Paired Box Research Articles

A case of syndromic congenital hypothyroidism with a 15.2 Mb interstitial deletion on 2q12.3q14.2 involving <i>PAX8</i>

Paired box 8 (PAX8) mutations are an established genetic cause of congenital hypothyroidism (CH). The majority of these mutations are found in the protein-coding exons of the gene. The proband, a 3-yr-old girl, had tetralogy of Fallot and polydactyly soon after birth. She was diagnosed with CH in the newborn screening for CH. She had a high serum TSH level (239 mU/L) and low free T4 level (0.7 ng/dL). Ultrasonography revealed thyroid hypoplasia. We performed array comparative genomic hybridization because the patient exhibited a variety of symptoms across multiple organ systems. The analysis revealed a novel heterozygous deletion that spanned a 15.2 Mb region in 2q12.3q14.3 (GRCh37; chr2:109,568,260-124,779,449). There were 71 protein-coding genes in this region, including two genes (PAX8 and GLI2) associated with congenital endocrine disorders. The common clinical features of the two previously reported patients with a total PAX8 deletion and our case were CH, short stature and intellectual disability, but the severity of hypothyroidism and other clinical features were variable. In conclusion, we describe a syndromic CH patient with a novel 2q12.3q14.3 deletion involving PAX8. Patients with CH, whose unifying diagnosis is not obvious, could have a genomic deletion involving PAX8.

ERN1 dependent impact of glucose and glutamine deprivations on PBX3, PBXIP1, PAX6, MEIS1, and MEIS2 genes expression in U87 glioma cells.

Objective. Homeobox genes play a fundamental role in the embryogenesis, but some of them have been linked to oncogenesis. The present study is aimed to investigate the impact of glucose and glutamine deprivations on the expression of homeobox genes such as PAX6 (paired box 6), PBX3 (PBX homeobox 3), PBXIP1 (PBX homeobox interacting protein 1), MEIS1 (MEIS homeobox 1), and MEIS2 in ERN1 knockdown U87 glioma cells with the intent to reveal the role of ERN1 (endoplasmic reticulum to nucleus signaling 1) signaling pathway on the endoplasmic reticulum stress dependent regulation of homeobox genes. Methods. The control (transfected by empty vector) and ERN1 knockdown (transfected by dominant-negative ERN1) U87 glioma cells were exposed to glucose and glutamine deprivations for 24 h. The cells RNA was extracted and reverse transcribed. The expression level of PAX6, PBX3, PBXIP1, MEIS1, and MEIS2 genes was evaluated by a real-time quantitative polymerase chain reaction analysis and normalized to ACTB. Results. It was found that glucose deprivation down-regulated the expression level of PAX6, MEIS1, and MEIS2 genes in control glioma cells, but did not significantly alter PBX3 and PBXIP1 genes expression. At the same time, ERN1 knockdown significantly modified the sensitivity of all studied genes to glucose deprivation. Other changes in gene expression were detected in control glioma cells under the glutamine deprivation. The expression of PBX3 and MEIS2 genes was down- while PAX6 and PBXIP1 genes up-regulated. Furthermore, ERN1 knockdown significantly modified the effect of glutamine deprivation on the majority of studied genes expression in U87 glioma cells. Conclusion. The results of the present study demonstrate that the exposure of U87 glioma cells under glucose and glutamine deprivations affected the expression of the majority of the studied homeobox genes and that the sensitivity of PAX6, PBX3, PBXIP1, MEIS1, and MEIS2 genes expression under these experimental conditions is mediated by ERN1, the major pathway of the endoplasmic reticulum stress signaling.

Neural progenitor cells derived from fibroblasts induced by small molecule compounds under hypoxia for treatment of Parkinson's disease in rats.

