dehydrogenase-deficient, owing to the risk of hemolytic anemia.

Finally, in the area of transplantation, mycophenolic acid is contraindicated in patients with hereditary deficiency of hypoxanthine-guanine phosphoribosyltransferase, as use of mycophenolate in such patients may cause exacerbation of disease symptoms. To date, the routinely used pharmacogenetic biomarkers reflect relatively simple, well-defined genetic changes.

Multiple Sclerosis International

Considerable efforts are now being made to establish pharmacogenetic biomarkers for polygenic diseases, such as cancer, chronic kidney disease, MS, cardiovascular disease, and neuropsychiatric illnesses. In these indications, numerous genes and their products are potentially involved in disease manifestation, drug metabolism, and drug mechanism of action, and the individual contribution of each gene may be small [ 28 — 30 ]. In , a systematic review of pharmacogenetic studies found that most had examined genetic variations in drug targets i.

However, this is no doubt a consequence of early studies using a candidate-gene approach to identify potential genes. The candidate-gene approach directly tests the effects of genetic variants of a potentially contributing gene in an association study. A higher frequency of a particular allele or genotype in a series of individuals with a specific disease or phenotype can be interpreted as meaning that the allelic variant or genotype is associated with that disease or the disease phenotype [ 31 ].

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