Neuropsychiatric disorders, such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), autism spectrum disorder (ASD), and Alzheimer’s disease (AD), are relatively common. More than one-third of the population in most countries is diagnosed with at least one of these disorders at some point in their life (WHO International Consortium in Psychiatric Epidemiology, 2000). Although these diseases are characterized by different clinical diagnostic categories, they share some biological features, such as genetic mutations, molecular changes, and brain activity alterations (Argyelan et al., 2014; Cardno and Owen, 2014; Douaud et al., 2014; Forero et al., 2016; Hall et al., 2015), suggesting a common underlying biological basis. Accumulating evidence suggests that metabolic changes in the brain are common to several neuropsychiatric disorders. Increased levels of lactate, an end product of the glycolysis pathway, have been observed in the brains of patients with SZ, BD, ASD, MDD, and epilepsy (Dager et al., 2004; Goh et al., 2014; Greene et al., 2003; Halim et al., 2008; Machado-Vieira et al., 2017; Prabakaran et al., 2004; Rossignol and Frye, 2012; Rowland et al., 2016; Soeiro-de-Souza et al., 2016; Sullivan et al., 2019). Brain lactate levels have been observed to rise during neuronal excitation induced by somatic stimuli (Koush et al., 2019; Mangia et al., 2007) and epileptic seizures (During et al., 1994; Lazeyras et al., 2000; Najm et al., 1997; Siesjö et al., 1985b). This increase is accompanied by a concurrent elevation in the excitatory neurotransmitter glutamate (Fernandes et al., 2020; Schaller et al., 2014; Schaller et al., 2013). Additionally, lactate has been found to increase the excitability of several populations of neurons (Magistretti and Allaman, 2018). The presence of increased brain lactate levels aligns with the neuronal hyperexcitation hypothesis proposed for neuropsychiatric disorders, such as SZ (Heckers and Konradi, 2015; Whitfield-Gabrieli et al., 2009), BD (Chen et al., 2011; Mertens et al., 2015), and AD (Bi et al., 2020; Busche and Konnerth, 2015).

Increased lactate levels decrease tissue pH, which may also be associated with deficits in brain energy metabolism (Prabakaran et al., 2004). Lactate is a relatively strong acid and is almost completely dissociated into H⁺ ions and lactate anions at cellular pH (Siesjö, 1985a). Furthermore, H⁺ ions are one of the most potent intrinsic neuromodulators in the brain in terms of concentration and thus play an important role in the control of gene expression (Hagihara et al., 2023; Mexal et al., 2006; Mistry and Pavlidis, 2010) and cellular functions of neurons and glial cells (Chesler, 2003; Kaila and Ransom, 1998). Recent meta-analyses have confirmed decreased brain pH and increased lactate levels in patients with SZ and BD (Dogan et al., 2018; Pruett and Meador-Woodruff, 2020). These changes have also been observed in the brains of AD patients (Lehéricy et al., 2007; Liguori et al., 2016; Liguori et al., 2015; Lyros et al., 2020; Mullins et al., 2018; Paasila et al., 2019; Youssef et al., 2018). However, the observed phenomena are potentially confounded by secondary factors inherent to human studies, such as the administration of antipsychotic drugs (Halim et al., 2008). Agonal experiences associated with these disorders may also complicate the interpretation of postmortem study results (Li et al., 2004; Tomita et al., 2004; Vawter et al., 2006). Although some human studies have suggested that medication use is not a major factor in regulating brain pH and lactate levels (Dager et al., 2004; Halim et al., 2008; Kato et al., 1998; Machado-Vieira et al., 2017; Soeiro-de-Souza et al., 2016), it is technically difficult to exclude the effects of other potential confounding factors in such studies, especially those using postmortem brain samples. Animal models are exempt from such confounding factors and may therefore help confirm whether increased brain lactate levels and decreased pH are involved in the pathophysiology of neuropsychiatric and neurodegenerative disorders.

Recently, we reported that increased lactate levels and decreased pH are commonly observed in the postmortem brains of five genetic mouse models of SZ, BD, and ASD (Hagihara et al., 2018). All mice used in the study were drug-naive, with equivalent agonal states, postmortem intervals, and ages within each strain. An in vivo magnetic resonance spectroscopy (MRS) study showed increased brain lactate levels in another mouse model of SZ (das Neves Duarte et al., 2012), suggesting that this change is not a postmortem artifact. Thus, these findings in mouse models suggest that increased lactate levels and decreased pH reflect the underlying pathophysiology of the disorders and are not mere artifacts. However, knowledge of brain lactate and especially pH in animal models of neuropsychiatric and neurodegenerative diseases is limited to a small number of models. In particular, few studies have examined brain pH and lactate levels in animal models of MDD, epilepsy, and AD. In addition, few studies other than ours Hagihara et al., 2018 have examined the brain pH and lactate levels in the same samples in relevant animal models. Systematic evaluations using the same platform have not yet been performed. Therefore, given the availability of established relevant animal models, we launched a research project named the ‘Brain pH Project’ (Hagihara et al., 2021b). The aim of this project was to improve our understanding of changes in brain pH, particularly in animal models of neuropsychiatric and neurodegenerative disorders. We have extended our previous small-scale study (Hagihara et al., 2018) by using a greater variety of animal models of neuropsychiatric disorders and neurodegenerative disorders, including not only SZ, BD, and ASD, but also MDD, epilepsy, AD, and peripheral diseases or conditions comorbid with psychiatric disorders (e.g. diabetes mellitus [DM], colitis, and peripheral nerve injury). These animal models included 109 strains or conditions of mice, rats, and chicks with genetic modifications, drug treatments, and other experimental manipulations such as exposure to physical and psychological stressors. Of these, 65 strains/conditions of animal models constituted an exploratory cohort (Hagihara et al., 2021b) and 44 constituted a confirmatory cohort used to test the hypothesis developed in the initial exploratory studies. We also implemented a statistical learning algorithm that integrated large-scale brain lactate data with comprehensive behavioral measures covering a broad range of behavioral domains (Takao and Miyakawa, 2006; e.g. working memory, locomotor activity in a novel environment, sensorimotor gating functions, anxiety-like behavior, and depression-like behavior) to identify behavioral signatures intrinsically related to changes in brain lactate levels. Importantly, by replicating these studies separately in a distinct cohort, we obtained reliable results regarding the potential functional significance of brain lactate changes in animal models of neuropsychiatric disorders.

