- Email: [email protected]
Comorbid Medical Conditions In Individuals With Major Psychiatric Disorders
S396
Abstracts of the XXIV World Congress of Psychiatric Genetics (WCPG) 2016
FRS served to identify diagnostically heterogeneous subgroups. GWAS was carried out with PLINK 1.07 using as covariates: age, age of onset, mode of onset, poor premorbid social adjustment, gender, course of illness and 4 population structure PCs. Test sample: A subsample of individuals (n = 198) with SZ, SA and BD from a longitudinal, multi-site cohort study (www.kfo241.de; www.PsyCourse.de) comprehensively phenotyped at 4 time points over 18 months. DNA samples were genotyped and imputed using the 1KG Phase3. 67 longitudinally measured variables derived from clinical symptom scales entered the cluster analyses. FAMD was applied to compute abstract data dimensions, which were used to derive longitudinal trajectories. Based on these trajectories, k-mean clustering for longitudinal data yielded 2 distinct subgroups. Identified clusters served as predictors for FR-PRS at 11 thresholds. Results: Two clusters of longitudinal trajectories were identified: i) consistently low psychopathology scores and ii) consistently high psychopathology scores. Cluster membership was not significantly associated with the FR-PRS in either cluster. Discussion: Although the results are preliminary and thus need to be interpreted with caution, the approach of longitudinal clustering to identify cross-diagnostic homogeneous subgroups of individuals appears feasible. The fact that more severe psychopathological features were not associated with increased genetic risk burden should be explored further. One possible explanation is a lack of power, another is that maybe psychopathology may be more influenced to a larger degree by other factors than genetics that may be easier to modify for future treatment options.
Disclosure Nothing to Disclose. http://dx.doi.org/10.1016/j.euroneuro.2016.09.433
M43. COMORBID MEDICAL CONDITIONS IN INDIVIDUALS WITH MAJOR PSYCHIATRIC DISORDERS
Margarita Rivera1, Paula Rovira2, Blanca Gutierrez3, Ana Ching-López4, Esther Molina5, María Victoria Martín-Laguna6, Inmaculada IbanezCasas6, Kathryn McKenney6, Isabel Ruiz-Pérez7, Miguel Rodríguez-Barranco8, Jorge Cervilla4 1
King's College London Psychiatric Genetics Unit, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Spain 3 University of Granada 4 Departamento de Psiquiatría e Instituto de Neurociencias, Universidad de Granada, Granada, Spain 2
5
Departamento de Enfermería, Universidad de Sevilla, Sevilla, Spain 6 CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)-Universidad de Granada, Granada, Spain 7 CIBER de Epidemiología y Salud Pública (CIBERESP), Granada, Spain 8 Andalusian School of Public Health, Granada, Spain Background: People with major psychiatric disorders (MPD) (schizophrenia, bipolar disorder major, depressive disorder), particularly with mood disorders, have higher prevalence of comorbid medical conditions, such as obesity, diabetes and cardiovascular diseases. There are a limited number of cross-national studies on comorbid mental and medical conditions. Although, it is well documented that people with MPD have an excess mortality rates. About 60% of this excess mortality is due to medical conditions, being cardiovascular disease the primary cause. Comorbid mental and medical conditions are associated with substantial individual and societal economic cost. The aim of this study is to examine the prevalence of medical conditions in people with MPD compare with a psychiatrically healthy control group. Methods: The sample is part of the PISMA-ep, a crosssectional study of a representative sample of the Andalusian population (Spain). The sample included 1005 participants with diagnosis of a major psychiatric disorder and 3502 psychiatrically healthy controls. A standard medical disorders checklist, of the kind commonly used in national health surveys including 21 self reported specific medical conditions was given to all participants. In addition, self-reported weight and height were obtained to calculate their body mass index (BMI), defined as weight in kilograms divided by height in meters squared (kg/m2). We carried out contingency table analyses and binary logistic regressions to examine the prevalence of the 21 medical conditions both in individuals with MPD and controls. The regression analyses were adjusted by affected status, BMI, gender and age. The statistical analyses were performed with the SPSS 15.0 software. Results: There were no statistically significant differences in BMI in the MPD group compared to controls (t = 1.20, d.f= 4492, p= 0.2306). In the MPD group, chronic pain, migraine, rhinitis and hypertension had the highest lifetime prevalence (24.3%, 14.7%, 13.7% and 13.2%, respectively) compare to controls. In controls, the highest lifetime prevalences where found for chronic pain, hypertension, rhinitis and hypercholesterolemia (12.5%, 11%, 8.3% and 7.5%, respectively). In contrast, embolism and epilepsy had the lowest lifetime prevalences in both groups.
