A Cross-Species Systems Genetics Analysis Links APBB1IP as a Candidate for Schizophrenia and Prepulse Inhibition

Ashbrook, David G.; Cahill, Stephanie; Hager, Reinmar

doi:10.3389/fnbeh.2019.00266

Cited by 12 publications

(6 citation statements)

References 84 publications

(115 reference statements)

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“…EGR2 [99], ADCYAP1 [100], CHRNA7 [101], NRN1 [102], ETV5 [103], STXBP1 [104], CAMKK2 [105], VAMP2 [106], SYNGR1 [107], NOD2 [108], TLR2 [109], BRCA2 [110] and LEF1 [111] were previously reported to be critical for the development of bipolar disorder. Accumulating evidence shows that EGR2 [112], WNT1 [113], ARC (activity regulated cytoskeleton associated protein) [114], ADCYAP1 [115], SCN5A [116], RTN4R [117], CHRNA7 [118], NRGN (neurogranin) [119], CHRM1 [120], CCK (cholecystokinin) [121], RGS4 [122], LINGO1 [123], PAK1 [124], PCDH19 [125], NRN1 [126], CX3CL1 [127], CNTNAP2 [128], SLC12A5 [129], GAS7 [130], NTNG1 [131], RAB3A [132], STXBP1 [104], CHRNB2 [133], CDK5 [134], HTR5A [135], SLC30A3 [136], HTR3B [137], HTR2C [138], TAMALIN (trafficking regulator and scaffold protein tamalin) [139], STX1A [140], GRM2 [141], SLC1A6 [142], NPTX2 [143], CAMKK2 [144], SYP (synaptophysin) [145], VAMP2 [146], ATP1A3 [147], SV2A [148], CNTNAP2 [149], CAP2[150], SYNGR1 [151], SNCB (synuclein beta) [152], RBP4 [153], KIF17 [154], CHI3L1 [155], CCR5 [156], C1QB [157], TLR7 [158], TLR2 [159], MNDA (myeloid cell nuclear differentiation antigen) [160], C3 [161], IL2RG [162], MICB (MHC class I polypeptide-related sequence B) [163], FKBP5 [164], NEFH (neurofilament heavy chain) [165], CELSR1 [166], APBB1IP [167], CD34 [168], BRCA2 [110], ITGB3 […”

Section: Discussionmentioning

confidence: 99%

Bioinformatics and next generation sequencing data analysis to identify key genes and pathways influencing in Parkinson’s disease

Vastrad¹,

Vastrad²

2022

Preprint

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Parkinson's disease (PD) is the most commonly diagnosed neurodegenerative disorder Identification of novel prognostic and pathogenesis biomarkers plays a pivotal role in the management of the PD. Next generation sequencing (NGS) dataset from the GEO (Gene Expression Omnibus) database were used to identify differentially expressed genes (DEGs) in PD. Gene Ontology (GO) and REACTOME pathway enrichmental analyses were performed to elucidate the functional roles of the DEGs. Protein-protein interaction (PPI), modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network were established. The receiver operating characteristic curve (ROC) analysis was used to explore the diagnostic values of hub genes in PD. In total, 957 DEGs were identified, of which 478 were up regulated genes and 479 were down regulated genes. GO and pathway enrichment analysis results revealed that the up regulated genes were mainly enriched in nervous system development, cell junction, transporter activity and neuronal system, whereas down regulated genes were mainly enriched in response to stimulus, cell periphery, identical protein binding and immune system. The top hub genes in the constructed PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network were OTUB1, PPP2R1A, AP2M1, PIN1, USP11, CDK2, IQGAP1, NEDD4, VIM and CDK1. Furthermore, ROC analysis showed that hub genes were having good diagnostic values. We identified a series of essential genes along with the pathways that were most closely related with PD initiation and progression. Our results provide a more detailed molecular mechanism for the advancement of PD, shedding light on the potential biomarkers and therapeutic targets.

