Aurélie Delacrétaz

Importance of early weight changes to predict long-term weight gain during psychotropic drug treatment.

BACKGROUND 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. METHOD 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. RESULTS 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). CONCLUSION 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.

Influence of MCHR2 and MCHR2-AS1 Genetic Polymorphisms on Body Mass Index in Psychiatric Patients and In Population-Based Subjects with Present or Past Atypical Depression

Obesity development during psychotropic treatments represents a major health issue in psychiatry. Melanin-concentrating hormone receptor 2 (MCHR2) is a central receptor involved in energy homeostasis. MCHR2 shares its promoter region with MCHR2-AS1, a long antisense non-coding RNA. The aim of this study was to determine whether tagging single nucleotide polymorphisms (tSNPs) of MCHR2 and MCHR2-AS1 are associated with the body mass index (BMI) in the psychiatric and in the general population. The influence of MCHR2 and MCHR2-AS1 tSNPs on BMI was firstly investigated in a discovery psychiatric sample (n1 = 474). Positive results were tested for replication in two other psychiatric samples (n2 = 164, n3 = 178) and in two population-based samples (CoLaus, n4 = 5409; GIANT, n5 = 113809). In the discovery sample, TT carriers of rs7754794C>T had 1.08 kg/m2 (p = 0.04) lower BMI as compared to C-allele carriers. This observation was replicated in an independent psychiatric sample (-2.18 kg/m2; p = 0.009). The association of rs7754794C>T and BMI seemed stronger in subjects younger than 45 years (median of age). In the population-based sample, a moderate association was observed (-0.17 kg/m2; p = 0.02) among younger individuals (<45y). Interestingly, this association was totally driven by patients meeting lifetime criteria for atypical depression, i.e. major depressive episodes characterized by symptoms such as an increased appetite. Indeed, patients with atypical depression carrying rs7754794-TT had 1.17 kg/m2 (p = 0.04) lower BMI values as compared to C-allele carriers, the effect being stronger in younger individuals (-2.50 kg/m2; p = 0.03; interaction between rs7754794 and age: p-value = 0.08). This study provides new insights on the possible influence of MCHR2 and/or MCHR2-AS1 on obesity in psychiatric patients and on the pathophysiology of atypical depression.

Association of CRTC1 polymorphisms with obesity markers in subjects from the general population with lifetime depression

BACKGROUND Psychiatric disorders have been hypothesized to share common etiological pathways with obesity, suggesting related neurobiological bases. We aimed to examine whether CRTC1 polymorphisms were associated with major depressive disorder (MDD) and to test the association of these polymorphisms with obesity markers in several large case-control samples with MDD. METHODS The association between CRTC1 polymorphisms and MDD was investigated in three case-control samples with MDD (PsyCoLaus n1=3,362, Radiant n2=3,148 and NESDA/NTR n3=4,663). The effect of CRTC1 polymorphisms on obesity markers was then explored. RESULTS CRTC1 polymorphisms were not associated with MDD in the three samples. CRTC1 rs6510997C>T was significantly associated with fat mass in the PsyCoLaus study. In fact, a protective effect of this polymorphism was found in MDD cases (n=1,434, β=-1.32%, 95% CI -2.07 to -0.57, p<0.001), but not in controls. In the Radiant study, CRTC1 polymorphisms were associated with BMI, exclusively in individuals with MDD (n=2,138, β=-0.75kg/m(2), 95% CI -1.30 to -0.21, p=0.007), while no association with BMI was found in the NESDA/NTR study. LIMITATIONS Estimated fat mass using bioimpedance that capture more accurately adiposity was only present in the PsyCoLaus sample. CONCLUSIONS CRTC1 polymorphisms seem to play a role with obesity markers in individuals with MDD rather than non-depressive individuals. Therefore, the weak association previously reported in the population-based samples was driven by cases diagnosed with lifetime MDD. However, CRTC1 seems not to be implicated directly in the development of psychiatric diseases.

Impact of HSD11B1 polymorphisms on BMI and components of the metabolic syndrome in patients receiving psychotropic treatments.

