High Functioning Autism with Missense Mutations in Synaptotagmin-Like Protein 4 (SYTL4) and Transmembrane Protein 187 (TMEM187) Genes: SYTL4- Protein Modeling, Protein-Protein Interaction, Expression Profiling and MicroRNA Studies

Bioinformatics and machine learning were used to validate glutamine metabolism-related genes and immunotherapy in osteoporosis patients

BACKGROUND

Osteoporosis (OP), often referred to as the "silent disease of the twenty-first century," poses a significant public health concern due to its severity, chronic nature, and progressive course, predominantly affecting postmenopausal women and elderly individuals. The pathogenesis and progression of this disease have been associated with dysregulation in tumor metabolic pathways. Notably, the metabolic utilization of glutamine has emerged as a critical player in cancer biology. While metabolic reprogramming has been extensively studied in various malignancies and linked to clinical outcomes, its comprehensive investigation within the context of OP remains lacking.

METHODS

This study aimed to identify and validate potential glutamine metabolism genes (GlnMgs) associated with OP through comprehensive bioinformatics analysis. The identification of GlnMgs was achieved by integrating the weighted gene co-expression network analysis and a set of 28 candidate GlnMgs. Subsequently, the putative biological functions and pathways associated with GlnMgs were elucidated using gene set variation analysis. The LASSO method was employed to identify key hub genes, and the diagnostic efficacy of five selected GlnMgs in OP detection was assessed. Additionally, the relationship between hub GlnMgs and clinical characteristics was investigated. Finally, the expression levels of the five GlnMgs were validated using independent datasets (GSE2208, GSE7158, GSE56815, and GSE35956).

RESULTS

Five GlnMgs, namely IGKC, TMEM187, RPS11, IGLL3P, and GOLGA8N, were identified in this study. To gain insights into their biological functions, particular emphasis was placed on synaptic transmission GABAergic, inward rectifier potassium channel activity, and the cytoplasmic side of the lysosomal membrane. Furthermore, the diagnostic potential of these five GlnMgs in distinguishing individuals with OP yielded promising results, indicating their efficacy as discriminative markers for OP.

CONCLUSIONS

This study discovered five GlnMgs that are linked to OP. They shed light on potential new biomarkers for OP and tracking its progression.

Four Decades of Carrier Detection and Prenatal Diagnosis in Hemophilia A: Historical Overview, State of the Art and Future Directions

Hemophilia A (HA), a rare recessive X-linked bleeding disorder, is caused by either deficiency or dysfunction of coagulation factor VIII (FVIII) resulting from deleterious mutations in the F8 gene encoding FVIII. Over the last 4 decades, the methods aimed at determining the HA carrier status in female relatives of HA patients have evolved from phenotypic studies based on coagulation tests providing merely probabilistic results, via genetic linkage studies based on polymorphic markers providing more accurate results, to next generation sequencing studies enabling highly precise identification of the causative F8 mutation. In parallel, the options for prenatal diagnosis of HA have progressed from examination of FVIII levels in fetal blood samples at weeks 20-22 of pregnancy to genetic analysis of fetal DNA extracted from chorionic villus tissue at weeks 11-14 of pregnancy. In some countries, in vitro fertilization (IVF) combined with preimplantation genetic diagnosis (PGD) has gradually become the procedure of choice for HA carriers who wish to prevent further transmission of HA without the need to undergo termination of pregnancies diagnosed with affected fetuses. In rare cases, genetic analysis of a HA carrier might be complicated by skewed X chromosome inactivation (XCI) of her non-hemophilic X chromosome, thus leading to the phenotypic manifestation of moderate to severe HA. Such skewed XCI may be associated with deleterious mutations in X-linked genes located on the non-hemophilic X chromosome, which should be considered in the process of genetic counseling and PGD planning for the symptomatic HA carrier. Therefore, whole exome sequencing, combined with X-chromosome targeted bioinformatic analysis, is highly recommended for symptomatic HA carriers diagnosed with skewed XCI in order to identify additional deleterious mutations potentially involved in XCI skewing. Identification of such mutations, which may profoundly impact the reproductive choices of HA carriers with skewed XCI, is extremely important.

