Neuroscience of Object Relations in Health and Disorder: A Proposal for an Integrative Model.

Recent advances in the neuroscience of episodic memory provide a framework to integrate object relations theory, a psychoanalytic model of mind development, with potential neural mechanisms. Object relations are primordial cognitive-affective units of the mind derived from survival- and safety-level experiences with caretakers during phase-sensitive periods of infancy and toddlerhood. Because these are learning experiences, their neural substrate likely involves memory, here affect-enhanced episodic memory. Inaugural object relations are encoded by the hippocampus-amygdala synaptic plasticity, and systems-consolidated by medial prefrontal cortex (mPFC). Self- and object-mental representations, extracted from these early experiences, are at first dichotomized by contradictory affects evoked by frustrating and rewarding interactions ("partial object relations"). Such affective dichotomization appears to be genetically hardwired the amygdala. Intrinsic propensity of mPFC to form schematic frameworks for episodic memories may pilot non-conscious integration of dichotomized mental representations in neonates and infants. With the emergence of working memory in toddlers, an activated self- and object-representation of a particular valence can be juxtaposed with its memorized opposites creating a balanced cognitive-affective frame (conscious "integration of object relations"). Specific events of object relations are forgotten but nevertheless profoundly influence the mental future of the individual, acting (i) as implicit schema-affect templates that regulate attentional priorities, relevance, and preferential assimilation of new information based on past experience, and (ii) as basic units of experience that are, under normal circumstances, integrated as attractors or "focal points" for interactive self-organization of functional brain networks that underlie the mind. A failure to achieve integrated object relations is predictive of poor adult emotional and social outcomes, including personality disorder. Cognitive, cellular-, and systems-neuroscience of episodic memory appear to support key postulates of object relations theory and help elucidate neural mechanisms of psychodynamic psychotherapy. Derived through the dual prism of psychoanalysis and neuroscience, the gained insights may offer new directions to enhance mental health and improve treatment of multiple forms of psychopathology.

Three genetic-environmental networks for human personality.

Phylogenetic, developmental, and brain-imaging studies suggest that human personality is the integrated expression of three major systems of learning and memory that regulate (1) associative conditioning, (2) intentionality, and (3) self-awareness. We have uncovered largely disjoint sets of genes regulating these dissociable learning processes in different clusters of people with (1) unregulated temperament profiles (i.e., associatively conditioned habits and emotional reactivity), (2) organized character profiles (i.e., intentional self-control of emotional conflicts and goals), and (3) creative character profiles (i.e., self-aware appraisal of values and theories), respectively. However, little is known about how these temperament and character components of personality are jointly organized and develop in an integrated manner. In three large independent genome-wide association studies from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phenotypic networks of temperament and character and also the genetic networks with which they are associated. We found three clusters of similar numbers of people with distinct combinations of temperament and character profiles. Their associated genetic and environmental networks were largely disjoint, and differentially related to distinct forms of learning and memory. Of the 972 genes that mapped to the three phenotypic networks, 72% were unique to a single network. The findings in the Finnish discovery sample were blindly and independently replicated in samples of Germans and Koreans. We conclude that temperament and character are integrated within three disjoint networks that regulate healthy longevity and dissociable systems of learning and memory by nearly disjoint sets of genetic and environmental influences.

Uncovering the complex genetics of human temperament.

Experimental studies of learning suggest that human temperament may depend on the molecular mechanisms for associative conditioning, which are highly conserved in animals. The main genetic pathways for associative conditioning are known in experimental animals, but have not been identified in prior genome-wide association studies (GWAS) of human temperament. We used a data-driven machine learning method for GWAS to uncover the complex genotypic-phenotypic networks and environmental interactions related to human temperament. In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified 3 clusters of people with distinct temperament profiles measured by the Temperament and Character Inventory regardless of genotype. Third, we found 51 SNP sets that identified 736 gene loci and were significantly associated with temperament. The identified genes were enriched in pathways activated by associative conditioning in animals, including the ERK, PI3K, and PKC pathways. 74% of the identified genes were unique to a specific temperament profile. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of the 51 Finnish SNP sets in healthy Korean (90%) and German samples (89%), as well as their associations with temperament. The identified SNPs explained nearly all the heritability expected in each sample (37-53%) despite variable cultures and environments. We conclude that human temperament is strongly influenced by more than 700 genes that modulate associative conditioning by molecular processes for synaptic plasticity and long-term memory.

