Article3 March 2021Open Access Transparent process Cooperation of LIM domain-binding 2 (LDB2) with EGR in the pathogenesis of schizophrenia Tetsuo Ohnishi Corresponding Author [email protected] orcid.org/0000-0002-6696-9725 Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, JapanThese authors contributed equally to this work Search for more papers by this author Yuji Kiyama orcid.org/0000-0001-5415-3473 Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan Laboratory of Biochemistry and Molecular Biology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, JapanThese authors contributed equally to this work Search for more papers by this author Fumiko Arima-Yoshida Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan Institute of Clinical Medicine and Research, The Jikei University School of Medicine, Tokyo, JapanThese authors contributed equally to this work Search for more papers by this author Mitsutaka Kadota orcid.org/0000-0002-1674-6697 Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, JapanThese authors contributed equally to this work Search for more papers by this author Tomoe Ichikawa Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Department of Infection Control Science, Meiji Pharmaceutical University, Kiyose, Japan Search for more papers by this author Kazuyuki Yamada School of Management, Shizuoka Sangyo University, Iwata, Japan RIKEN, Wako, Japan Search for more papers by this author Akiko Watanabe Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Hisako Ohba Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Kaori Tanaka Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan Search for more papers by this author Akihiro Nakaya Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan Search for more papers by this author Yasue Horiuchi orcid.org/0000-0003-0597-2514 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Yoshimi Iwayama Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan RIKEN, Wako, Japan Search for more papers by this author Manabu Toyoshima orcid.org/0000-0001-7291-8935 Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Itone Ogawa Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan Search for more papers by this author Chie Shimamoto-Mitsuyama orcid.org/0000-0002-8524-974X Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Motoko Maekawa Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Shabeesh Balan orcid.org/0000-0002-1098-1290 Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Makoto Arai Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Mitsuhiro Miyashita Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Kazuya Toriumi orcid.org/0000-0002-8593-3269 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Yayoi Nozaki Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Rumi Kurokawa RIKEN, Wako, Japan Search for more papers by this author Kazuhiro Suzuki Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Akane Yoshikawa Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Tomoko Toyota orcid.org/0000-0003-0034-309X Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Toshihiko Hosoya orcid.org/0000-0001-8559-8344 RIKEN, Wako, Japan Biomedical Business Center, RICOH Company, LTD, Kawasaki, Japan Search for more papers by this author Hiroyuki Okuno orcid.org/0000-0001-6237-6503 Laboratory of Biochemistry and Molecular Biology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan Search for more papers by this author Haruhiko Bito orcid.org/0000-0001-6315-9594 Department of Neurochemistry, the University of Tokyo, Graduate School of Medicine, Tokyo, Japan Search for more papers by this author Masanari Itokawa orcid.org/0000-0003-4433-8030 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Shigehiro Kuraku orcid.org/0000-0003-1464-8388 Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan Search for more papers by this author Toshiya Manabe Corresponding Author [email protected] orcid.org/0000-0002-5359-6704 Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan Search for more papers by this author Takeo Yoshikawa Corresponding Author [email protected] orcid.org/0000-0003-2791-6679 Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Tetsuo Ohnishi Corresponding Author [email protected] orcid.org/0000-0002-6696-9725 Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, JapanThese authors contributed equally to this work Search for more papers by this author Yuji Kiyama orcid.org/0000-0001-5415-3473 Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan Laboratory of Biochemistry and Molecular Biology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, JapanThese authors contributed equally to this work Search for more papers by this author Fumiko Arima-Yoshida Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan Institute of Clinical Medicine and Research, The Jikei University School of Medicine, Tokyo, JapanThese authors