We performed a large-scale analysis of brain pH and lactate levels in 109 animal models of neuropsychiatric disorders, which revealed the diversity of brain energy metabolism among these animal models. The key findings of this study are as follows: (1) the generality of changes in brain pH and lactate levels across a diverse range of disease models and (2) the association of these phenomenon with specific behaviors. First, this large-scale animal model study revealed that alterations in brain pH/lactate levels can be found in approximately 30% of the animal models examined. This generality suggests a common basis in the neuropathophysiology of not only schizophrenia, bipolar disorder, and ASD, but also of Alzheimer’s disease (APP-J20 Tg mice), Down’s syndrome (Ts1Cje mice), Mowat–Wilson syndrome (Zeb2 KO mice), Dravet syndrome (Scn1a-A1783V KI mice), tuberous sclerosis complex (Tsc2 KO mice), Ehlers-Danlos syndrome (Tnxb KO mice), and comorbid depression in diabetes (streptozotocin-treated mice) and colitis (dextran sulfate sodium-treated mice). Secondly, this study demonstrated that these phenomenon in the brain are primarily associated with working memory impairment over depression- and anxiety-related behaviors. Importantly, developing these hypotheses in an exploratory cohort of animals and confirming them in an independent cohort within this study enhances the robustness and reliability of our hypotheses.

Some strains of mice that were considered models of different diseases showed similar patterns of changes in pH and lactate levels. Specifically, the SZ/ID models (Ppp3r1 KO, Nrgn KO mice, and Hivep2 KO mice), BD/ID model (Camk2a KO mice), ASD model (Chd8 KO mice), depression models (mice exposed to social defeat stress, corticosterone-treated mice, and Sert KO mice), and other disease models mentioned above commonly exhibited decreased brain pH and increased lactate levels. BD model Polg1 Tg mice showed no differences in pH or lactate levels. Interestingly, however, other BD model Clock mutant mice and ASD models, such as Shank2 KO (Lim et al., 2017), Fmr1 KO, Dyrk1 KO (Raveau et al., 2018), Auts2 KO (Hori et al., 2015), and 15q dup mice (Nakatani et al., 2009), were classified into a group with opposite changes (a group with decreased lactate levels and increased pH). Animal models with different patterns of changes in brain pH and lactate levels may represent subpopulations of patients or specific disease states (Rossignol and Frye, 2012). While increased brain lactate levels in neuropsychiatric conditions are almost consistent in the literature, decreased lactate levels have also been found in a cohort of patients with SZ (Beasley et al., 2009) and in the euthymic state of BD (Brady et al., 2012). Our results from animal studies may also support the idea that patients classified into specific neuropsychiatric disorders based on symptoms are biologically heterogeneous (Insel and Cuthbert, 2015) from a brain energy metabolism perspective. Detecting changes in brain pH and lactate levels, whether resulting in an increase or decrease due to their potential bidirectional alterations, using techniques such as MRS may help the diagnosis, subcategorization, and identification of specific disease states of these biologically heterogeneous and spectrum disorders, as has been shown for mitochondrial diseases (Lin et al., 2003).

Although previous studies have repeatedly reported that brain pH is decreased in SZ and BD (Dogan et al., 2018; Hagihara et al., 2018; Pruett and Meador-Woodruff, 2020), little is known about brain pH in MDD. Our present study demonstrated that decreased brain pH is a common feature in several preclinical animal models of depression (e.g. mice exposed to social defeat stress, corticosterone-treated mice, and Sert KO mice) and comorbid depression (DM mouse model induced by streptozotocin treatment and colitis mouse model induced by dextran sulfate sodium treatment). These findings raise the possibility that decreased brain pH associated with increased lactate levels may be a common endophenotype in MDD, shared with other neuropsychiatric disorders, and needs to be elucidated in future research.

