Non-rapid eye movement sleep and wake neurophysiology in schizophrenia
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Evaluation Summary:
This study, one of the largest of its kind, replicate previous findings regarding impairment of sleep rhythms in patients with schizophrenia relative to healthy controls. Specifically, slow but not fast sleep spindles are correlated with the severity of the symptoms.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
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Abstract
Motivated by the potential of objective neurophysiological markers to index thalamocortical function in patients with severe psychiatric illnesses, we comprehensively characterized key non-rapid eye movement (NREM) sleep parameters across multiple domains, their interdependencies, and their relationship to waking event-related potentials and symptom severity. In 72 schizophrenia (SCZ) patients and 58 controls, we confirmed a marked reduction in sleep spindle density in SCZ and extended these findings to show that fast and slow spindle properties were largely uncorrelated. We also describe a novel measure of slow oscillation and spindle interaction that was attenuated in SCZ. The main sleep findings were replicated in a demographically distinct sample, and a joint model, based on multiple NREM components, statistically predicted disease status in the replication cohort. Although also altered in patients, auditory event-related potentials elicited during wake were unrelated to NREM metrics. Consistent with a growing literature implicating thalamocortical dysfunction in SCZ, our characterization identifies independent NREM and wake EEG biomarkers that may index distinct aspects of SCZ pathophysiology and point to multiple neural mechanisms underlying disease heterogeneity. This study lays the groundwork for evaluating these neurophysiological markers, individually or in combination, to guide efforts at treatment and prevention as well as identifying individuals most likely to benefit from specific interventions.
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Author Response:
Reviewer #1:
Kozhemiako et al. characterized several NREM sleep parameters, including their relationship with each other and with waking event-related potentials and symptom severity in patients with schizophrenia (SCZ) relative to healthy control (HC) subjects. The authors confirmed a marked reduction in sleep spindle density in SCZ while also showing that only slow spindles predicted symptom severity, and that fast and slow spindle properties were largely uncorrelated. Also, the main sleep findings were replicated in a different sample, and a model based on multiple NREM components predicted disease status with good accuracy in the replication cohort. Furthermore, despite being altered in patients with SCZ relative to HC, auditory event-related potentials elicited during wakefulness were unrelated to NREM sleep …
Author Response:
Reviewer #1:
Kozhemiako et al. characterized several NREM sleep parameters, including their relationship with each other and with waking event-related potentials and symptom severity in patients with schizophrenia (SCZ) relative to healthy control (HC) subjects. The authors confirmed a marked reduction in sleep spindle density in SCZ while also showing that only slow spindles predicted symptom severity, and that fast and slow spindle properties were largely uncorrelated. Also, the main sleep findings were replicated in a different sample, and a model based on multiple NREM components predicted disease status with good accuracy in the replication cohort. Furthermore, despite being altered in patients with SCZ relative to HC, auditory event-related potentials elicited during wakefulness were unrelated to NREM sleep parameters. Based on these findings, the authors concluded that the present study lays the foundations for assessing these sleep and wakefulness EEG neurophysiological markers, individually or in combination, to guide efforts at identifying individuals with SCZ, and especially those who are most likely to benefit from specific treatment interventions.
This study has several strengths, but certain aspects of the data analyses and of the interpretation of the main findings need to be clarified and extended.
Strengths:
The authors conducted the largest replication study of sleep findings in patients with SCZ relative to HC. One of the main challenges in clinical research nowadays is confirming previously established findings (i.e., reduced sleep spindle density in patients with SCZ) in a different group of patients. The authors should therefore be commended for doing so in a quite large sample of SCZ patients. It should also be pointed out that they were able to replicate most of the sleep findings in a demographically distinct sample of patients with SCZ.
Another strength of the present study is the assessment of novel sleep spindle and slow oscillation (SO) measures in patients with SCZ relative to HC. In addition to a comprehensive characterization of previously known spindle and SO parameters, here the authors introduced some novel measures, including the intra-spindle frequency modulation (chirp/deceleration) and its relationship with the SO phase as well as the Phase Slope Index (PSI) as an index of functional connectivity.