Abstracts of the XXIV World Congress of Psychiatric Genetics (WCPG) 2016 Nineteen medical disorders were significantly more frequent in the MPD group. In particular, the highest significant differences were found for chronic pain, asthma, migraine, vertigo, rhinitis and arthritis (po10-6). There were also differences between groups in cancer, chronic bronchitis, diabetes, stomach ulcer, chronic allergy, hypercholesterolemia, thyroid problems, renal and liver difficulties, embolism, tinnitus, anemia and cancer (po0.05). In contrast, no significant differences were found for heart attack, epilepsy or hypertension. Discussion: Lifetime prevalence of medical disorders was significantly higher in the MPD group compare to psychiatrically healthy controls in the vast majority of the diseases. This study highlights the importance of address medical conditions in people with major psychiatric disorders.
Disclosure Nothing to Disclose. http://dx.doi.org/10.1016/j.euroneuro.2016.09.434
M44. INVESTIGATION OF GENETIC VARIANTS WITHIN GENES TARGETS OF ANTIPSYCHOTIC RESPONSE AND THEIR SIGNAL CASCADE IN SCHIZOPHRENIA AND ANTIPSYCHOTIC RESPONSE
Marco Calabrò1, Stefano Porcelli2, Concetta Crisafulli1, Antonella Sidoti1, Tae-Youn Jun3, Soo-Jung Lee3, Changsu Han4, Ashwin Paktar5, Prakash Masand6, Chi-un Pae3, Alessandro Serretti2
S397
Methods: Two independent samples were investigated in this study. A Korean sample of 176 in-patients and 326 healthy controls and an Italian sample of 83 patients and 195 healthy controls. A total of 100 SNPs within 18 genes were analyzed in the two samples. We investigated 1) differences among genotypic and allelic frequencies in patients with SCZ compared with healthy control subjects and 2) possible influence of the SNPs under investigation on clinical improvement, as measured with the PANSS total scale in SCZ patients. Results: In the Italian sample, rs12668837 within NCAPG2 and rs7439 within PKDCC showed a different allelic distribution between cases and controls. In the pharmacogenetic analysis, variants within CHRNA7, MAPK1 genes (which coding for antipsychotic targets) and variants within PLA2G4A, ESYT2 and HOMER1 genes (which are involved in the antipsychotic targets signal transduction) showed trends of association with antipsychotic response as measured by PANSS scale. Discussion: Overall, our data suggest a possible role of these two groups of genes in both SCZ pathophysiology and antipsychotic response. A limited sample size and the consequent risk of false positive findings should be carefully taken into consideration when evaluating these results.
Disclosure Nothing to Disclose. http://dx.doi.org/10.1016/j.euroneuro.2016.09.435
1
University of Messina University of Bologna 3 Catholic University of Korea, Seoul 4 Korea University 5 Duke University Medical Center 6 Global Medical Education, NY 2
Background: Schizophrenia (SCZ) is a devastating psychiatric disease that affects about 1% of the population and ranks among the top 10 causes of disability worldwide. Although environmental factors can play a relevant role in the development of SCZ, evidences from family, twin, and adoption studies suggest a strong genetic component in the etiology of the disease. Similarly, a genetic contribution for antipsychotic outcome has been suggested. In the present study we investigated the associations among two distinct groups of single nucleotide polymorphisms (SNPs) within 1) genes coding for molecular targets of antipsychotic drugs and 2) genes whose products were involved with the signal transduction of the primary molecular targets.