Echo2Pheno: a deep-learning application to uncover echocardiographic phenotypes in conscious mice

Echocardiography, a rapid and cost-effective imaging technique, assesses cardiac function and structure. Despite its popularity in cardiovascular medicine and clinical research, image-derived phenotypic measurements are manually performed, requiring expert knowledge and training. Notwithstanding great progress in deep-learning applications in small animal echocardiography, the focus has so far only been on images of anesthetized rodents. We present here a new algorithm specifically designed for echocardiograms acquired in conscious mice called Echo2Pheno, an automatic statistical learning workflow for analyzing and interpreting high-throughput non-anesthetized transthoracic murine echocardiographic images in the presence of genetic knockouts. Echo2Pheno comprises a neural network module for echocardiographic image analysis and phenotypic measurements, including a statistical hypothesis-testing framework for assessing phenotypic differences between populations. Using 2159 images of 16 different knockout mouse strains of the German Mouse Clinic, Echo2Pheno accurately confirms known cardiovascular genotype-phenotype relationships (e.g., Dystrophin) and discovers novel genes (e.g., CCR4-NOT transcription complex subunit 6-like, Cnot6l, and synaptotagmin-like protein 4, Sytl4), which cause altered cardiovascular phenotypes, as verified by H&E-stained histological images. Echo2Pheno provides an important step toward automatic end-to-end learning for linking echocardiographic readouts to cardiovascular phenotypes of interest in conscious mice.

Roles, molecular mechanisms, and signaling pathways of TMEMs in neurological diseases

Transmembrane protein family members (TMEMs) span the entire lipid bilayer and act as channels that allow the transport of specific substances through biofilms. The functions of most TMEMs are unexplored. Numerous studies have shown that TMEMs are involved in the pathophysiological processes of various nervous system diseases, but the specific mechanisms of TMEMs in the pathogenesis of diseases remain unclear. In this review, we discuss the expression, physiological functions, and molecular mechanisms of TMEMs in brain tumors, psychiatric disorders, abnormal motor activity, cobblestone lissencephaly, neuropathic pain, traumatic brain injury, and other disorders of the nervous system. Additionally, we propose that TMEMs may be used as prognostic markers and potential therapeutic targets in patients with various neurological diseases.

17q12 Recurrent Deletions and Duplications: Description of a Case Series with Neuropsychiatric Phenotype

Syndromic neurodevelopmental disorders are usually investigated through genetics technologies, within which array comparative genomic hybridization (Array-CGH) is still considered the first-tier clinical diagnostic test. Among recurrent syndromic imbalances, 17q12 deletions and duplications are characterized by neurodevelopmental disorders associated with visceral developmental disorders, although expressive variability is common. Here we describe a case series of 12 patients with 17q12 chromosomal imbalances, in order to expand the phenotypic characterization of these recurrent syndromes whose diagnosis is often underestimated, especially if only mild traits are present. Gene content and genotype-phenotype correlations have been discussed, with special regard to neuropsychiatric features, whose impact often requires etiologic analysis.

Molecular Mechanisms of Skewed X-Chromosome Inactivation in Female Hemophilia Patients-Lessons from Wide Genome Analyses

Introduction: Hemophilia A (HA) is an X-linked bleeding disorder caused by factor VIII (FVIII) deficiency or dysfunction due to F8 gene mutations. HA carriers are usually asymptomatic because their FVIII levels correspond to approximately half of the concentration found in healthy individuals. However, in rare cases, a carrier may exhibit symptoms of moderate to severe HA primarily due to skewed inactivation of her non-hemophilic X chromosome. Aim: The aim of the study was to investigate X-chromosome inactivation (XCI) patterns in HA carriers, with special emphasis on three karyotypically normal HA carriers presenting with moderate to severe HA phenotype due to skewed XCI, in an attempt to elucidate the molecular mechanism underlying skewed XCI in these symptomatic HA carriers. The study was based on the hypothesis that the presence of a pathogenic mutation on the non-hemophilic X chromosome is the cause of extreme inactivation of that X chromosome. Methods: XCI patterns were studied by PCR analysis of the CAG repeat region in the HUMARA gene. HA carriers that demonstrated skewed XCI were further studied by whole-exome sequencing (WES) followed by X chromosome-targeted bioinformatic analysis. Results: All three HA carriers presenting with the moderate to severe HA phenotype due to skewed XCI were found to carry pathogenic mutations on their non-hemophilic X chromosomes. Patient 1 was diagnosed with a frameshift mutation in the PGK1 gene that was associated with familial XCI skewing in three generations. Patient 2 was diagnosed with a missense mutation in the SYTL4 gene that was associated with familial XCI skewing in two generations. Patient 3 was diagnosed with a nonsense mutation in the NKAP gene that was associated with familial XCI skewing in two generations. Conclusion: Our results indicate that the main reason for skewed XCI in our female HA patients was negative selection against cells with a disadvantage caused by an additional deleterious mutation on the silenced X chromosome, thus complicating the phenotype of a monogenic X-linked disease. Based on our study, we are currently offering the X inactivation test to symptomatic hemophilia carriers and plan to expand this approach to symptomatic carriers of other X-linked diseases, which can be further used in pregnancy planning.