Neural progenitor cells (NPCs) capable of self-renewal and differentiation into neural cell lineages offer broad prospects for cell therapy for neurodegenerative diseases. However, cell therapy based on NPC transplantation is limited by the inability to acquire sufficient quantities of NPCs. Previous studies have found that a chemical cocktail of valproic acid, CHIR99021, and Repsox (VCR) promotes mouse fibroblasts to differentiate into NPCs under hypoxic conditions. Therefore, we used VCR (0.5 mM valproic acid, 3 μM CHIR99021, and 1 μM Repsox) to induce the reprogramming of rat embryonic fibroblasts into NPCs under a hypoxic condition (5%). These NPCs exhibited typical neurosphere-like structures that can express NPC markers, such as Nestin, SRY-box transcription factor 2, and paired box 6 (Pax6), and could also differentiate into multiple types of functional neurons and astrocytes in vitro. They had similar gene expression profiles to those of rat brain-derived neural stem cells. Subsequently, the chemically-induced NPCs (ciNPCs) were stereotactically transplanted into the substantia nigra of 6-hydroxydopamine-lesioned parkinsonian rats. We found that the ciNPCs exhibited long-term survival, migrated long distances, and differentiated into multiple types of functional neurons and glial cells in vivo. Moreover, the parkinsonian behavioral defects of the parkinsonian model rats grafted with ciNPCs showed remarkable functional recovery. These findings suggest that rat fibroblasts can be directly transformed into NPCs using a chemical cocktail of VCR without introducing exogenous factors, which may be an attractive donor material for transplantation therapy for Parkinson's disease.

Role of PAX2 in breast cancer verified by bioinformatics analysis and in vitro validation.

Breast cancer (BC) is the most frequently diagnosed cancer in women and the second most common cancer among newly diagnosed cancers worldwide. Studies have shown that paired box 2 (PAX2) participates in the tumorigenesis of some cancer cells, but its role in BC is still unclear. Transcriptome expression profiles and clinicopathological information of BC were downloaded from The Cancer Genome Atlas (TCGA) database to explore the expression level and prognostic value of PAX2. Gene set enrichment analysis (GSEA) and functional enrichment analysis were performed to investigate the functions and pathways of PAX2. Moreover, real-time reverse transcriptase-polymerase chain reaction (RT-qPCR) was used to determine the expression of PAX2 in BC tissues, and the predictive value of PAX2 in clinical samples was assessed. Cell Counting Kit-8 (CCK-8) assay was used to evaluate cell growth. The migration and invasive capacities of cells were assessed by wound healing assay and Transwell assay. PAX2 was upregulated in the TCGA-BC datasets. GSEA suggested that PAX2 may be involved in the regulation of signaling pathways such as MAPK. Moreover, PAX2 was overexpressed in BC tissues, and PAX2 expression was associated with tumor size and lymph node metastasis. PAX2 deficiency could promote the growth, migration, and invasion of BC cells. Upregulation of PAX2 inhibited BC cell growth, migration, and invasion, making PAX2 a potential therapeutic target for BC.

Unsupervised many-to-many stain translation for histological image augmentation to improve classification accuracy

BackgroundDeep learning tasks, which require large numbers of images, are widely applied in digital pathology. This poses challenges especially for supervised tasks since manual image annotation is an expensive and laborious process. This situation deteriorates even more in the case of a large variability of images. Coping with this problem requires methods such as image augmentation and synthetic image generation. In this regard, unsupervised stain translation via GANs has gained much attention recently, but a separate network must be trained for each pair of source and target domains. This work enables unsupervised many-to-many translation of histopathological stains with a single network while seeking to maintain the shape and structure of the tissues. MethodsStarGAN-v2 is adapted for unsupervised many-to-many stain translation of histopathology images of breast tissues. An edge detector is incorporated to motivate the network to maintain the shape and structure of the tissues and to have an edge-preserving translation. Additionally, a subjective test is conducted on medical and technical experts in the field of digital pathology to evaluate the quality of generated images and to verify that they are indistinguishable from real images. As a proof of concept, breast cancer classifiers are trained with and without the generated images to quantify the effect of image augmentation using the synthetized images on classification accuracy. ResultsThe results show that adding an edge detector helps to improve the quality of translated images and to preserve the general structure of tissues. Quality control and subjective tests on our medical and technical experts show that the real and artificial images cannot be distinguished, thereby confirming that the synthetic images are technically plausible. Moreover, this research shows that, by augmenting the training dataset with the outputs of the proposed stain translation method, the accuracy of breast cancer classifier with ResNet-50 and VGG-16 improves by 8.0% and 9.3%, respectively. ConclusionsThis research indicates that a translation from an arbitrary source stain to other stains can be performed effectively within the proposed framework. The generated images are realistic and could be employed to train deep neural networks to improve their performance and cope with the problem of insufficient numbers of annotated images.

