Molecular alterations in the medial temporal lobe in schizophrenia

SCHRES-08344; No of Pages 15 Schizophrenia Research xxx (xxxx) xxx

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Molecular alterations in the medial temporal lobe in schizophrenia Anastasia M. Bobilev ⁎,1, Jessica M. Perez 1, Carol A. Tamminga Department of Psychiatry, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX, United States of America

a r t i c l e

i n f o

Article history: Received 26 March 2019 Received in revised form 29 May 2019 Accepted 1 June 2019 Available online xxxx Keywords: Hippocampus Schizophrenia Amygdala Superior temporal gyrus Sequencing Psychosis

a b s t r a c t The medial temporal lobe (MTL) and its individual structures have been extensively implicated in schizophrenia pathophysiology, with considerable efforts aimed at identifying structural and functional differences in this brain region. The major structures of the MTL for which prominent differences have been revealed include the hippocampus, the amygdala and the superior temporal gyrus (STG). The different functions of each of these regions have been comprehensively characterized, and likely contribute differently to schizophrenia. While neuroimaging studies provide an essential framework for understanding the role of these MTL structures in various aspects of the disease, ongoing efforts have sought to employ molecular measurements in order to elucidate the biology underlying these macroscopic differences. This review provides a summary of the molecular findings in three major MTL structures, and discusses convergent findings in cellular architecture and inter-and intra-cellular networks. The findings of this effort have uncovered cell-type, network and gene-level specificity largely unique to each brain region, indicating distinct molecular origins of disease etiology. Future studies should test the functional implications of these molecular changes at the circuit level, and leverage new advances in sequencing technology to further refine our understanding of the differential contribution of MTL structures to schizophrenia. © 2019 Elsevier B.V. All rights reserved.

1. Introduction to the medical temporal lobe in schizophrenia The medial temporal lobe (MTL) has repeatedly been implicated in the pathophysiology of schizophrenia, using techniques like brain imaging (Altshuler et al., 2000), cognition (Medoff et al., 2001) and postmortem tissue studies (Vawter et al., 2002). While early studies with limited methodologies only supported speculations (J. Stevens, 1982), current research has been able to strengthen the association between MTL/hippocampal dysfunction and schizophrenia, especially when related to the signature function of hippocampus, declarative memory. With respect to underlying causes of this dysfunction, advances in sequencing technologies have and continue to refine our understanding of the molecular underpinnings of schizophrenia pathophysiology. Studies of the involvement of specific brain regions in the mechanisms of schizophrenia are typically supported by human imaging or postmortem tissue outcomes. Taken as a whole, these studies have, nonetheless, failed to definitively inform pathophysiology; it is important up front to ask the question why because these considerations will support our interpretation of available data. First, the DSM

⁎ Corresponding author at: Harry Hines Blvd., Mail Code #9127, Dallas, TX 75390, United States of America. E-mail addresses: [email protected] (A.M. Bobilev), [email protected] (J.M. Perez), [email protected] (C.A. Tamminga). 1 Authors contributed equally to this publication.

diagnostic constructs of our conventional diagnoses could be introducing disease heterogeneity into target groups because they may not be biologically cohesive. Alternative constructs are under study but not yet demonstrated to be an advance (Clementz et al., 2015). Additionally, we have to consider the possibility of a latent structure developing across the disease course, with markers changing over course of illness. Of course, an effect of medication could affect these measurements, as well as course of illness. Tissue quality in postmortem tissue is another confound (Stan et al., 2006). Still, a review of all findings in the literature, as done here, can uncover especially affected brain regions or point to affected molecular or cellular systems, that will inform future study. While the hippocampus has been extensively studied in schizophrenia pathophysiology and offers promising evidence of psychosis etiology, other structures of the MTL are rapidly gaining attention in the study of schizophrenia and related disorders. The amygdala and superior temporal gyrus have been implicated in the disease, exhibiting molecular alterations with pronounced specificity and therefore indicating a distinct role in schizophrenia. We will discuss findings from all these structures throughout this review. To obtain the literature for this review, PubMed was searched for literature that contained a combination of the following keywords: medial temporal lobe (MTL), hippocampus, superior temporal gyrus (STG), or amygdala; schizophrenia or psychosis; neurotransmitter, postmortem tissue, RNA, molecular, epigenetic. Results were evaluated for findings true to these categories and quality of postmortem tissue was considered. Reviews with any of the above

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Please cite this article as: A.M. Bobilev, J.M. Perez and C.A. Tamminga, Molecular alterations in the medial temporal lobe in schizophrenia, Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.06.001

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information were considered as well. Article references were screened for studies that may not have been identified in the original search and were included.

volume in CA1 of individuals with schizophrenia (Schobel et al., 2009). In summary, hippocampal hyperactivity has become nearly a biomarker of schizophrenia in its early stages, leaving open the question of its mechanism.

2. Hippocampus 2.1. Overview of the hippocampus in schizophrenia The neuroanatomy of the hippocampus is uniquely organized compared to other brain regions. The principal cell projections between the hippocampal subfields – dentate gyrus (DG), CA3, and CA1 – form the distinctive unidirectional excitatory pathway known as the trisynaptic circuit. Together, the hippocampal subfields govern the fundamental role of the hippocampus in learning and memory, in spatial navigation (Moser et al., 2015), emotional behavior (Beadle et al., 2013), and in regulation of hypothalamic functioning (Zhou et al., 2014). There is a comprehensive link between anatomical, molecular and functional hippocampal alterations and schizophrenia. Anatomically, a majority of studies analyzing hippocampal volume in schizophrenia find a decrease in volume relative to healthy controls (Altshuler et al., 2000; Arnold et al., 2015; Goldman et al., 2008; Ho et al., 2017; Nelson et al., 1998; Wright et al., 2000) and less studies report no change (Pearlson et al., 1997; Swayze et al., 1992). Postmortem studies of hippocampal cell number as a possible source of reduced volume in schizophrenia have shown varying outcomes. Several studies have shown no change in total cell density (Arnold, 2000; Dwork, 1997; Harrison, 1999) or neuron density (Heckers et al., 1991; Konradi et al., 2011; Schmitt et al., 2009; Walker et al., 2002). However, cell-type specific as well as subfield-specific changes have been reported. Neuron cell count was decreased in the anterior hippocampus in one study (Falkai et al., 2016). The DG has shown increases in granule cell number with basal dendrites (Lauer et al., 2003). Investigations of the DG hilus showed reductions in oligodendrocytes (Schmitt et al., 2009; Falkai et al., 2016). Additionally, a decline in parvalbumincontaining interneurons in multiple regions of the hippocampus has been the most replicated finding (Zhang and Reynolds, 2002; Knable et al., 2004; Torrey et al., 2005; Konradi et al., 2011; Schubert et al., 2015). Overall, cellular studies have not generated a consensus around hippocampal cell number changes, while most MR studies show reduced hippocampal volume in this disorder. 2.2. White matter changes Abnormalities in oligodendrocytes, myelin sheath-forming cells, have been implicated by several studies in different regions of the hippocampus in schizophrenia. Gene expression studies have shown an enrichment of myelin-related genes differentially expressed between individuals with schizophrenia and matched healthy controls (Aston et al., 2004; Dracheva et al., 2006; Haroutunian et al., 2007; Katsel et al., 2005). Along these lines, the putative risk gene for schizophrenia, DISC1, is associated with oligodendrocyte and myelin function (Drerup et al., 2009; Tan et al., 2011; Wood et al., 2009). Dysfunction in oligodendrocytes and myelin could impair the electrical properties of axons, leading to defective information transfer. This phenomenon has been extensively demonstrated by functional imaging studies. Several show increased regional cerebral blood flow (rCBF) in the hippocampus (Malaspina et al., 2004; Medoff et al., 2001; Scheef et al., 2010), which has been associated with positive symptomatology in schizophrenia (Bogerts, 1997). Furthermore, rCBF was significantly higher in the hippocampus of unmedicated schizophrenia compared to patients on antipsychotics. This suggests that antipsychotic medication could “normalize” rCBF, indicating that elevated hippocampal rCBF is a marker of schizophrenia psychosis (Medoff et al., 2001). Additional studies using high-resonance functional imaging have shown increased intrinsic activity in the hippocampus of those with schizophrenia (Tregellas et al., 2014) and even subfield-specific increases in cerebral blood

