Therefore, genome-wide significance may identify loci with larger genetic effects, while others with smaller effects remain undetected for a given population size. Variation in ADGRL3 has been implicated in ADHD in diverse populations. ADGRL3 is a member of the latrophilin subfamily of G-protein-coupled receptors and is most strongly expressed in brain regions implicated in the neurophysiological basis of ADHD. Mouse and zebrafish knockout models also support ADGRL3 implication in ADHD pathophysiology. More recently, Martinez et al. identified a brain-specific transcriptional enhancer within ADGRL3 that contains an ADHD risk haplotype associated with reduced ADGRL3 mRNA expression in the thalamus. This haplotype was associated not only with ADHD, but also with disruptive behaviors, including SUD. A member of the family of leucine-rich repeat transmembrane proteins has been identified as an endogenous postsynaptic ligand for latrophilins. Interferencewith this interaction reduces excitatory synapse density in cultured neurons and decreases afferent input strength and dendritic spine number in dentate granule cells, which implicates ADGRL3 and FLRT3 in glutamatergic synapse development. Similarly, convergent evidence from a network analysis of a gene set significantly associated and/or linked to ADHD and SUD revealed pathways involved in axon guidance,mobile grow system regulation of synaptic transmission, and regulation of transmission of nerve impulse. These data altogether suggest that ADGRL3 may be an important SUD susceptibility gene. Strong evidence from clinical and genetic association studies suggests that genetic factors play a crucial role in shaping the susceptibility to both ADHD and SUD.
More strikingly, ADHD treatment has been shown to reduce the risk of SUD. Though the neurobiological basis for this association remains unclear, a variety of causal pathways from ADHD to SUD have been proposed that involve conduct problems. Clinical studies have suggested that the link between SUD and ADHD disappears after controlling for co-morbid CD. In agreement with these studies, the presence of CD was a major predictor of SUD in the ARPA-based predictive models for SUD in the Paisa and Spanish cohorts . Some researchers implicate genetically mediated personality traits, such as impulsivity and lack of inhibitory control as a link between ADHD and SUD resulting from common neurological substrates. Some investigators have proposed that patients with ADHD use addictive substances to self-medicate and that the differential response to drugs of abuse and atypical behavioral regulation in response to social cues may fuel substance use. Others suggest that the poor judgment and impulsivity associated with ADHD contribute to the development of substance dependence. Clinical variables from childhood have also been associated with SUD in patients with ADHD, such ADHD sub-type, temper characteristics , sexual abuse, suspension from school, and a family history of ADHD. In summary, our results support a possible functional role for ADGRL3 in modulating drug seeking behavior. Regardless of the type of abused substance, longitudinal studies generally find that the onset of ADHD precedes that of SUD, suggesting that the psychopathology of ADHD is not secondary to SUD in most patients. Accordingly, it is reasonable to consider that timely diagnosis and treatment of ADHD with stimulant medication may reduce the occurrence and/or severity of SUD. Based on the relationship with medication response, we speculate that ADGRL3 variants may underlie a differential genetic susceptibility not only to SUD, but also to the long-term protective effects of medication treatment. Inasmuch as ADGRL3 participates in synaptic formation and function, its involvement in SUD could be mediated by either influencing brain development or moderating drug-induced changes in synaptic strength. Molecular studies are required to elucidate the pathogenic mechanism associated with ADGRL3 dysfunction in SUD.Adaptive reward processing is critical for successful goal attainment and functioning across most domains of life.
Emerging research has begun to investigate different aspects of reward processing that may be impaired in schizophrenia and contribute to the diminished motivation and goal-directed behavior that often accompany this disorder . In addition to studies of reward anticipation and learning , investigators have examined reward-related decision making processes, such as effort based decision making . Another decision-making process that has received increased attention is “delay discounting” , which refers to whether one is willing to forego a smaller, sooner reward for the sake of a larger, later reward. Delay discounting is well suited for cross-species translational research, as a number of animal models of DD have been developed . Neurobiological studies in animals demonstrate central roles for the nucleus accumbens core and the orbitofrontal cortex in DD. In line with these findings, human fMRI studies of DD implicate a limbic circuit showing activity during selection of smaller sooner rewards, prefrontal areas associated with cognitive control showing activity during selection of larger but later rewards, and relative activity across these regions associated with behavioral preference . The vast majority of human DD studies use conventional decision making paradigms in which subjects make a series forced choices between smaller, sooner or a larger, later monetary rewards. In these paradigms, participants either receive no actual rewards, referred to as “hypothetical delay discounting tasks”, or are paid out for only one or a few randomly selected trials, referred to as “potentially real reward delay discounting tasks” , but receive no actual rewards or are paid out for only one or a few randomly selected trials. Numerous studies show that, all things being equal, the more a reward is delayed the less subjective value it has. People typically display a monotonically decreasing function such that reward value progressively diminishes as the delay to a reward grows longer. There are, however, substantial individual differences in the degree to which reward values are discounted as delays grow longer. For example, individuals with relatively greater discounting show a steeper reward/delay curve, such that smaller/sooner rewards are more readily chosen than larger/later rewards. Such individuals are more susceptible to proximal rewards and have been described as “temporally myopic” or “impulsive” . Consistent with this description, steeper discounting curves are associated with impulse control difficulties, including nicotine use, substance use disorders, and unhealthy behaviors .