Genes Linked with Orthodontic Issues and the Knowledge Gaps in This Association

Orthodontics is the study of malpositioned teeth and jaws. Some commonly found orthodontic issues are malocclusions, mandibular prognathism, retrognathism, and facial asymmetry. These issues are associated with several genetic factors. For instance, mandibular prognathism is related to gene variations, such as insulin-like growth factor 1 and the HoxC gene cluster. Facial asymmetry is related to NFATC1 and NBAS genes. Dental agenesis is related to several genes, including paired box 9 (PAX9), homeobox 1 (MSX1), and ectodysplasin A. Apart from these genes, several other genes, such as MYO1H gene, ACTN3 gene, ENPP1, ESR1 genes, PITX1 and PITX2 genes, IL1 gene, and PAX9 gene, have been studied in the orthodontic issues faced by people. Some of these genes, such as ENPP1 and ESR1 genes, are directly related to orthodontic issues, whereas some of the genes, such as ACTN3 genes, are associated with issues in the muscle tone that can eventually lead to orthodontic issues. This review deals with genes linked with orthodontics and the knowledge gaps in its association.

Maternal Transmission of the PAX7 Single Nucleotide Polymorphisms among Indian Cleft Trios.

Cleft lip and/or cleft palate (CL/P) is one of the most common congenital anomalies of the human face with a complex etiology involving multiple genetic and environmental factors. Several studies have shown the association of the paired box 7 ( PAX7 ) gene with CL/P in different populations worldwide. However, the current literature reveals no reported case-parent trio studies to evaluate the association between the PAX7 gene and the risk of nonsyndromic cleft lip and/or palate (NSCL/P) in the Indian population. Hence, the purpose of this study was to assess the PAX7 gene single nucleotide polymorphisms (SNPs) in the etiology of NSCL/P among the Indian cleft trios. Forty Indian case-parent trios of NSCL/P were included. The cases and their parents' genomic DNA were extracted. The SNPs rs9439714, rs1339062, rs6695765, rs742071, and rs618941of the PAX7 gene were genotyped using the Agena Bio MassARRAY analysis. The allelic transmission disequilibrium test was performed using PLINK software while pair-wise linkage disequilibrium by the Haploview program. The SNP rs9439714 showed evidence of association ( p -value = 0.02, odds ratio = 3) with NSCL/P. Considering the parent-of-origin effects, the SNPs rs9439714 and rs618941 showed an excess maternal transmission of allele C at rs9439714 ( p -value = 0.05) and G allele at rs618941 ( p -value = 0.04). The results of the present study suggested that the SNPs rs9439714 and rs618941 showed an excess maternal transmission of alleles suggestive of the possible role of the PAX7 gene involvement in the etiology of NSCL/P in the Indian population.

A Genetic Algorithm based Domain Adaptation Framework for Classification of Disaster Topic Text Tweets

The ability to post short text and media messages on Social media platforms like Twitter, Facebook, etc., plays a huge role in the exchange of information following a mass emergency event like hurricane, earthquake, tsunami etc. Disaster victims, families, and other relief operation teams utilize social media to help and support one another. Despite the benefits offered by these communication media, the disaster topic related posts (posts that indicate conversations about the disaster event in the aftermath of the disaster) gets lost in the deluge of posts since there would be a surge in the amount of data that gets exchanged following a mass emergency event. This hampers the emergency relief effort, which in turn affects the delivery of useful information to the disaster victims. Research in emergency coordination via social media has received growing interest in recent years, mainly focusing on developing machine learning-based models that can separate disaster-related topic posts from non-disaster related topic posts. Of these, supervised machine learning approaches performed well when the machine learning model trained using source disaster dataset and target disaster dataset are similar. However, in the real world, it may not be feasible as different disasters have different characteristics. So, models developed using supervised machine learning approaches do not perform well in unseen disaster datasets. Therefore, domain adaptation approaches, which address the above limitation by learning classifiers from unlabeled target data in addition to source labelled data, represent a promising direction for social media crisis data classification tasks. The existing domain adaptation techniques for the classification of disaster tweets are experimented with using single disaster event dataset pairs; then, self-training is performed on the source target dataset pairs by considering the highly confident instances in subsequent iterations of training. This could be improved with better feature engineering. Thus, this research proposes a Genetic Algorithm based Domain Adaptation Framework (GADA) for the classification of disaster tweets. The proposed GADA combines the power of 1) Hybrid Feature Selection component using the Genetic Algorithm and Chi-Square Feature Evaluator for feature selection and 2) the Classifier component using Random Forest to classify disaster-related posts from noise on Twitter. The proposed framework addresses the challenge of the lack of labeled data in the target disaster event by proposing a Genetic Algorithm based approach. Experimental results on Twitter datasets corresponding to four disaster domain pair shows that the proposed framework improves the overall performance of the previous supervised approaches and significantly reduces the training time over the previous domain adaptation techniques that do not use the Genetic Algorithm (GA) for feature selection.