2.3. Abnormalities associated with neurotransmitter systems in the hippocampus Since the discovery that phencyclidine (PCP), an N-methyl-Daspartate (NMDA) receptor antagonist, induces schizophrenia-like psychosis in humans (Luby et al., 1959), the glutamatergic neurotransmitter system has been central to understanding the abnormal connectivity in schizophrenia. Glutamate signaling activates ionotropic and metabotropic glutamate receptors (mGluRs). The ionotropic glutamate receptors are divided into three groups: N-methyl-D-aspartate (NMDA), αamino-3-hydroxyl-5-methyl-4-isoxazolepropionic acid (AMPA), and kainate (KA) receptors. mGluRs are categorized into three groups as well. Conversely, glutamate signaling is halted by glutamate transporters via glutamate uptake from the extracellular space. Studies demonstrating lower MK-801 binding in the hippocampus of individuals with schizophrenia (Beneyto et al., 2007) indicate a change in quantity and activity levels of NMDA receptors, which could underlie the anomalies in hippocampal function. The most consistent abnormality in the hippocampal glutamatergic system is a reduction in the obligatory subunit of the NMDA receptor, GluN1, in the DG (Gao et al., 2000; Law and Deakin, 2001; Vrajová et al., 2010). Changes in other NMDA receptor subunits have been less studied. One study has shown an increase in GluN2b in CA3 and CA2 (Gao et al., 2000), while another study showed a reduction in DG (Geddes et al., 2014). The subfield and subunitspecific nature of these alterations can explain why some studies found no changes in total NMDA receptor subunits when the whole hippocampus was examined (Beneyto et al., 2007; Vrajová et al., 2010). Therefore, future studies will be examined for informative subfield layer and regional outcomes. With regard to the AMPA receptors, subunits GluA1 and GluA2 have been the most studied. GluA1 has been shown to be reduced in the DG, CA4 (Eastwood et al., 1995) and CA3 (Eastwood et al., 1995; Harrison et al., 1991) with one study reporting no change (Breese et al., 1995), while GluA2 has exhibited decreases in multiple subfields of the hippocampus (Breese et al., 1995; Eastwood et al., 1995, 1997). Changes in AMPA receptor binding have been mixed, with one study reporting no change in binding (Beneyto et al., 2007) and another showing a decrease specifically in the CA2 subfield (Gao et al., 2000). The kainate receptors have been less studied, but reductions in the kainate receptor subunits 5, 6, and 7 have been shown in the hippocampus (Benes et al., 2001; Porter et al., 1997). These results do not delineate any specific change as liable for glutamate receptor dysfunction in schizophrenia, but further specific study by subfield, by region, and by cell specificity will be necessary. mGluRs affect a variety of cellular functions, ranging from synaptic transmission to homeostasis and synaptic plasticity by regulating an array of ion channels as well as second messenger signaling pathways. mGluR modulation of neurotransmitter release occurs at excitatory (glutamatergic), inhibitory (GABAergic), and neuromodulatory (e.g. monoamines) synapses. The diverse method of action of mGluRs provides further complexity to the mechanisms that may underlie glutamatergic signaling dysfunction in schizophrenia. Specific mGluR subunits have been associated to schizophrenia (Moghaddam, 2004). mGluR1 was significantly reduced in CA1 in schizophrenia in one study (Matosin et al., 2016). mGluR3 has been reported as unchanged in anterior hippocampus in another study (Ghose et al., 2009). mGluR5 has diverging results with either increases in CA1 (Matosin et al., 2015) or no changes in protein expression according to genotype in hippocampus (Matosin et al., 2018). No clear trends have emerged regarding mGluR expression levels in hippocampus. However, a group II mGluR agonist, LY 404039, was tested in a phase III clinical trial for

Please cite this article as: A.M. Bobilev, J.M. Perez and C.A. Tamminga, Molecular alterations in the medial temporal lobe in schizophrenia, Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.06.001

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the treatment of individuals with schizophrenia (Adams et al., 2014), illustrating the promise that mGluRs play a critical role in schizophrenia pathophysiology. Vesicular glutamate transporters (vGluTs) package glutamate from the extracellular space into synaptic vesicles (Fremeau et al., 2004b), affecting glutamate signaling. vGluT1, as opposed to vGluT2, is preferentially expressed in cortical and hippocampal neurons (Fremeau et al., 2001, 2004a, 2004b). One study found a decrease in vGluT1 in hippocampus (Eastwood and Harrison, 2005), but others have found no change (Shan et al., 2013; Uezato et al., 2009). When looking in specific hippocampal subfields, however, vGluT1 was increased in the DG (Talbot et al., 2004), illustrating the need for subfield-specific experimental designs in order to judiciously analyze the molecular alterations in glutamate transporters in schizophrenia. The major excitatory cell type in the hippocampus is the glutamatergic pyramidal neuron while a far smaller portion albeit in a critical position to affect function is the GABAergic interneuron. These inhibitory interneurons direct hippocampal function and are vital for normal cognition and behavior (Somogyi and Klausberger, 2005). As previously mentioned, significant reductions in schizophrenia in one of the largest classes of hippocampal interneurons, parvalbumin-containing interneurons, have been reported. The GABA neurotransmitter system has been extensively examined in schizophrenia. GABA is synthesized from glutamate by the enzyme, glutamic acid decarboxylase (GAD). GAD is encoded by two genes, GAD1 and GAD2, and is expressed in two isoforms, GAD65 and GAD67. In addition, there are two groups of GABA receptors. The GABAA receptors are ionotropic while the GABAB receptors are metabotropic. The GABAA receptor has been reported to be increased in multiple hippocampal regions (Benes et al., 1996). On the other hand, the GABAB receptor has been shown to be decreased (Mizukami et al., 2000). The GAD1 gene was reported as unchanged in one study (Straub et al., 2007). The GAD65 and GAD67 isoforms have shown diverging results. Both isoforms have either been reduced in several regions of the hippocampus like DG, CA4, and CA1 (Heckers et al., 2002; Ray et al., 2011; Steiner et al., 2016) or unchanged (Li et al., 2015; Stan et al., 2015; Todtenkopf and Benes, 1998). These outcomes are conflicting, leaving the question of the GABAergic system's contribution to hippocampal pathology in schizophrenia unanswered.

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schizophrenia postmortem tissue (Blennow et al., 2000; Davidsson et al., 1999). The implications of these synaptic abnormalities in hippocampus are still ambiguous and precise localization has not been done. 2.5. Evidence for alterations in neurogenesis In DG of the hippocampus, adult neurogenesis refers to adult neural stem cells which generate new and functional dentate granule cells, as well as, incorporate these new neurons into the existing hippocampal circuitry. Measuring neurogenesis in the hippocampus typically involves staining with Ki-67, a marker of cell proliferation during adult neurogenesis (Gerdes et al., 1984; Kee et al., 2002), or proliferating cell nuclear antigen (PCNA), a marker of proliferating neural stem cells (Celis and Celis, 1985; Limke et al., 2003). With regard to Ki-67, two studies have shown reductions in adult neurogenesis in schizophrenia compared to healthy controls (Allen et al., 2016; Reif et al., 2006). Analysis of PCNA in schizophrenia showed no change in neurogenesis (Walton et al., 2012). Analyses of molecular alterations indirectly associated with neurogenesis have also influenced the hypothesis that neurogenesis may be dysfunctional in schizophrenia. AKT, which has been shown to be critical for cell proliferation and synaptic development (Coffer et al., 1998; Manning and Cantley, 2007), was reported as downregulated in hippocampus in schizophrenia (Emamian et al., 2004). In a separate study while no difference in total AKT levels was found, there was a significant reduction in AKT phosphorylation in DG, suggesting deficient AKT activation in schizophrenia (Balu et al., 2012). In addition, AKT mediates cell signaling for several schizophrenia-associated risk genes like neuregulin, dysbindin, and DISC1 (Harrison and Weinberger, 2005; Li et al., 2003; Numakawa et al., 2004), which have all been shown to be either affected in hippocampus in schizophrenia (Marballi et al., 2012; Talbot et al., 2004; Weickert et al., 2008) or to affect hippocampal function in individuals with schizophrenia (Callicott et al., 2005). Together, these results indicate an association between schizophrenia and hippocampal neurogenesis impairments. However, caution should be exercised in interpreting these changes because neurogenesis levels are sensitive to psychotropic medications. 2.6. Immune system alterations in the hippocampus