Uncovering the complex genetics of human character.

Human personality is 30-60% heritable according to twin and adoption studies. Hundreds of genetic variants are expected to influence its complex development, but few have been identified. We used a machine learning method for genome-wide association studies (GWAS) to uncover complex genotypic-phenotypic networks and environmental interactions. The Temperament and Character Inventory (TCI) measured the self-regulatory components of personality critical for health (i.e., the character traits of self-directedness, cooperativeness, and self-transcendence). In a discovery sample of 2149 healthy Finns, we identified sets of single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (i.e., SNP sets) regardless of phenotype. Second, we identified five clusters of people with distinct profiles of character traits regardless of genotype. Third, we found 42 SNP sets that identified 727 gene loci and were significantly associated with one or more of the character profiles. Each character profile was related to different SNP sets with distinct molecular processes and neuronal functions. Environmental influences measured in childhood and adulthood had small but significant effects. We confirmed the replicability of 95% of the 42 SNP sets in healthy Korean and German samples, as well as their associations with character. The identified SNPs explained nearly all the heritability expected for character in each sample (50 to 58%). We conclude that self-regulatory personality traits are strongly influenced by organized interactions among more than 700 genes despite variable cultures and environments. These gene sets modulate specific molecular processes in brain for intentional goal-setting, self-reflection, empathy, and episodic learning and memory.

Decomposition of brain diffusion imaging data uncovers latent schizophrenias with distinct patterns of white matter anisotropy.

Fractional anisotropy (FA) analysis of diffusion tensor-images (DTI) has yielded inconsistent abnormalities in schizophrenia (SZ). Inconsistencies may arise from averaging heterogeneous groups of patients. Here we investigate whether SZ is a heterogeneous group of disorders distinguished by distinct patterns of FA reductions. We developed a Generalized Factorization Method (GFM) to identify biclusters (i.e., subsets of subjects associated with a subset of particular characteristics, such as low FA in specific regions). GFM appropriately assembles a collection of unsupervised techniques with Non-negative Matrix Factorization to generate biclusters, rather than averaging across all subjects and all their characteristics. DTI tract-based spatial statistics images, which output is the locally maximal FA projected onto the group white matter skeleton, were analyzed in 47 SZ and 36 healthy subjects, identifying 8 biclusters. The mean FA of the voxels of each bicluster was significantly different from those of other SZ subjects or 36 healthy controls. The eight biclusters were organized into four more general patterns of low FA in specific regions: 1) genu of corpus callosum (GCC), 2) fornix (FX)+external capsule (EC), 3) splenium of CC (SCC)+retrolenticular limb (RLIC)+posterior limb (PLIC) of the internal capsule, and 4) anterior limb of the internal capsule. These patterns were significantly associated with particular clinical features: Pattern 1 (GCC) with bizarre behavior, pattern 2 (FX+EC) with prominent delusions, and pattern 3 (SCC+RLIC+PLIC) with negative symptoms including disorganized speech. The uncovered patterns suggest that SZ is a heterogeneous group of disorders that can be distinguished by different patterns of FA reductions associated with distinct clinical features.

Depression in type 2 diabetes mellitus: prevalence, impact, and treatment.

Clinically significant depression is present in one of every four people with type 2 diabetes mellitus (T2DM). Depression increases the risk of the development of T2DM and the subsequent risks of hyperglycemia, insulin resistance, and micro- and macrovascular complications. Conversely, a diagnosis of T2DM increases the risk of incident depression and can contribute to a more severe course of depression. This linkage reflects a shared etiology consisting of complex bidirectional interactions among multiple variables, a process that may include autonomic and neurohormonal dysregulation, weight gain, inflammation, and hippocampal structural alterations. Two recent meta-analyses of randomized controlled depression treatment trials in patients with T2DM concluded that psychotherapy and antidepressant medication (ADM) were each moderately effective for depression and that cognitive behavior therapy (CBT) had beneficial effects on glycemic control. However, the number of studies (and patients exposed to randomized treatment) included in these analyses is extremely small and limits the certainty of conclusions that can be drawn from the data. Ultimately, there is no escaping the paucity of the evidence base and the need for additional controlled trials that specifically address depression management in T2DM. Future trials should determine both the effects of treatment and the change in depression during treatment on measures of mood, glycemic control, and medical outcome.