A New Multisource Domain Bearing Fault Diagnosis Method With Adaptive Dual-Domain Obfuscation Weighting Strategy

In the fault diagnosis of modern industrial equipment, domain adaptation is widely utilized to address the challenge of data distribution changes. However, traditional domain adaptation method only learns single domain knowledge and experiences difficulty in coping with scenarios wherein working conditions change drastically. Accordingly, learning knowledge from multiple different source domains can effectively improve the generalization ability of the model and the reliability of the diagnosis results. Simultaneously, aligning marginal and conditional distributions can weaken data distribution differences caused by drastic changes in operating conditions, enabling more accurate knowledge transfer between source and target domains, and improving the performance of model cross-domain fault diagnosis. Furthermore, when the data comes from multiple different domains, completely aligning all source domains is arduous and impractical, and thus, selectively synthesizing different source domain migration diagnostic results is necessary. To address the aforementioned issues, this study proposes a multibranch weight-adaptive adversarial fault diagnosis method. This method uses multiple branch networks to match each source–target domain pair independently, aligns them as much as possible with two domain confusion networks, and calculates the alignment degree to assign the source domain weight coefficient. The final fault diagnosis result is obtained by synthesizing the domain classifier results that correspond to the weighted coefficient domain. Experiments verify the reliability and stability of this method under various working conditions, such as high span speed and variable speed.

Structural and Functional Analysis of Dengue Virus Non-Structural Protein 5 (NS5) Using Molecular Dynamics

Dengue is an infection transmitted by the Aedes mosquito and is considered a major public health concern in many tropical and Asian countries, including the Philippines. It is caused by the dengue virus (DENV) which belongs to the Flaviviridae family and has four serotypes. The non-structural protein 5 (NS5), which consists of an MTase domain and an RdRp domain, is the largest and most conserved protein among flaviviruses and thus a potential target against DENV. However, there are very limited studies on the functional homodimer structure of NS5. Through molecular dynamics, it was found that residues 458–470, 583–586, 630–637, 743–744, and 890–900 of monomer A and residues 14–24, 311–315, and 462–464 of monomer B undergo essential motions for the conformational changes in the RdRp template tunnel and GTP binding in the MTase domain. Through the analysis of these motions, it was also proposed that in the dimeric structure of NS5 only one pair of domains contribute to the function of the protein. Other essential residues, specifically A-ASP533, A-LYS689, A-ARG620, A-ARG688, A-SER710, B-ARG620, B-LYS689, A-GLU40, A-ARG262, A-GLU267, A-ARG673, and B-ARG673, were also identified to play important roles in the information flow necessary for the function of the protein. In particular, shortest paths analysis led to the identification of ARG673 as an essential residue for the communication between RdRp and MTase catalytic sites. Mutation of this residue led to changes in the conformational flexibility of the RdRp finger subdomain, which may influence the RdRp catalytic function. These findings serve as a basis for future studies on the mechanism and inhibition of the NS5 dimer for dengue drug discovery.

Deception Detection Within and Across Domains: Identifying and Understanding the Performance Gap

NLP approaches to automatic deception detection have gained popularity over the past few years, especially with the proliferation of fake reviews and fake news online. However, most previous studies of deception detection have focused on single domains. We currently lack information about how these single-domain models of deception may or may not generalize to new domains. In this work, we conduct empirical studies of cross-domain deception detection in five domains to understand how current models perform when evaluated on new deception domains. Our experimental results reveal a large gap between within and across domain classification performance. Motivated by these findings, we propose methods to understand the differences in performances across domains. We formulate five distance metrics that quantify the distance between pairs of deception domains. We experimentally demonstrate that the distance between a pair of domains negatively correlates with the cross-domain accuracies of the domains. We thoroughly analyze the differences in the domains and the impact of fine-tuning BERT based models by visualization of the sentence embeddings. Finally, we utilize the distance metrics to recommend the optimal source domain for any given target domain. This work highlights the need to develop robust learning algorithms for cross-domain deception detection that generalize and adapt to new domains and contributes toward that goal.

