Genotype–Phenotype Association Studies of Chromosome 8P Inverted Duplication Deletion Syndrome
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Cellular and Synaptic Network Defects in Autism
Cellular and synaptic network defects in autism The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Peca, Joao, and Guoping Feng. “Cellular and Synaptic Network Defects in Autism.” Current Opinion in Neurobiology 22, no. 5 (October 2012): 866–872. As Published http://dx.doi.org/10.1016/j.conb.2012.02.015 Publisher Elsevier Version Author's final manuscript Citable link http://hdl.handle.net/1721.1/102179 Terms of Use Creative Commons Attribution-Noncommercial-NoDerivatives Detailed Terms http://creativecommons.org/licenses/by-nc-nd/4.0/ NIH Public Access Author Manuscript Curr Opin Neurobiol. Author manuscript; available in PMC 2013 October 01. Published in final edited form as: Curr Opin Neurobiol. 2012 October ; 22(5): 866–872. doi:10.1016/j.conb.2012.02.015. Cellular and synaptic network defects in autism João Peça1 and Guoping Feng1,2 $watermark-text1McGovern $watermark-text Institute $watermark-text for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA 2Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA 02142, USA Abstract Many candidate genes are now thought to confer susceptibility to autism spectrum disorder (ASD). Here we review four interrelated complexes, each composed of multiple families of genes that functionally coalesce on common cellular pathways. We illustrate a common thread in the organization of glutamatergic synapses and suggest a link between genes involved in Tuberous Sclerosis Complex, Fragile X syndrome, Angelman syndrome and several synaptic ASD candidate genes. When viewed in this context, progress in deciphering the molecular architecture of cellular protein-protein interactions together with the unraveling of synaptic dysfunction in neural networks may prove pivotal to advancing our understanding of ASDs. -
Genetic Analysis of the Calcineurin Pathway Identifies Members of the EGR Gene Family, Specifically EGR3, As Potential Susceptibility Candidates in Schizophrenia
Genetic analysis of the calcineurin pathway identifies members of the EGR gene family, specifically EGR3, as potential susceptibility candidates in schizophrenia Kazuo Yamada*, David J. Gerber†, Yoshimi Iwayama*, Tetsuo Ohnishi*, Hisako Ohba*, Tomoko Toyota*, Jun Aruga‡, Yoshio Minabe*§, Susumu Tonegawa†¶, and Takeo Yoshikawa*ʈ** Laboratories for *Molecular Psychiatry and ‡Comparative Neural Development, RIKEN Brain Science Institute, Saitama 351-0198, Japan; †Howard Hughes Medical Institute and RIKEN–MIT Neuroscience Research Center, The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139; §Department of Psychiatry and Neurology, Kanazawa University School of Medicine, Ishikawa 920-8641, Japan; and ʈCore Research for Evolutional Science and Technology, Japan Science and Technology Agency, Saitama 332-0012, Japan Contributed by Susumu Tonegawa, December 7, 2006 (sent for review September 22, 2006) The calcineurin cascade is central to neuronal signal transduction, cineurin is particularly enriched in the CNS, where it plays a critical and genes in this network are intriguing candidate schizophrenia role in the regulation of a diverse array of neuronal functions (5, 6). susceptibility genes. To replicate and extend our previously re- Interestingly, calcineurin is positioned downstream of dopaminer- ported association between the PPP3CC gene, encoding the cal- gic signaling (7) and is involved in NMDA receptor-mediated cineurin catalytic ␥-subunit, and schizophrenia, we examined 84 synaptic plasticity (8) and could therefore provide an important SNPs from 14 calcineurin-related candidate genes for genetic as- functional link between these two neurotransmitter systems. To sociation by using 124 Japanese schizophrenic pedigrees. Four of further explore the involvement of calcineurin dysfunction in these genes (PPP3CC, EGR2, EGR3, and EGR4) showed nominally schizophrenia, we have tested for genetic association of a subset of significant association with schizophrenia. -