contributed equally to this work Search for more papers by this author Mitsutaka Kadota orcid.org/0000-0002-1674-6697 Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, JapanThese authors contributed equally to this work Search for more papers by this author Tomoe Ichikawa Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Department of Infection Control Science, Meiji Pharmaceutical University, Kiyose, Japan Search for more papers by this author Kazuyuki Yamada School of Management, Shizuoka Sangyo University, Iwata, Japan RIKEN, Wako, Japan Search for more papers by this author Akiko Watanabe Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Hisako Ohba Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Kaori Tanaka Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan Search for more papers by this author Akihiro Nakaya Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan Search for more papers by this author Yasue Horiuchi orcid.org/0000-0003-0597-2514 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Yoshimi Iwayama Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan RIKEN, Wako, Japan Search for more papers by this author Manabu Toyoshima orcid.org/0000-0001-7291-8935 Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Itone Ogawa Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan Search for more papers by this author Chie Shimamoto-Mitsuyama orcid.org/0000-0002-8524-974X Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Motoko Maekawa Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Shabeesh Balan orcid.org/0000-0002-1098-1290 Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Makoto Arai Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Mitsuhiro Miyashita Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Kazuya Toriumi orcid.org/0000-0002-8593-3269 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Yayoi Nozaki Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Rumi Kurokawa RIKEN, Wako, Japan Search for more papers by this author Kazuhiro Suzuki Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Akane Yoshikawa Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Tomoko Toyota orcid.org/0000-0003-0034-309X Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Toshihiko Hosoya orcid.org/0000-0001-8559-8344 RIKEN, Wako, Japan Biomedical Business Center, RICOH Company, LTD, Kawasaki, Japan Search for more papers by this author Hiroyuki Okuno orcid.org/0000-0001-6237-6503 Laboratory of Biochemistry and Molecular Biology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan Search for more papers by this author Haruhiko Bito orcid.org/0000-0001-6315-9594 Department of Neurochemistry, the University of Tokyo, Graduate School of Medicine, Tokyo, Japan Search for more papers by this author Masanari Itokawa orcid.org/0000-0003-4433-8030 Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan Search for more papers by this author Shigehiro Kuraku orcid.org/0000-0003-1464-8388 Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan Search for more papers by this author Toshiya Manabe Corresponding Author [email protected] orcid.org/0000-0002-5359-6704 Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan Search for more papers by this author Takeo Yoshikawa Corresponding Author [email protected] orcid.org/0000-0003-2791-6679 Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan Search for more papers by this author Author Information Tetsuo Ohnishi *,1, Yuji Kiyama2,3, Fumiko Arima-Yoshida2,4, Mitsutaka Kadota5, Tomoe Ichikawa6,7, Kazuyuki Yamada8,9, Akiko Watanabe1, Hisako Ohba1, Kaori Tanaka5, Akihiro Nakaya1,10, Yasue Horiuchi6, Yoshimi Iwayama1,9, Manabu Toyoshima1, Itone Ogawa2, Chie Shimamoto-Mitsuyama1, Motoko Maekawa1, Shabeesh Balan1, Makoto Arai6, Mitsuhiro Miyashita6, Kazuya Toriumi6, Yayoi Nozaki1, Rumi Kurokawa9, Kazuhiro Suzuki6, Akane Yoshikawa6, Tomoko Toyota1, Toshihiko Hosoya9,11, Hiroyuki Okuno3, Haruhiko Bito12, Masanari Itokawa6, Shigehiro Kuraku5, Toshiya Manabe *,2 and Takeo Yoshikawa *,1 1Laboratory for Molecular Psychiatry, RIKEN Center for Brain Science, Wako, Japan 2Division of Neuronal Network, Institute of Medical Science, the University of Tokyo, Tokyo, Japan 3Laboratory of Biochemistry and Molecular Biology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan 4Institute of Clinical Medicine and Research, The Jikei University School of Medicine, Tokyo, Japan 5Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Kobe, Japan 6Schizophrenia Research Project, Tokyo Metropolitan Institute of Medical Sciences, Shizuoka, Japan 7Department of Infection Control Science, Meiji Pharmaceutical University, Kiyose, Japan 8School of Management, Shizuoka Sangyo University, Iwata, Japan 9RIKEN, Wako, Japan 10Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan 11Biomedical Business Center, RICOH Company, LTD, Kawasaki, Japan 12Department of