Psychotropic drugs can induce substantial weight gain, particularly during the first 6 months of treatment. The authors aimed to determine the potential predictive power of an early weight gain after the introduction of weight gain-inducing psychotropic drugs on long-term weight gain. Data were obtained from a 1-year longitudinal study ongoing since 2007 including 351 psychiatric (ICD-10) patients, with metabolic parameters monitored (baseline and/or 1, 3, 6, 9, 12 months) and with compliance ascertained. International Diabetes Federation and World Health Organization definitions were used to define metabolic syndrome and obesity, respectively. Prevalences of metabolic syndrome and obesity were 22% and 17%, respectively, at baseline and 32% and 24% after 1 year. Receiver operating characteristic analyses indicated that an early weight gain > 5% after a period of 1 month is the best predictor for important long-term weight gain (≥ 15% after 3 months: sensitivity, 67%; specificity, 88%; ≥ 20% after 12 months: sensitivity, 47%; specificity, 89%). This analysis identified most patients (97% for 3 months, 93% for 12 months) who had weight gain ≤ 5% after 1 month as continuing to have a moderate weight gain after 3 and 12 months. Its predictive power was confirmed by fitting a longitudinal multivariate model (difference between groups in 1 year of 6.4% weight increase as compared to baseline, P = .0001). Following prescription of weight gain-inducing psychotropic drugs, a 5% threshold for weight gain after 1 month should raise clinician concerns about weight-controlling strategies.

A high prevalence of obesity has been described in psychiatric patients, with reported increased mortality,^1-3 due not only to the underlying illness and related comorbidities, but also to the pharmacological treatment.^4-8 Atypical antipsychotics and other drugs, such as the mood stabilizers lithium and valproate,^9-12 can induce substantial weight gain in selected patients. This is a serious adverse effect considering that obesity can lead to metabolic complications such as dyslipidemia, type 2 diabetes, and cardiovascular disease, which may ultimately reduce life expectancy by several years.^13-15

Objectives: More than 40 drugs are available to treat affective disorders. Individual selection of the optimal drug and dose is required to attain the highest possible efficacy and acceptable tolerability for every patient. Methods: This review, which includes more than 500 articles selected by 30 experts, combines relevant knowledge on studies investigating the pharmacokinetics, pharmacodynamics and pharmacogenetics of 33 antidepressant drugs and of 4 drugs approved for augmentation in cases of insufficient response to antidepressant monotherapy. Such studies typically measure drug concentrations in blood (i.e. therapeutic drug monitoring) and genotype relevant genetic polymorphisms of enzymes, transporters or receptors involved in drug metabolism or mechanism of action. Imaging studies, primarily positron emission tomography that relates drug concentrations in blood and radioligand binding, are considered to quantify target structure occupancy by the antidepressant drugs in vivo. Results: Evidence is given that in vivo imaging, therapeutic drug monitoring and genotyping and/or phenotyping of drug metabolising enzymes should be an integral part in the development of any new antidepressant drug. Conclusions: To guide antidepressant drug therapy in everyday practice, there are multiple indications such as uncertain adherence, polypharmacy, nonresponse and/or adverse reactions under therapeutically recommended doses, where therapeutic drug monitoring and cytochrome P450 genotyping and/or phenotyping should be applied as valid tools of precision medicine.

For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialized tools are used. Three tools have been proven useful to personalize drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging. In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 50 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)). Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings. All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimize treatment effects, minimize side effects and ultimately reduce the global burden of diseases, personalized drug treatment has not yet become the standard of care in psychiatry.

Cardiovascular diseases and dyslipidemia represent a major health issue in psychiatry. Many psychotropic drugs can induce a rapid and substantial increase of blood lipid levels. This study aimed to determine the potential predictive power of an early change of blood lipid levels during psychotropic treatment on long-term change and on dyslipidemia development. Data were obtained from a prospective study including 181 psychiatric patients with metabolic parameters monitored during the first year of treatment and with adherence ascertained. Blood lipid levels (ie, total cholesterol [TC], low-density lipoprotein cholesterol [LDL-C], high-density lipoprotein cholesterol [HDL-C], non-high-density lipoprotein cholesterol [non-HDL-C], and fasting triglycerides [TGs]) were measured at baseline and after 1, 3, and/or 12 months of treatment. Receiver-operating characteristic analyses indicated that early (ie, after 1 month of psychotropic treatment) increases (≥5%) for TC, LDL-C, TG, and non-HDL-C and decrease (≥5%) for HDL-C were the best predictors for clinically relevant modifications of blood lipid levels after 3 months of treatment (≥30% TC, ≥40% LDL-C, ≥45% TG, ≥55% non-HDL-C increase, and ≥20% HDL-C decrease; sensitivity 70%-100%, specificity 53%-72%). Predictive powers of these models were confirmed by fitting longitudinal multivariate models in the same cohort (P ≤ .03) as well as in a replication cohort (n = 79; P ≤ .003). Survival models showed significantly higher incidences of new onset dyslipidemia (TC, LDL-C, and non-HDL-C hypercholesterolemia, HDL-C hypocholesterolemia, and hypertriglyceridemia) for patients with early changes of blood lipid levels compared to others (P ≤ .01). Early modifications of blood lipid levels following prescription of psychotropic drugs inducing dyslipidemia should therefore raise questions on clinical strategies to control long-term dyslipidemia.