Supp Material.Pdf
Supplemental Materials Genome-wide Mapping of SMAD Target genes Reveals the Role of BMP Signaling in Embryonic Stem Cell Fate Determination Teng Fei1#, Kai Xia2#, Zhongwei Li1^, Bing Zhou2^, Shanshan Zhu2^, Hua Chen1, Jianping Zhang1, Zhang Chen2, Huasheng Xiao3, Jing-Dong J. Han2*, Ye-Guang Chen1* Supplemental Methods Supplemental References Supplemental Figures S1–S17 Supplemental Tables S1-S9 1 Supplemental Methods Cell culture and antibodies Murine R1 ES cells were first plated on mitomycin-treated murine embryonic fibroblasts (MEFs) and grown under typical ES cell conditions (DMEM supplemented with 15% fetal calf serum, leukemia inhibitory factor (LIF), non-essential amino acids, GlutaMax-I (Invitrogen Gibco), beta-mercaptoethanol and penicillin/streptomycin. For ChIP assay, cells were cultured on gelatinized tissue culture plates for two passages to eliminate MEFs. KO-DMEM and Knockout serum replacement (Invitrogen Gibco) were used to substitute DMEM and fetal calf serum for feeder free culture. For ChIP experiments and immunoblotting, we used affinity-purified SMAD1/5 and SMAD4 antibodies that can recognize a specific band corresponding to endogenous SMAD proteins in R1 ES cells (Fig. S1A). Rabbit anti-SMAD1/5 antibody was generated with recombinant human SMAD1-linker (aa145-267)-His, and rabbit anti-SMAD4 antibody with recombinant human SMAD4-linker (aa144-316)-His. Anti-SMAD1/5 antibody can recognize both overexpressed SMAD1 and SMAD5 proteins but minimally SMAD8 (Fig. S1B). Phospho-SMAD1/5 antibody was purchased from Chemicon International (AB3848) and anti-nestin antibody from Chemicon International (MAB353). H3K27me3 antibody (ab6002) and histone H3 antibody (ab1791) were from Abcam. GFP (SC-8334), GST (SC-138), His (SC-803) antibody were from Santa Cruz Biotech. -
SPATA33 Localizes Calcineurin to the Mitochondria and Regulates Sperm Motility in Mice
SPATA33 localizes calcineurin to the mitochondria and regulates sperm motility in mice Haruhiko Miyataa, Seiya Ouraa,b, Akane Morohoshia,c, Keisuke Shimadaa, Daisuke Mashikoa,1, Yuki Oyamaa,b, Yuki Kanedaa,b, Takafumi Matsumuraa,2, Ferheen Abbasia,3, and Masahito Ikawaa,b,c,d,4 aResearch Institute for Microbial Diseases, Osaka University, Osaka 5650871, Japan; bGraduate School of Pharmaceutical Sciences, Osaka University, Osaka 5650871, Japan; cGraduate School of Medicine, Osaka University, Osaka 5650871, Japan; and dThe Institute of Medical Science, The University of Tokyo, Tokyo 1088639, Japan Edited by Mariana F. Wolfner, Cornell University, Ithaca, NY, and approved July 27, 2021 (received for review April 8, 2021) Calcineurin is a calcium-dependent phosphatase that plays roles in calcineurin can be a target for reversible and rapidly acting male a variety of biological processes including immune responses. In sper- contraceptives (5). However, it is challenging to develop molecules matozoa, there is a testis-enriched calcineurin composed of PPP3CC and that specifically inhibit sperm calcineurin and not somatic calci- PPP3R2 (sperm calcineurin) that is essential for sperm motility and male neurin because of sequence similarities (82% amino acid identity fertility. Because sperm calcineurin has been proposed as a target for between human PPP3CA and PPP3CC and 85% amino