Neurochemistry, the University of Tokyo, Graduate School of Medicine, Tokyo, Japan *Corresponding author Lead contact . Tel: +81 48 467 5946; Fax: +81 48 467 5946; E-mail: [email protected] *Corresponding author. Tel: +81 3 5449 5517; Fax: +81 3 5449 5794; E-mail: [email protected] *Corresponding author. Tel: +81 48 467 5968; Fax: +81 48 467 7462; E-mail: [email protected] EMBO Mol Med (2021)13:e12574https://doi.org/10.15252/emmm.202012574 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Genomic defects with large effect size can help elucidate unknown pathologic architecture of mental disorders. We previously reported on a patient with schizophrenia and a balanced translocation between chromosomes 4 and 13 and found that the breakpoint within chromosome 4 is located near the LDB2 gene. We show here that Ldb2 knockout (KO) mice displayed multiple deficits relevant to mental disorders. In particular, Ldb2 KO mice exhibited deficits in the fear-conditioning paradigm. Analysis of the amygdala suggested that dysregulation of synaptic activities controlled by the immediate early gene Arc is involved in the phenotypes. We show that LDB2 forms protein complexes with known transcription factors. Consistently, ChIP-seq analyses indicated that LDB2 binds to > 10,000 genomic sites in human neurospheres. We found that many of those sites, including the promoter region of ARC, are occupied by EGR transcription factors. Our previous study showed an association of the EGR family genes with schizophrenia. Collectively, the findings suggest that dysregulation in the gene expression controlled by the LDB2-EGR axis underlies a pathogenesis of subset of mental disorders. Synopsis The LDB2 gene is mapped in the breakpoint of a balanced chromosomal translocation seen in a patient with schizophrenia. This study provides a role of LDB2 and transcriptional regulation exerted by the "LDB2-EGR axis" in the pathogenesis of mental disorders. LDB2 forms protein complexes with known transcription regulators such as the LHX and SSBP family proteins. ChIP-seq analysis identified more than 10,000 LDB2 binding sites, which contained consensus DNA binding sequence for the EGR family proteins at high proportion. Dysregulation of LDB2 induces modulation in synaptic function via synapse-related genes such as ARC. A potential role of the "LDB-EGR axis" in the pathogenesis of mental disorders is suggested. The paper explained Problem The pathogenesis of mental disorders including schizophrenia remains largely unknown. Our group reported a schizophrenia patient who harbored a balanced chromosomal translocation t(4;13)(p16.1;q21.31) and recently identified the LDB2 (Lim Domain-binding 2) gene in the breakpoint at chromosome 4 by next-generation sequencing. However, a potential role of the LDB2 gene, which encodes a putative transcription regulator without DNA-binding domains, in disease mechanism remains elusive. Results Ldb2 knockout (KO) mice displayed multiple behavioral abnormalities including hyperactivity, enhanced sensitivities to a psychostimulant and a hallucinogenic drug, and deficits in fear-conditioning test. Some of these were alleviated by the treatment with an antipsychotic or with a mood stabilizer lithium, indicating that the Ldb2 KO mice satisfy both face validity and predictive validity as a model for schizophrenia and bipolar mania. Molecular analyses revealed that LDB2 binds to multiple transcription factors and transcription regulatory factors and that Ldb2 regulates the expression of immediate early gene Arc in the amygdala. ChIP-seq analyses suggested that LDB2 cooperates with the EGR transcription factors, whose genes are associated with schizophrenia, to control synaptogenesis-related genes including Arc/ARC. These results suggest that the LDB2-EGR signaling cascade has a role in psychiatric diseases including schizophrenia and bipolar disorder. Impact This study revealed a potential role of transcription factor cooperation, the "LDB2-EGR axis", in the pathogenesis of schizophrenia and bipolar disorder, providing a novel insight into the mechanism of mental disorders. Introduction Schizophrenia, a chronic and debilitating mental disorder, is characterized by a variety of symptoms, including delusions, hallucinations, affective flattening, and cognitive deficits. To date, numerous "risk" genes have been reported by genome-wide association studies (GWAS; Bray & O'Donovan, 2019; Dennison et al, 2019) and exome sequencing (Bray & O'Donovan, 2019). However, the effect size of most of these genes is small, and it remains unclear how each genetic variation constitutes an integrative pathogenic architecture. On the other hand, a causal relationship is perspicuous in exceptional cases with gross chromosomal abnormalities. For instance, a large Scottish pedigree with multiple family members diagnosed with psychiatric