Nuria Saigi-Morgui

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.

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.

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.

Association between 28 single nucleotide polymorphisms and type 2 diabetes mellitus in the Kazakh population: a case-control study

BackgroundWe evaluated the associations between single nucleotide polymorphisms and different clinical parameters related to type 2 diabetes mellitus (T2DM), obesity risk, and metabolic syndrome (MS) in a Kazakh cohort.MethodsA total of 1336 subjects, including 408 T2DM patients and 928 control subjects, were recruited from an outpatient clinic and genotyped for 32 polymorphisms previously associated with T2DM and obesity-related phenotypes in other ethnic groups. For association studies, the chi-squared test or Fisher’s exact test for binomial variables were used. Logistic regression was conducted to explore associations between the studied SNPs and the risk of developing T2DM, obesity, and MS, after adjustments for age and sex.ResultsAfter excluding four SNPs due to Hardy-Weinberg disequilibrium, significant associations in age-matched cohorts were found betweenT2DM and the following SNPs: rs9939609 (FTO), rs13266634 (SLC30A8), rs7961581 (TSPAN8/LGR5), and rs1799883 (FABP2). In addition, examination of general unmatched T2DM and control cohorts revealed significant associations between T2DM and SNPsrs1799883 (FABP2) and rs9939609 (FTO). Furthermore, polymorphisms in the FTO gene were associated with increased obesity risk, whereas polymorphisms in the FTO and FABP2 genes were also associated with the risk of developing MS in general unmatched cohorts.ConclusionWe confirmed associations between polymorphisms within the SLC30A8, TSPAN8/LGR5, FABP2, and FTO genes and susceptibility to T2DM in a Kazakh cohort, and revealed significant associations with anthropometric and metabolic traits. In particular, FTO and FABP2 gene polymorphisms were significantly associated with susceptibility to MS and obesity in this cohort.

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.

Weighted Genetic Risk Scores and Prediction of Weight Gain in Solid Organ Transplant Populations

Background Polygenic obesity in Solid Organ Transplant (SOT) populations is considered a risk factor for the development of metabolic abnormalities and graft survival. Few studies to date have studied the genetics of weight gain in SOT recipients. We aimed to determine whether weighted genetic risk scores (w-GRS) integrating genetic polymorphisms from GWAS studies (SNP group#1 and SNP group#2) and from Candidate Gene studies (SNP group#3) influence BMI in SOT populations and if they predict ≥10% weight gain (WG) one year after transplantation. To do so, two samples (nA = 995, nB = 156) were obtained from naturalistic studies and three w-GRS were constructed and tested for association with BMI over time. Prediction of 10% WG at one year after transplantation was assessed with models containing genetic and clinical factors. Results w-GRS were associated with BMI in sample A and B combined (BMI increased by 0.14 and 0.11 units per additional risk allele in SNP group#1 and #2, respectively, p-values<0.008). w-GRS of SNP group#3 showed an effect of 0.01 kg/m2 per additional risk allele when combining sample A and B (p-value 0.04). Models with genetic factors performed better than models without in predicting 10% WG at one year after transplantation. Conclusions This is the first study in SOT evaluating extensively the association of w-GRS with BMI and the influence of clinical and genetic factors on 10% of WG one year after transplantation, showing the importance of integrating genetic factors in the final model. Genetics of obesity among SOT recipients remains an important issue and can contribute to treatment personalization and prediction of WG after transplantation.

New-onset obesity after liver transplantation-outcomes and risk factors: the Swiss Transplant Cohort Study

Weight gain after liver transplantation (LTx) facilitates development of new‐onset obesity; however, its risk factors and outcomes are poorly understood. We identified the impact of new‐onset obesity on cardiovascular events (CVEs) and patient survival, and risk factors for new‐onset obesity. Multiple Cox regression models examined risk factors for CVEs, patient survival, and new‐onset obesity in 253 adults (mean age 52.2 ± 11.6 years, male gender 63.6%, mean follow up 5.7 ± 2.1 years). Cumulative incidence of post‐LTx CVE was 28.1%; that of new‐onset obesity was 21.3%. Regardless of CVE at LTx, post‐LTx CVEs were predicted by new‐onset obesity [Hazard Ratio (HR), 2.95; P = 0.002] and higher age at LTx (HR, 1.05; P < 0.001). In patients without known pre‐LTx CVEs (n = 214), risk factors for post‐LTx CVEs were new‐onset obesity (HR, 2.59; P = 0.014) and higher age (HR, 1.04; P = 0.001). Survival was not associated with new‐onset obesity (P = 0.696). Alcoholic liver disease predicted new‐onset obesity (HR, 3.37; P = 0.025), female gender was protective (HR, 0.39; P = 0.034). In 114 patients with available genetic data, alcoholic liver disease (HR, 12.82; P = 0.014) and hepatocellular carcinoma (HR, 10.02; P = 0.048) predicted new‐onset obesity, and genetics remained borderline significant (HR, 1.07; P = 0.071). Early introduction of post‐LTx weight management programs may suggest a potential pathway to reduce CVE risk.

Genetic and clinic predictors of new onset diabetes mellitus after transplantation

New Onset Diabetes after Transplantation (NODAT) is a frequent complication after solid organ transplantation, with higher incidence during the first year. Several clinical and genetic factors have been described as risk factors of Type 2 Diabetes (T2DM). Additionally, T2DM shares some genetic factors with NODAT. We investigated if three genetic risk scores (w-GRS) and clinical factors were associated with NODAT and how they predicted NODAT development 1 year after transplantation. In both main (n = 725) and replication (n = 156) samples the clinical risk score was significantly associated with NODAT (ORmain: 1.60 [1.36–1.90], p = 3.72*10−8 and ORreplication: 2.14 [1.39–3.41], p = 0.0008, respectively). Two w-GRS were significantly associated with NODAT in the main sample (ORw-GRS 2:1.09 [1.04–1.15], p = 0.001 and ORw-GRS 3:1.14 [1.01–1.29], p = 0.03) and a similar ORw-GRS 2 was found in the replication sample, although it did not reach significance probably due to a power issue. Despite the low OR of w-GRS on NODAT compared to clinical covariates, when integrating w-GRS 2 and w-GRS 3 in the clinical model, the Area under the Receiver Operating Characteristics curve (AUROC), specificity, sensitivity and accuracy were 0.69, 0.71, 0.58 and 0.68, respectively, with significant Likelihood Ratio test discrimination index (p-value 0.0004), performing better in NODAT discrimination than the clinical model alone. Twenty-five patients needed to be genotyped in order to detect one misclassified case that would have developed NODAT 1 year after transplantation if using only clinical covariates. To our knowledge, this is the first study extensively examining genetic risk scores contributing to NODAT development.

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.