2.4. Synaptic molecular alterations in the hippocampus in SZ The neurotransmitter system alterations in the MTL in schizophrenia may be affecting signaling transmission across pre- and post- synapses. Dysregulation at any step of neurotransmission would have critical and complex effects on behavioral symptomatology. Thus, many studies have queried postmortem hippocampal tissue for alterations at the synapse. Effectively, electron microscopy studies have shown reductions in mossy fiber synapses onto CA3 pyramidal neurons in schizophrenia postmortem tissue (Kolomeets et al., 2005, 2007). In addition, Golgi staining of CA3 pyramidal neurons has shown an increase in spine density on their apical dendrites (Li et al., 2015). There are a number of markers whose alterations would indicate synaptic pathology in schizophrenia: synaptophysin, Ras-related protein (Rab3), synapsin, synaptosomal-associated protein 25 (SNAP-25), postsynaptic density protein 95 (PSD-95). Synaptophysin has been shown as decreased in the hippocampus of individuals with schizophrenia (Chambers et al., 2005; Davidsson et al., 1999; Eastwood and Harrison, 1995; Matosin et al., 2016; Osimo et al., 2018) as well as unchanged (Browning et al., 1993; Talbot et al., 2004; Young et al., 1998). SNAP-25 was reduced in three studies (Fatemi et al., 2001; Thompson et al., 2003; Young et al., 1998). PSD-95 has been less studied with one study showing an increase in PSD-95 in the CA3 (Li et al., 2015) one showing a decrease in DG (Toro and Deakin, 2005), and another showing no change (Ohnuma et al., 2000). Synapsin was decreased in three studies (Browning et al., 1993; Nowakowski et al., 2002; Vawter et al., 2002) and Rab3 was reduced in two studies in the hippocampus from

Microglial-mediated neuroinflammation is a proposed mechanism underlying schizophrenia pathophysiology. Microglia are the primary innate immune cells of the CNS (Monji et al., 2009; Munn, 2000). During normal physiological conditions, microglia serve to scan the brain for foreign invaders or debris (Nimmerjahn et al., 2005). In response to specific pathological threats, which are accompanied by inflammation, microglia undergo ‘microglia activation’ (Perry et al., 1993), transforming their morphology and function. Microglia activation profiles can range from responding to inflammation inducing the major histocompatibility complex class II (MHCII), TNF-α, IL-6, IL-1β, ROS and glutamate to resolving inflammation by releasing IL-4, IL-13, IL-25, IL-1ra, insulin-like growth factor 1 (IGF1), BDNF and COX1 (Réus et al., 2015). Microglial activation serves both pro-inflammatory and neuroprotective functions. Postmortem studies in the hippocampus of individuals with schizophrenia have focused on the number or density of microglia by labeling for MHCII molecules (e.g. HLA-DR, HLA-DPA1, HLA-DPB1), as opposed to microglia activation. These studies have provided disparate results. One study showed an increase in microglia in a subgroup of individuals with paranoid schizophrenia in the hippocampus (Busse et al., 2012). A next-generation sequencing study showed that immune/inflammation response was significantly over-represented by genes upregulated in the hippocampus in individuals with schizophrenia compared to healthy controls (Hwang et al., 2013). On the other hand, microglial markers have also been reduced in a few studies either throughout the hippocampus (Morgan et al., 2016) or in specific subfields like CA1 or CA3 (Benes et al., 2007; Gos et al., 2014). Several studies have

Please cite this article as: A.M. Bobilev, J.M. Perez and C.A. Tamminga, Molecular alterations in the medial temporal lobe in schizophrenia, Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.06.001

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found no change in either number of microglia in hippocampus in individuals with schizophrenia (Steiner et al., 2006) or proinflammatory gene markers (Togo et al., 2000; Yokota et al., 2004) and cell types which exert immunological function (Arnold et al., 1996; Schmitt et al., 2009). In a meta-analysis of postmortem brain studies examining factors related to the immune system in individuals with schizophrenia and matched healthy controls, there was no significant change in overall expression of proinflammatory genes in the hippocampus (van Kesteren et al., 2017). Taken together, more research into the abnormalities of the immune system in the hippocampus in individuals with schizophrenia is needed. Studies are necessary regarding markers of microglial activation not just microglial cell count. Because microglia are now being shown to not only be involved in inflammatory responses, but also neuroplasticity, neurogenesis, synaptic pruning and formation (Hagemeyer et al., 2017; Moran and Graeber, 2004; Schafer et al., 2012; Shigemoto-Mogami et al., 2014; Tremblay et al., 2010; Wakselman et al., 2008; Zhan et al., 2014), investigations into the effects of microglial activation on schizophrenia pathophysiology will be critical. In fact, microglial activation has been shown to reduce reelin expression levels in the hippocampus (Ratnayake et al., 2012), a molecular alteration that has been repeatedly shown in studies of schizophrenia (Eastwood and Harrison, 2006; Torrey et al., 2005). There is common agreement that immune disruption could underlie a subgroup of individuals with schizophrenia. The anti-NMDAR antibody group is a prominent example. However, there is no anticipation that every case of schizophrenia will have an immune etiology.

fear responses, and memory encoding associated with all aforementioned functions. As such, it is tremendously important in the study of MTL circuitry in psychosis and mood disorders. Extensive research demonstrates abnormalities in amygdala activity in schizophrenia relative to healthy comparison subjects in various behavioral tasks associated with fear, emotion, facial expression discrimination, and amygdalaassociated memory (Phelps, 2006). Previous structural MRI studies measuring amygdala volume have reported conflicting results, some reporting increases in volume, decreases in volume, lateralized decreases in the left hemisphere, or no change (Birur et al., 2017; Highley et al., 1999). Postmortem studies of amygdala volume and neuron number also show inconsistent findings, with one identifying decreases of both measures in the amygdala (Berretta et al., 2007; Kreczmanski et al., 2007) and no differences found in another (Chance et al., 2002). However, this may be because reductions in amygdala volume could be exclusively characteristic of early-course schizophrenia, and most studies have not adequately accounted for illness duration (Rich et al., 2016), or adjusted treatment effects (Berretta et al., 2007; Mier et al., 2018; Penadés et al., 2017; Radua et al., 2012). With variable findings, it is likely that the gross anatomical size or total cell density is not driving the functional abnormalities of the amygdala in schizophrenia. Examination of discrete cellular and molecular level changes could shed light on the underpinnings of functional involvement of this region in schizophrenia.