While we analyzed 109 strains/conditions of animals, we included both those that are widely recognized as animal models for specific neuropsychiatric disorders and those that are not. For example, while interleukin 18 (Il18) KO mice and mitofusin 2 (hMfn2-D210V) Tg mice exhibited changes in pH and lactate levels, the evidence that these genes are associated with specific neuropsychiatric disorders is limited. However, these strains of mice exhibited behavioral abnormalities related to neuropsychiatric disorders, such as depressive-like behaviors and impaired working memory (Ishikawa et al., 2021; Ishikawa et al., 2019; Yamanishi et al., 2019). Furthermore, these mice showed maturation abnormality in the hippocampal dentate gyrus and neuronal degeneration due to mitochondrial dysfunction, respectively, suggesting conceptual validity for utilization as animal models for neuropsychiatric and neurodegenerative disorders (Burté et al., 2015; Cunnane et al., 2020; Hagihara et al., 2019; Hagihara et al., 2013). In contrast, mice with heterozygous KO of the synaptic Ras GTPase-activating protein 1 (syngap1), whose mutations have been identified in human patients with ID and ASD, showed an array of behavioral abnormalities relevant to the disorders (Komiyama et al., 2002; Nakajima et al., 2019), but did not show changes in brain pH or lactate levels. Therefore, while changes in brain pH and lactate levels could be transdiagnostic endophenotypes of neuropsychiatric disorders, they might occur depending on the subpopulation due to the distinct genetic and environmental causes or specific disease states in certain disorders.

The present animal studies revealed a strong negative correlation between brain pH and lactate levels, which supports our previous findings from small-scale animal studies (Hagihara et al., 2018). A negative correlation between brain pH and lactate levels was found in a human postmortem study (Halim et al., 2008). These results suggest that brain lactate is an important regulator of tissue pH (Prabakaran et al., 2004), although we cannot exclude the possibility that other factors, such as neuronal activity-regulated production of carbon dioxide, another metabolic acid, may also contribute to changes in brain pH (Chesler, 2003; Zauner et al., 1995). Furthermore, the observed pH changes may be due to the dysregulation of neuronal (Li et al., 2022; Pruett et al., 2023) and astroglial (Theparambil et al., 2020) mechanisms of H⁺ ion transport and buffering to regulate intracellular and extracellular pH homeostasis, which should be investigated in our model animals.

We observed no significant correlation between brain pH and age in the wild-type/control rodents. In human studies, inconsistent results have been obtained regarding the correlation between brain pH and age; some studies showed no significant correlation (Monoranu et al., 2009; Preece and Cairns, 2003), whereas others showed a negative correlation (Forester et al., 2010; Harrison et al., 1995). The effect of sex on brain pH has been inconsistent in human studies (Monoranu et al., 2009; Preece and Cairns, 2003). Systematic analyses focusing on the effects of age and sex on brain pH in animal models may help explain the inconsistency in human studies.

Our prediction analysis revealed that poorer working memory performance in animal models of neuropsychiatric disorders may be predominantly associated with higher lactate levels, which was reliably confirmed in an independent cohort. Higher lactate levels have been associated with lower cognition in individuals with SZ (Rowland et al., 2016) and mild cognitive impairment (Weaver et al., 2015). Based on these observations, abnormal accumulation of lactate would be expected to have a negative impact on brain function, especially memory formation. However, lactate production stimulated by learning tasks has been suggested to be a requisite for memory formation. Lactate production by astrocytic glycogenolysis and its transport to neurons serves as an energy substrate for neuronal activity and is referred to as astrocyte-neuron lactate shuttle (ANLS). Animal studies have shown that pharmacological disruption of learning task-stimulated lactate production and transport via the ANLS immediately before testing impairs memory formation, as assessed by the plus-shaped maze spontaneous alteration task (testing short-term memory; Newman et al., 2011) and inhibitory avoidance task (testing long-term memory; Descalzi et al., 2019; Suzuki et al., 2011). Collectively, considering that brain lactate levels increase during stimulation in a temporally (and spatially) restricted manner under physiological conditions (Mangia et al., 2007; Schaller et al., 2014), pathologically sustained elevation of brain lactate levels may have negative effects on brain functions, including memory processing, although causality is unknown. Another possibility is that the reduced consumption of lactate for energy production due to mitochondrial dysfunction in neurons may underlie impaired learning and memory functions in disease conditions. Mitochondrial dysfunction is thought to lead to lactate accumulation due to the insufficient capacity of mitochondrial metabolism to metabolize the lactate produced (Dogan et al., 2018; Regenold et al., 2009; Stork and Renshaw, 2005). Mitochondrial dysfunction has been consistently implicated in several neuropsychiatric disorders, including SZ, BD, MDD, ASD, and AD (Holper et al., 2019; Manji et al., 2012; Pei and Wallace, 2018), among which working memory deficits are a common symptom (Millan et al., 2012). In addition, increased lactate levels reflect neuronal activation (Hagihara et al., 2018). Thus, activation in brain regions other than the frontal cortex, a brain region critical for working memory (Andrés, 2003), interferes with working memory performance, as it has been proposed that the activity of the core brain region may be affected by noise from the rest of the brain during cognitive tasks in patients with SZ (Foucher et al., 2005). Moreover, increased lactate may have a positive or beneficial effect on memory function to compensate for its impairment, as lactate administration with an associated increase in brain lactate levels attenuates cognitive deficits in human patients (Bisri et al., 2016) and rodent models (Rice et al., 2002) of traumatic brain injury. In addition, lactate administration exerts antidepressant effects in a mouse model of depression (Carrard et al., 2021; Carrard et al., 2018; Karnib et al., 2019; Shaif et al., 2018). Lactate has also shown to promote learning and memory (Descalzi et al., 2019; Dong et al., 2017; El Hayek et al., 2019; Lu et al., 2019; Roumes et al., 2021; Suzuki et al., 2011), synaptic plasticity (Herrera-López et al., 2020; Yang et al., 2014; Zhou et al., 2021), adult hippocampal neurogenesis (Lev-Vachnish et al., 2019), and mitochondrial biogenesis and antioxidant defense (Akter et al., 2023), while its effects on adult hippocampal neurogenesis and learning and memory are controversial (Ikeda et al., 2021; Lev-Vachnish et al., 2019; Wang et al., 2019). Moreover, increased lactate levels may also be involved in behavioral changes other than memory deficits, such as anxiety. The results of our previous study showed that increased brain lactate levels were associated with altered anxiety-like behaviors in a social defeat stress model of depression (Hagihara et al., 2021a). Further studies are needed to address these hypotheses by chronically inducing deficits in mitochondrial function to manipulate endogenous lactate levels in a brain-region-specific manner and to analyze their effects on working memory. It is also important to consider whether pH or lactate contributes more significantly to the observed behavioral abnormalities.