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Section: Discussionmentioning

confidence: 99%

Bioinformatics and next generation sequencing data analysis to identify key genes and pathways influencing in Parkinson’s disease

Vastrad¹,

Vastrad²

2022

Preprint

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“…Breeders were not maintained longer than 12 months of age. Sample size power calculations were carried out using the publicly available BXD power app, based on qtlDesign (Ashbrook DG 2019;Belknap 1998). C3Tag-BXD F1 hybrids were termed "BXD-BC" followed by the BXD strain ID #.…”

Section: Animalsmentioning

confidence: 99%

Determining susceptibility loci in triple negative breast cancer using a novel pre-clinical model

Simon,

Simmons,

Kim

et al. 2024

Preprint

Self Cite

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Breast cancer (BC) is the most common cancer and the second cause of death in US women. Our lack of understanding of how genetic variants affect molecular mechanisms that mediate BC aggression poses a substantial obstacle to advancements in cancer diagnosis and therapy. To examine genetic variants on BC traits, a novel murine model was created with robust phenotypic and genomic variation. The FVB C3(1)-T-antigen (C3Tag) mouse develops spontaneous tumors in the mammary glands of female mice with a mean latency of 4-5 months of age. This genetically engineered mouse model (GEMM) is well established to resemble human basal-like TNBC. TNBC is an aggressive subtype with few clinical approaches and poor patient outcomes. Thus, to model human heterogeneity in BC outcomes, we systematically crossed the C3Tag GEMM into the BXD recombinant inbred family - the largest and best characterized genetic reference population. The new model is termed BXD-BC and F1 hybrids of the cross have isogenic genomes that are reproducible. BXD-BCs are a potent tool to determine the impact of genetic modifiers on BC tumor traits. We hypothesized that examination of BXD-BC GEMMs will enable the identification of susceptibility loci, candidate genes, and molecular networks that underlie variation of multiple BC phenotypes. Using N=29 BXD-BC strains, we demonstrated significant heritable variations in the severity of TNBC characteristics such as tumor latency, multiplicity, and survival. Interestingly, 2 BXD-BC strains never developed tumors out to 1 year of age. Thus, BXD-BC strains demonstrate variance in cancer susceptibility and progression compared to the parent C3Tag GEMM, indicating the presence of genetic modifiers. Through an unbiased systematic quantification of breast cancer severity across BXD-BC hybrids, we identified several significant quantitative trait loci (QTL) and candidate genes for specific tumor traits. In combination with public human GWAS datasets, we defined syntenic regions, candidate genes, and underlying networks through cross-species systems genetics analyses to demonstrate the translational validity of conserved, biologically relevant, and targetable candidates. Our findings suggest conserved candidates predicting TNBC patient survival. In sum, the BXD-BC resource is an innovative, reliable, and robust preclinical model that reflects robust genetic heterogeneity. Using cutting-edge systems genetics, we have identified genetic modifiers of BC phenotypic variation that could be targeted to advance therapeutic limitations or as biomarkers of risk or response to therapy.

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“…Human GWAS data can be used to refine QTL found in mice, e.g. taking advantage of the power to detect associations in the BXD to identify a homologous region in humans, and then using the precision of human GWAS to identify a candidate gene [185][186][187].…”

Section: Integration and Translation With Other Populationsmentioning

confidence: 99%

Recombinant Inbred Mice as Models for Experimental Precision Medicine and Biology

Ashbrook¹,

Lu²

2022

Preclinical Animal Modeling in Medicine

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Recombinant inbred rodents form immortal genome-types that can be resampled deeply at many stages, in both sexes, and under multiple experimental conditions to model genome-environment interactions and to test genome-phenome predictions. This allows for experimental precision medicine, for which sophisticated causal models of complex interactions among DNA variants, phenotype variants at many levels, and innumerable environmental factors are required. Large families and populations of isogenic lines of mice and rats are now available and have been used across fields of biology. We will use the BXD recombinant inbred family and their derived diallel cross population as an example for predictive, experimental precision medicine and biology.

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A Cross-Species Systems Genetics Analysis Links APBB1IP as a Candidate for Schizophrenia and Prepulse Inhibition

Cited by 12 publications

References 84 publications

Bioinformatics and next generation sequencing data analysis to identify key genes and pathways influencing in Parkinson’s disease

Bioinformatics and next generation sequencing data analysis to identify key genes and pathways influencing in Parkinson’s disease

Determining susceptibility loci in triple negative breast cancer using a novel pre-clinical model

Recombinant Inbred Mice as Models for Experimental Precision Medicine and Biology

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