acid reversible male contraceptives, identifying proteins that interact with identity between human PPP3R1 and PPP3R2). Therefore, identi- sperm calcineurin widens the choice for developing specific inhibitors. fying proteins that interact with sperm calcineurin widens the choice Here, by screening the calcineurin-interacting PxIxIT consensus motif of inhibitors that target the sperm calcineurin pathway. in silico and analyzing the function of candidate proteins through the The PxIxIT motif is a conserved sequence found in generation of gene-modified mice, we discovered that SPATA33 inter- calcineurin-binding proteins (8, 9). -
Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases. -
Broad Poster Vivek
A novel computational method for finding regions with copy number abnormalities in cancer cells Vivek, Manuel Garber, and Mike Zody Broad Institute of MIT and Harvard, Cambridge, MA, USA Introduction Results Cancer can result from the over expression of oncogenes, genes which control and regulate cell growth. Sometimes oncogenes increase in 1 2 3 activity due to a specific genetic mutation called a translocation (Fig 1). SMAD4 – a gene known to be deleted in pancreatic COX10 – a gene deleted in cytochrome c oxidase AK001392 – a hereditary prostate cancer protein This translocation allows the oncogene to remain as active as its paired carcinoma deficiency, known to be related to cell proliferation gene. Amplification of this mutation can occur, thereby creating the proper conditions for uncontrolled cell growth; consequently, each Results from Analysis Program Results from Analysis Program Results from Analysis Program component of the translocation will amplify in similar quantities. In this mutation, the chromosomal region containing the oncogene displaces to Region 1 Region 2 R2 Region 1 Region 2 R2 Region 1 Region 2 R2 a region on another chromosome containing a gene that is expressed Chr18:47044749-47311978 Chr17:13930739-14654741 0.499070821478475 Chr17:13930739-14654741 Chr18:26861790-27072166 0.47355172850856 Chr17:12542326-13930738 Chr8:1789292-1801984 0.406208680312004 frequently. Actual region containing gene Actual region containing gene Actual region containing gene chr18: 45,842,214 - 48,514,513 chr17: 13,966,862 - 14,068,461 chr17: 12,542,326 - 13,930,738 Fig 1. Two chromosomal regions (abcdef and ghijk) are translocating to create two new regions (abckl and ghijedf). -
Pnas.201413825SI.Pdf
Supporting Information Impens et al. 10.1073/pnas.1413825111 13 15 13 15 SI Methods beling) (Silantes Gmbh), or C6 N2 L-lysine HCl and C6 N4 L- Plasmids. pSG5-His6-SUMO1 plasmid encodes the N-terminal arginine HCl (heavy labeling) (Silantes Gmbh). L-Lysine HCl was His6-tagged mature Small ubiquitin modifier 1 (SUMO1) isoform added at its normal concentration in DMEM (146 mg/L), but the (kind gift of A. Dejean, Institut Pasteur, Paris). The pSG5-His6- concentration of L-arginine HCl was reduced to 25 mg/L (30% of SUMO1 T95R mutat was derived from this plasmid using PCR the normal concentration in DMEM) to prevent metabolic con- mutagenesis. pSG5-His6-SUMO2 was obtained by inserting the version of arginine to proline (4). Cells were kept for at least six cDNA corresponding to the human mature SUMO2 isoform population doublings to ensure complete incorporation of the la- with an N-terminal His6 tag in the pSG5 vector (Stratagene). beled lysine and arginine. 2 The pSG5-His6-SUMO2 T91R mutant was derived from this For transfections, cells were seeded in 75-cm flasks or in 6- or plasmid by PCR mutagenesis. N-terminally HA-tagged human 24-well plates at a density of 2.7 × 106 cells per flask or 3 × 105 or cDNA of ZBTB20 (Zinc finger and BTB domain containing 0.5 × 105 cells per well, respectively. The next day cells were 20) isoform 2 (UniProt identifier Q9HC78-2), HMBOX1 (Ho- transfected with Lipofectamine LTX reagents (Invitrogen) (20 μg meobox containing protein 1) isoform 1 (HMBOX1A) (UniProt of DNA per flask, 3.5 μg per well in the six-well plates, or 0.75 μg identifier Q6NT76-1), NACC1 (Nucleus accumbens-associated per well in the 24-well plates) for 48 h. -
