The transcriptional landscape of cortical interneurons underlies in-vivo brain function and schizophrenia risk

Inhibitory interneurons orchestrate information flow across cortex and are implicated in psychiatric illness. Although classes of interneurons have unique functional properties and spatial distributions throughout the brain, the relative influence of interneuron subtypes on brain function, cortical specialization, and illness risk remains elusive. Here, we demonstrate stereotyped organizational properties of somatostatin and parvalbumin related transcripts within human and non-human primates. Interneuron spatial distributions recapitulate cortico-striato-thalamic functional networks and track regional differences in functional MRI signal amplitude. In the general population (n=9,627), parvalbumin-linked genes account for an enriched proportion of genome-wide heritable variance in in-vivo functional MRI signal amplitude. This relationship is spatially dependent, following the topographic organization of parvalbumin expression in independent post-mortem brain tissue. Finally, genetic risk for schizophrenia is enriched among interneuron-linked genes and predictive of cortical signal amplitude in parvalbumin-biased regions. These data indicate that the molecular genetic basis of resting-state brain function across cortex is shaped by the spatial distribution of interneuron-related transcripts and underlies individual differences in risk for schizophrenia. Key Findings Spatial distributions of somatostatin (SST) and parvalbumin (PVALB) are negatively correlated in mature human and non-human primate cortex, paralleling patterns observed in utero. SST and PVALB are differentially expressed within distinct limbic and somato/motor cortico-striato-thalamic networks, respectively. In-vivo resting-state signal amplitude is heritable in the general population and tracks relative SST/PVALB expression across cortex. Single-nucleotide polymorphisms tied to PVALB-related genes account for an enriched proportion of the heritable variance in resting-state signal amplitude. PVALB-mediated heritability of resting-state signal amplitude in the general population is spatially heterogeneous, mirroring the cortical expression of PVALB in independent post-mortem brain tissue. Polygenic risk for schizophrenia is enriched among interneuron-linked genes and predicts resting-state signal amplitude in a manner that also follows the cortical expression of PVALB.

[1]  D. Lewis,et al.  Alterations in cortical interneurons and cognitive function in schizophrenia , 2019, Neurobiology of Disease.

[2]  Gerome Breen,et al.  Genetic identification of brain cell types underlying schizophrenia , 2017, Nature Genetics.

[3]  E. Yuliwati,et al.  A Review , 2019, Current Trends and Future Developments on (Bio-) Membranes.

[4]  P. Pavlidis,et al.  Transcriptomic evidence for alterations in astrocytes and parvalbumin interneurons in bipolar disorder and schizophrenia subjects , 2018, Biological Psychiatry.

[5]  M. Feldman,et al.  Analysis of Polygenic Score Usage and Performance in Diverse Human Populations , 2018, bioRxiv.

[6]  A. Bernacchia,et al.  Hierarchy of transcriptomic specialization across human cortex captured by structural neuroimaging topography , 2018, Nature Neuroscience.

[7]  Fenna M. Krienen,et al.  Gene expression links functional networks across cortex and striatum , 2018, Nature Communications.

[8]  Mingfeng Li,et al.  Early emergence of cortical interneuron diversity in the mouse embryo , 2018, Science.

[9]  Annchen R. Knodt,et al.  A Polygenic Score for Higher Educational Attainment is Associated with Larger Brains , 2018, bioRxiv.

[10]  S. Redner,et al.  Dynamics of starvation and recovery predict extinction risk and both Damuth’s law and Cope’s rule , 2018, Nature Communications.

[11]  Peter Fonagy,et al.  Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex , 2017, NeuroImage.

[12]  Etienne Sibille,et al.  Somatostatin-Positive Gamma-Aminobutyric Acid Interneuron Deficits in Depression: Cortical Microcircuit and Therapeutic Perspectives , 2017, Biological Psychiatry.

[13]  Miao He,et al.  Brain-wide Maps Reveal Stereotyped Cell-Type-Based Cortical Architecture and Subcortical Sexual Dimorphism , 2017, Cell.