Lysine Demethylase 1B Promotes Tear Secretion Disorder in Sjogren’s Syndrome by Regulating the PAX6/CLU Axis

The impacts of lysine demethylase 1B (KDM1B) have been probed in multiple diseases, but the effects of KDM1B on SS remained obscure. The study aimed to unravel the efficiency of KDM1B on SS progression via the paired box 6 (PAX6)/clusterin (CLU) axis. NODB10. H2b mice were selected to establish the SS model. KDM1B, Pax6, and CLU expression in SS mice was assessed. Adeno-associated viruses carrying KDM1B, Pax6, and CLU were injected into the SS mice to detect tear secretion, epithelium corneal fluorescein staining scores, and levels of specific markers of lacrimal gland epithelial cells, neurotransmitter receptors that induce secretion from the lacrimal gland, and genes encoding normal tear components. The relation among KDM1B, Pax6, and CLU was examined. The rescue experiments were conducted for verifying the interaction among KDM1B, Pax6, and CLU. KDM1B expression was elevated, while Pax6 and CLU levels were decreased in the lacrimal gland tissues of SS mouse models. KDM1B decrement and Pax6 augmentation improved tear secretion, reduced corneal fluorescein staining score, decreased levels of specific markers of lacrimal gland epithelial cells, and increased levels of neurotransmitter receptors that induce secretion from the lacrimal gland and genes encoding normal tear components. KDM1D suppressed Pax6 expression by mediating H3K4me2 demethylation. Pax6 promoted the expression of CLU at the transcriptional level by binding to the CLU promoter. Silencing of Pax6 or CLU could reverse the effects of KDM1B reduction on improving the tear secretion disorder of SS mice. Silencing KDM1B mitigates the tear secretion disorder of SS mice via modulating the Pax6/CLU axis.

Use of clinicopathological factors to predict prognosis of fertility-sparing treatment for endometrial endometrioid carcinoma and atypical hyperplasia.

The incidence of endometrial endometrioid carcinoma (EEC) has been gradually increasing over the past decade. Fertility-sparing therapy with progestin is a treatment option for EEC or endometrial atypical hyperplasia (AH). The present study evaluated the role of numerous prognostic factors following fertility-sparing therapy for EEC or AH. Furthermore, the present study assessed the strength of various clinicopathological indicators for the prediction of treatment efficacy. A retrospective analysis was performed of patients with EEC and AH who received fertility-sparing therapy between August 2013 and September 2021 at Peking University People's Hospital (Beijing, China). Endometrial specimens were obtained from each patient after 3 months of treatment and at the end of the fertility-sparing therapy, before treatment efficacy and prognosis were evaluated using the χ2 test. Furthermore, the protein expression levels of EEC biomarkers, such as estrogen receptor (ER), progesterone receptor (PR), paired box 2 (PAX2), PTEN and p53 were assessed using immunohistochemistry. The overall complete response (CR) rate of fertility-sparing treatment in the EEC group was 67.39% (31/46), whereas that in the AH group was 86.49% (32/37). The difference between the CR rates in the EEC and AH groups was statistically significant (P<0.05). There was no association between prognosis after treatment and ER, PAX2, PTEN or Ki-67 expression in the initially untreated AH or EEC groups. However, tissues with >50% positive PR expression were demonstrated to have a higher CR rate compared with those with ≤50% positive PR expression in both the EEC and AH groups. Furthermore, the PAX2-positive group tended to demonstrate higher CR rates compared with the PAX2-negative group in the patients with EEC. In conclusion, these data suggested that fertility-sparing therapy is effective for patients with EEC and AH who wish to remain fertile after treatment. Specifically, in the AH group, a higher proportion of patients achieved a CR whilst also achieving this more rapidly. Furthermore, PR was demonstrated to be a useful marker for the evaluation of EEC and AH.

Disparate Regions of the Human Chemokine CXCL10 Exhibit Broad-Spectrum Antimicrobial Activity against Biodefense and Antibiotic-Resistant Bacterial Pathogens.