M45. EXPLORING THE EFFECTS OF MUSCARINIC M1 RECEPTOR SEQUENCE VARIATION ON EXECUTIVE FUNCTIONING IN SCHIZOPHRENIA AND HEALTHY CONTROLS
Sean Carruthers1, Vanessa Cropley2, Caroline Gurvich3, Kiymet Bozaoglu4, Christos Pantellis5, Susan Rossell6 1
Swinburne University of Technology Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health; Department of Psychiatry, The University of Melbourne 3 Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia 4 Baker IDI Heart and Diabetes Institute, Melbourne, Australia 2
Abstracts of the XXIV World Congress of Psychiatric Genetics (WCPG) 2016
FRS served to identify diagnostically heterogeneous subgroups. GWAS was carried out with PLINK 1.07 using as covariates: age, age of onset, mode of onset, poor premorbid social adjustment, gender, course of illness and 4 population structure PCs. Test sample: A subsample of individuals (n = 198) with SZ, SA and BD from a longitudinal, multi-site cohort study (www.kfo241.de; www.PsyCourse.de) comprehensively phenotyped at 4 time points over 18 months. DNA samples were genotyped and imputed using the 1KG Phase3. 67 longitudinally measured variables derived from clinical symptom scales entered the cluster analyses. FAMD was applied to compute abstract data dimensions, which were used to derive longitudinal trajectories. Based on these trajectories, k-mean clustering for longitudinal data yielded 2 distinct subgroups. Identified clusters served as predictors for FR-PRS at 11 thresholds. Results: Two clusters of longitudinal trajectories were identified: i) consistently low psychopathology scores and ii) consistently high psychopathology scores. Cluster membership was not significantly associated with the FR-PRS in either cluster. Discussion: Although the results are preliminary and thus need to be interpreted with caution, the approach of longitudinal clustering to identify cross-diagnostic homogeneous subgroups of individuals appears feasible. The fact that more severe psychopathological features were not associated with increased genetic risk burden should be explored further. One possible explanation is a lack of power, another is that maybe psychopathology may be more influenced to a larger degree by other factors than genetics that may be easier to modify for future treatment options.
Disclosure Nothing to Disclose. http://dx.doi.org/10.1016/j.euroneuro.2016.09.433
M43. COMORBID MEDICAL CONDITIONS IN INDIVIDUALS WITH MAJOR PSYCHIATRIC DISORDERS
Margarita Rivera1, Paula Rovira2, Blanca Gutierrez3, Ana Ching-López4, Esther Molina5, María Victoria Martín-Laguna6, Inmaculada IbanezCasas6, Kathryn McKenney6, Isabel Ruiz-Pérez7, Miguel Rodríguez-Barranco8, Jorge Cervilla4 1
King's College London Psychiatric Genetics Unit, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Spain 3 University of Granada 4 Departamento de Psiquiatría e Instituto de Neurociencias, Universidad de Granada, Granada, Spain 2
5
Departamento de Enfermería, Universidad de Sevilla, Sevilla, Spain 6 CIBERSAM (Centro de Investigación Biomédica en Red de Salud Mental)-Universidad de Granada, Granada, Spain 7 CIBER de Epidemiología y Salud Pública (CIBERESP), Granada, Spain 8 Andalusian School of Public Health, Granada, Spain Background: People with major psychiatric disorders (MPD) (schizophrenia, bipolar disorder major, depressive disorder), particularly with mood disorders, have higher prevalence of comorbid medical conditions, such as obesity, diabetes and cardiovascular diseases. There are a limited number of cross-national studies on comorbid mental and medical conditions. Although, it is well documented that people with MPD have an excess mortality rates. About 60% of this excess mortality is due to medical conditions, being cardiovascular disease the primary cause. Comorbid mental and medical conditions are associated with substantial individual and societal economic cost. The aim of this study is to examine the prevalence of medical conditions in people with MPD compare with a psychiatrically healthy control group. Methods: The sample is part of the PISMA-ep, a crosssectional study of a representative sample of the Andalusian population (Spain). The sample included 1005 participants with diagnosis of a major psychiatric disorder and 3502 psychiatrically healthy controls. A standard medical disorders checklist, of the kind commonly used in national health surveys including 21 self reported specific medical conditions was given to all participants. In addition, self-reported weight and height were obtained to calculate their body mass index (BMI), defined as weight in kilograms divided by height in meters squared (kg/m2). We carried out contingency table analyses and binary logistic regressions to examine the prevalence of the 21 medical conditions both in individuals with MPD and controls. The regression analyses were adjusted by affected status, BMI, gender and age. The statistical analyses were performed with the SPSS 15.0 software. Results: There were no statistically significant differences in BMI in the MPD group compared to controls (t = 1.20, d.f= 4492, p= 0.2306). In the MPD group, chronic pain, migraine, rhinitis and hypertension had the highest lifetime prevalence (24.3%, 14.7%, 13.7% and 13.2%, respectively) compare to controls. In controls, the highest lifetime prevalences where found for chronic pain, hypertension, rhinitis and hypercholesterolemia (12.5%, 11%, 8.3% and 7.5%, respectively). In contrast, embolism and epilepsy had the lowest lifetime prevalences in both groups.