TMP- SSurface2: A Novel Deep Learning-Based Surface Accessibility Predictor for Transmembrane Protein Sequence

Transmembrane protein (TMP) is an important type of membrane protein that is involved in various biological membranes related biological processes. As major drug targets, TMPs’ surfaces are highly concerned to form the structural biases of their material-bindings for drugs or other biological molecules. However, the quantity of determinate TMP structures is still far less than the requirements, while artificial intelligence technologies provide a promising approach to accurately identify the TMP surfaces, merely depending on their sequences without any feature-engineering. For this purpose, we present an updated TMP surface residue predictor TMP-SSurface2 which achieved an even higher prediction accuracy compared to our previous version. The method uses an attention-enhanced Bidirectional Long Short Term Memory (BiLSTM) network, benefiting from its efficient learning capability, some useful latent information is abstracted from protein sequences, thus improving the Pearson correlation coefficients (CC) value performance of the old version from 0.58 to 0.66 on an independent test dataset. The results demonstrate that TMP-SSurface2 is efficient in predicting the surface of transmembrane proteins, representing new progress in transmembrane protein structure modeling based on primary sequences. TMP-SSurface2 is freely accessible at https://github.com/NENUBioCompute/TMP-SSurface-2.0.

Rab11fip5 regulates telencephalon development via ephrinB1 recycling

Rab11 family-interacting protein 5 (Rab11fip5) is an adaptor protein that binds to the small GTPase Rab11, which has an important function in endosome recycling and trafficking of cellular proteins to the plasma membrane. Rab11fip5 is involved in many cellular processes, such as cytoskeleton rearrangement, iron uptake and exocytosis in neuroendocrine cells, and is also known as a candidate gene for autism-spectrum disorder. However, the role of Rab11fip5 during early embryonic development is not clearly understood. In this study, we identified Rab11fip5 as a protein that interacts with ephrinB1, a transmembrane ligand for Eph receptors. The PDZ binding motif in ephrinB1 and the Rab-binding domain in Rab11fip5 are necessary for their interaction in a complex. EphrinB1 and Rab11fip5 display overlapping expression in the telencephalon of developing amphibian embryos. The loss of Rab11fip5 function causes a reduction in telencephalon size and a decrease in the expression level of ephrinB1. Moreover, morpholino oligonucleotide-mediated knockdown of Rab11fip5 decreases cell proliferation in the telencephalon. The overexpression of ephrinB1 rescues these defects, suggesting that ephrinB1 recycling by the Rab11/Rab11fip5 complex is crucial for proper telencephalon development.

Summary: Rab11fip5, genetic mutations of which are associated with autism spectrum disorders in humans, plays a role in regulating telencephalon development via recycling of the crucial cargo ephrinB1.

The 15q11.2 BP1-BP2 Microdeletion (Burnside-Butler) Syndrome: In Silico Analyses of the Four Coding Genes Reveal Functional Associations with Neurodevelopmental Phenotypes