The assessment of wake EEG abnormalities in the same group of SCZ patients showing altered sleep parameters is another strength and novelty of the present study. Neurophysiological alterations during wakefulness, assessed with Mismatch Negativity (MMN), auditory P50 S2/S1, and auditory steady state response (ASSR) power have been previously reported in patients with SCZ. By computing these wake neurophysiological parameters along with sleep EEG measures in this study, the authors were able to investigate whether these wake and sleep abnormalities were associated with or rather reflected distinct alterations in underlying neural circuits in SCZ.
Finally, by using a Joint model analysis across sleep EEG metrics that were altered in SCZ, the authors were able to establish an excellent ability in predicting case/control (SCZ/HC) status in the training sample along with a good ability in predicting SCZ/HC status in the independent target sample.
We thank the reviewer for these comments and for pointing out strengths of this study: the size of the cohort, confirmation, comprehensiveness of the analyses with novel metrics, parallel wake EEG measures, and the joint model using multiple parameters from NREM sleep.
Weaknesses:
An important finding of this study was the correlation between sleep spindles and severity of symptoms. The authors should, however, report whether this correlation between slow spindles and clinical symptoms was confirmed in the replication sample of SCZ patients.
As comparably-coded clinical data (PANSS) were not available for the replication samples we were not able to conduct such a replication analysis. Acknowledging this limitation, we have removed the reference to this result from the abstract, and we now state in the manuscript that future studies will be needed to replicate this finding.
The authors computed novel sleep measures, some of which were altered in patients with SCZ relative to HC. For example, a decrease in overlap between slow spindles and SO (a proxy measure of spindle=SO coupling) as well as an increase in PSI (a proxy measure of connectivity) was reported in SCZ patients. However, the relevance and the functional implications of these alterations are barely addressed in the discussion.
We have extended our discussion to address the implication of these alterations.
In the abstract, as well as towards the end of the discussion, the authors suggest that the present findings may index risk, sequelae, or modifiable therapeutic targets. Each of these claims needs to be further elaborated on.
We have extended our discussion to address these points.
Reviewer #2:
This study sets out to replicate the large and accumulating literature which shows alterations in sleep neurophysiology in individuals with schizophrenia. The strengths of this study include the sample size and the analyses performed, which are thorough.
One limitation of the work is that too many analyses are presented which do not contribute to the overall "story" of the paper. It has long been known that different features of sleep, such as slow oscillations and spindles, map onto somewhat distinct networks and that additional information can be derived from combining these measures. Therefore, the section on PSC analysis can be reduced. Furthermore, the value of a "replication" sample is not clear. These previously published data have already shown spindle deficits in their samples, so the argument is rather circular here. The additional analyses which were done with the "replication" sample do not add significantly to our knowledge of the neurobiology of schizophrenia.
A key and novel result is that this study pointed to multiple, independent alterations in SCZ. We agree with the reviewer that, as a general principle, "... additional information can be derived from combining these measures". Indeed, this is precisely the rationale for the PSC analyses, which provide a rigorous and quantitative way to combine information (which we see as a strength). However, prior research specifically on NREM sleep and SCZ has not attempted to delineate the joint contributions of these measures (including wake ERPs), and this was a knowledge gap our work was intended to address.
Regarding the role of the replication samples: a main aim of this manuscript was a comprehensive analysis of sleep and wake EEG in SCZ, attempting both a replication of previous findings (i.e. replicated in the GRINS sample) as well as testing novel GRINS-derived alterations in the independent replication studies (i.e. metrics which had not previously been assessed in those samples, and yet were meaningfully distinct - and statistically independent - from the core (fast) spindle density findings, e.g. slow spindle parameters, PSI, chirp). Although an optimal study design might indeed involve (multiple) fully independent replication samples, we strove to efficiently make use of extant data in a methodologically consistent manner, and to show transferability of results across ethnically distinct samples.