3.2. Abnormalities in discrete cellular populations in the amygdala 2.7. Changes in additional molecular networks Exploratory analyses performed by querying the global transcriptome of the hippocampal or hippocampal subfield tissue of schizophrenia cases and matched comparisons suggest several leads on disrupted gene networks for further investigation. In addition to the changes discussed in the context of specific networks above, pathways involved in cytoskeletal function, metabolic function, microRNA signaling, apoptosis, mitochondria and oxidative stress, endocannabinoid system, nicotinic, adrenergic, glucocorticoid, estrogen, and muscarinic receptors were also implicated in hippocampal dysfunction in the disease (Altar et al., 2005; Crook et al., 2000; Föcking et al., 2011; Haroutunian et al., 2007; Katsel et al., 2005; Klimek et al., 1999; Kohen et al., 2014; Merenlender-Wagner et al., 2015; Muguruza et al., 2013; Perlman et al., 2005; Thomsen et al., 2011; Webster et al., 2002). In addition to microarray and RNA sequencing studies which have identified vast differences in the hippocampal transcriptome of schizophrenia cases, one study extended our understanding of functional genomics in this area by probing the epigenomic profile of two hippocampal subfields. The control of gene expression is causally associated with methylation patterns in the genome, and a methylation bead array identified 53 differentially methylated positions between schizophrenia and healthy comparison cases within the 108 risk loci previously identified (Ruzicka et al., 2017; Schizophrenia Working Group of the Psychiatric Genomics, 2014). Future studies evaluating complementary aspects of functional genomics, especially with single-cell resolution, will provide a more complete picture of the cellular abnormalities in the hippocampus in schizophrenia. A complete list of all molecular findings discussed can be found in Table 1A. 3. Amygdala 3.1. Overview of the amygdala in schizophrenia The amygdala is a central structure in the limbic system that has long been functionally implicated in schizophrenia. It has extensive connectivity with the hippocampus and prefrontal cortex (PFC), and is critical for emotional processing. In addition, it regulates normal stress and

Although the total number of cells in the amygdala may not be altered in schizophrenia, several studies have discovered abnormalities in the proportions of different cellular sub-types in this region. Astrocyte number (GFAP+ cell counts and Nissl staining) remains normal in the amygdala tissue of schizophrenia cases (Pakkenberg, 1990; Trépanier et al., 2016), while studies of glial cell density have shown either no change or dramatic increases (CSPG+ glial cells specifically showing this increase) (Pantazopoulos et al., 2010). The same study found a marked decrease in perineuronal nets in the laternal nucleus of the amygdala, implicating extracellular matrix-glial interactions as a possible mechanism of schizophrenia etiology (Pantazopoulos et al., 2010). One study also identified the presence of increased fibrous gliosis in the amygdala and other structures in schizophrenia (J.R. Stevens, 1982). Several studies have specifically looked at the proportions of different sub-classes of neurons, suggesting that the functional cytoarchitecture of neurons specifically may be partly responsible for circuit-level functional abnormalities. Namely, discrete interneuron populations may be abnormal in the amygdala in schizophrenia. While there is no change in parvalbumin positive (PV+) interneurons (Pantazopoulos et al., 2010), there were fewer cholecystokinin positive (CCK+) interneurons and an increased number of vasoactive intestinal polypeptide positive (VIP+) interneurons in the amygdala of schizophrenia cases (Roberts et al., 1983). Somatostatin positive (SST+) interneurons were found to have no change in one study (Roberts et al., 1983), but a significant decrease in a recent investigation (Pantazopoulos et al., 2017). Further, studies have observed no change in neurotensin positive (dopaminergic neurons) or substance P positive cells, as well as no change in AMPA receptor density (glutamatergic neurons) or serotonin 5-HT3 binding sites (Abi-Dargham et al., 1993; Noga and Wang, 2002; Roberts et al., 1983; Trépanier et al., 2016). Collectively, this evidence not only indicates an interneuron-specific disruption in amygdala circuitry in schizophrenia, but that these disruptions exist in a discrete subset of GABAergic interneurons altering the inhibitory population in a subtle yet functionally significant way. These changes are extraordinarily distinct, specific to the amygdala in the MTL, and likely disrupt longer-range inhibitory signaling in a specific and testable manner.

Please cite this article as: A.M. Bobilev, J.M. Perez and C.A. Tamminga, Molecular alterations in the medial temporal lobe in schizophrenia, Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.06.001

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Table 1A Summary of molecular changes in the hippocampus. Reference

Method used

Sample size (N)

SZ Δ HC

(Beneyto et al., 2007)

ISH, autoradiography

15SZ, 15HC

(Gao et al., 2000) (Law and Deakin, 2001) (Vrajová et al., 2010)

ISH, autoradiography ISH

35SZ; 31HC 15SZ;15 HC

↓MK-801 binding, ↔GluN1, GluN2A, GluN2B, GluN2C, GluN2D, GluA1, GluA2, GluA3, GluA4, GluA5, GluA6, GluA7, KA1, KA2 ↑GluN2B in CA3 and CA2, ↓GluN1 DG, ↔ GluN2a ↓ GluN1 in DG

qPCR, Western Blot

13SZ; 8HC

(Geddes et al., 2014) (Eastwood et al., 1995) (Habl et al., 2009) (Eastwood et al., 1997) (Harrison et al., 1991) (Breese et al., 1995)

Immunoblot, in situ ISH ISH qPCR ISH Western blot

20SZ; 20HC 9SZ; 14HC 10SZ; 13 HC 11SZ; 11HC 6SZ; 8HC 14SZ; 7HC

(Porter et al., 1997) (Benes et al., 2001) (Matosin et al., 2015) (Matosin et al., 2018) (Ghose et al., 2009) (Dean et al., 1997) (Pinacho et al., 2014) (Eastwood and Harrison, 2005) (Shan et al., 2013) (Uezato et al., 2009) (Steffek et al., 2006) (Sawada et al., 2005) (Huffaker et al., 2009) (Tian et al., 2007) (Benes et al., 1996) (Todtenkopf and Benes, 1998) (Mizukami et al., 2000) (Ruzicka et al., 2015)

ISH Immunocytochemistry Immunoblot Western blot ISH Autoradiography Immunoblot, qPCR ISH, Northern blot

11SZ; 13HC 15SZ; 15 HC 20SZ; 20HC 19SZ; 20HC 20SZ; 20 HC 20SZ male; 20HC male 14SZ; 11HC 13SZ;12HC

↑ GluN1 isoform 1 and 3, ↓ GluN1 isoform 4 and 2, total GluN1 in SZ males, ↔ total GluN1 isoforms in total SZ ↓ GluN2B DG ↓GLUR1 & GLUR2 DG, CA4, CA3, subiculum ↑ DAAO in CA4 ↓GLUR2 ↓GLUR1 CA3 ↓GLUR2, GLUR3 ↔GLUR1, GLUR5, NCAM, tau ↓ GLUR6 & KA2 ↓Kainate R 5,6,7 in CA3, CA2, CA1 pyramidal cells ↑mGluR5, norbin, and tamalin protein CA1 ↔mGluR5 protein CA1 by genotype ↓GCPII in anterior hippocampal CA1, ↔ mGluR3 ↓ adenylate cyclase density DG ↑SP4 mRNA and protein, ↑ SP1 mRNA ↓vGlut1

Western blot ISH Western blot Immunocytochemistry qPCR IHC Autoradiography Immunocytochemistry

23SZ; 27 HC 13SZ; 13HC 23 SZ; 27 HC 12SZ; 12HC 29SZ; 59 HC 15SZ; 15 HC 8SZ; 15 HC 13SZ; 12 HC

↓EAAT2, ↔ vGlut1, 2, EAAT3 ↔ vGlut1, 2, 3 ↑ serine racemase ↓Complexin 1 & Complexin 2 ↑ KCNH2–3.1 ↓ GAP-43 in DG hilar region ↑ GABAA receptor binding DG, CA4, CA3, subiculum ↔ GAD65

IHC

5SZ; 3 HC

↓GABAb

DMRegion validation Methylation ISH qPCR ISH Western blot IHC IHC

8SZ; 8HC

146 DMPs GAD1 regulatory network genes CA3/2, CA1

15 SZ; 15 HC 32SZ; 76 HC 15SZ; 15HC 11SZ; 11HC 16SZ; 16HC 11SZ; 17 HC

(Konradi et al., 2011) (Zhang and Reynolds, 2002) (Knable et al., 2004) (Torrey et al., 2005) (Schubert et al., 2015) (Fachim et al., 2018) (Sinkus et al., 2013)