[14]  Mark W. Woolrich,et al.  Investigations into within- and between-subject resting-state amplitude variations , 2017, NeuroImage.

[15]  G. Tseng,et al.  Transcriptome alterations of prefrontal cortical parvalbumin neurons in schizophrenia , 2017, Molecular Psychiatry.

[16]  Thomas E. Nichols,et al.  The heritability of multi-modal connectivity in human brain activity , 2017, eLife.

[17]  P. Visscher,et al.  10 Years of GWAS Discovery: Biology, Function, and Translation. , 2017, American journal of human genetics.

[18]  Evan M. Gordon,et al.  Local-Global Parcellation of the Human Cerebral Cortex From Intrinsic Functional Connectivity MRI , 2017, bioRxiv.

[19]  Mert R. Sabuncu,et al.  Heritability analysis with repeat measurements and its application to resting-state functional connectivity , 2017, Proceedings of the National Academy of Sciences.

[20]  Gord Fishell,et al.  Genetic and activity-dependent mechanisms underlying interneuron diversity , 2017, Nature Reviews Neuroscience.

[21]  René S. Kahn,et al.  Connectome Disconnectivity and Cortical Gene Expression in Patients With Schizophrenia , 2017, Biological Psychiatry.

[22]  T. Fuchs,et al.  Disinhibition of somatostatin-positive GABAergic interneurons results in an anxiolytic and antidepressant-like brain state , 2016, Molecular Psychiatry.

[23]  Maxwell A. Bertolero,et al.  The Human Thalamus Is an Integrative Hub for Functional Brain Networks , 2016, The Journal of Neuroscience.

[24]  Lachlan T. Strike,et al.  Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group , 2016, Molecular Psychiatry.

[25]  P. Matthews,et al.  Multimodal population brain imaging in the UK Biobank prospective epidemiological study , 2016, Nature Neuroscience.

[26]  Allan R. Jones,et al.  Comprehensive transcriptional map of primate brain development , 2016, Nature.

[27]  Benjamin A. Logsdon,et al.  Gene Expression Elucidates Functional Impact of Polygenic Risk for Schizophrenia , 2016, Nature Neuroscience.

[28]  Ben D. Fulcher,et al.  A transcriptional signature of hub connectivity in the mouse connectome , 2016, Proceedings of the National Academy of Sciences.

[29]  Fenna M. Krienen,et al.  Transcriptional profiles of supragranular-enriched genes associate with corticocortical network architecture in the human brain , 2016, Proceedings of the National Academy of Sciences.

[30]  D. Geschwind,et al.  Correspondence between Resting-State Activity and Brain Gene Expression , 2015, Neuron.

[31]  Allan R. Jones,et al.  Canonical Genetic Signatures of the Adult Human Brain , 2015, Nature Neuroscience.

[32]  D. Lewis,et al.  Alterations in Cortical Network Oscillations and Parvalbumin Neurons in Schizophrenia , 2015, Biological Psychiatry.

[33]  C. Poulsen,et al.  Long-term climate forcing by atmospheric oxygen concentrations , 2015, Science.

[34]  M. Rietschel,et al.  Correlated gene expression supports synchronous activity in brain networks , 2015, Science.

[35]  Joris M. Mooij,et al.  MAGMA: Generalized Gene-Set Analysis of GWAS Data , 2015, PLoS Comput. Biol..

[36]  H. Kennedy,et al.  A Large-Scale Circuit Mechanism for Hierarchical Dynamical Processing in the Primate Cortex , 2015, Neuron.

[37]  Jack Euesden,et al.  PRSice: Polygenic Risk Score software , 2014, Bioinform..

[38]  E. Sibille,et al.  Somatostatin, neuronal vulnerability and behavioral emotionality , 2014, Molecular Psychiatry.

[39]  Alan C. Evans,et al.  Anxious/depressed symptoms are linked to right ventromedial prefrontal cortical thickness maturation in healthy children and young adults. , 2014, Cerebral cortex.