disorders, including schizophrenia, bipolar disorder, and recurrent depression, has been described in the literature (Blackwood et al, 2001). Importantly, most of the subjects who developed psychiatric symptoms are shown to harbor the balanced translocation t(1;11)(q42.1;q14.3) (Blackwood et al, 2001). Since this translocation directly disrupts the protein coding gene termed disrupted in schizophrenia 1 (DISC1) in chromosome 1, researchers have pursued the pathological mechanism caused by the disruption of DISC1 (Porteous et al, 2006; Mackie et al, 2007; Korth, 2009; Tomoda et al, 2017). In 2004, our group reported a patient with schizophrenia who harbored a balanced chromosomal translocation t(4;13)(p16.1;q21.31) (Itokawa et al, 2004). No individuals with psychiatric symptoms or with the same chromosomal translocation were found within the second-degree relatives of the proband, thereby supporting that the translocation was causal for the proband (Itokawa et al, 2004). Subsequently, we set out to determine the exact breakpoints on chromosomes 4 and 13 by using next-generation DNA-sequencing analysis in combination with fluorescent in situ hybridization (FISH) experiments (Horiuchi et al, 2020). The breakpoint on chromosome 13 is within the so-called "gene desert" interval where no known genes have been mapped. The breakpoint on chromosome 4 is mapped to the 32.6-kbp upstream region of a gene encoding a putative transcription regulator lacking a DNA-binding domain, LIM domain-binding 2 (LDB2), also called CLIM1 (Appendix Fig S1). By reanalyzing the NGS data (Horiuchi et al, 2020) carefully, we found that the proband's genome harbors large deletions in two chromosomes: chromosome 6 (10,657,982–10,660,876; 2,885 bp) and chromosome X (55,702,373–55,709,904; 7,447 bp). Due to unavailability of genomic DNAs from the proband's patients, we were not able to determine whether these deletions were de novo or inherited from one of the proband's parents, who manifested no psychiatric symptoms. However, no known genes are mapped to these two deleted regions. Moreover, to our best knowledge, no reports have identified these regions as susceptibility loci for schizophrenia or bipolar disorder. Although the breakpoint does not disrupt LDB2, LDB2 and the breakpoint are located on the same topologically associating domain (TAD) region (Szalaj & Plewczynski, 2018; Appendix Fig S1) in the human brain (adult dorsolateral prefrontal cortex; PsychEncode; Wang et al, 2018). Hence, the chromosomal break should disrupt the TAD organization, in turn, affecting the interaction between the regulatory elements of LDB2 and the gene expression. Schizophrenia and bipolar disorder share genetic risk elements. Intriguingly Horiuchi et al (2020) detected rare missense variants (T83N and P170L) in bipolar patients, supporting a common role of LDB2 across mental disorders. Mammals have a close homolog to LDB2, namely LDB1 (Matthews & Visvader, 2003; Love et al, 2014), and many studies have reported the role of LDB1 in multiple biological processes (Love et al, 2014; Costello et al, 2015; Ediger et al, 2017; de Melo et al, 2018; Kinare et al, 2019). In contrast, little is known about the biological functions of LDB2, especially in the brain, while the protein has been regarded as a layer V-specific expression marker in the cerebral cortex (Bulchand et al, 2003; Molyneaux et al, 2007). In the current study, we aimed to clarify the causal relationship between the LDB2 deficiency and the pathogenesis of mental disorders by phenotyping Ldb2 knockout mice and harnessing manifold approaches including behavioral, electrophysiological, biochemical, and ChIP (chromatin immunoprecipitation)-seq analyses. The present study reveals a major molecular pathway that leverages LDB2 and immediate early genes, in the pathogenesis of mental disorders including schizophrenia and bipolar disorder. Results LDB2 is expressed in neurons of restricted regions in the brain We first attempted to examine expression of the LDB2 gene in the proband's patient. As a biological sample from the patient, only Epstein–Barr virus-transformed lymphoblastoid cells were available. Since the LDB2 transcripts were not detected in those cells, we established iPS cells from those cells (LiPS; Toyoshima et al, 2016) from the patient and a healthy control (39 y.o, male). We observed reduced LDB2 expression in the patient compared to the control subject in iPS cells and iPS cell-derived neurospheres (Appendix Fig S2), suggesting the chromosomal break in the patient negatively affected expression of LDB2. LDB2 is a protein that lacks known DNA-binding domains but has a putative self-dimerization domain, a nuclear-localization signal, and a Lim (Lin11, Isl1, and Mec3)-binding domain that potentially mediates binding to the self and other proteins through the Lim domain (Fig 1A). Since