There exists a close relationship between neuronal activity and energy metabolism in the brain. In vitro studies have indicated that the uptake of glutamate into astrocytes stimulates glycolysis and lactate production following neuronal excitation (Pellerin and Magistretti, 1994). However, an in vivo investigation on cerebellar Purkinje cells has demonstrated that lactate is produced in neurons in an activity-dependent manner, suggesting that astrocytes may not be the sole supplier of lactate to neurons (Caesar et al., 2008). Shifts in the neuronal excitation and inhibition (E/I) balance toward excitation of specific neural circuits have been implicated in the pathogenesis and pathophysiology of various neuropsychiatric disorders, including SZ, BD, ASD, AD, and epilepsy (Brealy et al., 2015; Busche and Konnerth, 2016; Marín, 2012; Nelson and Valakh, 2015; Yizhar et al., 2011). An imbalance favoring excitation could lead to increased energy expenditure and potentially heightened glycolysis. Such alterations in energy metabolism may be associated with increased lactate production. Indeed, in our previous studies using Hivep2 KO mice, characterized by increased brain lactate levels and decreased pH, we observed elevated glutamate levels and upregulated expression of many glycolytic genes in the hippocampus (Hagihara et al., 2018; Takao et al., 2013). Furthermore, Actl6b (also known as Baf53b) KO mice (Wenderski et al., 2020) and APP-J20 Tg mice (Bomben et al., 2014; Brown et al., 2018; Palop et al., 2007) exhibited neuronal hyperexcitation, as evidenced by increased expression of activity-regulated genes and epileptiform discharges recorded by electroencephalography. Dravet syndrome model mice with a clinically relevant SCN1A mutation (Scn1a-A1783V knock-in mice) (Ricobaraza et al., 2019) and mutant Snap25 (S187A) knock-in mice (Kataoka et al., 2011) developed convulsive seizures. These findings suggest that neuronal hyperexcitation may be one of the common factors leading to increased lactate production and decreased pH in the brain. We consider that alterations in brain pH and lactate levels occur, whether they are a direct and known consequence or indirect and unknown ones of genetic modifications. We have proposed that genetic modifications, along with environmental stimulations, may induce various changes, which subsequently converge toward specific endophenotypes in the brain, such as neuronal hyperexcitation, inflammation, and maturational abnormalities (Hagihara et al., 2013; Yamasaki et al., 2008). The findings of this study, demonstrating the commonality of alterations in brain pH and lactate levels, align with this concept and suggest that these alterations could serve as brain endophenotypes in multiple neuropsychiatric disorders.

The major limitations of this study include the absence of analyses specific to brain regions or cell types and the lack of functional investigations. Because we used whole brain samples to measure pH and lactate levels, we could not determine whether the observed changes in pH and/or lactate levels occurred ubiquitously throughout the brain or selectively in specific brain region(s) in each strain/condition of the models. It is known that certain molecular expression profiles and signaling pathways display brain region-specific alterations, and in some cases, even exhibit opposing changes in neuropsychiatric disease models (Floriou-Servou et al., 2018; Hosp et al., 2017; Reim et al., 2017). Indeed, brain region-specific increases in lactate levels were observed in human patients with ASD in an MRS study (Goh et al., 2014). Furthermore, while increased lactate levels were observed in whole-brain measurements in mice with chronic social defeat stress (Figure 2—figure supplement 5; Hagihara et al., 2021a), decreased lactate levels were found in the dorsomedial prefrontal cortex (Yao et al., 2023). Additionally, it has been reported that the basal intracellular pH differs between neurons and astrocytes (lower in astrocytes than in neurons), and their responsiveness to conditions simulating neural hyperexcitation and the metabolic acidosis in terms of intracellular pH also varies (Raimondo et al., 2016; Salameh et al., 2017). It would also be possible that the brain region/cell type-specific changes may occur even in animal models in which undetectable changes were observed in the present study. This could be due to the masking of such changes in the analysis when using whole-brain samples. Given the assumption that the brain regions and cell types responsible for pH and lactate changes vary across different strains/conditions, comprehensive studies are needed to thoroughly examine this issue for each animal model individually. This can be achieved through techniques such as evaluating microdissected brain samples, conducting in vivo analyses using pH- or lactate-sensitive biosensor electrodes (Marunaka et al., 2014; Newman et al., 2011) and MRS (Davidovic et al., 2011). Subsequently, based on such findings, it is also necessary to conduct functional analyses for each model animal by manipulating pH or lactate levels in specific brain regions/cell types and evaluating behavioral phenotypes relevant to neuropsychiatric disorders.