[40]  David J. Freedman,et al.  A hierarchy of intrinsic timescales across primate cortex , 2014, Nature Neuroscience.

[41]  C. Spencer,et al.  Biological Insights From 108 Schizophrenia-Associated Genetic Loci , 2014, Nature.

[42]  C. Tamminga,et al.  Kv3.1-containing K+ channels are reduced in untreated schizophrenia and normalized with antipsychotic drugs , 2014, Molecular Psychiatry.

[43]  B T Thomas Yeo,et al.  Disruption of cortical association networks in schizophrenia and psychotic bipolar disorder. , 2014, JAMA psychiatry.

[44]  G. Fishell,et al.  Interneuron cell types are fit to function , 2014, Nature.

[45]  T. Woo,et al.  Developmental Pattern of Perineuronal Nets in the Human Prefrontal Cortex and Their Deficit in Schizophrenia , 2013, Biological Psychiatry.

[46]  Fenna M. Krienen,et al.  Opportunities and limitations of intrinsic functional connectivity MRI , 2013, Nature Neuroscience.

[47]  B. Hangya,et al.  Distinct behavioural and network correlates of two interneuron types in prefrontal cortex , 2013, Nature.

[48]  Ellen T. Gelfand,et al.  The Genotype-Tissue Expression (GTEx) project , 2013, Nature Genetics.

[49]  Randy L. Buckner,et al.  Individual Differences in Amygdala-Medial Prefrontal Anatomy Link Negative Affect, Impaired Social Functioning, and Polygenic Depression Risk , 2012, The Journal of Neuroscience.

[50]  Allan R. Jones,et al.  An anatomically comprehensive atlas of the adult human brain transcriptome , 2012, Nature.

[51]  Marisa O. Hollinshead,et al.  Identification of common variants associated with human hippocampal and intracranial volumes , 2012, Nature Genetics.

[52]  K. Nakazawa,et al.  GABAergic interneuron origin of schizophrenia pathophysiology , 2012, Neuropharmacology.

[53]  David A. Lewis,et al.  Cortical parvalbumin interneurons and cognitive dysfunction in schizophrenia , 2012, Trends in Neurosciences.

[54]  N. Logothetis,et al.  The Amplitude and Timing of the BOLD Signal Reflects the Relationship between Local Field Potential Power at Different Frequencies , 2012, The Journal of Neuroscience.

[55]  Oscar Marín,et al.  Interneuron dysfunction in psychiatric disorders , 2012, Nature Reviews Neuroscience.

[56]  R. Buckner,et al.  The organization of the human striatum estimated by intrinsic functional connectivity. , 2012, Journal of neurophysiology.

[57]  Timothy O. Laumann,et al.  Informatics and Data Mining Tools and Strategies for the Human Connectome Project , 2011, Front. Neuroinform..

[58]  Jochen Ditterich,et al.  Splash: A Software Tool for Stereotactic Planning of Recording Chamber Placement and Electrode Trajectories , 2011, Front. Neuroinform..

[59]  P. Visscher,et al.  GCTA: a tool for genome-wide complex trait analysis. , 2011, American journal of human genetics.

[60]  Paul M. Matthews,et al.  Connectivity-based segmentation of the substantia nigra in human and its implications in Parkinson's disease , 2010, NeuroImage.

[61]  Dae-Shik Kim,et al.  Global and local fMRI signals driven by neurons defined optogenetically by type and wiring , 2010, Nature.

[62]  M. Schölvinck,et al.  Neural basis of global resting-state fMRI activity , 2010, Proceedings of the National Academy of Sciences.

[63]  Christian Windischberger,et al.  Toward discovery science of human brain function , 2010, Proceedings of the National Academy of Sciences.

[64]  W. Singer,et al.  Abnormal neural oscillations and synchrony in schizophrenia , 2010, Nature Reviews Neuroscience.

[65]  S. Haber,et al.  The Reward Circuit: Linking Primate Anatomy and Human Imaging , 2010, Neuropsychopharmacology.