basic information on the LDB2 protein was limited, we first examined the tissue distribution of LDB2 in a mouse with a self-made antibody raised against the N-terminal portion of LDB2 (Fig 1 A and B) using rabbits. This region is divergent between LDB1 and LDB2 (Fig 1B), minimizing the possibility of cross-reaction of the antibody to LDB1. A Western blot analysis showed a tissue-specific and brain region-specific expression of LDB2 with apparent molecular masses of 48 and 35 kDa (Fig 1C). The lower band likely corresponds to a splice variant that lacks the C-terminal Lim-interaction domain (Tran et al, 2006; Fig 1A, bottom). These two bands disappeared in the tissue from the Ldb2 knockout (KO) mice, indicating that these two bands correspond to the Ldb2 gene products (see the next section). The expression of LDB2 in the brain was evident in the frontal cortex, hippocampus, and midbrain, but not in the cerebellum or brain stem (Fig 1C). While the 48-kDa band was also seen in the lung, the other tissues examined showed no discrete band. Immunohistochemical analyses using a rat monoclonal anti-Ldb2 antibody (clone 4-1F) revealed that LDB2 is expressed exclusively in the nuclei of neurons in the brain (Fig 1D–G). In the cerebral cortex, > 80% of LDB2-positive cells were NeuN-positive in the layers II/III, V, and VI, showing neuron-selective expression of LDB2 (Fig 1D, F, and G). Here, it is of note that most of Neu-positive cells in the layers I and IV were LDB2-negative. In the hippocampus, expression appeared to be restricted in the pyramidal cell layer in the adult stage (Fig EV1F). In addition, a selective expression was seen in neurons in the amygdala (Fig 1E, right panel). Consistent with the Western blot data, signals were rarely seen in the olfactory bulb, striatum, thalamus, or cerebellum (Fig EV1F), suggesting the region-specific roles of LDB2 in the brain. We showed most of the LDB2 signals disappeared in the cerebral cortex, hippocampus, and amygdala from Ldb2 KO mice (Fig EV1-EV5), evidencing specificity of the antibody used (Fig EV1F). Figure 1. Expression of Ldb2 in the specific regions in the mouse brains A. Schematic representation of the human LDB2 protein. Positions for the variants found in bipolar patients are also shown. The shorter isoform predicted from the splice variant (Tran et al, 2006) is shown below. B. Multiple alignments of the N-terminal regions of the human and mouse LDB family. Please note that the N-terminal regions are highly diverged between LDB1 and LDB2. The bar indicated the position for the peptide for antibody production. C. Tissue distribution of the LDB2 protein. Representative Western blot image is shown. Yellow asterisks indicate uncharacterized bands. D. Expression of Ldb2 in the cerebral cortex. DAPI-stained nuclei visualized (right) in the cerebral cortex. E. Expression of LDB2 in the amygdala. LA; lateral amygdala, BLA; basolateral amygdala, Ce; central nucleus of amygdala. F, G. Expression of LDB2 in neurons. The merged images obtained with LDB2 (stained in green) and NeuN (stained in red) antibodies are shown for cerebral cortex layers I-VI and the amygdala (F). Please note that most of LDB2-positive cells are NeuN-positive. (G). NeuN-positive cells/LDB2-positive cells (left) and LDB2-positive cells/NeuN-positive cells were counted in cerebral cortex layers I-VI. Data are shown as means ± SD (10 independent view fields/group). Download figure Download PowerPoint Click here to expand this figure. Figure EV1. Basic Characterization of Ldb2 KO mice Genotyping of WT, heterozygous (HET), and homozygous (KO) mice by genomic PCR using DNA extracted from the tails. Quantitative RT–PCR did not detect the Ldb2 transcripts in the bran from KO. Note that no compensatory upregulation of the Ldb1 transcripts was seen in KO. Loss of the 48 and 35 kDa bands detected by the LDB2/Ldb2 polyclonal antibody in the two brain region from KO in Western blot analysis. No gross abnormalities were seen in KO. No apparent abnormalities were seen in the histological architecture of the brain from KO. Hematoxylin and eosin (HE) and Nissl staining were conducted using sagittal sections of the brains. Magnified image (Nissl staining) of the hippocampus is presented at bottom. Brain sections (the cerebral cortex, hippocampus, amygdala, olfactory bulb, striatum, thalamus, and cerebellum) form WT and KO mice were stained with anti-Ldb2 antibody. Download figure Download PowerPoint Click here to expand this figure. Figure EV2. mEPSCs recorded in LA neurons of Venus-positive or -negative cells in Ldb2 KO mice Sample traces of mEPSCs from LA neurons in brain slices of AV-WT/ Venus+, AV-WT/ Venus-, AV-KO/ Venus+ and AV-KO/ Venus- mice. Neither median amplitudes (upper panel) nor mean frequency (lower panel) of mEPSCs was statistically different between the genotypes. Scatter plots of