We also note that there are several potential confounding factors in this study. The brain samples analyzed in this study contained cerebral blood. The cerebral blood volume is estimated to be approximately 20–50 μl/g in human and feline brains (Leenders et al., 1990; van Zijl et al., 1998). When we extrapolate these values to murine brains, it would imply that the proportion of blood contamination in the brain homogenates analyzed is 0.2–0.6%. Additionally, lactate concentrations in the blood are two to three times higher than those in the brains of mice (Béland-Millar et al., 2017). Therefore, even if there were differences in the amount of resident blood in the brains between control and experimental animals, the impact of such differences on the lactate measurements would likely be minimal. Other confounding factors include circadian variation and locomotor activity before the brain sampling. Lactate levels are known to exhibit circadian rhythm in the rodent cortex, transitioning gradually from lower levels during the light period to higher levels during the dark period (Dash et al., 2012; Shram et al., 2002; Wallace et al., 2020). The variation in the times of sample collection during the day was basically kept minimized within each strain/condition of animals. However, the sample collection times were not explicitly matched across the different laboratories, which may contribute to variations in the baseline control levels of pH and lactate among different strains/conditions of animals (Supplementary file 3). In addition, motor activity and wake/sleep status immediately before brain sampling can also influence brain lactate levels (Naylor et al., 2012; Shram et al., 2002). These factors have the potential to act as confounding variables in the measurement of brain lactate and pH in animals.

In conclusion, the present study demonstrated that altered brain pH and lactate levels are commonly observed in animal models of SZ, BD, ID, ASD, AD, and other neuropsychiatric disorders. These findings provide further evidence supporting the hypothesis that altered brain pH and lactate levels are not mere artifacts, such as those resulting from medication confounding, but are rather involved in the underlying pathophysiology of some patients with neuropsychiatric disorders. Altered brain energy metabolism or neural hyper- or hypoactivity leading to abnormal lactate levels and pH may serve as a potential therapeutic targets for neuropsychiatric disorders (Pruett and Meador-Woodruff, 2020). Future studies are needed to identify effective treatment strategies specific to sets of animal models that could recapitulate the diversity of brain energy metabolism in human disease conditions. This could contribute to the development of treatments for biologically defined subgroups of patients or disease states of debilitating diseases beyond clinically defined boundaries.

The data analyzed in this study are available in Supplementary files 1–5.

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Author details

1. Hideo Hagihara

   Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Toyoake, Japan

   Contribution

   Conceptualization, Formal analysis, Funding acquisition, Investigation, Writing - original draft, Writing – review and editing

   For correspondence

   h-hagi@fujita-hu.ac.jp

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9602-9518

2. Hirotaka Shoji

   Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Toyoake, Japan

   Contribution

   Resources, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

3. Satoko Hattori

   Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Toyoake, Japan

   Contribution

   Resources, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

4. Giovanni Sala

   Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Toyoake, Japan

   Contribution

   Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

5. Yoshihiro Takamiya

   Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Toyoake, Japan

   Contribution

   Investigation

   Competing interests

   No competing interests declared

6. Mika Tanaka

   Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Toyoake, Japan

   Contribution

   Investigation

   Competing interests

   No competing interests declared

7. Masafumi Ihara

   Department of Neurology, National Cerebral and Cardiovascular Center, Suita, Japan

   Contribution

   Resources, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

8. Mihiro Shibutani

   Laboratory of Genome Science, Biosignal Genome Resource Center, Institute for Molecular and Cellular Regulation, Gunma University, Maebashi, Japan

   Contribution

   Resources, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

9. Izuho Hatada

   Laboratory of Genome Science, Biosignal Genome Resource Center, Institute for Molecular and Cellular Regulation, Gunma University, Maebashi, Japan

   Contribution

   Resources, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

10. Kei Hori

    Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

11. Mikio Hoshino

    Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-9526-3473

12. Akito Nakao

    Department of Synthetic Chemistry and Biological Chemistry, Graduate School of Engineering, Kyoto University, Kyoto, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2296-8245

13. Yasuo Mori

    Department of Synthetic Chemistry and Biological Chemistry, Graduate School of Engineering, Kyoto University, Kyoto, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

14. Shigeo Okabe

    Department of Cellular Neurobiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-1216-8890

15. Masayuki Matsushita

    Department of Molecular Cellular Physiology, Graduate School of Medicine, University of the Ryukyus, Nishihara, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

16. Anja Urbach

    Department of Neurology, Jena University Hospital, Jena, Germany

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

17. Yuta Katayama

    Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

18. Akinobu Matsumoto

    Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

19. Keiichi I Nakayama

    Department of Molecular and Cellular Biology, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

20. Shota Katori

    Laboratory of Mammalian Neural Circuits, National Institute of Genetics, Mishima, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

21. Takuya Sato

    Laboratory of Mammalian Neural Circuits, National Institute of Genetics, Mishima, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

