p53 MAINTAINS HEPATIC CELL IDENTITY DURING LIVER REGENERATION

p53 MAINTAINS HEPATIC CELL IDENTITY DURING LIVER REGENERATION Zeynep Hande Coban Akdemir, B.S.,M.A. Advisory Professor: Michelle Craig Barton, Ph.D. p53 is a tumor suppressor that has been well studied in tumor-derived, cultured cells. However, its functions in normal proliferating cells and tissues are generally overlooked. We propose that p53 functions during the G1-S transition can be studied in normal, differentiated cells during surgery-induced liver regeneration. Two-thirds partial hepatectomy (PH) of mouse liver offers a unique model to compare p53 functions in regenerating versus sham (control) cells. My hypothesis is that intersection of global expression analyses (microarray and RNA sequencing) and profiling of p53 interactions with chromatin (ChIP sequencing) at the G1-S transition of normal cell cycle, corresponding to 24h post-PH in mice liver regeneration, will reveal p53 functions during cell cycle regulation in normal cells and during tissue regeneration. Combining chromatin immunoprecipitation with next generation sequencing technology (ChIP-Seq) allowed detection of genome-wide binding of p53 to target genes in liver. We found 5074 de novo p53 target genes, 92% of which participate in non-canonical p53 functions, mainly developmental processes. Integration of ChIP-Seq findings with global expression profiling (RNA-Seq) of both normal and p53-null liver allowed us to identify functional p53 target genes. Intriguingly, our data analysis revealed that a specific subset of p53-activated target genes is involved in liver-enriched functions such as lipid biosynthetic process, steroid metabolic process, circadian rhythm, and drug detoxification. These findings suggested that the loss of p53-chromatin interactions in regenerating liver may result in a decreased activity of differentiation-specific cellular processes and in attenuation of hepatic cell identity. Remarkably, p53 cooperates with the master regulator of hepatocyte differentiation, HNF4α, to induce 78% of these genes, including a number of liver-enriched transcription factors such as CCAAT/enhancer binding protein beta (CEBPβ), hepatocyte nuclear factor 6 alpha (HNF6α), hepatocyte nuclear factor 6 beta (HNF6β). Thus, p53 acts in concert with HNF4α to promote the maintenance of liver functions during the G1àS transition of the cell cycle of normal proliferating livers cells

Ai-Drugnet: a Network-Based Deep Learning Model For Drug Repurposing and Combination therapy in Neurological Disorders

Discovering effective therapies is difficult for neurological and developmental disorders in that disease progression is often associated with a complex and interactive mechanism. Over the past few decades, few drugs have been identified for treating Alzheimer\u27s disease (AD), especially for impacting the causes of cell death in AD. Although drug repurposing is gaining more success in developing therapeutic efficacy for complex diseases such as common cancer, the complications behind AD require further study. Here, we developed a novel prediction framework based on deep learning to identify potential repurposed drug therapies for AD, and more importantly, our framework is broadly applicable and may generalize to identifying potential drug combinations in other diseases. Our prediction framework is as follows: we first built a drug-target pair (DTP) network based on multiple drug features and target features, as well as the associations between DTP nodes where drug-target pairs are the DTP nodes and the associations between DTP nodes are represented as the edges in the AD disease network; furthermore, we incorporated the drug-target feature from the DTP network and the relationship information between drug-drug, target-target, drug-target within and outside of drug-target pairs, representing each drug-combination as a quartet to generate corresponding integrated features; finally, we developed an AI-based Drug discovery Network (AI-DrugNet), which exhibits robust predictive performance. The implementation of our network model help identify potential repurposed and combination drug options that may serve to treat AD and other diseases

Ad-Syn-Net: Systematic Identification of alzheimer\u27s Disease-Associated Mutation and Co-Mutation Vulnerabilities Via Deep Learning

Alzheimer\u27s disease (AD) is one of the most challenging neurodegenerative diseases because of its complicated and progressive mechanisms, and multiple risk factors. Increasing research evidence demonstrates that genetics may be a key factor responsible for the occurrence of the disease. Although previous reports identified quite a few AD-associated genes, they were mostly limited owing to patient sample size and selection bias. There is a lack of comprehensive research aimed to identify AD-associated risk mutations systematically. to address this challenge, we hereby construct a large-scale AD mutation and co-mutation framework (\u27AD-Syn-Net\u27), and propose deep learning models named Deep-SMCI and Deep-CMCI configured with fully connected layers that are capable of predicting cognitive impairment of subjects effectively based on genetic mutation and co-mutation profiles. Next, we apply the customized frameworks to data sets to evaluate the importance scores of the mutations and identified mutation effectors and co-mutation combination vulnerabilities contributing to cognitive impairment. Furthermore, we evaluate the influence of mutation pairs on the network architecture to dissect the genetic organization of AD and identify novel co-mutations that could be responsible for dementia, laying a solid foundation for proposing future targeted therapy for AD precision medicine. Our deep learning model codes are available open access here: https://github.com/Pan-Bio/AD-mutation-effectors

Identification of a RAI1-associated disease network through integration of exome sequencing, transcriptomics, and 3D genomics.

