The structure of genetic and environmental influences on normative personality, abnormal personality traits, and personality disorder symptoms.
ABSTRACT: BACKGROUND:Can the structure of genetic and environmental influences on normative personality traits (NPTs), abnormal personality traits (APTs), and DSM-IV criteria for personality disorders (PD) fit a high or low congruence model positing, respectively, close or more limited etiologic continuity? METHOD:Exploratory factor analysis was applied to transformed correlation matrices from Cholesky twin decompositions obtained in OpenMx. In 2801 adult twins from the Norwegian Institute of Public Health Twin Panel, NPTs and APTs were assessed by self-report using the Big Five Inventory (BFI) and PID-5-Norwegian Brief Form (PID-5-NBF), respectively. PDs were assessed at interview using the Structured Interview for DSM-IV Personality (SIDP-IV). RESULTS:The best model yielded three genetic and three unique environmental factors. Genetic factors were dominated, respectively, by (i) high loadings on nearly all PDs and NPT/APT neuroticism and compulsivity, (ii) negative loadings on NPT agreeableness/conscientiousness and positive loadings on APT/PD measures of antisocial traits, and (iii) negative loadings on NPT extraversion and histrionic PD, and positive loadings on APT detachment and schizoid/avoidant PD. Unique environmental factors were dominated, by (i) high loadings on all PDs, (ii) high loadings on all APT dimensions and NPT neuroticism, and (iii) negative loadings on NPT extraversion and positive loadings on NPT detachment/avoidant PD. CONCLUSIONS:Two genetic and one environmental common factor were consistent with a high congruence model while one genetic and two environmental factors were more supportive of a low congruence model. The relationship between genetic and environmental influences on personality assessed by NPTs, APTs, and PDs is complex and does not fit easily into a low or high congruence model.
Project description:BACKGROUND AND AIMS:Individual differences in DSM-IV personality disorders (PDs) are associated with increased prevalence of substance use disorders. Our aims were to determine which combination of PDs trait scores best predict cannabis use (CU) and cannabis use disorder (CUD), and to estimate the size and significance of genetic and environmental risks in PD traits shared with CU and CUD. DESIGN:Linear mixed-effects models were used to identify PD traits for inclusion in twin analyses to explore the genetic and environmental associations between the traits and cannabis use. SETTING:Cross-sectional data were obtained from Norwegian adult twins in a face-to-face interview in 1999-2004 as part of a population-based study of mental health. PARTICIPANTS:Subjects were 1419 twins (?age = 28.2 years, range = 19-36) from the Norwegian Institute of Public Health Twin Panel with complete PD and cannabis data. MEASUREMENTS:PD traits were assessed using DSM-IV criteria. Life-time CU and CUD were based on DSM-IV abuse and dependence criteria, including withdrawal and craving. FINDINGS:After adjusting for age and sex, antisocial [? = 0.23, 95% confidence interval (CI) = 0.19-0.28] and borderline PDs (? = 0.20, 95% CI = 0.14-0.26) were associated strongly with CU. Antisocial (? = 0.26, 95% CI = 0.21-0.31) and borderline PDs (? = 0.12, 95% CI = 0.06-0.18) were also linked strongly to CUD. Genetic risks in antisocial and borderline PD traits explained 32-60% of the total variance in CU and CUD. Dependent and avoidant PDs explained 11 and 16% of the total variance in CU and CUD, respectively. CONCLUSIONS:Individual differences in the liability to cannabis use and cannabis use disorder appear to be linked to genetic risks correlated with antisocial and borderline personality disorder traits.
Project description:The localization and signaling of S-palmitoylated peripheral membrane proteins is sustained by an acylation cycle in which acyl protein thioesterases (APTs) depalmitoylate mislocalized palmitoylated proteins on endomembranes. However, the APTs are themselves reversibly S-palmitoylated, which localizes thioesterase activity to the site of the antagonistc palmitoylation activity on the Golgi. Here, we resolve this conundrum by showing that palmitoylation of APTs is labile due to autodepalmitoylation, creating two interconverting thioesterase pools: palmitoylated APT on the Golgi and depalmitoylated APT in the cytoplasm, with distinct functionality. By imaging APT-substrate catalytic intermediates, we show that it is the depalmitoylated soluble APT pool that depalmitoylates substrates on all membranes in the cell, thereby establishing its function as release factor of mislocalized palmitoylated proteins in the acylation cycle. The autodepalmitoylating activity on the Golgi constitutes a homeostatic regulation mechanism of APT levels at the Golgi that ensures robust partitioning of APT substrates between the plasma membrane and the Golgi.