CXCL10 is a pro-inflammatory chemokine produced by the host in response to microbial infection. In addition to canonical, receptor-dependent actions affecting immune-cell migration and activation, CXCL10 has also been found to directly kill a broad range of pathogenic bacteria. Prior investigations suggest that the bactericidal effects of CXCL10 occur through two distinct pathways that compromise the cell envelope. These observations raise the intriguing notion that CXCL10 features a separable pair of antimicrobial domains. Herein, we affirm this possibility through peptide-based mapping and structure/function analyses, which demonstrate that discrete peptides derived from the N- and C-terminal regions of CXCL10 mediate bacterial killing. The N-terminal derivative, peptide P1, exhibited marked antimicrobial activity against Bacillus anthracis vegetative bacilli and spores, as well as antibiotic-resistant clinical isolates of Klebsiella pneumoniae, Acinetobacter baumannii, Enterococcus faecium, and Staphylococcus aureus, among others. At bactericidal concentrations, peptide P1 had a minimal degree of chemotactic activity, but did not cause red blood cell hemolysis or cytotoxic effects against primary human cells. The C-terminal derivative, peptide P9, exhibited antimicrobial effects, but only against Gram-negative bacteria in low-salt medium─conditions under which the peptide can adopt an α-helical conformation. The introduction of a hydrocarbon staple induced and stabilized α-helicity; accordingly, stapled peptide P9 displayed significantly improved bactericidal effects against both Gram-positive and Gram-negative bacteria in media containing physiologic levels of salt. Together, our findings identify and characterize the antimicrobial regions of CXCL10 and functionalize these novel determinants as discrete peptides with potential therapeutic utility against difficult-to-treat pathogens.

GSK126 an inhibitor of epigenetic regulator EZH2 suppresses cardiac fibrosis by regulating the EZH2-PAX6-CXCL10 pathway.

Myocardial fibrosis is a common pathological companion of various cardiovascular diseases. To date, the role of enhancer of zeste homolog 2 (EZH2) in cancer has been well demonstrated including in renal carcinoma and its inhibitors have entered the stage of phase I/II clinical trials. However, the precise mechanism of EZH2 in cardiac diseases is largely unclear. In the current study, we first found that EZH2 expression was increased in Ang-II-treated cardiac fibroblasts (CFs) and mouse heart homogenates following isoproterenol (ISO) administration for 21 days, respectively. Ang-II induces CFs activation and increased collagen-I, collagen-III, α-SMA, EZH2, and trimethylates lysine 27 on histone 3 (H3K27me3) expressions can be reversed by EZH2 inhibitor (GSK126) and EZH2 siRNA. The ISO-induced cardiac hypertrophy, and fibrosis in vivo which were also related to the upregulation of EZH2 and its downstream target, H3K27me3, could be recovered by GSK126. Furthermore, the upregulation of EZH2 induces the decrease of paired box 6 (PAX6) and C-X-C motif ligand 10 (CXCL10) "which" were also reversed by GSK126 treatment. In summary, the present evidence strongly suggests that GSK126 could be a therapeutic intervention, blunting the development and progression of myocardial fibrosis in an EZH2-PAX6-CXCL10-dependent manner.

A Genome‐Wide Search for Pleiotropy in Cognitive Domain Scores

AbstractBackgroundGenome‐wide association studies (GWASs) have identified loci for Alzheimer’s disease (AD)‐related cognitive traits, and genetic correlations among these traits suggest that a single gene may affect them jointly, i.e., pleiotropy.MethodWe conducted GWASs for scores previously generated by factor analyses for cognitive domains—executive function, language, and memory—using longitudinal data from 7,503 Framingham Heart Study (FHS) and 6,758 National Alzheimer’s Coordinating Center (NACC) subjects who had an average of five and three exams, respectively. We averaged domain scores for each participant by weighting down scores at the visit without normal cognition and used the sum of weights to account for heterogeneous residual variances. The association of each domain score with 8.9 million genetic variants (MAF&gt;0.01), imputed using the TOPMed reference panel (GRCh38), was tested separately in each dataset using linear models including age, sex, education level, and five principal components of ancestry as covariates. Results from FHS and NACC datasets were combined by meta‐analyses using the inverse‐variance method. Pleiotropy for each pair of cognitive domains was evaluated using PLACO (pleiotropic analysis under the composite null hypothesis).ResultScores for paired cognitive domains were moderately genetically correlated—executive function and language (ρP =0.46, ρG =0.69), executive function and memory (ρP =0.39, ρG =0.43), language and memory (ρP =0.44, ρG =0.46). Pleiotropy analyses revealed genome‐wide significant associations for all paired domain scores with many variants in the APOE region (p&lt;3.91×10‐9 for each). For pleiotropy of executive function and language, we identified genome‐wide significant associations with DOK5 (rs28663252, p=4.51×10‐8) and suggestive associations with SOX14 (rs55829884, p=8.03×10‐8), IL20RB (rs11925531, p=9.26×10‐8), and RIMS2 (rs140291972, p=8.76×10‐7). We also found suggestive associations for pleiotropy of language and memory with LHFPL4 (rs2936482, p=5.08×10‐8) and for pleiotropy of executive function and memory with MC4R (rs1943220, p=7.54×10‐8) and CDH20 (rs78756286, p=1.50×10‐7).ConclusionWe identified significant evidence of pleiotropy for multiple cognitive domains, and these findings may improve the interpretation of the genetic basis of cognition and AD‐related traits. These results highlight the benefits of factor scores derived from groups of subjects assessed with various cognitive tests and pleiotropy analysis as a tool for identifying genes that contribute to performance in multiple cognitive domains.