Whereas other fields (e.g. human genetics) now routinely require replication to be an integral part of every report, we note that this is not the norm for biomarker studies of sleep neurophysiology. As such, we feel that the inclusion of replication data in our manuscript provides a positive example for the field. We also note that we preemptively addressed the criticism of 'circularity' in the original manuscript, in which we explicitly described both the value and limitation of these additional samples:
"The three datasets have previously reported spindle deficits in patients (see the references above). However, these three datasets have not previously been combined, and the comprehensive set of micro- architecture measures employed here has not been consistently applied across all studies. For example, 1) spectral power analysis was limited to band-specific analyses in GRRC & Lunesta, 2) only fast spindles were measured, 3) spindle chirp was not assessed, and 4) and only one low density study considered connectivity (measured as coherence). Nonetheless, given the extant literature, we present these replication samples not to address the general hypothesis of whether or not there is altered spindle activity in SCZ - as that would be circular - but rather to provide a methodologically integrated analysis of the specific sleep EEG metrics tested in GRINS."
Reviewer #3:
Understanding of the mechanisms of sleep alterations in patients with schizophrenia, may provide important information for the development of new therapies for psychosis. The main strength of this study is that it provides a most comprehensive analysis of sleep EEG in patients with schizophrenia. The results presented are generally consistent with the existing knowledge. The main weakness of this study is that it fails to take into account the potential contribution of sleep homeostasis and circadian rhythms, as well as relevant environmental factors, such as light.
We appreciate the reviewer’s comments on the comprehensiveness of our analyses. We performed additional analyses to address the potential contribution of sleep homeostasis and circadian rhythms.
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Evaluation Summary:
This study, one of the largest of its kind, replicate previous findings regarding impairment of sleep rhythms in patients with schizophrenia relative to healthy controls. Specifically, slow but not fast sleep spindles are correlated with the severity of the symptoms.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)
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Reviewer #1 (Public Review):
Kozhemiako et al. characterized several NREM sleep parameters, including their relationship with each other and with waking event-related potentials and symptom severity in patients with schizophrenia (SCZ) relative to healthy control (HC) subjects. The authors confirmed a marked reduction in sleep spindle density in SCZ while also showing that only slow spindles predicted symptom severity, and that fast and slow spindle properties were largely uncorrelated. Also, the main sleep findings were replicated in a different sample, and a model based on multiple NREM components predicted disease status with good accuracy in the replication cohort. Furthermore, despite being altered in patients with SCZ relative to HC, auditory event-related potentials elicited during wakefulness were unrelated to NREM sleep …
Reviewer #1 (Public Review):
Kozhemiako et al. characterized several NREM sleep parameters, including their relationship with each other and with waking event-related potentials and symptom severity in patients with schizophrenia (SCZ) relative to healthy control (HC) subjects. The authors confirmed a marked reduction in sleep spindle density in SCZ while also showing that only slow spindles predicted symptom severity, and that fast and slow spindle properties were largely uncorrelated. Also, the main sleep findings were replicated in a different sample, and a model based on multiple NREM components predicted disease status with good accuracy in the replication cohort. Furthermore, despite being altered in patients with SCZ relative to HC, auditory event-related potentials elicited during wakefulness were unrelated to NREM sleep parameters. Based on these findings, the authors concluded that the present study lays the foundations for assessing these sleep and wakefulness EEG neurophysiological markers, individually or in combination, to guide efforts at identifying individuals with SCZ, and especially those who are most likely to benefit from specific treatment interventions.
This study has several strengths, but certain aspects of the data analyses and of the interpretation of the main findings need to be clarified and extended.