Background Metabolic syndrome (MetS) associated with psychiatric disorders and psychotropic treatments represents a major health issue. 11&bgr;-Hydroxysteroid dehydrogenase type 1 (11&bgr;-HSD1) is an enzyme that catalyzes tissue regeneration of active cortisol from cortisone. Elevated enzymatic activity of 11&bgr;-HSD1 may lead to the development of MetS. Methods We investigated the association between seven HSD11B1 gene (encoding 11&bgr;-HSD1) polymorphisms and BMI and MetS components in a psychiatric sample treated with potential weight gain-inducing psychotropic drugs (n=478). The polymorphisms that survived Bonferroni correction were analyzed in two independent psychiatric samples (nR1=168, nR2=188) and in several large population-based samples (n1=5338; n2=123 865; n3>100 000). Results HSD11B1 rs846910-A, rs375319-A, and rs4844488-G allele carriers were found to be associated with lower BMI, waist circumference, and diastolic blood pressure compared with the reference genotype (Pcorrected<0.05). These associations were exclusively detected in women (n=257) with more than 3.1 kg/m2, 7.5 cm, and 4.2 mmHg lower BMI, waist circumference, and diastolic blood pressure, respectively, in rs846910-A, rs375319-A, and rs4844488-G allele carriers compared with noncarriers (Pcorrected<0.05). Conversely, carriers of the rs846906-T allele had significantly higher waist circumference and triglycerides and lower high-density lipoprotein-cholesterol exclusively in men (Pcorrected=0.028). The rs846906-T allele was also associated with a higher risk of MetS at 3 months of follow-up (odds ratio: 3.31, 95% confidence interval: 1.53–7.17, Pcorrected=0.014). No association was observed between HSD11B1 polymorphisms and BMI and MetS components in the population-based samples. Conclusions Our results indicate that HSD11B1 polymorphisms may contribute toward the development of MetS in psychiatric patients treated with potential weight gain-inducing psychotropic drugs, but do not play a significant role in the general population.

Association of PCK1 with Body Mass Index and Other Metabolic Features in Patients With Psychotropic Treatments.

Abstract Weight gain is a major health problem among psychiatric populations. It implicates several receptors and hormones involved in energy balance and metabolism. Phosphoenolpyruvate carboxykinase 1 is a rate-controlling enzyme involved in gluconeogenesis, glyceroneogenesis and cataplerosis and has been related to obesity and diabetes phenotypes in animals and humans. The aim of this study was to investigate the association of phosphoenolpyruvate carboxykinase 1 polymorphisms with metabolic traits in psychiatric patients treated with psychotropic drugs inducing weight gain and in general population samples. One polymorphism (rs11552145G > A) significantly associated with body mass index in the psychiatric discovery sample (n = 478) was replicated in 2 other psychiatric samples (n1 = 168, n2 = 188), with AA-genotype carriers having lower body mass index as compared to G-allele carriers. Stronger associations were found among women younger than 45 years carrying AA-genotype as compared to G-allele carriers (−2.25 kg/m2, n = 151, P = 0.009) and in the discovery sample (−2.20 kg/m2, n = 423, P = 0.0004). In the discovery sample for which metabolic parameters were available, AA-genotype showed lower waist circumference (−6.86 cm, P = 0.008) and triglycerides levels (−5.58 mg/100 mL, P < 0.002) when compared to G-allele carriers. Finally, waist-to-hip ratio was associated with rs6070157 (proxy of rs11552145, r2 = 0.99) in a population-based sample (N = 123,865, P = 0.022). Our results suggest an association of rs11552145G > A polymorphism with metabolic-related traits, especially in psychiatric populations and in women younger than 45 years.

Prediction of early weight gain during psychotropic treatment using a combinatorial model with clinical and genetic markers.

Background Psychotropic drugs can induce significant (>5%) weight gain (WG) already after 1 month of treatment, which is a good predictor for major WG at 3 and 12 months. The large interindividual variability of drug-induced WG can be explained in part by genetic and clinical factors. Aim The aim of this study was to determine whether extensive analysis of genes, in addition to clinical factors, can improve prediction of patients at risk for more than 5% WG at 1 month of treatment. Methods Data were obtained from a 1-year naturalistic longitudinal study, with weight monitoring during weight-inducing psychotropic treatment. A total of 248 Caucasian psychiatric patients, with at least baseline and 1-month weight measures, and with compliance ascertained were included. Results were tested for replication in a second cohort including 32 patients. Results Age and baseline BMI were associated significantly with strong WG. The area under the curve (AUC) of the final model including genetic (18 genes) and clinical variables was significantly greater than that of the model including clinical variables only (AUCfinal: 0.92, AUCclinical: 0.75, P<0.0001). Predicted accuracy increased by 17% with genetic markers (Accuracyfinal: 87%), indicating that six patients must be genotyped to avoid one misclassified patient. The validity of the final model was confirmed in a replication cohort. Patients predicted before treatment as having more than 5% WG after 1 month of treatment had 4.4% more WG over 1 year than patients predicted to have up to 5% WG (P⩽0.0001). Conclusion These results may help to implement genetic testing before starting psychotropic drug treatment to identify patients at risk of important WG.