Genetic dissection of eye development – Lessons from Pax6

AbstractA paired domain and homeodomain‐containing transcription factor Pax6 is an evolutionarily conserved regulator implicated in the eye development of both vertebrates and invertebrates. Mutations of the Pax6 gene disrupt eye development in both mammals and insects while Pax6 misexpression can lead to the formation of ectopic eyes. Genetic and expression studies have indicated that the development of vertebrate eyes is guided by a conserved gene regulatory network with Pax6 being one of the key transcription factors. To define the regulatory inputs into Pax6 gene we performed a genetic dissection of its regulatory landscape. To uncover the direct target genes of Pax6 we performed chromatin immunoprecipitation (ChIP‐seq) using mouse embryonic retina as a sample. We will present our preliminary genetic data on functional validation of Pax6‐regulated enhancers.

Multiple Myeloma with Aberrant CD3 Expression in a Red-Lored Amazon Parrot (Amazona autumnalis).

A 20-year-old, female, red-lored Amazon parrot (Amazona autumnalis) was presented for a 2-week history of weakness. On physical examination, the bird was quiet, fluffed, weak, and had a distended coelom. Radiographic and ultrasound imaging revealed coelomic distention, increased pulmonary parenchymal opacity, renomegaly, dilated intestines, and a thickened ventricular wall. The results of a complete blood cell count indicated the patient was anemic (28%) and had intermediate to large lymphocytes with immature chromatin that were suspected to be neoplastic. Immunocytochemistry on peripheral blood determined that the suspected circulating neoplastic cells were cluster of differentiation (CD) 3+ and occasionally expressed multiple myeloma oncogene 1 (MUM1). Abnormalities from a plasma biochemistry panel were moderate hyperphosphatemia (6.8 mg/dL), marked hyperproteinemia (13.6 g/L), analbuminemia (0 g/dL), and marked hyperglobulinemia (13.6 g/dL). Agarose gel plasma protein electrophoresis documented the presence of albumin (1.2 g/dL) and monoclonal bands which, on reduced lithium dodecyl sulfate polyacrylamide gel electrophoresis, resolved as 60-kd and ∼25-kd bands consistent with immunoglobulin Y heavy and light chains. On the basis of these findings, multiple myeloma was diagnosed. Because of a poor prognosis, the bird was euthanized for postmortem examination. Bone marrow cytology from samples collected during the postmortem examination revealed 17.4% plasma cells and 24% large immature cells with occasional plasmacytoid features. Histopathologic findings included aggregates of neoplastic plasma cells in the bone marrow, spleen, kidney, liver, gastrointestinal tract, muscle, ovary, and brain. The neoplastic cells were strongly immunoreactive for MUM1 and cluster of differentiation 3 (CD3), but negative for CD79a, paired box protein 5, and CD20. This confirmed the clinical diagnosis of multiple myeloma. This report describes an avian immunoglobulin Y-secreting multiple myeloma with aberrant CD3 expression and pseudoanalbuminemia. Aberrant CD3 expression by avian multiple myeloma may explain previously published cases of birds with a monoclonal gammopathy and apparent T-cell lymphoma diagnosed by CD3 immunoreactivity.

Restoration of functional PAX3 transcriptional factor enhanced neuronal differentiation in PAX3b isoform-depleted neuroblastoma cells.