IHC and qPCR IHC

13SZ; 20 HC 15SZ; 15 HC

↔ GAD65, GAD67 ↔ GAD1 mRNA ↓BDNF CA4, GAD67 DG & CA4, TRKB-TK+ CA4 SZ ↓GluN1 protein DG, ↔ in GAD67 ↓GAD-ir neuropil density CA1 ↓somatostatin+ and PV+ interneurons Entorhinal Ctx, ↔ calbindin + interneurons ↓somatostatin+ and PV+ interneurons ↓ PV+ interneurons, ↔ Calretinin+ interneurons

Meta analysis Meta analysis 2-D DIGE proteomics Bisulfite pyrosequencing qPCR & ISH

(Hwang et al., 2013) (Busse et al., 2012)

mRNAseq, qPCR, IHC IHC

48 datasets; 15SZ; 15 HC 15SZ; 15 HC 20SZ; 20HC – 42SZ (14nonsmokers; 28smokers); 47HC (24nonsmokers;23smokers) 15SZ; 15 HC 17SZ;11HC

(Steiner et al., 2006) (Morgan et al., 2016) (Gos et al., 2014) (Benes et al., 2007)

IHC qPCR IHC LCM microarray

16SZ; 16 HC 15SZ; 49HC 13SZ; 12HC 7SZ; 7HC

(Arnold et al., 1996) (Roberts et al., 1986) (Webster et al., 2001) (Steiner et al., 2008) (Steffek et al., 2008) (Casanova et al., 1990) (Yokota et al., 2004) (Togo et al., 2000) (van Kesteren et al., 2017) (Osimo et al., 2018) (Young et al., 1998)

IHC IHC IHC IHC Western blot Holzer's technique IHC IHC Meta analysis

7SZ; 14SZ + dementia; 12HC 5SZ; 7HC 15SZ; 15 HC 16SZ; 10 HC 23SZ; 27 HC 6SZ; 7 HC 17SZ; 22 HC 4 SZ; 2HC 41 studies

↑123 genes; ↓ 21 genes ↑CD3+ & CD20+ lymphocytes, HLA-DR+ microglia in patients with paranoid SZ ↔ in HLA-DR microglia ↓ HLA-DPA1, CD74, HLA-DRB1 ↓ QUIN-immunoreactive microglial cells CA1 ↑ GRIK2, GRIK3, TGFB2, TGFBR1, IL1B, DAXX, HDAC1, CCND2 – all CA2/3 ↓ GAD67, GAD65, GRIK1, TLE1, FOXG1B, LHX2 – all CA2/3, ↓GAD67 CA1 ↑ GFAP+ astrocyte # SZ + dementia group ↔ GFAP ↔ phosphorylated GFAP ↔ microglial HLA-DR ↔ GFAP, glutamine synthetase ↔ fibrillary astrocytes ↔ in COX-2 ↑ CD40 ↔proinflammatory genes

Meta analysis Immunocytochemistry; ELISA; Western blot Single-cell microarray,

8 studies 13SZ; 13 HC

↓ synaptophysin ↓SNAP-25 DG granule cell layer, ↔synaptophysin

8 SZ; 9 HC (24 neurons/condition)

↑ 2574 genes entorhinal ctx, ↓1565 genes entorhinal ctx

(Heckers et al., 2002) (Straub et al., 2007) (Ray et al., 2011) (Stan et al., 2015) (Steiner et al., 2016) (Wang et al., 2011)

(Hemby et al., 2002)

↓ PV in CA2 ↓PV+ interneurons DG, CA4, CA2, PV+ cell density CA2, Reelin protein CA4 ↓parvalbumin, 58 proteins DE ↑PVALB methylation ↑ HLA-B only in SZ non-smokers

(continued on next page)

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Table 1A (continued) Method used

Sample size (N)

SZ Δ HC

Immunocytochemistry ISH Immunoautoradiography

5 SZ; 6 HC 15SZ; 15 HC

↔ PSD-95 ↓ PSD-95 DG

IHC

17SZ; 16HC

↓ synapsin 1, chromogranin B CA4 & CA3

Immunocytochemistry

14SZ; 14 HC

ISH IHC; Western blot

10SZ; 10HC 10SZ; 11HC

↓GAP43 hilus & inner molecular layer DG, synaptophysin inner & outer molecular layer DG ↓ spinophilin CA4, CA3, subiculum, entorhinal ctx, ↔ MAP2 ↓PSA-NCAM staining, ↔ overall expression of NCAM

Western blot Immunoautoradiography

7SZ; 7 HC 11SZ; 13 HC

↓ synapsin, ↔synaptophysin ↓ synaptophysin in CA4, CA3

Western blot

13SZ; 10 HC

↓ synaptophysin, rab3a

Western blot, IHC IHC Western blot

22SZ; 24 HC 15SZ; 15HC 7SZ; 8 HC

↓ rab3a ↓ SNAP-25 ↓ SNAP-25

Western blot Western blot Autoradiography

16SZ; 13 HC 20SZ; 20 HC 8SZ; 8 HC

↓ synapsin ↑ Homer1a CA1, ↓synaptophysin, mGluR1, PSD95, Homer1b/c CA1 ↓nAChR in DG & CA1

Microarray, qPCR, Western blot BTX-Autoradiography ELISA qPCR ISH Western Blot ISH, IHC ISH

18 SZ (7nonsmokers; 11smokers); 18HC (9nonsmokers; 9 smokers) 13SZ; 15 HC 11 SZ; 11 HC 19SZ; 19HC 10SZ; 10HC 32SZ; 32HCa 13SZ; 12 HC

↓CHRNA7 in SZ nonsmokers, ↔ CHRNA7 in SZ smokers ↔ in nAChR levels ↓BDNF, ↔ NT-3 ↓ BDNF I, BDNF IIc, BDNF VI ↓ dysbindin DG granule cells & CA3, ↔CA1 ↑vGluT1 DG, ↓presynaptic dysbindin-1 DG, ↔synaptophysin, synapsin 1 DG ↓ reelin+ cells DG molecular layer

ISH, immunoblot IHC IHC IHC IHC Western Blot IHC

54 SZ; 126HCa 15SZ; 15 HC 10SZ; 16 HC 15SZ; 15 HC 18SZ; 18HC 4SZ; 5 HC 10SZ;11 HC

↓ NUDEL, FEZ1, LIS1, ↔ DISC1, REELIN ↓proliferation of hippocampal neural stem cells ↓ Ki67 ↔ PCNA ↓Akt phosphorylated at serine 473 in DG ↓ AKT ↑ RAR-alpha protein DG, ↔ total cell density

Northern Blot, ISH qPCR & Western Blot Timm's staining

15SZ; 15 HC 24SZ; 21 HC 11SZ; 8 HC

↓estrogen receptor alpha DG ↓ CLDN11, CNP, MAG, SOX10, PMP22 ↓staining intensity of MF pathway

Stereology

10SZ; 10HC

Golgi staining Electron Microscopy

7SZ; 6HC 9SZ; 10 HC

Electron Microscopy

8SZ; 10 HC

↓ # of oligodendrocytes in CA4, CA4 volume, # neurons in anterior hippocampus ↑DG granule cells with basal dendrites ↓ dendritic spine size CA3 pyramidal neurons, synapses formed by mossy fiber terminals on CA3 pyr. Neurons ↔ in mean area of presynaptic MFT

Stereology Autoradiography

10 SZ; 10 HC 8SZ; 20 HC

(Marballi et al., 2012) (Merenlender-Wagner et al., 2015) (Wu et al., 2016)

Western blot qPCR

6SZ; 5 HC 12SZ; 12HC

IHC, TUNEL assay, qPCR

9SZ (4 ON, 5OFF); 9HC

(Hamazaki et al., 2015) (Dresner et al., 2011) (Nesvaderani et al., 2009) (Che et al., 2010) (Mamdani et al., 2014) (Konradi et al., 2004) (Altar et al., 2005) (Muguruza et al., 2013) (Scarr et al., 2007) (Crook et al., 2000) (Katsel et al., 2005) (Haroutunian et al., 2007) (Föcking et al., 2011)

