19 research outputs found
Role of N-methyl-D-aspartate receptors in action-based predictive coding deficits in schizophrenia
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
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
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
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
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Bihemispheric network dynamics coordinating vocal feedback control.
Modulation of vocal pitch is a key speech feature that conveys important linguistic and affective information. Auditory feedback is used to monitor and maintain pitch. We examined induced neural high gamma power (HGP) (65-150 Hz) using magnetoencephalography during pitch feedback control. Participants phonated into a microphone while hearing their auditory feedback through headphones. During each phonation, a single real-time 400 ms pitch shift was applied to the auditory feedback. Participants compensated by rapidly changing their pitch to oppose the pitch shifts. This behavioral change required coordination of the neural speech motor control network, including integration of auditory and somatosensory feedback to initiate change in motor plans. We found increases in HGP across both hemispheres within 200 ms of pitch shifts, covering left sensory and right premotor, parietal, temporal, and frontal regions, involved in sensory detection and processing of the pitch shift. Later responses to pitch shifts (200-300 ms) were right dominant, in parietal, frontal, and temporal regions. Timing of activity in these regions indicates their role in coordinating motor change and detecting and processing of the sensory consequences of this change. Subtracting out cortical responses during passive listening to recordings of the phonations isolated HGP increases specific to speech production, highlighting right parietal and premotor cortex, and left posterior temporal cortex involvement in the motor response. Correlation of HGP with behavioral compensation demonstrated right frontal region involvement in modulating participant's compensatory response. This study highlights the bihemispheric sensorimotor cortical network involvement in auditory feedback-based control of vocal pitch
Bihemispheric network dynamics coordinating vocal feedback control
Modulation of vocal pitch is a key speech feature that conveys important linguistic and affective information. Auditory feedback is used to monitor and maintain pitch. We examined induced neural high gamma power (HGP) (65-150 Hz) using magnetoencephalography during pitch feedback control. Participants phonated into a microphone while hearing their auditory feedback through headphones. During each phonation, a single real-time 400 ms pitch shift was applied to the auditory feedback. Participants compensated by rapidly changing their pitch to oppose the pitch shifts. This behavioral change required coordination of the neural speech motor control network, including integration of auditory and somatosensory feedback to initiate change in motor plans. We found increases in HGP across both hemispheres within 200 ms of pitch shifts, covering left sensory and right premotor, parietal, temporal, and frontal regions, involved in sensory detection and processing of the pitch shift. Later responses to pitch shifts (200-300 ms) were right dominant, in parietal, frontal, and temporal regions. Timing of activity in these regions indicates their role in coordinating motor change and detecting and processing of the sensory consequences of this change. Subtracting out cortical responses during passive listening to recordings of the phonations isolated HGP increases specific to speech production, highlighting right parietal and premotor cortex, and left posterior temporal cortex involvement in the motor response. Correlation of HGP with behavioral compensation demonstrated right frontal region involvement in modulating participant's compensatory response. This study highlights the bihemispheric sensorimotor cortical network involvement in auditory feedback-based control of vocal pitch
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Interactive effects of an N-methyl-d-aspartate receptor antagonist and a nicotinic acetylcholine receptor agonist on mismatch negativity: Implications for schizophrenia.
N-methyl-d-aspartate glutamate receptor (NMDAR) hypofunction has been implicated in the pathophysiology of schizophrenia, including auditory processing abnormalities reflected by the mismatch negativity (MMN) event-related potential component. Evidence suggesting cognitive benefits from nicotine administration, together with the high rate of cigarette use in patients with schizophrenia, has stimulated interest in whether nicotine modulates NMDAR hypofunction. We examined the interactive effects of ketamine, an NMDAR antagonist that produces transient schizophrenia-like neurophysiological effects, and nicotine, a nicotinic acetylcholine receptor (nAChR) agonist, in 30 healthy volunteers to determine whether nicotine prevents or attenuates MMN abnormalities. Secondary analyses compared the profile of ketamine and schizophrenia effects on MMN using previously reported data from 24 schizophrenia patients (Hay et al. 2015). Healthy volunteers completed four test days, during which they received ketamine/placebo and nicotine/placebo in a double-blind, counterbalanced design. MMN to intensity, frequency, duration, and frequency+duration double deviant sounds was assessed each day. Ketamine decreased intensity, frequency, and double deviant MMN amplitudes, whereas nicotine increased intensity and double deviant MMN amplitudes. A ketamineĂ—nicotine interaction indicated, however, that nicotine failed to attenuate the decrease in MMN associated with ketamine. Although the present dose of ketamine produced smaller decrements in MMN than those associated with schizophrenia, the profile of effects across deviant types did not differ between ketamine and schizophrenia. Results suggest that while ketamine and schizophrenia produce similar profiles of MMN effects across deviant types, nicotinic agonists may have limited potential to improve these putative NMDAR hypofunction-mediated impairments in schizophrenia
Molecular assessment of antibody-mediated rejection in human pancreas allograft biopsies
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