Project description:One of the major challenges in the development of targeted nanoparticles (NPs) for cancer therapy is to discover targeting ligands that allow for differential binding and uptake by the target cancer cells. Using prostate cancer (PCa) as a model disease, we developed a cell-uptake selection strategy to isolate PCa-specific internalizing 2'-O-methyl RNA aptamers (Apts) for NP incorporation. Twelve cycles of selection and counter-selection were done to obtain a panel of internalizing Apts, which can distinguish PCa cells from nonprostate and normal prostate cells. After Apt characterization, size minimization, and conjugation of the Apts with fluorescently labeled polymeric NPs, the NP-Apt conjugates exhibit PCa specificity and enhancement in cellular uptake when compared to nontargeted NPs lacking the internalizing Apts. Furthermore, when docetaxel, a chemotherapeutic agent used for the treatment of PCa, was encapsulated within the NP-Apt, a significant improvement in cytotoxicity was achieved in targeted PCa cells. Rather than isolating high-affinity Apts as reported in previous selection processes, our selection strategy was designed to enrich cancer cell-specific internalizing Apts. A similar cell-uptake selection strategy may be used to develop specific internalizing ligands for a myriad of other diseases and can potentially facilitate delivering various molecules, including drugs and siRNAs, into target cells.
Project description:Outpatient facilities, such as community behavioral health organizations (CBHOs), play a critical role in the care of patients with serious mental illness, but there is a paucity of "real-world" patient outcomes data from this health care setting. Therefore, we conducted The Research and Evaluation of Antipsychotic Treatment in Community Behavioral Health Organizations, Outcomes (REACH-OUT) trial, a real-world, prospective, noninterventional observational study of patients with mental illness treated at CBHOs across the United States. We describe demographic and clinical characteristics, antipsychotic therapy (APT) treatment patterns, and health care resource utilization in patients with schizophrenia undergoing medical care as usual.This study enrolled adults with schizophrenia or bipolar I disorder who initiated APT treatment at various time points: 1) within 8 weeks of initiating risperidone long-acting injectables (RLAIs) or other APTs except paliperidone palmitate (PP), 2) after more than 24 weeks of continuous RLAI treatment, or 3) at any time after initiating PP LAI treatment (schizophrenia only). Study assessments were performed via participant interview, medical chart abstraction, and clinical survey at enrollment and at month 12.A total of 1065 patients from 46 CBHOs were enrolled. Of these, 944 (88.6%) had a diagnosis of schizophrenia and 121 (11.4%) had bipolar I disorder. At enrollment, 599 (63.5%) of patients with schizophrenia were receiving RLAIs or PP LAI, 281 (29.8%) were receiving oral APTs, and 64 (6.8%) were receiving other injectable APTs. A number of differences in patient characteristics and outcomes were observed between patients in the LAI APT cohort and the oral APT cohort.Descriptive analyses from this observational study suggest differences in the patient characteristics, treatment patterns, and clinical and economic outcomes among those with schizophrenia treated at CBHOs with LAI APT or oral APTs. Additional analyses will be conducted to delineate the impact of LAI APT versus oral APTs on patient outcomes.Clinical Trial Registry: NCT01181960 . Registered 12 August 2010.