Lipid Analysis qPCR 2D-DGE & MALDI-TOF-MS

15SZ; 15 HC 14SZ; 14 HC 9SZ PH; 9HC PH; 7SZ AH; 7HC AH

IHC qPCR Microarray and qPCR LCM microarray Liquid chromatography

15SZ; 15 HC 10SZ; 10 HC 8SZ; 10 HC 22SZ; 24HCa 19SZ;19HC

↓ apoptosis rate in clozapine-treated SZ cases compared to antipsychotic naive patients ↓ docosatetraenoic acid entorhinal ctx, ↔ in DHA or AA entorhinal ctx ↔ ADNP and ADNP2 34 proteins changed in AH; 14 proteins changed in PH; Mitochondrial dysfunction and compromised oxidative stress response processes ↑ oxidative damage staining for cytoplasmic RNA DG, CA3, and CA1 ↔ mtDNA common deletion ↔mitochondrial mRNA expression levels ↓ in mitochondria and energy metabolism genes DG granule cells ↑ 2AG, ↓ AEA, DHEA

ISH with autoradiography Autoradiography Microarray Microarray

35SZ; 35 HCa 15 SZ; 18 HC 9-21SZ; 8-18 HCb 13SZ; 13HC

↓ M4 R, ↔ in M1R ↓ M1 and/or M4 receptors ↑ 5 genes, ↓ 45 genes 50 DE genes; ↓MAG, CNP, QKI, transferrin

2D-DIGE, ELISA, Western

20SZ; 20HC

108 proteins DE

Reference (Ohnuma et al., 2000) (Toro and Deakin, 2005) (Nowakowski et al., 2002) (Chambers et al., 2005) (Law et al., 2004) (Barbeau and Liang, 1995) (Browning et al., 1993) (Eastwood and Harrison, 1995) (Davidsson et al., 1999) (Blennow et al., 2000) (Fatemi et al., 2001) (Thompson et al., 2003) (Vawter et al., 2002) (Matosin et al., 2016) (Freedman et al., 1995) (Mexal et al., 2010) (Thomsen et al., 2011) (Durany et al., 2001) (Reinhart et al., 2015) (Weickert et al., 2008) (Talbot et al., 2004) (Eastwood and Harrison, 2006) (Lipska et al., 2006) (Reif et al., 2006) (Allen et al., 2016) (Walton et al., 2012) (Balu et al., 2012) (Emamian et al., 2004) (Rioux and Arnold, 2005) (Perlman et al., 2005) (Dracheva et al., 2006) (Goldsmith and Joyce, 1995) (Falkai et al., 2016) (Lauer et al., 2003) (Kolomeets et al., 2005) (Kolomeets et al., 2007) (Schmitt et al., 2009) (Klimek et al., 1999)

↓ Oligodendrocytes in CA4, ↔ in astrocyte or neuron number ↓beta-1 adrenoreceptors in CA4, CA3, CA1, DG, ↔ alpha or beta-2 adrenoreceptors, ↓neuregulin-1 ↓ beclin-1

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Table 1A (continued) Reference

Method used

(Ruzicka et al., 2017) (Chung et al., 2003)

blot Single-cell total RNAseq (LCM) DNA Methylation; LCM Microarray and q-PCR

(Webster et al., 2002)

ISH, Northern blot

(Kohen et al., 2014)

Sample size (N)

SZ Δ HC

17SZ; 29 HC

miR-182 target genes DE

8SZ; 8BP; 8HC 7 SZ; 8 HC

1 DMP SZ CA2/3 vs HC CA2/3 ↑Chondrex, Histamine releasing factor, HERC2, heat-shock 70 via Microarray ↑ Chondrex, ↓ HRF via qPCR ↓GR in DG, CA4, CA3, CA1

15SZ; 15 HC

The first column contains references that are linked to the bibliography. The second column indicates the type of experiment conducted to measure molecular gene products. The third column lists sample size (N) for schizophrenia (SZ) and healthy comparison, meaning those with confirmation of no known psychiatric conditions (HC). Of note: some studies included additional disease populations, which are not included in the sample sizes listed in this table. The final column details the change (Δ) between SZ and HC, with ↑ indicating an increase or upregulation in SZ compared to HC, ↓ indicating a decrease or downregulation in SZ compared to HC, and ↔ denoting no change between the two groups. Abbreviations: ISH = in situ hybridization, IHC = immunohistochemistry, PH = posterior hippocampus, AH = anterior hippocampus, LCM = laser-capture microdissection, 2D DGE = 2-D gel electrophoresis, 2D-DIGE = 2-D difference in gel electrophoresis, ELISA = enzyme-linked immunosorbent assay, MALDI-TOF-MS = matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometer, DMP = differentially methylated position, DE = differentially expressed, GR = glucocorticoid receptor, ctx = cortex. a Two tissue cohorts were used. b N for hippocampus was unreported.

3.3. Global molecular alterations in the amygdala In addition to abnormalities in interneuron populations and potentially glial cells in the amygdala in schizophrenia, several studies have observed gene expression. Agnostic measurements such as microarray and RNA-sequencing studies have consistently found abnormal gene expression, specifically downregulation, of genes and functional modules related to synaptic transmission (Chang et al., 2017; Tian et al., 2018; Weidenhofer et al., 2006). Furthermore, three specific genes associated with the cytomatrix active zone of synapses were significantly upregulated (Weidenhofer et al., 2006). Downregulated genes were also associated with behavior, while upregulated gene modules were functionally enriched for immune response and vasculature (Chang et al., 2017; Tian et al., 2018). Consistent with the functional gene network alterations and interneuron sub-population abnormalities, one study found reduced GABA uptake in the bilateral amygdala and hippocampus (Simpson et al., 1989). Another noteworthy finding that has emerged is the dysregulation of noncoding RNAs. In addition to long noncoding RNAs (lncRNAs) supporting amygdala abnormalities in synaptic transmission and the immune response, another study identified 250 individual lncRNAs that were abnormal in amygdala tissue from schizophrenia cases (Liu et al., 2018; Tian et al., 2018). MicroRNAs (miRNAs) were also identified, with 17 total miRNAs (10 novel) reaching statistical significance, although miRNA data analysis from traditional RNA-sequencing can be problematic (Liu et al., 2018). Single-cell genetic analyses in brain will soon become routin and yield much more precise outcomes. A full summary of the molecular alterations discussed can be found in Table 1B.

4. Superior temporal gyrus 4.1. Overview of the superior temporal gyrus in schizophrenia The superior temporal gyrus (STG) encompasses the auditory cortex and Wernicke's area, and has been associated with schizophrenia pathophysiology. Neuroimaging studies employing structural MRI have consistently reported reductions in STG volume in schizophrenia subjects, and this reduction is frequently correlated with clinical symptomatology (Sun et al., 2009). This region is critical not only for auditory information processing and integration (Howard et al., 2000), but also for language comprehension (Dronkers and Baldo, 2009; Friederici et al., 2003; Lüders et al., 1991). Interestingly, several volumetric studies of the STG demonstrate a sensitivity to detect correlations between occurrence or severity of auditory hallucinations and delusional/disordered thought and volume reductions in the bilateral STG and subfields, but primarily in the left STG (Barta et al., 1990; Sun et al., 2009). White matter reductions have been shown in connection with the STG in