Smith-Magenis syndrome (SMS) is a developmental disability/multiple congenital anomaly disorder resulting from haploinsufficiency of RAI1. It is characterized by distinctive facial features, brachydactyly, sleep disturbances, and stereotypic behaviors. We investigated a cohort of 15 individuals with a clinical suspicion of SMS who showed neither deletion in the SMS critical region nor damaging variants in RAI1 using whole exome sequencing. A combination of network analysis (co-expression and biomedical text mining), transcriptomics, and circularized chromatin conformation capture (4C-seq) was applied to verify whether modified genes are part of the same disease network as known SMS-causing genes. Potentially deleterious variants were identified in nine of these individuals using whole-exome sequencing. Eight of these changes affect KMT2D, ZEB2, MAP2K2, GLDC, CASK, MECP2, KDM5C, and POGZ, known to be associated with Kabuki syndrome 1, Mowat-Wilson syndrome, cardiofaciocutaneous syndrome, glycine encephalopathy, mental retardation and microcephaly with pontine and cerebellar hypoplasia, X-linked mental retardation 13, X-linked mental retardation Claes-Jensen type, and White-Sutton syndrome, respectively. The ninth individual carries a de novo variant in JAKMIP1, a regulator of neuronal translation that was recently found deleted in a patient with autism spectrum disorder. Analyses of co-expression and biomedical text mining suggest that these pathologies and SMS are part of the same disease network. Further support for this hypothesis was obtained from transcriptome profiling that showed that the expression levels of both Zeb2 and Map2k2 are perturbed in Rai1 (-/-) mice. As an orthogonal approach to potentially contributory disease gene variants, we used chromatin conformation capture to reveal chromatin contacts between RAI1 and the loci flanking ZEB2 and GLDC, as well as between RAI1 and human orthologs of the genes that show perturbed expression in our Rai1 (-/-) mouse model. These holistic studies of RAI1 and its interactions allow insights into SMS and other disorders associated with intellectual disability and behavioral abnormalities. Our findings support a pan-genomic approach to the molecular diagnosis of a distinctive disorder

Biallelic variants in ADAMTS15 cause a novel form of distal arthrogryposis

Purpose We aimed to identify the underlying genetic cause for a novel form of distal arthrogryposis. Methods Rare variant family-based genomics, exome sequencing, and disease-specific panel sequencing were used to detect ADAMTS15 variants in affected individuals. Adamts15 expression was analyzed at the single-cell level during murine embryogenesis. Expression patterns were characterized using in situ hybridization and RNAscope. Results We identified homozygous rare variant alleles of ADAMTS15 in 5 affected individuals from 4 unrelated consanguineous families presenting with congenital flexion contractures of the interphalangeal joints and hypoplastic or absent palmar creases. Radiographic investigations showed physiological interphalangeal joint morphology. Additional features included knee, Achilles tendon, and toe contractures, spinal stiffness, scoliosis, and orthodontic abnormalities. Analysis of mouse whole-embryo single-cell sequencing data revealed a tightly regulated Adamts15 expression in the limb mesenchyme between embryonic stages E11.5 and E15.0. A perimuscular and peritendinous expression was evident in in situ hybridization in the developing mouse limb. In accordance, RNAscope analysis detected a significant coexpression with Osr1, but not with markers for skeletal muscle or joint formation. Conclusion In aggregate, our findings provide evidence that rare biallelic recessive trait variants in ADAMTS15 cause a novel autosomal recessive connective tissue disorder, resulting in a distal arthrogryposis syndrome