Psychometric properties and factor structure of the Temperament and Character Inventory-Revised (TCI-R) in a Croatian psychiatric outpatient sample.

OBJECTIVE: The goal of this study was to investigate psychometric properties and factorial structure of the Croatian adaptation of the Temperament and Character Inventory-Revised (TCI-R) in a sample of psychiatric outpatients (n=328). METHOD: The participants filled out the TCI-R, as well as self-report measures of the Big-Five personality traits (IPIP-50), trait impulsivity (BIS-11), depression (BDI-II), suicidality (SBQ-R), and life satisfaction (SWLS). We explored the internal consistency of 7 domains and 29 subscales and compared it with the Croatian version of the original TCI used in prior studies. Principal component analysis with promax rotation was conducted on temperament and character subscales separately, while concurrent validity was examined through the TCI-R's relations with the abovementioned psychological measures. RESULTS: The TCI-R scales showed adequate internal consistencies, with Cronbach's alpha values ranging from 0.77 to 0.93. The internal consistency showed to be higher in comparison with the Croatian version of the original TCI. The postulated four-factor structure of temperament and the three-factor structure of character were confirmed. The meaningful associations with other measures supported the concurrent validity of the TCI-R. CONCLUSION: The Croatian adaptation of the TCI-R exhibited satisfactory reliability and validity in a sample of psychiatric outpatients. These findings support the use of the TCI-R in Croatian clinical settings over its predecessor (TCI).

Uncovering the hidden risk architecture of the schizophrenias: confirmation in three independent genome-wide association studies.

OBJECTIVE: The authors sought to demonstrate that schizophrenia is a heterogeneous group of heritable disorders caused by different genotypic networks that cause distinct clinical syndromes. METHOD: In a large genome-wide association study of cases with schizophrenia and controls, the authors first identified sets of interacting single-nucleotide polymorphisms (SNPs) that cluster within particular individuals (SNP sets) regardless of clinical status. Second, they examined the risk of schizophrenia for each SNP set and tested replicability in two independent samples. Third, they identified genotypic networks composed of SNP sets sharing SNPs or subjects. Fourth, they identified sets of distinct clinical features that cluster in particular cases (phenotypic sets or clinical syndromes) without regard for their genetic background. Fifth, they tested whether SNP sets were associated with distinct phenotypic sets in a replicable manner across the three studies. RESULTS: The authors identified 42 SNP sets associated with a 70% or greater risk of schizophrenia, and confirmed 34 (81%) or more with similar high risk of schizophrenia in two independent samples. Seventeen networks of SNP sets did not share any SNP or subject. These disjoint genotypic networks were associated with distinct gene products and clinical syndromes (i.e., the schizophrenias) varying in symptoms and severity. Associations between genotypic networks and clinical syndromes were complex, showing multifinality and equifinality. The interactive networks explained the risk of schizophrenia more than the average effects of all SNPs (24%). CONCLUSIONS: Schizophrenia is a group of heritable disorders caused by a moderate number of separate genotypic networks associated with several distinct clinical syndromes.

Prescription opioid analgesics increase the risk of depression.

BACKGROUND: Prescription opioid analgesic use has quintupled recently. Evidence linking opioid use with depression emanates from animal models and studies of persons with co-occurring substance use and major depression. Little is known about depressogenic effects of opioid use in other populations. OBJECTIVE: The purpose of this study was to determine whether prescription opioids are associated with increased risk of diagnosed depression. DESIGN: Retrospective cohort study, new user design. PATIENTS: Medical record data from 49,770 US Department of Veterans Affairs (VA) health care system patients with no recent (24-month) history of opioid use or a diagnosis of depression in 1999 and 2000. MAIN MEASURES: Propensity scores were used to control for bias by indication, and the data were weighted to balance the distribution of covariates by duration of incident opioid exposure. Cox proportional hazard models with adjustment for painful conditions were used to estimate the association between duration of prescription opioid use and the subsequent risk of development of depression between 2001 and 2007. KEY RESULTS: Of 49,770 patients who were prescribed an opioid analgesic, 91 % had a prescription for < 90 days, 4 % for 90-180 days, and 5 % for > 180 days. Compared to patients whose prescription was for < 90 days, the risk of depression increased significantly as the duration of opioid prescription increased (HR = 1.25; 95 % CI: 1.05-1.46 for 90-180 days, and HR = 1.51; 95 % CI:1.31-1.74 for > 180 days). CONCLUSIONS: In this sample of veterans with no recent (24-month) history of depression or opioid analgesic use, the risk of development of depression increased as the duration of opioid analgesic exposure increased. The potential for depressogenic effect should be considered in risk-benefit discussions, and patients initiating opioid treatment should be monitored for development of depression.