Venus fluorescence intensities of patch-clamped cells. There was no significant difference in fluorescent intensities of Venus-positive cells between AV-KO mice and their AV-WT littermates (t-test, n = 11/group). Download figure Download PowerPoint Click here to expand this figure. Figure EV3. A schematic representation of behavioral experiments and Venus fluorescence counterstained by cell markers in the LA A schematic representation of the experimental procedure. Mice were moved from their home cage to the experimental room at least 3 h before conditioning. Mice of the Unpaired and Paired groups received conditioning (see the Methods section), while mice of the Naïve group were kept in their home cage in the experimental room. Mice were then transcardially perfused with 4% PFA 3 h after the fear conditioning. A typical Venus fluorescence image of the basolateral complex of the amygdala in AV-WT mice of the Paired group. The boxed areas in the left panel are enlarged in the middle and right panels. Representative examples of CaMKIIα-positive (upper panels), CaMKIIα-negative (middle panels) and GAD67-positive (bottom panels) neurons with Venus fluorescence in the LA. Stacked bar charts of the percentage of CaMKIIα-positive and -negative cells with Venus fluorescen
Genome-wide association studies have been performed to identify common genetic variants associated with hepatitis B (HB). However, little is known about copy number variations (CNVs) in HB. In this study, we performed a genome-wide CNV analysis between 1830 healthy controls and 1031 patients with HB infection after quality control. Using signal calling by the Axiom Analysis Suite and CNV detection by PennCNV software, we obtained a total of 4494 CNVs across all individuals. The genes with CNVs that were found only in the HB patients were associated with the immune system, such as antigen processing. A gene-level CNV association test revealed statistically significant CNVs in the contactin 6 (CNTN6) gene. Moreover, we also performed gene-level CNV association tests in disease subgroups, including hepatocellular carcinoma patients, liver cirrhosis patients, and HBV carriers, including asymptomatic carriers and patients with HBV-derived chronic hepatitis. Our findings from germline cells suggested that patient-specific CNVs may be inherent genetic risk factors for HB.
SUMMARY We address the problem of computing various types of expressive tests for decision trees and regression trees. Using expressive tests is promising, because it may improve the prediction accuracy of trees, and it may also provide us some hints on scientific discovery. The drawback is that computing an optimal test could be costly. We present a unified framework to approach this problem, and we revisit the design of efficient algorithms for computing important special cases. We also prove that it is intractable to compute an optimal conjunction or dis
Non-alcoholic fatty liver disease (NAFLD) progresses because of the interaction between numerous genes. Thus, we carried out a weighted gene coexpression network analysis to identify core gene networks and key genes associated with NAFLD progression.We enrolled 39 patients with mild NAFLD (fibrosis stages 0-2) and 21 with advanced NAFLD (fibrosis stages 3-4). Total RNA was extracted from frozen liver biopsies, and sequenced to capture a large dynamic range of expression levels.A total of 1777 genes differentially expressed between mild and advanced NAFLD (q-value <0.05) clustered into four modules. One module was enriched for genes that encode cell surface or extracellular matrix proteins, and are involved in cell adhesion, proliferation, and signaling. This module formed a scale-free network containing four hub genes (PAPLN, LBH, DPYSL3, and JAG1) overexpressed in advanced NAFLD. PAPLN is a component of the extracellular matrix, LBH and DPYSL3 are reported to be tumor suppressors, and JAG1 is tumorigenic. Another module formed a random network, and was enriched for genes that accumulate in the mitochondria. These genes were downregulated in advanced NAFLD, reflecting impaired mitochondrial function. However, the other two modules did not form unambiguous networks. KEGG analysis indicated that 71 differentially expressed genes were involved in "pathways in cancer". Strikingly, expression of half of all differentially expressed genes was inversely correlated with methylation of CpG sites (q-value <0.05). Among clinical parameters, serum type IV collagen 7 s was most strongly associated with the epigenetic status in NAFLD.Newly identified core gene networks suggest that the NAFLD liver undergoes mitochondrial dysfunction and fibrosis, and acquires tumorigenic potential epigenetically. Our data provide novel insights into the pathology and etiology of NAFLD progression, and identify potential targets for diagnosis and treatment.