Whole-Exome Sequencing in Familial Parkinson Disease

IMPORTANCE: Parkinson disease (PD) is a progressive neurodegenerative disease for which susceptibility is linked to genetic and environmental risk factors. OBJECTIVE: To identify genetic variants contributing to disease risk in familial PD. DESIGN, SETTING, AND PARTICIPANTS: A 2-stage study design that included a discovery cohort of families with PD and a replication cohort of familial probands was used. In the discovery cohort, rare exonic variants that segregated in multiple affected individuals in a family and were predicted to be conserved or damaging were retained. Genes with retained variants were prioritized if expressed in the brain and located within PD-relevant pathways. Genes in which prioritized variants were observed in at least 4 families were selected as candidate genes for replication in the replication cohort. The setting was among individuals with familial PD enrolled from academic movement disorder specialty clinics across the United States. All participants had a family history of PD. MAIN OUTCOMES AND MEASURES: Identification of genes containing rare, likely deleterious, genetic variants in individuals with familial PD using a 2-stage exome sequencing study design. RESULTS: The 93 individuals from 32 families in the discovery cohort (49.5% [46 of 93] female) had a mean (SD) age at onset of 61.8 (10.0) years. The 49 individuals with familial PD in the replication cohort (32.6% [16 of 49] female) had a mean (SD) age at onset of 50.1 (15.7) years. Discovery cohort recruitment dates were 1999 to 2009, and replication cohort recruitment dates were 2003 to 2014. Data analysis dates were 2011 to 2015. Three genes containing a total of 13 rare and potentially damaging variants were prioritized in the discovery cohort. Two of these genes (TNK2 and TNR) also had rare variants that were predicted to be damaging in the replication cohort. All 9 variants identified in the 2 replicated genes in 12 families across the discovery and replication cohorts were confirmed via Sanger sequencing. CONCLUSIONS AND RELEVANCE: TNK2 and TNR harbored rare, likely deleterious, variants in individuals having familial PD, with similar findings in an independent cohort. To our knowledge, these genes have not been previously associated with PD, although they have been linked to critical neuronal functions. Further studies are required to confirm a potential role for these genes in the pathogenesis of PD

Biallelic GRM7 variants cause epilepsy, microcephaly, and cerebral atrophy

Objective: Defects in ion channels and neurotransmitter receptors are implicated in developmental and epileptic encephalopathy (DEE). Metabotropic glutamate receptor 7 (mGluR7), encoded by GRM7, is a presynaptic G-protein-coupled glutamate receptor critical for synaptic transmission. We previously proposed GRM7 as a candidate disease gene in two families with neurodevelopmental disorders (NDDs). One additional family has been published since. Here, we describe three additional families with GRM7 biallelic variants and deeply characterize the associated clinical neurological and electrophysiological phenotype and molecular data in 11 affected individuals from six unrelated families. Methods: Exome sequencing and family-based rare variant analyses on a cohort of 220 consanguineous families with NDDs revealed three families with GRM7 biallelic variants; three additional families were identified through literature search and collaboration with a clinical molecular laboratory. Results: We compared the observed clinical features and variants of 11 affected individuals from the six unrelated families. Identified novel deleterious variants included two homozygous missense variants (c.2671G>A:p.Glu891Lys and c.1973G>A:p.Arg685Gln) and one homozygous stop-gain variant (c.1975C>T:p.Arg659Ter). Developmental delay, neonatal- or infantile-onset epilepsy, and microcephaly were universal. Three individuals had hypothalamic–pituitary–axis dysfunction without pituitary structural abnormality. Neuroimaging showed cerebral atrophy and hypomyelination in a majority of cases. Two siblings demonstrated progressive loss of myelination by 2 years in both and an acquired microcephaly pattern in one. Five individuals died in early or late childhood. Conclusion: Detailed clinical characterization of 11 individuals from six unrelated families demonstrates that rare biallelic GRM7 pathogenic variants can cause DEEs, microcephaly, hypomyelination, and cerebral atrophy. © 2020 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association

Biallelic mutations in IRF8 impair human NK cell maturation and function

Human NK cell deficiencies are rare yet result in severe and often fatal disease, particularly as a result of viral susceptibility. NK cells develop from hematopoietic stem cells, and few monogenic errors that specifically interrupt NK cell development have been reported. Here we have described biallelic mutations in IRF8, which encodes an interferon regulatory factor, as a cause of familial NK cell deficiency that results in fatal and severe viral disease. Compound heterozygous or homozygous mutations in IRF8 in 3 unrelated families resulted in a paucity of mature CD56dim NK cells and an increase in the frequency of the immature CD56bright NK cells, and this impairment in terminal maturation was also observed in Irf8–/–, but not Irf8+/–, mice. We then determined that impaired maturation was NK cell intrinsic, and gene expression analysis of human NK cell developmental subsets showed that multiple genes were dysregulated by IRF8 mutation. The phenotype was accompanied by deficient NK cell function and was stable over time. Together, these data indicate that human NK cells require IRF8 for development and functional maturation and that dysregulation of this function results in severe human disease, thereby emphasizing a critical role for NK cells in human antiviral defense