Project description:BACKGROUND:Objective and longitudinal measurements of disability in patients with multiple sclerosis (MS) are desired in order to monitor disease status and response to disease-modifying and symptomatic therapies. Technology-enabled comprehensive assessment of MS patients, including neuroperformance tests (NPTs), patient-reported outcome measures (PROMs), and MRI, is incorporated into clinical care at our center. The relationships of each NPT with PROMs and MRI measures in a real-world setting are incompletely studied, particularly in larger datasets. OBJECTIVES:To demonstrate the utility of comprehensive neurological assessment and determine the association between NPTs, PROMs, and quantitative MRI measures in a large MS clinical cohort. METHODS:NPTs (processing speed [PST], contrast sensitivity [CST], manual dexterity [MDT], and walking speed [WST]) and physical disability-related PROMs (Quality of Life in Neurological Disorders [Neuro-QoL], Patient Determined Disease Steps [PDDS], and Patient-Reported Outcomes Measurement Information System Global-10 [PROMIS-10] physical) were collected as part of routine clinical care. Fully-automated MRI analysis calculated T2-lesion volume (T2LV), whole brain fraction (WBF), thalamic volume (TV), and cervical spinal cord cross-sectional area (CA) for brain MRIs completed within 3 months of a clinic visit during which NPTs and PROMs were assessed. Spearman's rank correlation coefficients evaluated the cross-sectional associations of NPTs with PROMs and MRI measures. Linear regression was utilized to determine which combination of clinical characteristics, patient demographics, MRI measures, and PROMs best cross-sectionally explained each NPT result. RESULTS:997 unique patients (age 47.7?±?11.4 years, 71.8% female) who underwent assessments over a 2-year period were included. Correlations among NPTs and PROMs were moderate. PST correlations were strongest for Neuro-QoL upper extremity (NQ-UE) (Spearman's rho?=?0.43) and lower extremity (NQ-LE) (0.47). CST correlations were strongest for NQ-UE (0.33), NQ-LE (0.36), and PDDS (-0.31). MDT correlations were strongest for NQ-UE (-0.53), NQ-LE (-0.54), and PDDS (0.53). WST correlations were strongest for PDDS (0.64) and NQ-LE (-0.65). NPTs also had moderate correlations with MRI metrics, the strongest of which were observed with PST (with T2LV (-0.44) and WBF (0.49)). Spearman's rho for other NPT-MRI correlations ranged from 0.23 to 0.36. Linear regression identified age, disease duration, PROMIS-10 physical, NQ-UE, NQ-LE, T2LV and WBF as significant cross-sectional explanatory variables for PST (adjusted R2=0.46). For CST, significant variables included age and NQ-LE (adjusted R2?=?0.30). For MDT, significant variables included PDDS, PROMIS-10 physical, NQ-UE, NQ-LE, T2LV, and WBF (adjusted R2=0.37). For WST, significant variables included sex, PDDS, NQ-LE, T2LV, and CA (adjusted R2=0.39). CONCLUSIONS:Impaired performance on NPTs correlated with worse physical disability-related PROMs and MRI disease severity, but the strongest cross-sectional explanatory variables for each NPT component varied. This study supports the use of comprehensive, objective quantification of MS status in clinical and research settings. Future longitudinal analyses can determine predictors of treatment response and disability worsening.
Project description:Axis I comorbidity complicates diagnosing axis II personality disorders (PDs). PDs might influence Axis I outcome. No research has examined psychotherapy effects on PDs of treating Axis I comorbidity. Secondary analysis of a randomized controlled trial examined PD diagnostic stability after brief psychotherapy of chronic posttraumatic stress disorder (PTSD).Patients with chronic PTSD were randomly assigned to 14 weeks of prolonged exposure, interpersonal psychotherapy, or relaxation therapy. Assessments included the Structured Clinical Interview for DSM-IV, Patient Version (SCID-P) and Structured Clinical Interview for DSM-IV Axis II Disorders (SCID-II) at baseline, week 14, and for treatment responders (?30% clinician-administered PTSD scale improvement, defined a priori) at week 26 follow-up. We hypothesized patients whose PTSD improved would retain fewer baseline PD diagnoses posttreatment, particularly with personality traits PTSD mimics, e.g. paranoid and avoidant.Forty-seven (47%) of 99 SCID-II patients evaluated at baseline received a SCID-II diagnosis: paranoid (28%), obsessive-compulsive (27%), and avoidant (23%) PDs were most prevalent. Among 78 patients who repeated SCID-II evaluations posttreatment, 45% (N = 35) had baseline PD diagnoses, of which 43% (N = 15/35) lost at week 14. Three (7%) patients without baseline PDs acquired diagnoses at week 14; 10 others shifted diagnoses. Treatment modality and PTSD response were unrelated to PD improvement. Of treatment responders reevaluated at follow-up (N = 44), 56% with any baseline Axis II diagnosis had none at week 26.This first evaluation of Axis I psychotherapy effects on personality disorder stability found that acutely treating a chronic state decreased apparent trait-across most PDs observed. These exploratory findings suggest personality diagnoses may have limited prognostic meaning in treating chronic PTSD.