Reexpressed PAX3 transcription factor is believed to be responsible for the differentiation defects observed in neuroblastoma. Although the importance of PAX3 in neuronal differentiation is documented how it is involved in the defective differentiation remains unexplored particularly with its isoforms. Here, first we have analyzed PAX3 expression, its functional status, and its correlation with the neuronal marker expression in SH-SY5Y and its parental SK-N-SH cells. We have found that SH-SY5Y cells which expressed more PAX3 showed increased expression of neuronal marker genes (TUBB, MAP2, NEFL, NEUROG2, SYP) and reported PAX3 target genes (MET, TGFA, and NCAM1) than the SK-N-SH cells that had low PAX3 level. Retinoic acid treatment is unable to induce neuronal differentiation in cells (SK-N-SH) with low PAX3 level/activity. Moreover, ectopic expression of PAX3 in SK-N-SH cells neither induces neuronal marker genes nor its target genes. PAX3 isoform expression analysis revealed the expression of PAX3b isoform that contains only paired domain in SK-N-SH cells, whereas in SH-SY5Y cells, we could also observe PAX3c isoform that contains all functional domains. Further, PAX3b depletion in SK-N-SH cells is not induced PAX3 target genes, and the cells remain poorly differentiated. Interestingly, ectopic PAX3 expression in PAX3b-depleted SK-N-SH cells enhanced neuronal outgrowth along with neuronal marker gene induction. Collectively, these results showed that the PAX3b isoform may be responsible for the differentiation defect observed in SK-N-SH cells and restoration of functional PAX3 in the absence of PAX3b can induce neurogenesis in these cells.

Abstract PR008: Overcoming PDAC T cell therapy barriers with CD47-targeted costimulatory fusion proteins

Abstract T cell therapy is a promising immunotherapy treatment option that uses genetically modified immune cells (T cells) to eliminate tumors. This approach uses the patients’ own immune cells to generate a “living drug” and can avoid the toxic side effects of other common therapies, such as radiation or chemotherapies. However, the pancreatic ductal adenocarcinoma (PDAC) tumor microenvironment (TME) can establish several obstacles to protect the tumor from T cells, including delivery of inhibitory and death signals that shut down T cells, usurping metabolic nutrients, and recruiting and/or converting immune cells to inhibitory phenotypes that block the T cell response. CD47 is upregulated in PDAC tumors, and patients with CD47hi tumors exhibit worse survival. CD47 serves as a “don’t eat me” signal by binding to the SIRPα receptor on macrophages to block phagocytosis. CD47 expression also inhibits T cell-mediated tumor rejection by blocking cross-presentation of tumor antigens by SIRPα+ dendritic cells. Reagents that interfere with SIRPα-CD47 signaling, such as monoclonal antibodies, are currently in clinical trials and have been shown to synergize with chemotherapy in PDA models, but native CD47 expression can produce erythrocyte and platelet depletion. Costimulatory signals delivered by surface-bound receptors can initiate gene expression programs that address multiple issues in the PDAC TME by mechanisms such as lowering the threshold of activation, altering metabolic programming, and reducing exhaustion. We develop engineering strategies to deliver costimulatory signals to engineered T cells. Immunomodulatory fusion proteins (IFPs) combine the ectodomain of an inhibitory T cell receptor with an intracellular costimulatory signaling domain and we have shown in proof-of-concept studies that this effectively “replaces a brake with an accelerator” in CD8 T cells. We have found that generating IFPs is not as simple as indiscriminately fusing any two proteins together and we have developed critical design concepts that inform the selection of the fusion site, ectodomain and costimulatory signaling domain pairing, and immunological synapse localization to enhance signaling. To develop a CD47-targeted IFP, we combined the SIRPa ectodomain with the CD28 signaling endodomain and tested this technology with our mesothelin-targeted TCR-T cell platform. In in vitrostudies, SIRPa-CD28 T cells exhibited enhanced proliferation, accumulation, and tumor cytotoxicity. SIRPa IFP-T cells exhibited increased intratumoral accumulation and therapeutic efficacy in the KrasLSL-G12D/+; Trp53LSL-R172H/+;p48Cre/+ (KPC) model, without toxicity or erythrocyte depletion. Here we describe how a thoughtfully engineered fusion protein can “armor” T cells against multiple obstacles and significantly improve therapeutic efficacy against PDAC. Citation Format: Shannon Oda, Leah Schmidt, Ashley Thelen, Cody Jenkins, Edison Chiu, Aitong Ruan, Philip Greenberg. Overcoming PDAC T cell therapy barriers with CD47-targeted costimulatory fusion proteins [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr PR008.