Strengths:
The authors conducted the largest replication study of sleep findings in patients with SCZ relative to HC. One of the main challenges in clinical research nowadays is confirming previously established findings (i.e., reduced sleep spindle density in patients with SCZ) in a different group of patients. The authors should therefore be commended for doing so in a quite large sample of SCZ patients. It should also be pointed out that they were able to replicate most of the sleep findings in a demographically distinct sample of patients with SCZ.
Another strength of the present study is the assessment of novel sleep spindle and slow oscillation (SO) measures in patients with SCZ relative to HC. In addition to a comprehensive characterization of previously known spindle and SO parameters, here the authors introduced some novel measures, including the intra-spindle frequency modulation (chirp/deceleration) and its relationship with the SO phase as well as the Phase Slope Index (PSI) as an index of functional connectivity.
The assessment of wake EEG abnormalities in the same group of SCZ patients showing altered sleep parameters is another strength and novelty of the present study. Neurophysiological alterations during wakefulness, assessed with Mismatch Negativity (MMN), auditory P50 S2/S1, and auditory steady state response (ASSR) power have been previously reported in patients with SCZ. By computing these wake neurophysiological parameters along with sleep EEG measures in this study, the authors were able to investigate whether these wake and sleep abnormalities were associated with or rather reflected distinct alterations in underlying neural circuits in SCZ.
Finally, by using a Joint model analysis across sleep EEG metrics that were altered in SCZ, the authors were able to establish an excellent ability in predicting case/control (SCZ/HC) status in the training sample along with a good ability in predicting SCZ/HC status in the independent target sample.
Weaknesses:
An important finding of this study was the correlation between sleep spindles and severity of symptoms. The authors should, however, report whether this correlation between slow spindles and clinical symptoms was confirmed in the replication sample of SCZ patients.
The authors computed novel sleep measures, some of which were altered in patients with SCZ relative to HC. For example, a decrease in overlap between slow spindles and SO (a proxy measure of spindle=SO coupling) as well as an increase in PSI (a proxy measure of connectivity) was reported in SCZ patients. However, the relevance and the functional implications of these alterations are barely addressed in the discussion.
In the abstract, as well as towards the end of the discussion, the authors suggest that the present findings may index risk, sequelae, or modifiable therapeutic targets. Each of these claims needs to be further elaborated on.
-
Reviewer #2 (Public Review):
This study sets out to replicate the large and accumulating literature which shows alterations in sleep neurophysiology in individuals with schizophrenia. The strengths of this study include the sample size and the analyses performed, which are thorough.
One limitation of the work is that too many analyses are presented which do not contribute to the overall "story" of the paper. It has long been known that different features of sleep, such as slow oscillations and spindles, map onto somewhat distinct networks and that additional information can be derived from combining these measures. Therefore, the section on PSC analysis can be reduced. Furthermore, the value of a "replication" sample is not clear. These previously published data have already shown spindle deficits in their samples, so the argument is …
Reviewer #2 (Public Review):
This study sets out to replicate the large and accumulating literature which shows alterations in sleep neurophysiology in individuals with schizophrenia. The strengths of this study include the sample size and the analyses performed, which are thorough.
One limitation of the work is that too many analyses are presented which do not contribute to the overall "story" of the paper. It has long been known that different features of sleep, such as slow oscillations and spindles, map onto somewhat distinct networks and that additional information can be derived from combining these measures. Therefore, the section on PSC analysis can be reduced. Furthermore, the value of a "replication" sample is not clear. These previously published data have already shown spindle deficits in their samples, so the argument is rather circular here. The additional analyses which were done with the "replication" sample do not add significantly to our knowledge of the neurobiology of schizophrenia.
-
Reviewer #3 (Public Review):
Understanding of the mechanisms of sleep alterations in patients with schizophrenia, may provide important information for the development of new therapies for psychosis. The main strength of this study is that it provides a most comprehensive analysis of sleep EEG in patients with schizophrenia. The results presented are generally consistent with the existing knowledge. The main weakness of this study is that it fails to take into account the potential contribution of sleep homeostasis and circadian rhythms, as well as relevant environmental factors, such as light.
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