In contrast to conventional paradigms, a more recent development in human research is the use of experiential DD paradigms in which subjects make a series of choices between smaller, sooner vs. later,mobile vertical grow rack larger monetary rewards and actually receive these rewards in real-time on a trial-by-trial basis. This format much more closely parallels DD tasks used in animal research . Like hypothetical tasks, experiential tasks show good sensitivity in differentiating between users and non-users of nicotine and other substances . Further, they may be more sensitive to treatment-related changes than hypothetical tasks, making them potentially attractive paradigms for endpoints in clinical trials. Despite the fact that both hypothetical and experiential tasks assess DD, they often show only small inter-correlations . The handful of DD studies in schizophrenia has only used hypothetical tasks. Findings have been mixed with several reporting greater DD in schizophrenia than controls , but others reporting normal DD . Findings regarding associations between DD and certain clinical symptoms and neurocognition have also been mixed. Although it has been proposed that negative symptoms may partly reflect DD disturbances , support has been inconsistent . Similarly inconsistent findings have been reported for associations with neurocognition . On the other hand, studies consistently indicate that DD is not significantly related to positive or mood-related symptoms or to anti-psychotic medications. Overall, it is difficult to integrate findings across studies and most of the studies have been under powered . Further, all studies have been cross-sectional, raising concerns that inconsistencies may reflect problems with the reliability of the paradigms used in these studies. The current study evaluated DD using a hypothetical task and, for the first time, an experiential task, in a relatively large sample of stabilized outpatients with schizophrenia. We had four primary goals. First, to address concerns about the validity of DD data in schizophrenia , we examined the orderliness of the DD data. In addition, we selected paradigms that enabled us to map the shape of the discounting curves to determine if individuals with schizophrenia show the typical hyperbolic shape . Second, we compared discount rates between the schizophrenia and control groups. Although prior studies using hypothetical tasks are mixed and did not support strong directional hypotheses, they led us to predict that the schizophrenia group would show higher DD rates than controls on both tasks. Third, we evaluated whether DD was related to clinical symptoms and neurocognition. We were particularly interested in whether greater discounting would relate to higher negative symptoms. Further, we determined whether the use of nicotine and other substances was associated with discounting rates in light of some evidence for steeper discounting rates among individuals with schizophrenia who are smokers . Fourth, in the schizophrenia group, we evaluated the one-month test-retest stability of the two tasks.The sample included 131 individuals with schizophrenia and 70 demographically-matched healthy controls. Individuals with schizophrenia were recruited from outpatient clinics at University of California, Los Angeles , the Veterans Affairs Greater Los Angeles Healthcare System , and from local clinics and board and care facilities.
Selection criteria for included Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnosis of schizophrenia determined with the Structured Clinical Interview for DSM-IV age 18–60 years, no clinically significant neurological disease, no history of serious head injury, no evidence of current alcohol, cannabis or other substance dependence disorder or current substance abuse disorder ; lifetime histories of these disorders were acceptable, and nicotine-related disorders were not formally assessed, no history of mental retardation or developmental disability, and clinically stable . Diagnostic assessments were conducted by interviewers trained according to established procedures . Eighty-five percent of the participants with schizophrenia were taking a second-generation anti-psychotic, 8% a first-generation anti-psychotic, 3% were taking both, and 4% were not taking an anti-psychotic. The mean chlorpromazine equivalent units was 375.95 . Control participants were recruited through advertisements posted on websites. Selection criteria for healthy controls included no psychiatric history involving schizophrenia spectrum disorder , or other psychotic or recurrent mood axis I disorder according to the SCID-I and SCID-II, no family history of a psychotic disorder among first-degree relatives based on participant report, and no evidence of current or lifetime history of alcohol, cannabis, or other substance dependence disorder, and not evidence of current substance abuse disorder ; nicotine-related disorders were not formally assessed. Criteria concerning age, neurological disease, and head trauma were the same as listed above for the schizophrenia group. Written informed consent was obtained prior to participation in accordance with approval from the local Institutional Review Board. The DD task data was collected as part of a larger grant-funded project on reward processing and negative symptoms in schizophrenia but has not been published elsewhere. An aim of the project was to examine associations between reward processing measures and negative symptoms among individuals with schizophrenia, and a larger clinical than healthy comparison sample was included to evaluate these within-group relationships. The hypothetical DD task was administered earlier in the assessment battery than the hypothetical DD task. The schizophrenia group was administered both DD tasks twice ; controls only received the tasks at baseline. Both groups completed a neurocognitive battery at baseline. $1,000 Delay-Discounting Task . Participants made a series of choices between receiving a $1,000 delayed hypothetical reward and an adjusting smaller immediate reward. The magnitude of the smaller immediate option was adjusted across trials according to a previously described algorithm until an indifference point was determined. Once an indifference point was determined, the larger later option was delayed further and the adjustment procedure was repeated with that new delay. Seven delays were assessed: 1 day, 1 week, 1 month, 6 months, 1 year, 5 years, and 25 years. Indifference points were expressed as a proportion of the larger later reward . Unlike the monetary choice questionnaire used in several prior studies of schizophrenia, the present task determined an indifference point for each delay , which enabled us to assess the orderliness of indifference points across delays and the shape of the discounting function. The Quick Discounting Operant Task used a coin dispenser for money reward delivery. A visual depiction of the task is shown in Supplemental Figure 1. Before beginning the task, participants were instructed to sit at the desk with eyes open during any waiting periods in the task, and were forbidden from engaging in other behaviors such as reading.