[66]  Jessica A. Cardin,et al.  Driving fast-spiking cells induces gamma rhythm and controls sensory responses , 2009, Nature.

[67]  K. Deisseroth,et al.  Parvalbumin neurons and gamma rhythms enhance cortical circuit performance , 2009, Nature.

[68]  Derek K. Jones,et al.  Resting GABA concentration predicts peak gamma frequency and fMRI amplitude in response to visual stimulation in humans , 2009, Proceedings of the National Academy of Sciences.

[69]  D. Leopold,et al.  Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest , 2008, Human brain mapping.

[70]  Bharat B. Biswal,et al.  Detection and scaling of task-induced fMRI-BOLD response using resting state fluctuations , 2008, NeuroImage.

[71]  S. Anderson,et al.  A spatial bias for the origins of interneuron subgroups within the medial ganglionic eminence. , 2008, Developmental biology.

[72]  R. Douglas,et al.  Mapping the Matrix: The Ways of Neocortex , 2007, Neuron.

[73]  Matthew Grist,et al.  Spatial Genetic Patterning of the Embryonic Neuroepithelium Generates GABAergic Interneuron Diversity in the Adult Cortex , 2007, The Journal of Neuroscience.

[74]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[75]  I. Fried,et al.  Coupling between Neuronal Firing Rate, Gamma LFP, and BOLD fMRI Is Related to Interneuronal Correlations , 2007, Current Biology.

[76]  Cheng Li,et al.  Adjusting batch effects in microarray expression data using empirical Bayes methods. , 2007, Biostatistics.

[77]  S. Anderson,et al.  The origin and specification of cortical interneurons , 2006, Nature Reviews Neuroscience.

[78]  Atul J. Butte,et al.  Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks , 2005, BMC Bioinformatics.

[79]  Bart De Moor,et al.  BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis , 2005, Bioinform..

[80]  W. Singer,et al.  Hemodynamic Signals Correlate Tightly with Synchronized Gamma Oscillations , 2005, Science.

[81]  H. Markram,et al.  Interneurons of the neocortical inhibitory system , 2004, Nature Reviews Neuroscience.

[82]  Stephen M. Smith,et al.  Probabilistic independent component analysis for functional magnetic resonance imaging , 2004, IEEE Transactions on Medical Imaging.

[83]  P. Sullivan,et al.  Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. , 2003, Archives of general psychiatry.

[84]  S. Haber.  The primate basal ganglia: parallel and integrative networks , 2003, Journal of Chemical Neuroanatomy.

[85]  Michael Brady,et al.  Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images , 2002, NeuroImage.

[86]  Danny Keogan,et al.  Distributed hierarchical processing , 2002, Photomask Japan.

[87]  P. Rakic,et al.  Origin of GABAergic neurons in the human neocortex , 2002, Nature.

[88]  Y. Kubota,et al.  GABAergic cell subtypes and their synaptic connections in rat frontal cortex. , 1997, Cerebral cortex.

[89]  R W Cox,et al.  AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. , 1996, Computers and biomedical research, an international journal.

[90]  E. G. Jones,et al.  Gene expression for glutamic acid decarboxylase is reduced without loss of neurons in prefrontal cortex of schizophrenics. , 1995, Archives of general psychiatry.

[91]  P. Goldman-Rakic,et al.  Preface: Cerebral Cortex Has Come of Age , 1991 .

[92]  D. J. Felleman,et al.  Distributed hierarchical processing in the primate cerebral cortex. , 1991, Cerebral cortex.

[93]  S. Cajal.  Recollections of my life , 1989 .

[94]  E. G. Jones,et al.  Numbers and proportions of GABA-immunoreactive neurons in different areas of monkey cerebral cortex , 1987, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[95]  G. E. Alexander,et al.  Parallel organization of functionally segregated circuits linking basal ganglia and cortex. , 1986, Annual review of neuroscience.

[96]  P. Rakić,et al.  Neuronal migration, with special reference to developing human brain: a review. , 1973, Brain research.