Association of a Single-Nucleotide Variant rs11100494 of the NPY5R Gene with Antipsychotic-Induced Metabolic Disorders

Clinical Utility and Implementation of Pharmacogenomics for the Personalisation of Antipsychotic Treatments

Decades of pharmacogenetic research have revealed genetic biomarkers of clinical response to antipsychotics. Genetic variants in antipsychotic targets, dopamine and serotonin receptors in particular, and in metabolic enzymes have been associated with the efficacy and toxicity of antipsychotic treatments. However, genetic prediction of antipsychotic response based on these biomarkers is far from accurate. Despite the clinical validity of these findings, the clinical utility remains unclear. Nevertheless, genetic information on CYP metabolic enzymes responsible for the biotransformation of most commercially available antipsychotics has proven to be effective for the personalisation of clinical dosing, resulting in a reduction of induced side effects and in an increase in efficacy. However, pharmacogenetic information is rarely used in psychiatric settings as a prescription aid. Lack of studies on cost-effectiveness, absence of clinical guidelines based on pharmacogenetic biomarkers for several commonly used antipsychotics, the cost of genetic testing and the delay in results delivery hamper the implementation of pharmacogenetic interventions in clinical settings. This narrative review will comment on the existing pharmacogenetic information, the clinical utility of pharmacogenetic findings, and their current and future implementations.

[Weight gain and treatment with psychotropic drugs : Background and management]

Psychotropic drug-induced weight gain (PIWG) is a well-known and frequent side effect which is relevant for the prognosis of patients. Individual medications have varying risks for the occurrence of PIWG, and at the same time there are individual risk factors on the part of patients, such as age, gender, metabolic and genetic factors. As the metabolic changes in the context of PIWG result in increased mortality in the long term, it is important to prevent PIWG by appropriate prevention and to intervene in a targeted manner if PIWG has already occurred. Appropriate monitoring is therefore essential. This article provides an overview of underlying mechanisms, risk constellations and possible countermeasures.

Valproate-Induced Metabolic Syndrome

Valproic acid (VPA) and its salts (sodium calcium magnesium and orotic) are psychotropic drugs that are widely used in neurology and psychiatry. The long-term use of VPA increases the risk of developing adverse drug reactions (ADRs), among which metabolic syndrome (MetS) plays a special role. MetS belongs to a cluster of metabolic conditions such as abdominal obesity, high blood pressure, high blood glucose, high serum triglycerides, and low serum high-density lipoprotein. Valproate-induced MetS (VPA-MetS) is a common ADR that needs an updated multidisciplinary approach to its prevention and diagnosis. In this review, we consider the results of studies of blood (serum and plasma) and the urinary biomarkers of VPA-MetS. These metabolic biomarkers may provide the key to the development of a new multidisciplinary personalized strategy for the prevention and diagnosis of VPA-MetS in patients with neurological diseases, psychiatric disorders, and addiction diseases.

Blood and Urinary Biomarkers of Antipsychotic-Induced Metabolic Syndrome

Metabolic syndrome (MetS) is a clustering of at least three of the following five medical conditions: abdominal obesity, high blood pressure, high blood sugar, high serum triglycerides, and low serum high-density lipoprotein (HDL). Antipsychotic (AP)-induced MetS (AIMetS) is the most common adverse drug reaction (ADR) of psychiatric pharmacotherapy. Herein, we review the results of studies of blood (serum and plasma) and urinary biomarkers as predictors of AIMetS in patients with schizophrenia (Sch). We reviewed 1440 studies examining 38 blood and 19 urinary metabolic biomarkers, including urinary indicators involved in the development of AIMetS. Among the results, only positive associations were revealed. However, at present, it should be recognized that there is no consensus on the role of any particular urinary biomarker of AIMetS. Evaluation of urinary biomarkers of the development of MetS and AIMetS, as one of the most common concomitant pathological conditions in the treatment of patients with psychiatric disorders, may provide a key to the development of strategies for personalized prevention and treatment of the condition, which is considered a complication of AP therapy for Sch in clinical practice.