A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus
Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated. -
Exploring Prostate Cancer Genome Reveals Simultaneous Losses of PTEN, FAS and PAPSS2 in Patients with PSA Recurrence After Radical Prostatectomy
Int. J. Mol. Sci. 2015, 16, 3856-3869; doi:10.3390/ijms16023856 OPEN ACCESS International Journal of Molecular Sciences ISSN 1422-0067 www.mdpi.com/journal/ijms Article Exploring Prostate Cancer Genome Reveals Simultaneous Losses of PTEN, FAS and PAPSS2 in Patients with PSA Recurrence after Radical Prostatectomy Chinyere Ibeawuchi 1, Hartmut Schmidt 2, Reinhard Voss 3, Ulf Titze 4, Mahmoud Abbas 5, Joerg Neumann 6, Elke Eltze 7, Agnes Marije Hoogland 8, Guido Jenster 9, Burkhard Brandt 10 and Axel Semjonow 1,* 1 Prostate Center, Department of Urology, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany; E-Mail: [email protected] 2 Center for Laboratory Medicine, University Hospital Muenster, Albert-Schweitzer-Campus 1, Gebaeude 1A, Muenster D-48149, Germany; E-Mail: [email protected] 3 Interdisciplinary Center for Clinical Research, University of Muenster, Albert-Schweitzer-Campus 1, Gebaeude D3, Domagkstrasse 3, Muenster D-48149, Germany; E-Mail: [email protected] 4 Pathology, Lippe Hospital Detmold, Röntgenstrasse 18, Detmold D-32756, Germany; E-Mail: [email protected] 5 Institute of Pathology, Mathias-Spital-Rheine, Frankenburg Street 31, Rheine D-48431, Germany; E-Mail: [email protected] 6 Institute of Pathology, Klinikum Osnabrueck, Am Finkenhuegel 1, Osnabrueck D-49076, Germany; E-Mail: [email protected] 7 Institute of Pathology, Saarbrücken-Rastpfuhl, Rheinstrasse 2, Saarbrücken D-66113, Germany; E-Mail: [email protected] 8 Department -
Primate Specific Retrotransposons, Svas, in the Evolution of Networks That Alter Brain Function
Title: Primate specific retrotransposons, SVAs, in the evolution of networks that alter brain function. Olga Vasieva1*, Sultan Cetiner1, Abigail Savage2, Gerald G. Schumann3, Vivien J Bubb2, John P Quinn2*, 1 Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, U.K 2 Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK 3 Division of Medical Biotechnology, Paul-Ehrlich-Institut, Langen, D-63225 Germany *. Corresponding author Olga Vasieva: Institute of Integrative Biology, Department of Comparative genomics, University of Liverpool, Liverpool, L69 7ZB, [email protected] ; Tel: (+44) 151 795 4456; FAX:(+44) 151 795 4406 John Quinn: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK, [email protected]; Tel: (+44) 151 794 5498. Key words: SVA, trans-mobilisation, behaviour, brain, evolution, psychiatric disorders 1 Abstract The hominid-specific non-LTR retrotransposon termed SINE–VNTR–Alu (SVA) is the youngest of the transposable elements in the human genome. The propagation of the most ancient SVA type A took place about 13.5 Myrs ago, and the youngest SVA types appeared in the human genome after the chimpanzee divergence. Functional enrichment analysis of genes associated with SVA insertions demonstrated their strong link to multiple ontological categories attributed to brain function and the disorders. SVA types that expanded their presence in the human genome at different stages of hominoid life history were also associated with progressively evolving behavioural features that indicated a potential impact of SVA propagation on a cognitive ability of a modern human. -