Prescription Opioid Analgesics Increase Risk of Major Depression: New Evidence, Plausible Neurobiological Mechanisms and Management to Achieve Depression Prophylaxis.

More than 200 million prescriptions are written annually for opioid analgesics despite limited evidence of their long-term efficacy. These medications currently are prescribed to 10% - 15% of Americans with use of long-acting opioids projected to double in the next three to four years. Despite this widespread use, little is known about the risks of opioids, particularly with chronic use. New data from our research group published in the Journal of General Internal Medicine provides clear evidence that prescription opioid used for non-cancer, non-HIV pain increases significantly the risk of development of major depressive disorder in opioid naïve individuals with no recent history of depression and substance used disorders. The risk of depression increased as the dose and/or the duration of opioid use increased. The purpose of the present paper is to elucidate the details of this study, to examine potential neurobiological mechanisms responsible for the depressogenic effect of opioid analgesics, and to discuss management options that emphasize depression prophylaxis.

Witnessed versus unwitnessed random urine tests in the treatment of opioid dependence.

BACKGROUND AND OBJECTIVES: Clinics licensed to provide pharmacotherapy for opiate dependence disorder are required to perform random urine drug screen (RUDS) tests. The results provide the empirical basis of individual treatment and programmatic effectiveness, and public health policy. Patients consent to witnessed testing but most tests are unwitnessed. The purpose of the present study was to compare treatment effectiveness estimates derived from witnessed versus unwitnessed urine samples. METHODS: We adopted a policy requiring visually witnessed urine drug screens (WUDS) and studied its impact (a single group, pretest-posttest design) on the RUDS test results in 115 male veterans enrolled in the St. Louis VA Opioid Treatment Program. RESULTS: The percentage of opioid-positive urine samples increased significantly following implementation of WUDS (25% vs. 41%, χ(2) = 66.5, p < .001). CONCLUSIONS AND SCIENTIFIC SIGNIFICANCE: Results of this preliminary study suggest that random testing alone does not ensure the integrity of UDS testing. Outcome calculations based on random unwitnessed tests may overestimate the effectiveness of opioid dependence disorder treatment.

Risk architecture of schizophrenia: the role of epigenetics.

PURPOSE OF REVIEW: To systematize existing data and review new findings on the cause of schizophrenia and outline an improved mixed model of schizophrenia risk. RECENT FINDINGS: Multiple and variable genetic and environmental factors interact to influence the risk of schizophrenia. Both rare variants with large effect and common variants with small effect contribute to genetic risk of schizophrenia, with no indication for differential impact on its clinical features. Accumulating evidence supports a genetic architecture of schizophrenia with multiple scenarios, including additive polygenic, heterogeneity, and mixed polygenic-heterogeneity. The epigenetic mechanisms that mediate gene-environment (GxE) interactions provide a framework to incorporate environmental factors into models of schizophrenia risk. Environmental pathogens with small effect on risk have robust effects in the context of family history of schizophrenia. Hence, genetic risk for schizophrenia may be expressed in part as sensitivity to environmental factors. SUMMARY: We propose an improved mixed model of schizophrenia risk in which abnormal epigenetic states with large effects are superimposed on a polygenic liability to schizophrenia. This scenario can account for GxE interactions and shared family environment, which in many cases are not explained by a single structural variant of large effect superimposed on polygenes (the traditional mixed model).

Temperament and character modify risk of drug addiction and influence choice of drugs.

