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

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

Phenotypic expansion of POGZ-related intellectual disability syndrome (White-Sutton syndrome)

White-Sutton syndrome (WHSUS) is a recently-identified genetic disorder resulting from de novo heterozygous pathogenic variants in POGZ. Thus far, over 50 individuals have been reported worldwide, however phenotypic characterization and data regarding the natural history are still incomplete. Here we report the clinical features of 22 individuals with 21 unique loss of function POGZ variants. We observed a broad spectrum of intellectual disability and/or developmental delay with or without autism, and speech delay in all individuals. Other common problems included ocular abnormalities, hearing loss and gait abnormalities. A validated sleep disordered breathing questionnaire identified symptoms of obstructive sleep apnea in 4/12 (33%) individuals. A higher-than-expected proportion of cases also had gastrointestinal phenotypes, both functional and anatomical, as well as genitourinary anomalies. In line with previous publications, we observed an increased body mass index (BMI) z-score compared to the general population (mean 0.59, median 0.9; p 0.0253). Common facial features included microcephaly, broad forehead, midface hypoplasia, triangular mouth, broad nasal root and flat nasal bridge. Analysis of the Baylor Genetics clinical laboratory database revealed that POGZ variants were implicated in approximately 0.14% of cases who underwent clinical exome sequencing for neurological indications with or without involvement of other body systems. This study describes a greater allelic series and expands the phenotypic spectrum of this new syndromic form of intellectual disability and autism

Centers For Mendelian Genomics: a Decade of Facilitating Gene Discovery

PURPOSE: Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration. METHODS: Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution. RESULTS: We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher. CONCLUSION: The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients

Genetic architecture of laterality defects revealed by whole exome sequencing

Aberrant left-right patterning in the developing human embryo can lead to a broad spectrum of congenital malformations. The causes of most laterality defects are not known, with variants in established genes accounting for <20% of cases. We sought to characterize the genetic spectrum of these conditions by performing whole-exome sequencing of 323 unrelated laterality cases. We investigated the role of rare, predicted-damaging variation in 1726 putative laterality candidate genes derived from model organisms, pathway analyses, and human phenotypes. We also evaluated the contribution of homo/hemizygous exon deletions and gene-based burden of rare variation. A total of 28 candidate variants (26 rare predicted-damaging variants and 2 hemizygous deletions) were identified, including variants in genes known to cause heterotaxy and primary ciliary dyskinesia (ACVR2B, NODAL, ZIC3, DNAI1, DNAH5, HYDIN, MMP21), and genes without a human phenotype association, but with prior evidence for a role in embryonic laterality or cardiac development. Sanger validation of the latter variants in probands and their parents revealed no de novo variants, but apparent transmitted heterozygous (ROCK2, ISL1, SMAD2), and hemizygous (RAI2, RIPPLY1) variant patterns. Collectively, these variants account for 7.1% of our study subjects. We also observe evidence for an excess burden of rare, predicted loss-of-function variation in PXDNL and BMS1- two genes relevant to the broader laterality phenotype. These findings highlight potential new genes in the development of laterality defects, and suggest extensive locus heterogeneity and complex genetic models in this class of birth defects