22. Takuji Iwasato

    Laboratory of Mammalian Neural Circuits, National Institute of Genetics, Mishima, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

23. Haruko Nakamura

    Department of Molecular Pharmacology and Neurobiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

24. Yoshio Goshima

    Department of Molecular Pharmacology and Neurobiology, Yokohama City University Graduate School of Medicine, Yokohama, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

25. Matthieu Raveau

    Laboratory for Neurogenetics, RIKEN Center for Brain Science, Wako, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

26. Tetsuya Tatsukawa

    Laboratory for Neurogenetics, RIKEN Center for Brain Science, Wako, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

27. Kazuhiro Yamakawa

    1. Laboratory for Neurogenetics, RIKEN Center for Brain Science, Wako, Japan
    2. Department of Neurodevelopmental Disorder Genetics, Institute of Brain Sciences, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-1478-4390

28. Noriko Takahashi

    1. Laboratory of Structural Physiology, Center for Disease Biology and Integrative Medicine, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
    2. Department of Physiology, Kitasato University School of Medicine, Sagamihara, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

29. Haruo Kasai

    1. Laboratory of Structural Physiology, Center for Disease Biology and Integrative Medicine, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
    2. International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-2327-9027

30. Johji Inazawa

    Research Core, Tokyo Medical and Dental University, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

31. Ikuo Nobuhisa

    Department of Stem Cell Regulation, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

32. Tetsushi Kagawa

    Department of Stem Cell Regulation, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

33. Tetsuya Taga

    Department of Stem Cell Regulation, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

34. Mohamed Darwish

    1. Department of Biochemistry, Faculty of Pharmacy, Cairo University, Cairo, Egypt
    2. Department of Behavioral Physiology, Graduate School of Innovative Life Science, University of Toyama, Toyama, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

35. Hirofumi Nishizono

    Medical Research Institute, Kanazawa Medical University, Kahoku, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

36. Keizo Takao

    1. Department of Behavioral Physiology, Graduate School of Innovative Life Science, University of Toyama, Toyama, Japan
    2. Department of Behavioral Physiology, Faculty of Medicine, University of Toyama, Toyama, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-4734-3583

37. Kiran Sapkota

    Department of Neuroscience, Southern Research, Birmingham, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

38. Kazutoshi Nakazawa

    Department of Neuroscience, Southern Research, Birmingham, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

39. Tsuyoshi Takagi

    Institute for Developmental Research, Aichi Developmental Disability Center, Kasugai, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

40. Haruki Fujisawa

    Department of Endocrinology, Diabetes and Metabolism, School of Medicine, Fujita Health University, Toyoake, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

41. Yoshihisa Sugimura

    Department of Endocrinology, Diabetes and Metabolism, School of Medicine, Fujita Health University, Toyoake, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

42. Kyosuke Yamanishi

    Department of Neuropsychiatry, Hyogo Medical University School of Medicine, Nishinomiya, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-5130-8193

43. Lakshmi Rajagopal

    Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

44. Nanette Deneen Hannah

    Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

45. Herbert Y Meltzer

    Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

46. Tohru Yamamoto

    Department of Molecular Neurobiology, Faculty of Medicine, Kagawa University, Kita-gun, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-1652-0233

47. Shuji Wakatsuki

    Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

48. Toshiyuki Araki

    Department of Peripheral Nervous System Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

49. Katsuhiko Tabuchi

    Department of Molecular & Cellular Physiology, Shinshu University School of Medicine, Matsumoto, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

50. Tadahiro Numakawa

    Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

51. Hiroshi Kunugi

    1. Department of Mental Disorder Research, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Japan
    2. Department of Psychiatry, Teikyo University School of Medicine, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

52. Freesia L Huang

    Program of Developmental Neurobiology, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

53. Atsuko Hayata-Takano

    1. Laboratory of Molecular Neuropharmacology, Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Japan
    2. Department of Pharmacology, Graduate School of Dentistry, Osaka University, Suita, Japan
    3. United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

54. Hitoshi Hashimoto

    1. Laboratory of Molecular Neuropharmacology, Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Japan
    2. United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Suita, Japan
    3. Division of Bioscience, Institute for Datability Science, Osaka University, Suita, Japan
    4. Transdimensional Life Imaging Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
    5. Department of Molecular Pharmaceutical Science, Graduate School of Medicine, Osaka University, Suita, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-6548-4016

55. Kota Tamada

    1. RIKEN Brain Science Institute, Wako, Japan
    2. Department of Physiology and Cell Biology, Kobe University School of Medicine, Kobe, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-6575-6189

56. Toru Takumi

    1. RIKEN Brain Science Institute, Wako, Japan
    2. Department of Physiology and Cell Biology, Kobe University School of Medicine, Kobe, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-7153-266X

57. Takaoki Kasahara

    1. Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Wako, Japan
    2. Institute of Biology and Environmental Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-0953-5146

58. Tadafumi Kato

    1. Laboratory for Molecular Dynamics of Mental Disorders, RIKEN Center for Brain Science, Wako, Japan
    2. Department of Psychiatry and Behavioral Science, Juntendo University Graduate School of Medicine, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

59. Isabella A Graef

    Department of Pathology, Stanford University School of Medicine, Stanford, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

60. Gerald R Crabtree

    Department of Pathology, Stanford University School of Medicine, Stanford, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

