The role of pharmacogenetics in treating central nervous system disorders.

Symptoms of central nervous system (CNS) disorders include abnormalities in both physical and psychological domains. Many drugs indicated for the treatment of CNS disorders are fraught with side effects and/or poor efficacy which impact patients' quality of life and drives non-compliance. Moreover, for many CNS drugs such as antidepressants and antipsychotics, it takes time to determine whether a particular drug is efficacious in an individual patient. To optimize drug treatment for each patient, prescribing physicians often need to raise or lower doses, switch drug classes, or prescribe additional drugs to mitigate side effects, often in a "trial and error" fashion. Pharmacogenetic (PGx) testing, particularly in the realm of CNS therapy, can reduce the unpredictability of this process. By determining a patient's genetic profile, individual therapy parameters may be predicted pre-treatment for drug efficacy, optimal drug dose, and the risk of adverse drug reactions (ADRs). The intent of this review is to highlight the power of PGx testing to predict the likelihood of ADRs and efficacy during the treatment of the following CNS disorders: epilepsy, bipolar disorder, schizophrenia and depression.

Commercial molecular diagnostics in the U.S.: The Human Genome Project to the clinical laboratory.

Molecular diagnosis is the detection of pathogenic mutations in DNA and RNA samples to aid in detection, diagnosis, subclassification, prognosis, and monitoring response to therapy. Principles underlying nucleic-based diagnosis originate from localization, identification, and characterization of genes responsible for human disease. Clinical molecular genetics is now part of the mainstream of medical care in the United States. All commercial clinical reference laboratories now have a molecular genetic diagnostic unit, many of which are in contractual agreement with third party payers to provide services. Gene discovery provides valuable insight into the mechanisms of disease processes and gene-based markers will enable clinicians to study disease predisposition, as well as improved methods for diagnoses, prognosis, and monitoring of therapy. The broad range of mutation spectrum and type performed in the clinical laboratory requires the use of multiple technologies rather than a single typing platform. Platform choice depends on such diverse factors as local expertise, test volume, economies of scale, R&D budget, and royalties. Test validation is a major hurdle and positive control samples are often not readily available. Oversight and the regulatory environment for clinical molecular genetics laboratories in the United States are evolving rapidly. Several government agencies and private organizations are currently involved in revision of specific laboratory standards, including the Secretary's Advisory Committee on Genetic Testing (SACGT), Food and Drug Administration (FDA), Center for Disease Control (CDC), College of American Pathologists (CAP), American College of Medical Genetics (ACMG), and the individual states.

Image analysis: a novel approach for the quantification of antineutrophil cytoplasmic antibody levels in patients with Wegener's granulomatosis.

Rises in antineutrophil cytoplasmic antibodies (ANCA) directed against proteinase 3 (PR3) have predictive potential for a relapse of Wegener's granulomatosis (WG). To assess the value of image analysis for monitoring ANCA levels, we measured PR3-ANCA in a cohort of PR3-ANCA positive patients with WG that were prospectively followed in our clinic and compared findings with other techniques. ANCA levels were measured serially by quantitative image analysis, titration in indirect immunofluorescence (IIF), two different directly coated antigen-specific enzyme-linked immunosorbent assays (ELISA), and a capture ELISA using a PR3-specific monoclonal antibody in 16 consecutive WG patients prior to a renal relapse, and in 16 age- and sex-matched patients with inactive WG. The positive predictive value (PPV) of an increase in ANCA titers by image analysis for relapse was 69% (11 of 16). The PPV of an increase in ANCA was 61% (11 of 18) by IIF, 71% (12 of 17) by a commercial direct ELISA, 63% (12 of 19) by in-house direct ELISA, and 75% (12 of 16) by capture ELISA. The negative predictive value (NPV) of the absence of an increase in ANCA titers by image analysis for relapse was 69% (11 of 16). The NPV of the absence of an increase in ANCA was 64% (9 of 14) by IIF, 73% (11 of 15) by a commercial direct ELISA, 63% (9 of 13) by in-house direct ELISA, and 75% (12 of 16) by capture ELISA. In conclusions, quantitative image analysis is a novel technique based on the principle of IIF to quantify ANCA levels in a single dilution in a patient sample. No major differences were observed between image analysis and the other techniques in their capacity to predict relapses of disease activity.