F227. PSYCHOLOGICAL TRAUMA OCCURRING DURING ADOLESCENCE IS ASSOCIATED WITH AN INCREASED RISK OF GREATER WAIST CIRCUMFERENCE IN EARLY PSYCHOSIS PATIENTS INDEPENDENTLY OF MEDICATION

Abstract Background The high prevalence of obesity in patients suffering from psychosis is a major concern as it dramatically increases the mortality rates of such patients in the long term. The mechanisms by which these patients develop overweight are poorly understood. It has been suggested that exposure to Childhood Trauma (CT) may play a role in the risk for obesity; however, whether this is the case for Early Psychosis (EP) patients and independently of the impact of medication has yet to be investigated. In addition, it is unknown whether the age at the time of exposure to CT can modulate the link between CT and obesity in EP patients. Methods 136 EP patients aged 18–35 were recruited from the Treatment and Early Intervention in Psychosis Program (TIPP-Lausanne). Body Mass Index (BMI), Weight Gain (WG) and Waist Circumference (WC) were measured and monitored prospectively after psychotropic prescription during a follow-up period of 1 year (patients were assessed at baseline, after 1, 2, 3, 6 months and 1 year of antipsychotic treatment). Patients were classified into Early-Trauma if they had faced at least one experience of abuse (physical, sexual, or emotional) or neglect (physical or emotional) before age 12, and Late-Trauma if the exposure had occurred between ages 12 and 16. Linear Mixed effect models with a random intercept were used to investigate the impact of Trauma (early or late) on the metabolic parameters longitudinally, Marko Chain Monte Carlo (MCMC) method was used to adjust these models with sufficiently large number of MCMC iterations. Models were adjusted for age, socioeconomic status, baseline BMI, medication intake prior to the first assessment and during the treatment phase, and by the diagnosis of depression. Results Patients were more likely to have a diagnosis of Schizophrenia (61%; N=83), they had a mean age of 26 at the time of first assessment, and exposure to 1 or more forms of traumatic experiences before 16 years of age was present in 32% of the sample. No differences between groups were found at baseline in terms of BMI or WC. Late-Trauma patients, when compared to Non-Trauma patients showed greater WCs during the follow-up (p=0.012). No differences between Early or Late-Trauma patients and Non-Trauma patients were found in any of the other outcome measures during the follow up. Baseline BMI and treatment duration were significantly associated with the level of BMI and WC during the follow up. None of the other potential confounding factors were significantly associated with the outcome measures during the follow up. Discussion Exposition to trauma during adolescence in EP patients is associated with a higher risk of greater WC during the early phase of the disease, independently of the medication intake, depression and other confounding factors. Specific preventive measures should be addressed in these patients in order to reduce the risk of obesity. Depending on the timing of traumatic exposure, different developmental mechanisms may underlie this differential possible impact on WC. Further studies on interactions between central consequences of traumatism and metabolic syndrome are warranted.

Influence of polygenic risk scores on lipid levels and dyslipidemia in a psychiatric population receiving weight gain-inducing psychotropic drugs.

Objectives Dyslipidemia represents a major health issue in psychiatry. We determined whether weighted polygenic risk scores (wPRSs) combining multiple single-nucleotide polymorphisms (SNPs) associated with lipid levels in the general population are associated with lipid levels [high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides] and/or dyslipidemia in patients receiving weight gain-inducing psychotropic drugs. We also determined whether genetics improve the predictive power of dyslipidemia. Patients and methods The influence of wPRS on lipid levels was firstly assessed in a discovery psychiatric sample (n=332) and was then tested for replication in an independent psychiatric sample (n=140). The contribution of genetic markers to predict dyslipidemia was evaluated in the combined psychiatric sample. Results wPRSs were significantly associated with the four lipid traits in the discovery (P⩽0.02) and in the replication sample (P⩽0.03). Patients whose wPRS was higher than the median wPRS had significantly higher LDL, TC, and triglyceride levels (0.20, 0.32 and 0.26 mmol/l, respectively; P⩽0.004) and significantly lower HDL levels (0.13 mmol/l; P<0.0001) compared with others. Adding wPRS to clinical data significantly improved dyslipidemia prediction of HDL (P=0.03) and a trend for improvement was observed for the prediction of TC dyslipidemia (P=0.08). Conclusion Population-based wPRSs have thus significant effects on lipid levels in the psychiatric population. As genetics improved the predictive power of dyslipidemia development, only 24 patients need to be genotyped to prevent the development of one case of HDL hypocholesterolemia. If confirmed by further prospective investigations, the present results could be used for individualizing psychotropic treatment.

Association of variants in SH2B1 and RABEP1 with worsening of low-density lipoprotein and glucose parameters in patients treated with psychotropic drugs.

