Clinical correlation but no elevation of striatal dopamine synthesis capacity in two independent cohorts of medication-free individuals with schizophrenia

Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Relationship between drug-induced movement disorders and psychosis in adults living in precarious housing or homelessness

BACKGROUND

Studies have reported positive associations between drug-induced movement disorders (DIMDs) and symptoms of psychosis in patients with schizophrenia. However, it is not clear which subtypes of symptoms are related to each other, and whether one symptom precedes another. The current report assessed both concurrent and temporal associations between DIMDs and symptoms of psychosis in a community-based sample of homeless individuals.

METHODS

Participants were recruited in Vancouver, Canada. Severity of DIMDs and psychosis was rated annually, allowing for the analysis of concurrent associations between DIMDs and Positive and Negative Syndrome Scale (PANSS) five factors. A brief version of the PANSS was rated monthly using five psychotic symptoms, allowing for the analysis of their temporal associations with DIMDs. Mixed-effects linear and logistic regression models were used to assess the associations.

RESULTS

401 participants were included, mean age of 40.7 years (SD = 11.2) and 77.4% male. DIMDs and symptoms of psychosis were differentially associated with each other, in which the presence of parkinsonism was associated with greater negative symptoms, dyskinesia with disorganized symptoms, and akathisia with excited symptoms. The presence of DIMDs of any type was not associated with depressive symptoms. Regarding temporal associations, preceding delusions and unusual thought content were associated with parkinsonism, whereas dyskinesia was associated with subsequent conceptual disorganization.

CONCLUSIONS

The current study found significant associations between DIMDs and symptoms of psychosis in individuals living in precarious housing or homelessness. Moreover, there were temporal associations between parkinsonism and psychotic symptoms (delusions or unusual thought content), and the presence of dyskinesia was temporally associated with higher odds of clinically relevant conceptual disorganization.

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [ 18 F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a 'bench to bedside' translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.

An automatic analysis framework for FDOPA PET neuroimaging

In this study we evaluate the performance of a fully automated analytical framework for FDOPA PET neuroimaging data, and its sensitivity to demographic and experimental variables and processing parameters. An instance of XNAT imaging platform was used to store the King's College London institutional brain FDOPA PET imaging archive, alongside individual demographics and clinical information. By re-engineering the historical Matlab-based scripts for FDOPA PET analysis, a fully automated analysis pipeline for imaging processing and data quantification was implemented in Python and integrated in XNAT. The final data repository includes 892 FDOPA PET scans organized from 23 different studies. We found good reproducibility of the data analysis by the automated pipeline (in the striatum for the Kicer: for the controls ICC = 0.71, for the psychotic patients ICC = 0.88). From the demographic and experimental variables assessed, gender was found to most influence striatal dopamine synthesis capacity (F = 10.7, p < 0.001), with women showing greater dopamine synthesis capacity than men. Our automated analysis pipeline represents a valid resourse for standardised and robust quantification of dopamine synthesis capacity using FDOPA PET data. Combining information from different neuroimaging studies has allowed us to test it comprehensively and to validate its replicability and reproducibility performances on a large sample size.