61. Nozomi Asaoka

    Department of Pharmacology, Kyoto Prefectural University of Medicine, Kyoto, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

62. Hikari Hatakama

    Department of Molecular Pharmacology, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

63. Shuji Kaneko

    Department of Molecular Pharmacology, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

64. Takao Kohno

    Department of Biomedical Science, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-2557-4281

65. Mitsuharu Hattori

    Department of Biomedical Science, Graduate School of Pharmaceutical Sciences, Nagoya City University, Nagoya, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

66. Yoshio Hoshiba

    Laboratory of Medical Neuroscience, Institute for Molecular and Cellular Regulation, Gunma University, Maebashi, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

67. Ryuhei Miyake

    Laboratory for Multi-scale Biological Psychiatry, RIKEN Center for Brain Science, Wako, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

68. Kisho Obi-Nagata

    Laboratory for Multi-scale Biological Psychiatry, RIKEN Center for Brain Science, Wako, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

69. Akiko Hayashi-Takagi

    1. Laboratory of Medical Neuroscience, Institute for Molecular and Cellular Regulation, Gunma University, Maebashi, Japan
    2. Laboratory for Multi-scale Biological Psychiatry, RIKEN Center for Brain Science, Wako, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

70. Léa J Becker

    Institut des Neurosciences Cellulaires et Intégratives, Centre National de la Recherche Scientifique, Université de Strasbourg, Strasbourg, France

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

71. Ipek Yalcin

    Institut des Neurosciences Cellulaires et Intégratives, Centre National de la Recherche Scientifique, Université de Strasbourg, Strasbourg, France

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

72. Yoko Hagino

    Addictive Substance Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

73. Hiroko Kotajima-Murakami

    Addictive Substance Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

74. Yuki Moriya

    Addictive Substance Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

75. Kazutaka Ikeda

    Addictive Substance Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

76. Hyopil Kim

    1. Department of Biological Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
    2. Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, United States

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

77. Bong-Kiun Kaang

    1. Department of Biological Sciences, College of Natural Sciences, Seoul National University, Seoul, Republic of Korea
    2. Center for Cognition and Sociality, Institute for Basic Science (IBS), Daejeon, Republic of Korea

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-7593-9707

78. Hikari Otabi

    1. College of Agriculture, Ibaraki University, Ami, Japan
    2. United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology, Fuchu, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

79. Yuta Yoshida

    College of Agriculture, Ibaraki University, Ami, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

80. Atsushi Toyoda

    1. College of Agriculture, Ibaraki University, Ami, Japan
    2. United Graduate School of Agricultural Science, Tokyo University of Agriculture and Technology, Fuchu, Japan
    3. Ibaraki University Cooperation between Agriculture and Medical Science (IUCAM), Ibaraki, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

81. Noboru H Komiyama

    1. Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
    2. Simons Initiative for the Developing Brain, Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

82. Seth GN Grant

    1. Genes to Cognition Program, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
    2. Simons Initiative for the Developing Brain, Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-8732-8735

83. Michiru Ida-Eto

    Department of Developmental and Regenerative Medicine, Mie University, Graduate School of Medicine, Tsu, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

84. Masaaki Narita

    Department of Developmental and Regenerative Medicine, Mie University, Graduate School of Medicine, Tsu, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

85. Ken-ichi Matsumoto

    Department of Biosignaling and Radioisotope Experiment, Interdisciplinary Center for Science Research, Organization for Research and Academic Information, Shimane University, Izumo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

86. Emiko Okuda-Ashitaka

    Department of Biomedical Engineering, Osaka Institute of Technology, Osaka, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

87. Iori Ohmori

    Department of Physiology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

88. Tadayuki Shimada

    Child Brain Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-7333-9847

89. Kanato Yamagata

    Child Brain Project, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

90. Hiroshi Ageta

    Division for Therapies Against Intractable Diseases, Center for Medical Science, Fujita Health University, Toyoake, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

91. Kunihiro Tsuchida

    Division for Therapies Against Intractable Diseases, Center for Medical Science, Fujita Health University, Toyoake, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-3983-5756

92. Kaoru Inokuchi

    1. Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
    2. Department of Biochemistry, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
    3. Core Research for Evolutionary Science and Technology (CREST), Japan Science and Technology Agency (JST), University of Toyama, Toyama, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-5393-3133

93. Takayuki Sassa

    Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0003-3145-9829

94. Akio Kihara

    Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0001-5889-0788

95. Motoaki Fukasawa

    Department of Anatomy II, Fujita Health University School of Medicine, Toyoake, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

96. Nobuteru Usuda

    Department of Anatomy II, Fujita Health University School of Medicine, Toyoake, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

97. Tayo Katano

    Department of Medical Chemistry, Kansai Medical University, Hirakata, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

98. Teruyuki Tanaka

    Department of Developmental Medical Sciences, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

99. Yoshihiro Yoshihara

    Laboratory for Systems Molecular Ethology, RIKEN Center for Brain Science, Wako, Japan

    Contribution

    Resources, Investigation, Writing – review and editing

    Competing interests

    No competing interests declared

100. Michihiro Igarashi

     1. Department of Neurochemistry and Molecular Cell Biology, School of Medicine, and Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
     2. Transdiciplinary Research Program, Niigata University, Niigata, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0003-1474-3385

101. Takashi Hayashi

     Biomedical Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0003-3591-2109

102. Kaori Ishikawa

     1. Institute of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
     2. Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0001-9895-5996