Genetic factors associated with Body Mass Index (BMI) have been widely studied over the last decade. We examined whether genetic variants previously associated with BMI in the general population are associated with cardiometabolic parameter worsening in the psychiatric population receiving psychotropic drugs, a high-risk group for metabolic disturbances. Classification And Regression Trees (CARTs) were used as a tool capable of describing hierarchical associations, to pinpoint genetic variants best predicting worsening of cardiometabolic parameters (i.e total, HDL and LDL-cholesterol, triglycerides, body mass index, waist circumference, fasting glucose, and blood pressure) following prescription of psychotropic drugs inducing weight gain in a discovery sample of 357 Caucasian patients. Significant findings were tested for replication in a second Caucasian psychiatric sample (n=140). SH2B1 rs3888190C>A was significantly associated with LDL levels in the discovery and in the replication sample, with A-allele carriers having 0.2mmol/l (p=0.005) and 0.36mmol/l (p=0.007) higher LDL levels compared to others, respectively. G-allele carriers of RABEP1 rs1000940A>G had lower fasting glucose levels compared to others in both samples (-0.16mmol/l; p<0.001 and -0.77mmol/l; p=0.03 respectively). The present study is the first to observe such associations in human subjects, which may in part be explained by a high risk towards dyslipidemia and diabetes in psychiatric patients receiving psychotropic treatments compared to population-based individuals. These results may therefore give new insight into the etiology of LDL-cholesterol and glucose regulation in psychiatric patients under psychotropic drug therapy.

Association of genetic risk scores with body mass index in Swiss psychiatric cohorts

Individual illness severity may be measured by the degree of overall psychosocial functioning. We studied whether the presence of one or more copy number variants (CNVs) is associated with the level of psychosocial impairment measured by the Global Assessment of Functioning (GAF; DSMIV Axis V) scale in a sample of individuals with DSM-IV schizophrenia (SZ). The GAF score measures the overall functioning level of an individual from 1 (lowest) to 100 (highest). Using a genome-wide, high-quality CNV dataset, we assessed whether CNVs are related to GAF values collected for three points in time over the individual course of disease: before illness onset, the “worst ever” (during an illness episode) and the current (in remission) GAF score. Investigating GAF values adjusted for phenotypic predictors, our analysis revealed a trend towards lower psychosocial functioning at the “worst ever” GAF in individuals possessing one or more CNVs compared to individuals without CNVs. An exploratory analysis of CNVs present in the study sample found a protective effect on the current GAF score for a duplication on chromosome 10q26.3.Background: Alcohol and nicotine consumption are two of the most important preventable causes of morbidity and premature death worldwide. In western populations, alcohol and nicotine consumption are highly correlated which further increases medical costs as co-use is associated with even worse health outcomes than either of the substances used alone. In order to improve the efficacy of prevention and treatment strategies, we need a better understanding of risk factors contributing to harmful alcohol and nicotine consumption. Phenotypic correlations between alcohol and nicotine consumption are at least partly explained by overlap in genetic risk factors. Therefore, we aim to investigate the genetic architecture of multiple phenotypes associated with alcohol and nicotine consumption, including the number of alcoholic beverages, heavy vs. non heavy drinking, number of cigarettes smoked per day (CPD), age of smoking initiation, ever vs. never smoker, and heavy vs. non-heavy smoker. Methods: Phenotypes have been assessed in a general population sample including 16,000 subjects from the Netherlands. All subjects have been genotyped on the Illumina Human Exome BeadChip v1.1 that interrogates 250,000 nonsense, missense, and splice site variants with an allele frequency >=1% allowing us to evaluate the role of functional, rare variants. Genotyping and calling was conducted at a single laboratory according to uniform procedures which facilitates comparison of genotype frequencies between groups. Results: Preliminary analysis of a single phenotype (i.e., number of alcoholic drinks per week) in a subset of the total sample (N=1,491) revealed several promising findings (see Figure 1). Interestingly, the genetic variant most strongly associated with alcohol consumption (beta=0.11; p=4*10-6) was located at chromosome 11 in the tumor P53-Regulated Apoptosis-Inducing Protein 1 (TP53AIP1). Mutations in a gene from the same P53 gene family were previously found to be associated with alcohol consumption. In this relatively small pilot study, no findings were statistically significant, but power analysis of the top finding (minor allele frequency=0.20, p=0.11) shows that increasing the sample size to ~16,000 will provide enough statistical power (0.83) to detect this particular variant. Discussion: This work will be extended to the full sample and will focus on the detection of rare genetic variants involved in different alcohol and nicotine phenotypes. Since all phenotypes have been assessed in the same subjects, we will also be able to determine genetic variants that explain the phenotypic concordance across multiple traits using multivariate genetic analyses. Methodological challenges specific to population-based association analysis of rare variants and quantitative behavioral traits will be discussed.