Abstracts of the XXIV World Congress of Psychiatric Genetics (WCPG) 2016 Nineteen medical disorders were significantly more frequent in the MPD group. In particular, the highest significant differences were found for chronic pain, asthma, migraine, vertigo, rhinitis and arthritis (po10-6). There were also differences between groups in cancer, chronic bronchitis, diabetes, stomach ulcer, chronic allergy, hypercholesterolemia, thyroid problems, renal and liver difficulties, embolism, tinnitus, anemia and cancer (po0.05). In contrast, no significant differences were found for heart attack, epilepsy or hypertension. Discussion: Lifetime prevalence of medical disorders was significantly higher in the MPD group compare to psychiatrically healthy controls in the vast majority of the diseases. This study highlights the importance of address medical conditions in people with major psychiatric disorders.
Disclosure Nothing to Disclose. http://dx.doi.org/10.1016/j.euroneuro.2016.09.434
M44. INVESTIGATION OF GENETIC VARIANTS WITHIN GENES TARGETS OF ANTIPSYCHOTIC RESPONSE AND THEIR SIGNAL CASCADE IN SCHIZOPHRENIA AND ANTIPSYCHOTIC RESPONSE
Marco Calabrò1, Stefano Porcelli2, Concetta Crisafulli1, Antonella Sidoti1, Tae-Youn Jun3, Soo-Jung Lee3, Changsu Han4, Ashwin Paktar5, Prakash Masand6, Chi-un Pae3, Alessandro Serretti2
S397
Methods: Two independent samples were investigated in this study. A Korean sample of 176 in-patients and 326 healthy controls and an Italian sample of 83 patients and 195 healthy controls. A total of 100 SNPs within 18 genes were analyzed in the two samples. We investigated 1) differences among genotypic and allelic frequencies in patients with SCZ compared with healthy control subjects and 2) possible influence of the SNPs under investigation on clinical improvement, as measured with the PANSS total scale in SCZ patients. Results: In the Italian sample, rs12668837 within NCAPG2 and rs7439 within PKDCC showed a different allelic distribution between cases and controls. In the pharmacogenetic analysis, variants within CHRNA7, MAPK1 genes (which coding for antipsychotic targets) and variants within PLA2G4A, ESYT2 and HOMER1 genes (which are involved in the antipsychotic targets signal transduction) showed trends of association with antipsychotic response as measured by PANSS scale. Discussion: Overall, our data suggest a possible role of these two groups of genes in both SCZ pathophysiology and antipsychotic response. A limited sample size and the consequent risk of false positive findings should be carefully taken into consideration when evaluating these results.
Disclosure Nothing to Disclose. http://dx.doi.org/10.1016/j.euroneuro.2016.09.435
1
University of Messina University of Bologna 3 Catholic University of Korea, Seoul 4 Korea University 5 Duke University Medical Center 6 Global Medical Education, NY 2
Background: Schizophrenia (SCZ) is a devastating psychiatric disease that affects about 1% of the population and ranks among the top 10 causes of disability worldwide. Although environmental factors can play a relevant role in the development of SCZ, evidences from family, twin, and adoption studies suggest a strong genetic component in the etiology of the disease. Similarly, a genetic contribution for antipsychotic outcome has been suggested. In the present study we investigated the associations among two distinct groups of single nucleotide polymorphisms (SNPs) within 1) genes coding for molecular targets of antipsychotic drugs and 2) genes whose products were involved with the signal transduction of the primary molecular targets.
M45. EXPLORING THE EFFECTS OF MUSCARINIC M1 RECEPTOR SEQUENCE VARIATION ON EXECUTIVE FUNCTIONING IN SCHIZOPHRENIA AND HEALTHY CONTROLS
Sean Carruthers1, Vanessa Cropley2, Caroline Gurvich3, Kiymet Bozaoglu4, Christos Pantellis5, Susan Rossell6 1
Swinburne University of Technology Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health; Department of Psychiatry, The University of Melbourne 3 Monash Alfred Psychiatry Research Centre (MAPrc), The Alfred Hospital and Central Clinical School, Monash University, Melbourne, Australia 4 Baker IDI Heart and Diabetes Institute, Melbourne, Australia 2