schizophrenia subjects as well, specifically in the arcuate fasciculus and significantly associated with auditory verbal hallucinations (de Weijer et al., 2011). The effects of antipsychotic medications and duration of illness on these volumetric reductions remains a topic of debate and considerable interest (Radua et al., 2012; Takahashi et al., 2009, 2010). While the association between the STG and schizophrenia has been demonstrated at the macroscopic level, select studies have pursued the molecular underpinnings of this region's significance in schizophrenia pathophysiology. 4.2. Molecular alterations in the STG Although other cortical areas have been more extensively studied in schizophrenia postmortem tissues than the STG, there is evidence that it could be one of the most prominently affected regions with molecular alterations in functional gene products. In a study evaluating mRNA expression using microarray in 15 different brain regions, the STG of schizophrenia subjects demonstrated the maximal number of transcript changes (approximately 1200) from healthy tissue (Katsel et al., 2005). Microarray focused specifically on the STG found an overall trend of downregulation of gene expression in schizophrenia, and identified alterations in genes involved in neurotransmission, presynaptic function and development (Bowden et al., 2008), as well as notable overlap of altered transcripts identified in a previous study of peripheral blood samples from schizophrenia subjects (Bowden et al., 2006). Examination of microRNA expression in both the STG and DLPFC indicates a global increase in microRNA biogenesis in schizophrenia, which could be upstream of and related to the observed global reduction in mRNA transcriptome as a whole (Beveridge et al., 2010). Transcriptome analysis from another study revealed altered promotor usage and splicing in the STG in schizophrenia (Wu et al., 2012), collectively indicating that global abnormalities in this tissue may be primarily driven by regulatory and post-transcriptional elements of gene expression. Several studies have focused on specific candidate molecular targets for evaluation in schizophrenia postmortem STG samples. In pursuit of evaluating changes in neurotransmission, autoradiography has shown reduced muscarinic receptor density (Deng and Huang, 2005) and increased GABAA receptor density (Deng and Huang, 2006) in the schizophrenia STG. One study found significant reductions in RSG4 mRNA in 10/13 schizophrenia cases (Bowden et al., 2007). Interestingly, this transcript was the first ever to be associated with schizophrenia in the PFC through microarray-based discovery, and encodes a protein which activates GTPases and consequently shortens the duration of Gprotein mediated intercellular signaling (Mirnics et al., 2000). In the examination of microRNAs, expression of let7g and miR181b was increased in schizophrenia relative to healthy comparisons, although only the significant increase of miR181b was confirmed via rtPCR (Beveridge et al., 2008). The mature miRNA181b inhibits translation of

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Table 1B Summary of molecular changes in the amygdala. Method used

(Pantazopoulos et al., 2017) (Roberts et al., 1983) (Noga and Wang, 2002) (J.R. Stevens, 1982b) (Carletti et al., 2005) (Trépanier et al., 2016) (Pantazopoulos et al., 2010) (Perlman et al., 2004) (Tian et al., 2018)

Immunocytochemistry N = 12 SZ, 15 HC Radioimmuno N = 14 SZ, 12 HC Autoradiography N = 15 SZ, 15 HC Holzer's staining N = 18 SZ

↓ CCK+ in SZ with negative symptoms; ↑ VIP+ in SZ without negative symptoms; ↔ SRIF+ (somatostatin), NT, substance P ↔ AMPA receptor binding

ISH, autoradiography

↓ preprotachykinin A; ↔ 5-HT3 binding sites, NK1 receptors

(Chang et al., 2017) (Liu et al., 2018) (Weidenhofer et al., 2006) (Weidenhofer et al., 2009) (Simpson et al., 1989) (Pakkenberg, 1990) (Abi-Dargham et al., 1993)

Various (review) Histology, IHC, qPCR Autoradiography/ISH RNA sequencing RNA sequencing RNA sequencing qPCR qPCR, western blot, ELISA Autoradiography Nissl staining Autoradiography

Sample size (N)

SZ Δ HC

Reference

N = 14 SZ, 15 HC Various N = 21 SZ, 25 HC N = 15 SZ, 15 HC N = 22 SZ, 24 HC N = 22 SZ, 24 HC N = 13 SZ, 14 HC N = 11 SZ, 11 HC N = 13 SZ, 13 HC N = 22 SZ, 22 HC N = 12 SZ, 12 HC N = 7 SZ, 10 HC

↓ SST+ neurons; ↔ NPY+ neurons

Fibrous gliosis present

↔ substance P; ↔ GFAP+ astrocytes ↓ perineuronal nets; ↑ CSPG+ glial cells; ↔ GFAP+ astrocytes & PV+ neurons ↓ glucocorticoid receptor mRNA; ↔ estrogen receptor alpha 839 novel lncRNAs in amygdala; changes in functional modules involving lncs related to synaptic transmissions, ribosomes, and immune response ↑ 569 genes functionally enriched for immune response and blood vessel development; ↓192 genes down functionally enriched for synaptic transmission and behavior pathways 17 differentially expressed miRNAs (10 novel) ↑ piccolo, RIMS2 RIMS3 ↑ piccolo, RIMS2 RIMS3; ↔ bassoon, RIMS1, CASK, lin7a, Rab3a, PRA1 ↓ GABA uptake sites ↔ astrocytes ↔ 5-HT3 receptor binding sites

The first column contains references that are linked to the bibliography. The second column indicates the type of experiment conducted to measure molecular gene products. The third column lists sample size (N) for schizophrenia (SZ) and healthy comparison, meaning those with confirmation of no known psychiatric conditions (HC). Of note: some studies included additional disease populations, which are not included in the sample sizes listed in this table. The final column details the change (Δ) between SZ and HC, with ↑ indicating an increase or upregulation in SZ compared to HC, ↓ indicating a decrease or downregulation in SZ compared to HC, and ↔ denoting no change between the two groups. Abbreviations: ISH = in situ hybridization, IHC = immunohistochemistry, ELISA = enzyme-linked immunosorbent assay.

numerous transcripts, including VSNL1 which encodes a calcium sensor, and GRIA2 which encodes a subunit of an ionotropic AMPA receptor, both with reduced mRNA in the same tissue from this study. The increase in miR181b has the potential to effect change not only on glutamate signaling through suppression or alterations of AMPA receptors, but through a multitude of other downstream targets regulated by its expression. A summary of all the global and specific gene product changes in the STG is discussed is in Table 1C. 4.3. Prevalence of glutamate signaling-related findings A noteworthy number of findings from studies examining functional gene products in the STG point to a glutamate-related dysfunction in this region, which could be directly responsible for functional abnormalities at the local circuit level. Because the STG is highly connected with other brain regions that have been significantly implicated in schizophrenia including the hippocampus, amygdala and PFC, the effects of this glutamate dysfunction could be widespread. In addition to the discovery-based experiments detailed above, some studies have focused directly on glutamatergic signaling via the examination of AMPA receptors and their subunits. One study showed that mRNA of a specific isoform (without either spliced exon) of the NR1 subunit of the glutamatergic AMPA receptor is upregulated in the STG of schizophrenia subjects (Le Corre et al., 2000). Another group examined the NR1 subunit at the protein level, and found that NR1 demonstrates increased AMPA receptor density in schizophrenia relative to both healthy controls and persons with affective disorders (bipolar disorder and depression) (Nudmamud-Thanoi and Reynolds, 2004). However, it is possible that

some or all of these AMPA receptor effects are functional genomic responses to antipsychotic and/or antidepressant medications (Barygin et al., 2017; O'Connor et al., 2007), which should be further investigated both in future studies of postmortem tissue and with functional assessment using in vivo and in vitro models. 5. Functional modeling of molecular MTL findings An example of a contemporary neurobiologically-based formulation connecting schizophrenia and MTL is our model of hippocampal dysfunction (Li et al., 2015; Tamminga et al., 2010). We built this model with a number of foundational observations made in schizophrenia. (i) Abnormal associations and incorrect memories are routine in persons with schizophrenia and are memory-like. (ii) Declarative memory is severely affected in persons with the disorder. (iii) The hippocampus is hyperactive, as measured with brain imaging, consistently across laboratories and in CA1, in particular (Schobel et al., 2009). After reporting hyperactivity in whole hippocampus (Medoff et al., 2001), we focused on examining the molecular basis of the hyperactivity. For this, we used human schizophrenia hippocampal tissue dissected by subfield (DG, CA3 CA1), and analyzed inhibitory and excitatory synaptic markers in schizophrenia versus healthy comparisons. Because hippocampal hyperactivity could be a product of interneuron disinhibition and/or increased excitatory neuron excitation, we measured markers broadly. No reductions in the inhibitory marker GAD67 were observed in any subfields. However, in DG, GluN1 was reduced, suggesting reduced excitatory drive from DG to CA3. As described in Section 2.3 and Table 1A, this reduction in GluN1, specifically in DG, is the most