Abstract A major challenge in current exome sequencing in autosomal recessive (AR) families is the lack of an effective method to prioritize single-nucleotide variants (SNVs). AR families are generally too small for linkage analysis and length of homozygous regions is unreliable for identification of causative variants. Various common filtering steps usually result in a list of candidate variants that cannot be narrowed down further or ranked. To prioritize shortlisted SNVs we consider each homozygous candidate variant together with a set of SNVs flanking it. We compare the resulting array of genotypes between an affected family member and a number of control individuals and argue that, in a family, differences between family member and controls should be larger for a pathogenic variant and SNVs flanking it than for a random variant. We assess differences between arrays in two individuals by the Hamming distance and develop a suitable test statistic, which is expected to be large for a causative variant and flanking SNVs. We prioritize candidate variants based on this statistic and applied our approach to six patients with known pathogenic variants and found these to be in the top 2 to 10 percentiles of ranks.
The LAMA5 gene encodes laminin α5, an indispensable component of glomerular basement membrane and other types of basement membrane. A homozygous pathological variant in LAMA5 is known to cause a systemic developmental syndrome including glomerulopathy. However, the roles of heterozygous LAMA5 gene variants in human renal and systemic diseases have remained unclear. We performed whole-exome sequencing analyses of a family with slowly progressive nephropathy associated with hereditary focal segmental glomerulosclerosis, and we identified what we believe to be a novel probable pathogenic variant of LAMA5, NP_005551.3:p.Val3687Met. In vitro analyses revealed cell type-dependent changes in secretion of variant laminin α5 laminin globular 4-5 (LG4-5) domain. Heterozygous and homozygous knockin mice with a corresponding variant of human LAMA5, p.Val3687Met, developed focal segmental glomerulosclerosis-like pathology with reduced laminin α5 and increased glomerular vinculin levels, which suggested that impaired cell adhesion may underlie this glomerulopathy. We also identified pulmonary defects such as bronchial deformity and alveolar dilation. Reexaminations of the family revealed phenotypes compatible with reduced laminin α5 and increased vinculin levels in affected tissues. Thus, the heterozygous p.Val3687Met variant may cause a new syndromic nephropathy with focal segmental glomerulosclerosis through possibly defective secretion of laminin α5. Enhanced vinculin may be a useful disease marker.
Objective: This study aimed to investigate whether interactions between multiple serum cytokines may be implicated in the mechanism of action (MOA) of sublingual immunotherapy (SLIT) for Japanese cedar pollinosis. Methods: A Tokyo Metropolitan Bureau of Social Welfare and Public Health-initiated clinical study of active SLIT involving 202 patients with Japanese cedar pollinosis was jointly conducted by Tokyo Metropolitan Institute of Medical Science and Nippon Medical School between 2006 and 2008. Fifty target cytokines were quantified in serum samples collected at 6 times from baseline to the end of the study, for 300 cytokine measurements in total, using Bio-Plex Pro Human Cytokine Group I/II Panels. Therapeutic outcome was assessed based on nasal symptom scores and quality-of-life questionnaire results. Results: Fifty-five percent of patients were free of symptoms or reported symptomatic improvements by 2 grades or greater after 2 years of SLIT treatment, while 27% showed no improvement or worsening of symptoms. Thirty-eight patients who benefited the most from treatment (responders) as well as 37 patients who benefited the least from treatment (non-responders) were identified and their serum cytokine profiles were compared. Cluster analysis of the 300 cytokine measurements identified 6 cytokine clusters that were strongly correlated with a positive response to treatment, and this correlation was consistent throughout the treatment. Conclusion: Certain cytokine clusters are strongly correlated with a positive therapeutic outcome, suggesting they have a role in the MOA of immunotherapy.
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