103. Satoshi Yamamoto

     Integrated Technology Research Laboratories, Pharmaceutical Research Division, Takeda Pharmaceutical Company, Ltd, Fujisawa, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     Employee of Takeda Pharmaceutical Company, Ltd

104. Naoya Nishimura

     Integrated Technology Research Laboratories, Pharmaceutical Research Division, Takeda Pharmaceutical Company, Ltd, Fujisawa, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     Employee of Takeda Pharmaceutical Company, Ltd

105. Kazuto Nakada

     1. Institute of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Japan
     2. Graduate School of Science and Technology, University of Tsukuba, Tsukuba, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

106. Shinji Hirotsune

     Department of Genetic Disease Research, Osaka City University Graduate School of Medicine, Osaka, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

107. Kiyoshi Egawa

     Department of Pediatrics, Hokkaido University Graduate School of Medicine, Sapporo, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

108. Kazuma Higashisaka

     Laboratory of Toxicology and Safety Science, Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

109. Yasuo Tsutsumi

     Laboratory of Toxicology and Safety Science, Graduate School of Pharmaceutical Sciences, Osaka University, Suita, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

110. Shoko Nishihara

     Glycan & Life Systems Integration Center (GaLSIC), Soka University, Tokyo, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-1668-2603

111. Noriyuki Sugo

     Graduate School of Frontier Biosciences, Osaka University, Suita, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

112. Takeshi Yagi

     Graduate School of Frontier Biosciences, Osaka University, Suita, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

113. Naoto Ueno

     Laboratory of Morphogenesis, National Institute for Basic Biology, Okazaki, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-8375-2317

114. Tomomi Yamamoto

     Division of Biophysics and Neurobiology, National Institute for Physiological Sciences, Okazaki, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

115. Yoshihiro Kubo

     Division of Biophysics and Neurobiology, National Institute for Physiological Sciences, Okazaki, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0001-6707-0837

116. Rie Ohashi

     1. Laboratory of Neuronal Cell Biology, National Institute for Basic Biology, Okazaki, Japan
     2. Department of Basic Biology, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Japan
     3. Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

117. Nobuyuki Shiina

     1. Laboratory of Neuronal Cell Biology, National Institute for Basic Biology, Okazaki, Japan
     2. Department of Basic Biology, SOKENDAI (Graduate University for Advanced Studies), Okazaki, Japan
     3. Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-1854-4239

118. Kimiko Shimizu

     Department of Biological Sciences, School of Science, The University of Tokyo, Tokyo, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0003-4943-2552

119. Sayaka Higo-Yamamoto

     Healthy Food Science Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

120. Katsutaka Oishi

     1. Healthy Food Science Research Group, Cellular and Molecular Biotechnology Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan
     2. Department of Applied Biological Science, Graduate School of Science and Technology, Tokyo University of Science, Noda, Japan
     3. Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan
     4. School of Integrative and Global Majors (SIGMA), University of Tsukuba, Tsukuba, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-4870-0837

121. Hisashi Mori

     Department of Molecular Neuroscience, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0001-9743-2456

122. Tamio Furuse

     Mouse Phenotype Analysis Division, Japan Mouse Clinic, RIKEN BioResource Research Center (BRC), Tsukuba, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

123. Masaru Tamura

     Mouse Phenotype Analysis Division, Japan Mouse Clinic, RIKEN BioResource Research Center (BRC), Tsukuba, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

124. Hisashi Shirakawa

     Department of Molecular Pharmacology, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-4129-0978

125. Daiki X Sato

     1. Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Toyoake, Japan
     2. Graduate School of Life Sciences, Tohoku University, Sendai, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-9527-8253

126. Yukiko U Inoue

     Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-4105-9127

127. Takayoshi Inoue

     Department of Biochemistry and Cellular Biology, National Institute of Neuroscience, National Center of Neurology and Psychiatry, Kodaira, Japan

     Contribution

     Resources, Writing – review and editing, Investigation

     Competing interests

     No competing interests declared

128. Yuriko Komine

     1. Young Researcher Support Group, Research Enhancement Strategy Office, National Institute for Basic Biology, National Institute of Natural Sciences, Okazaki, Japan
     2. Division of Brain Biology, National Institute for Basic Biology, Okazaki, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-0097-8813

129. Tetsuo Yamamori

     1. Division of Brain Biology, National Institute for Basic Biology, Okazaki, Japan
     2. Laboratory for Molecular Analysis of Higher Brain Function, RIKEN Center for Brain Science, Wako, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

130. Kenji Sakimura

     1. Department of Cellular Neurobiology, Brain Research Institute, Niigata University, Niigata, Japan
     2. Department of Animal Model Development, Brain Research Institute, Niigata University, Niigata, Japan

     Contribution

     Resources, Investigation, Writing – review and editing

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0002-8091-8879

131. Tsuyoshi Miyakawa

     Division of Systems Medical Science, Center for Medical Science, Fujita Health University, Toyoake, Japan

     Contribution

     Conceptualization, Resources, Funding acquisition, Investigation, Writing - original draft, Writing – review and editing

     For correspondence

     miyakawa@fujita-hu.ac.jp

     Competing interests

     No competing interests declared

     "This ORCID iD identifies the author of this article:" 0000-0003-0137-8200