Project description:Until now, data have not been available to elucidate the genetic and environmental sources of comorbidity between all 10 DSM-IV personality disorders (PDs) and cocaine use. Our aim was to determine which PD traits are linked phenotypically and genetically to cocaine use. Cross-sectional data were obtained in a face-to-face interview between 1999 and 2004. Subjects were 1,419 twins (µage = 28.2 years, range = 19-36) from the Norwegian Institute of Public Health Twin Panel, with complete lifetime cocaine use and criteria for all 10 DSM-IV PDs. Stepwise multiple and Least Absolute Shrinkage and Selection Operator (LASSO) regressions were used to identify PDs related to cocaine use. Twin models were fitted to estimate genetic and environmental associations between the PD traits and cocaine use. In the multiple regression, antisocial (OR = 4.24, 95% CI [2.66, 6.86]) and borderline (OR = 2.19, 95% CI [1.35, 3.57]) PD traits were significant predictors of cocaine use. In the LASSO regression, antisocial, borderline, and histrionic were significant predictors of cocaine use. Antisocial and borderline PD traits each explained 72% and 25% of the total genetic risks in cocaine use, respectively. Genetic risks in histrionic PD were not significantly related to cocaine use. Importantly, after removing criteria referencing substance use, antisocial PD explained 65% of the total genetic variance in cocaine use, whereas borderline explained only 4%. Among PD traits, antisocial is the strongest correlate of cocaine use, for which the association is driven largely by common genetic risks.
Project description:BACKGROUND:Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data. METHODS:Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimer's disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination. RESULTS:The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66?±?0.52% of the balanced dataset and 97.23?±?0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49?±?0.53 and 96.34?±?1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The 'time orientation' and '3-word recall' score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment. CONCLUSIONS:The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting.
Project description:This study examined the prevalence of nicotine dependence (ND) and its associations with DSM-IV personality disorders (PDs) among current smokers (n=7078), controlling for sociodemographic characteristics and comorbid Axis I and II disorders. Data were derived from a nationally representative sample of the U.S. population. Although all PDs were significantly associated with ND when sociodemographic factors were controlled, only schizotypal, borderline, narcissistic and obsessive-compulsive PDs were associated with ND after adding controls for Axis I and other Axis II disorders. These associations remained significant after controlling for degree of smoking exposure. The results suggest that both shared and PD-specific pathogenetic factors underlie these PD-ND associations. Implications are also discussed in terms of the relationship between personality features of schizotypal, borderline, narcissistic and obsessive-compulsive PDs and the self-medication hypothesis and the role of neurotransmission.
Project description:BACKGROUND AND AIMS:The DSM-IV personality disorders (PDs) are comorbid with alcohol use disorder (AUD) and with each other. It remains unclear which PD criteria are most likely to drive onset and recurrence of AUD and which are merely confounded with those criteria. We determine which individual PD criteria predict AUD and the degree of underlying genetic and/or environmental aetiology. DESIGN:A prospective observational twin study. SETTING:Norway 1999-2011. PARTICIPANTS:A total of 2528 and 2275 Norwegian adult twins in waves 1 and 2 variable-selection analyses, and 2785 in biometric analyses. MEASUREMENTS:DSM-IV PDs and their 80 criteria were assessed using a structured personal interview, and AUD using the World Health Organization's Composite International Diagnostic Interview. FINDINGS:In a variable-selection analysis, two PD criteria were associated with AUD even after taking all the other criteria into account: criterion 8 of antisocial PD (childhood conduct disorder) and criterion 4 of borderline PD (self-damaging impulsive behaviours). Adjusting for each other, their respective odds ratios were 3.4 [confidence interval (CI) = 2.1-5.4] and 5.0 (CI = 3.3-7.7). Endorsement strength of the criteria was associated with AUD in a dose-response manner and they explained 5.5% of variation in AUD risk-more than the full diagnoses of antisocial and borderline PDs together (0.5%). The association between borderline criterion 4 and AUD 10 years later derived mainly from their overlapping genetic factors, whereas the association between antisocial criterion 8 and AUD 10 years later was due to both genetic and non-genetic factors. CONCLUSIONS:Conduct disorder and self-harming impulsivity are the foremost risk traits for alcohol use disorder among the 80 personality disorder criteria of DSM-IV, predicting alcohol use disorder more effectively than personality disorder diagnoses. The twin-study analysis suggested that conduct disorder represents a joint genetic and developmental risk for alcohol use disorder and that impulsivity is a genetic risk.