18 research outputs found

    Role of N-methyl-D-aspartate receptors in action-based predictive coding deficits in schizophrenia

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    Published in final edited form as:Biol Psychiatry. 2017 March 15; 81(6): 514–524. doi:10.1016/j.biopsych.2016.06.019.BACKGROUND: Recent theoretical models of schizophrenia posit that dysfunction of the neural mechanisms subserving predictive coding contributes to symptoms and cognitive deficits, and this dysfunction is further posited to result from N-methyl-D-aspartate glutamate receptor (NMDAR) hypofunction. Previously, by examining auditory cortical responses to self-generated speech sounds, we demonstrated that predictive coding during vocalization is disrupted in schizophrenia. To test the hypothesized contribution of NMDAR hypofunction to this disruption, we examined the effects of the NMDAR antagonist, ketamine, on predictive coding during vocalization in healthy volunteers and compared them with the effects of schizophrenia. METHODS: In two separate studies, the N1 component of the event-related potential elicited by speech sounds during vocalization (talk) and passive playback (listen) were compared to assess the degree of N1 suppression during vocalization, a putative measure of auditory predictive coding. In the crossover study, 31 healthy volunteers completed two randomly ordered test days, a saline day and a ketamine day. Event-related potentials during the talk/listen task were obtained before infusion and during infusion on both days, and N1 amplitudes were compared across days. In the case-control study, N1 amplitudes from 34 schizophrenia patients and 33 healthy control volunteers were compared. RESULTS: N1 suppression to self-produced vocalizations was significantly and similarly diminished by ketamine (Cohen’s d = 1.14) and schizophrenia (Cohen’s d = .85). CONCLUSIONS: Disruption of NMDARs causes dysfunction in predictive coding during vocalization in a manner similar to the dysfunction observed in schizophrenia patients, consistent with the theorized contribution of NMDAR hypofunction to predictive coding deficits in schizophrenia.This work was supported by AstraZeneca for an investigator-initiated study (DHM) and the National Institute of Mental Health Grant Nos. R01 MH-58262 (to JMF) and T32 MH089920 (to NSK). JHK was supported by the Yale Center for Clinical Investigation Grant No. UL1RR024139 and the US National Institute on Alcohol Abuse and Alcoholism Grant No. P50AA012879. (AstraZeneca for an investigator-initiated study (DHM); R01 MH-58262 - National Institute of Mental Health; T32 MH089920 - National Institute of Mental Health; UL1RR024139 - Yale Center for Clinical Investigation; P50AA012879 - US National Institute on Alcohol Abuse and Alcoholism)Accepted manuscrip

    Stroke genetics informs drug discovery and risk prediction across ancestries

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    Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

    Stroke genetics informs drug discovery and risk prediction across ancestries

    Get PDF
    Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

    A bilateral cortical network responds to pitch perturbations in speech feedback

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    Auditory feedback is used to monitor and correct for errors in speech production, and one of the clearest demonstrations of this is the pitch perturbation reflex. During ongoing phonation, speakers respond rapidly to shifts of the pitch of their auditory feedback, altering their pitch production to oppose the direction of the applied pitch shift. In this study, we examine the timing of activity within a network of brain regions thought to be involved in mediating this behavior. To isolate auditory feedback processing relevant for motor control of speech, we used magnetoencephalography (MEG) to compare neural responses to speech onset and to transient (400ms) pitch feedback perturbations during speaking with responses to identical acoustic stimuli during passive listening. We found overlapping, but distinct bilateral cortical networks involved in monitoring speech onset and feedback alterations in ongoing speech. Responses to speech onset during speaking were suppressed in bilateral auditory and left ventral supramarginal gyrus/posterior superior temporal sulcus (vSMG/pSTS). In contrast, during pitch perturbations, activity was enhanced in bilateral vSMG/pSTS, bilateral premotor cortex, right primary auditory cortex, and left higher order auditory cortex. We also found speaking-induced delays in responses to both unaltered and altered speech in bilateral primary and secondary auditory regions, left vSMG/pSTS and right premotor cortex. The network dynamics reveal the cortical processing involved in both detecting the speech error and updating the motor plan to create the new pitch output. These results implicate vSMG/pSTS as critical in both monitoring auditory feedback and initiating rapid compensation to feedback errors

    Molecular assessment of antibody-mediated rejection in human pancreas allograft biopsies

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    Pancreas transplant longevity is limited by immune rejection, which is diagnosed by graft biopsy using the Banff Classification. The histological criteria for antibody-mediated rejection (AMR) are poorly reproducible and inconsistently associated with outcome. We hypothesized that a 34-gene set associated with antibody-mediated rejection in other solid organ transplants could improve diagnosis in pancreas grafts. The AMR 34-gene set, comprising endothelial, natural killer cell and inflammatory genes, was quantified using the NanoString platform in 52 formalin-fixed, paraffin-embedded pancreas transplant biopsies from 41 patients: 15 with pure AMR or mixed rejection, 22 with T cell-mediated rejection/borderline and 15 without rejection. The AMR 34-gene set was significantly increased in pure AMR and mixed rejection (P = .001) vs no rejection. The gene set predicted histological AMR with an area under the receiver operating characteristic curve (ROC AUC) of 0.714 (P = .004). The AMR 34-gene set was the only biopsy feature significantly predictive of allograft failure in univariate analysis (P = .048). Adding gene expression to DSA and histology increased ROC AUC for the prediction of failure from 0.736 to 0.770, but this difference did not meet statistical significance. In conclusion, assessment of transcripts has the potential to improve diagnosis and outcome prediction in pancreas graft biopsies
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