FGFR1 Fusion and Amplification in a Solid Variant of Alveolar Rhabdomyosarcoma
Modern Pathology (2011) 24, 1327–1335 & 2011 USCAP, Inc. All rights reserved 0893-3952/11 $32.00 1327 FOXO1–FGFR1 fusion and amplification in a solid variant of alveolar rhabdomyosarcoma Jinglan Liu1,2, Miguel A Guzman1,2, Donna Pezanowski1, Dilipkumar Patel1, John Hauptman1, Matthew Keisling3, Steve J Hou2,3, Peter R Papenhausen4, Judy M Pascasio1,2, Hope H Punnett1,5, Gregory E Halligan2,6 and Jean-Pierre de Chadare´vian1,2 1Department of Pathology and Laboratory Medicine, St Christopher’s Hospital for Children, Philadelphia, PA, USA; 2Drexel University College of Medicine, Philadelphia, PA, USA; 3Department of Pathology and Laboratory Medicine, Hahnneman University Hospital, Philadelphia, PA, USA; 4Laboratory Corporation of America, The Research Triangle Park, NC, USA; 5Department of Pathology and Laboratory Medicine, Temple University School of Medicine, Philadelphia, PA, USA and 6Department of Pediatrics, Section of Oncology, St Christopher’s Hospital for Children, Philadelphia, PA, USA Rhabdomyosarcoma is the most common pediatric soft tissue malignancy. Two major subtypes, alveolar rhabdomyosarcoma and embryonal rhabdomyosarcoma, constitute 20 and 60% of all cases, respectively. Approximately 80% of alveolar rhabdomyosarcoma carry two signature chromosomal translocations, t(2;13)(q35;q14) resulting in PAX3–FOXO1 fusion, and t(1;13)(p36;q14) resulting in PAX7–FOXO1 fusion. Whether the remaining cases are truly negative for gene fusion has been questioned. We are reporting the case of a 9-month-old girl with a metastatic neck mass diagnosed histologically as solid variant alveolar rhabdomyosarcoma. Chromosome analysis showed a t(8;13;9)(p11.2;q14;9q32) three-way translocation as the sole clonal aberration. Fluorescent in situ hybridization (FISH) demonstrated a rearrangement at the FOXO1 locus and an amplification of its centromeric region. -
Supplemental Table 1. Complete Gene Lists and GO Terms from Figure 3C
Supplemental Table 1. Complete gene lists and GO terms from Figure 3C. Path 1 Genes: RP11-34P13.15, RP4-758J18.10, VWA1, CHD5, AZIN2, FOXO6, RP11-403I13.8, ARHGAP30, RGS4, LRRN2, RASSF5, SERTAD4, GJC2, RHOU, REEP1, FOXI3, SH3RF3, COL4A4, ZDHHC23, FGFR3, PPP2R2C, CTD-2031P19.4, RNF182, GRM4, PRR15, DGKI, CHMP4C, CALB1, SPAG1, KLF4, ENG, RET, GDF10, ADAMTS14, SPOCK2, MBL1P, ADAM8, LRP4-AS1, CARNS1, DGAT2, CRYAB, AP000783.1, OPCML, PLEKHG6, GDF3, EMP1, RASSF9, FAM101A, STON2, GREM1, ACTC1, CORO2B, FURIN, WFIKKN1, BAIAP3, TMC5, HS3ST4, ZFHX3, NLRP1, RASD1, CACNG4, EMILIN2, L3MBTL4, KLHL14, HMSD, RP11-849I19.1, SALL3, GADD45B, KANK3, CTC- 526N19.1, ZNF888, MMP9, BMP7, PIK3IP1, MCHR1, SYTL5, CAMK2N1, PINK1, ID3, PTPRU, MANEAL, MCOLN3, LRRC8C, NTNG1, KCNC4, RP11, 430C7.5, C1orf95, ID2-AS1, ID2, GDF7, KCNG3, RGPD8, PSD4, CCDC74B, BMPR2, KAT2B, LINC00693, ZNF654, FILIP1L, SH3TC1, CPEB2, NPFFR2, TRPC3, RP11-752L20.3, FAM198B, TLL1, CDH9, PDZD2, CHSY3, GALNT10, FOXQ1, ATXN1, ID4, COL11A2, CNR1, GTF2IP4, FZD1, PAX5, RP11-35N6.1, UNC5B, NKX1-2, FAM196A, EBF3, PRRG4, LRP4, SYT7, PLBD1, GRASP, ALX1, HIP1R, LPAR6, SLITRK6, C16orf89, RP11-491F9.1, MMP2, B3GNT9, NXPH3, TNRC6C-AS1, LDLRAD4, NOL4, SMAD7, HCN2, PDE4A, KANK2, SAMD1, EXOC3L2, IL11, EMILIN3, KCNB1, DOK5, EEF1A2, A4GALT, ADGRG2, ELF4, ABCD1 Term Count % PValue Genes regulation of pathway-restricted GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, SMAD protein phosphorylation 9 6.34 1.31E-08 ENG pathway-restricted SMAD protein GDF3, SMAD7, GDF7, BMPR2, GDF10, GREM1, BMP7, LDLRAD4, phosphorylation