Please cite this article as: A.M. Bobilev, J.M. Perez and C.A. Tamminga, Molecular alterations in the medial temporal lobe in schizophrenia, Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.06.001

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Table 1C Summary of molecular changes in the superior temporal gyrus. Reference

Method used

Sample size (N)

SZ Δ HC

(Bowden et al., 2007)

Relative RT-PCR

↓ RGS4 IN 10/13 SZ

(Nudmamud-Thanoi and Reynolds, 2004) (Le Corre et al., 2000)

Radioligand binding, quantitative IHC Isotropic ISH

(Beveridge et al., 2008)

Global miRNA, qPCR

(Bowden et al., 2008)

Microarray

(Katsel et al., 2005)

Microarray

(Deng and Huang, 2005)

Autoradiography

(Deng and Huang, 2006)

Autoradiography

(Beveridge et al., 2010)

microRNA expression profiling, qPCR RNA sequencing

N = 13 SZ, 13 HC N = 15 SZ, 15 HC N = 6 SZ, 6 HC N = 21 SZ, 21 HC N = 7 SZ, 7 HC N = 13 SZ, 13 HC N = 8 SZ, 8 HC N = 8 SZ, 8 HC N = 21 SZ, 21 HC N = 9 SZ, 9 HC

(Wu et al., 2012)

↑ NR1 Subunit of NMDA receptor density ↑ NR1 isoform with neither spliced exon ↑ let7g in seq but ↔ in rtPCR; ↑ mir181b; ↓ VSNL1/GRIA2 ↓ overall gene expression; ↓ lin7b, iPLAY2-γ, PIK31R1 & ATBF1 STG showed most changes out of 15 brain regions measured ↓ muscarinic M1 and M4 receptor density ↑ GABAA receptor density ↑ microRNA biogenesis, DGCR8, miR-15 ↓ 398 differentially expressed genes; ↑ 374 differentially expressed genes; gene ontology SZ-associated modules functionally enriched for neurotransmission, synaptic vesicle trafficking and neurodevelopment; N2000 genes demonstrated SZ-associated alternative promotor usage and N1000 genes showed differential splicing

The first column contains references that are linked to the bibliography. The second column indicates the type of experiment conducted to measure molecular gene products. The third column lists sample size (N) for schizophrenia (SZ) and healthy comparison, meaning those with confirmation of no known psychiatric conditions (HC). Of note: some studies included additional disease populations, which are not included in the sample sizes listed in this table. The final column details the change (Δ) between SZ and HC, with ↑ indicating an increase or upregulation in SZ compared to HC, ↓ indicating a decrease or downregulation in SZ compared to HC, and ↔ denoting no change between the two groups. Abbreviations: ISH = in situ hybridization, IHC = immunohistochemistry.

consistent abnormality in the hippocampal glutamatergic system reported in the schizophrenia literature (Law and Deakin, 2001; Stan et al., 2015; Vrajová et al., 2010). Paradoxically in CA3, there was an increase in excitatory synaptic markers (Li et al., 2015). Moreover, Golgi staining in CA3 showed increased thorny excrescences, dendrite spine number and spine size, where the mossy fibers (MF) insert onto the CA3 pyramidal cells. In the context of the literature summarized in this review, alterations in MF have been repeatedly shown. Reduced staining intensity of the MF pathway (Goldsmith and Joyce, 1995) and reductions in mossy fiber synapses onto CA3 pyramidal neurons in schizophrenia postmortem tissue have been shown (Kolomeets et al., 2005, 2007). Logically, we drew the plausible interpretation that the DG afferents in the MF pathway regulate excitatory drive in CA3 in an inverse manner as has already been described in hippocampal cell cultures (Lee et al., 2013). These results suggested that this MF/CA3 synapse is an “independently tunable excitatory gain control” which sets neuronal activity in CA3 inversely, in response to afferent input. If DG is dysfunctional in schizophrenia, this could generate ‘run-away CA3 excitation’ and transmit hyperactivity downstream directly to CA1. The reverse-translational animal model we created to mimic this human pathology has confirmed the critical aspects of this disruption at the MF/ CA3 synapse (Segev et al., 2018). The DG-selective GluN1 mouse knock out shows hippocampal hyperactivity, increased markers of LTP in CA3, increased AMPA receptor and NMDA receptor EPSPs and reduced ‘probability of glutamate release’ (PPR) from the DG afferents, as well as psychosis-like behaviors (Segev et al., 2018). The evidence used to generate this model, as well as data from the KO mouse consistent with this model are summarized in Fig 1. Even more interesting, this KO mouse shows neural regions of hyperactivity downstream in projection targets of hippocampus, including medial prefrontal cortex, basolateral amygdala and nucleus accumbens. DREADD inhibition of DG recapitulates many of these same functional and behavioral outcomes (unpublished). In the context of the literature summarized in this review, this functional model of altered activity across subfields of the hippocampus could be driven by discrete changes in the molecular forces governing excitatory/inhibitory balance at the cellular level. Further, these

molecular alterations are almost undoubtedly effecting change in a cell-type and subfield specific manner, yet yield such striking circuit function changes downstream. One of the most prominent and consistent findings across the studies we reviewed of the hippocampus is a change in glutamate signaling-related gene expression, as described in-depth in Section 2.3 and Table 1A. The diversity of cell types, abundance of molecular evidence and disagreement between studies of important molecular findings serves to highlight the complexity of the components of the hippocampal circuit, and suggests that subtle molecular changes could translate to critical functional abnormalities. All of this collectively emphasizes the demand for future studies to explore the hippocampal subfields and even layerspecific or single-cell level changes as opposed to the whole hippocampus. This will serve to better inform the cellular identities associated with the observed molecular changes, and elucidate the mechanistic underpinnings of functional abnormalities in the circuit. Furthermore, this indicates a need for a similar effort to examine the relationship between cellular identity, location and molecular changes in other structures of the MTL, and ultimately the observation of these measurements in the context of whole-brain circuitry. This model is a back-translation from human schizophrenia tissue findings, hence a strong inference platform, but not yet fully studied. It would be an aspirational goal to find pathological elements from these animal models for psychosis upon which to build treatment targets, using pharmacology, neuromodulation, or remediation. Our understanding of MTL dysfunction in schizophrenia would benefit greatly from continued functional application of the findings described here, as well as continued sequencing efforts at the single-cell level throughout the structures of the MTL to further refine the working model of schizophrenia pathology in these tissues.

Role of the funding source There was no direct funding source for this review, however the following grants supported the work cited from our laboratory: NIMH MH077851; NIMH MH062236.

Please cite this article as: A.M. Bobilev, J.M. Perez and C.A. Tamminga, Molecular alterations in the medial temporal lobe in schizophrenia, Schizophrenia Research, https://doi.org/10.1016/j.schres.2019.06.001

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Fig. 1. Evidence for a hippocampal hyperactivity model of schizophrenia. A: Schematic of the hippocampal circuit with molecular and functional evidence in humans in specific subfields leading to the generation of the model (black text) and evidence consistent with previous findings from the GLUN1 conditional knockout mouse model (red text). B: Schematic of functional model of hippocampal dysfunction in schizophrenia. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Contributors Author AB and JP conducted the literature search and review. Authors AB, JP and CT contributed to writing the review article. Authors AB and JP contributed equally as firstauthors on this work. All authors contributed to and approved the final manuscript.

Declaration of Competing Interest Authors AB, JP and CT state that they have no known actual or potential conflicts of interest to declare. Acknowledgements There are no additional acknowledgements for this review.

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