BACKGROUND: Drug addiction and alcoholism involve a complex etiopathogenesis with a variable degree of risk contributions from the host (person), environment, and addictive substances. In this work, temperament and character features of individuals addicted to opiates or alcohol are compared with normal controls to study personality factors in the overall risk for drug addiction. METHODS: The study was done in a permissive environment, with easy access to alcohol and heroin, which facilitated analyses of personality factors in drug choice. Participants included 412 consecutive patients (312 opiate addicts, 100 alcohol addicts) treated at the Specialized Hospital for Chemical Dependency in Belgrade, Serbia, and a community sample of 346 controls. RESULTS: Opiate addicts manifested antisocial temperament configuration (high Novelty Seeking, low Reward Dependence) coupled with high Self-transcendence (ie, susceptibility to fantasy and imagination). Alcohol addicts manifested sensitive temperament configuration (high Novelty Seeking coexisting with high Harm Avoidance). Immature personality was observed far more frequently in opiate addicts than in alcoholics or normals. CONCLUSIONS: Novelty Seeking appears to be a general risk factor for drug addiction. High Harm Avoidance appears to channel individuals with high Novelty Seeking towards alcoholism. Immature character traits and probable Personality Disorder increase the risk of illegal drugs. Based on equivalent research in nonpermissive environments, at least a portion of our opiate addicts could have developed alcoholism instead in environments with more limited access to opiates. Personality factors provide useful guidelines for preventive work with young individuals with personality risk factors for drug addiction.

Legalization, decriminalization & medicinal use of cannabis: a scientific and public health perspective.

Empirical and clinical studies clearly demonstrate significant adverse effects of cannabis smoking on physical and mental health as well as its interference with social and occupational functioning. These negative data far outweigh a few documented benefits for a limited set of medical indications, for which safe and effective alternative treatments are readily available. If there is any medical role for cannabinoid drugs, it lies with chemically defined compounds, not with unprocessed cannabis plant. Legalization or medical use of smoked cannabis is likely to impose significant public health risks, including an increased risk of schizophrenia, psychosis, and other forms of substance use disorders.

Treating prepartum depression to improve infant developmental outcomes: a study of diabetes in pregnancy.

Whether and how the co-occurrence of depression and diabetes in pregnancy may worsen infant development has not been reported. Pregnant women with diabetes and with (n = 34) or without (n = 34) major depressive disorder (MDD) were followed during pregnancy and 6-months postpartum. The MDD subset received randomly assigned treatment with cognitive behavior therapy (CBT) or supportive counseling (SC). Depression severity was measured with the Beck Depression Inventory (BDI); infant developmental outcomes were measured with the Bayley Scales of Infant Development (BSID) and its Behavior Rating Scale (BRS). Infants of women with MDD had lower BRS scores (p = .02). Reduction in depression scores was associated with better infant outcomes on the BSID and BRS (p values <.03). These preliminary findings suggest depression occurring in pregnant women with diabetes is associated with poorer infant development and improvement in prepartum depression is associated with improvement in measures of infant development.

Why schizophrenia genetics needs epigenetics: a review.

Schizophrenia (SZ) is a highly heritable disorder, with about 80% of the variance attributable to genetic factors. There is accumulating evidence that both common genetic variants with small effects and rare genetic lesions with large effects determine risk of SZ. As recently shown, thousands of common single nucleotide polymorphisms (SNPs), each with small effect, cumulatively could explain about 30% of the underlying genetic risk of SZ. On the other hand, rare and large copy number variants (CNVs) with high but incomplete penetrance, variable in different individual, could explain about additional 30% of SZ cases. Although these rare CNVs frequently develop de novo, it is not clear whether they affect risk independently or via interaction with a polygenic liability in the background. Finally, the role of environmental risk factors has been well established in SZ. Environmental factors are rarely sufficient to cause SZ independently, but act in parallel or in synergy with the underlying genetic liability. Epigenetic misregulation of the genome and direct CNS injury are probably the main mechanism to mediate prenatal environmental effects (e.g., viruses, ethanol, or nutritional deficiency) whereas postnatal risk factors (e.g., stress, urbanicity, cannabis use) may also affect risk via use-based potentiation of vulnerable CNS pathways implicated in SZ. In this review, we outline a general theoretical background of epigenetic mechanisms involved in GxE interactions, and then discuss epigenetic and neurodevelopmental features of SZ based on available information from genetics, epigenetics, epidemiology, neuroscience, and clinical research. We argue that epigenetic model of SZ provides a framework to integrate a variety of diverse empirical data into a powerful etiopathogenetic synthesis. The promising future of this model is the possibility to develop truly specific prevention and treatment strategies for SZ.