The 15q11.2 BP1-BP2 microdeletion (Burnside–Butler) syndrome is emerging as the most frequent pathogenic copy number variation (CNV) in humans associated with neurodevelopmental disorders with changes in brain morphology, behavior, and cognition. In this study, we explored functions and interactions of the four protein-coding genes in this region, namely NIPA1, NIPA2, CYFIP1, and TUBGCP5, and elucidate their role, in solo and in concert, in the causation of neurodevelopmental disorders. First, we investigated the STRING protein-protein interactions encompassing all four genes and ascertained their predicted Gene Ontology (GO) functions, such as biological processes involved in their interactions, pathways and molecular functions. These include magnesium ion transport molecular function, regulation of axonogenesis and axon extension, regulation and production of bone morphogenetic protein and regulation of cellular growth and development. We gathered a list of significantly associated cardinal maladies for each gene from searchable genomic disease websites, namely MalaCards.org: HGMD, OMIM, ClinVar, GTR, Orphanet, DISEASES, Novoseek, and GeneCards.org. Through tabulations of such disease data, we ascertained the cardinal disease association of each gene, as well as their expanded putative disease associations. This enabled further tabulation of disease data to ascertain the role of each gene in the top ten overlapping significant neurodevelopmental disorders among the disease association data sets: (1) Prader–Willi Syndrome (PWS); (2) Angelman Syndrome (AS); (3) 15q11.2 Deletion Syndrome with Attention Deficit Hyperactive Disorder & Learning Disability; (4) Autism Spectrum Disorder (ASD); (5) Schizophrenia; (6) Epilepsy; (7) Down Syndrome; (8) Microcephaly; (9) Developmental Disorder, and (10) Peripheral Nervous System Disease. The cardinal disease associations for each of the four contiguous 15q11.2 BP1-BP2 genes are NIPA1- Spastic Paraplegia 6; NIPA2—Angelman Syndrome and Prader–Willi Syndrome; CYFIP1—Fragile X Syndrome and Autism; TUBGCP5—Prader–Willi Syndrome. The four genes are individually associated with PWS, ASD, schizophrenia, epilepsy, and Down syndrome. Except for TUBGCP5, the other three genes are associated with AS. Unlike the other genes, TUBGCP5 is also not associated with attention deficit hyperactivity disorder and learning disability, developmental disorder, or peripheral nervous system disease. CYFIP1 was the only gene not associated with microcephaly but was the only gene associated with developmental disorders. Collectively, all four genes were associated with up to three-fourths of the ten overlapping neurodevelopmental disorders and are deleted in this most prevalent known pathogenic copy number variation now recognized among humans with these clinical findings.

Whole exome sequencing of a Saudi family and systems biology analysis identifies CPED1 as a putative causative gene to Celiac Disease

Celiac disease (CD) is a gastrointestinal disorder whose genetic basis is not fully understood. Therefore, we studied a Saudi family with two CD affected siblings to discover the causal genetic defect. Through whole exome sequencing (WES), we identified that both siblings have inherited an extremely rare and deleterious CPED1 genetic variant (c.241 A > G; p.Thr81Ala) segregating as autosomal recessive mutation, suggesting its putative causal role in the CD. Saudi population specific minor allele frequency (MAF) analysis has confirmed its extremely rare prevalence in homozygous condition (MAF is 0.0004). The Sanger sequencing analysis confirmed the absence of this homozygous variant in 100 sporadic Saudi CD cases. Genotype-Tissue Expression (GTEx) data has revealed that CPED1 is abundantly expressed in gastrointestinal mucosa. By using a combination of systems biology approaches like protein 3D modeling, stability analysis and nucleotide sequence conservation analysis, we have further established that this variant is deleterious to the structural and functional aspects of CPED1 protein. To the best of our knowledge, this variant has not been previously reported in CD or any other gastrointestinal disease. The cell culture and animal model studies could provide further insight into the exact role of CPED1 p.Thr81Ala variant in the pathophysiology of CD. In conclusion, by using WES and systems biology analysis, present study for the first-time reports CPED1 as a potential causative gene for CD in a Saudi family with potential implications to both disease diagnosis and genetic counseling.

Integrated analysis of miRNA and mRNA expression profiles in the brains of BTBR mice

The BTBR T⁺  Itpr3^tf (BTBR) mouse has developmental disorders in brain and many aberrant neuroanatomical structures and brain dysfunction. However, identification of the pathological mechanisms underlying abnormal brain development in the brains of BTBR mice is still lacking. Increasingly evidence showed that epigenetics plays an important role in the processes of brain development. In this study, we analyzed microRNA (miRNA) and mRNA expression profiles in the cortical brain tissue from BTBR mice, using RNA sequencing. As compared to C57BL/6J (B6) mice, 1,271 differentially expressed genes (DEGs) and 36 known differentially expressed miRNAs (DEMs) were found in the brain from BTBR mice. The functional annotation and categories of DEGs and DEMs were analyzed. Integration analysis identified 103 known miRNA-mRNA interaction pairs. We further verified selected several genes and miRNAs which may be associated with brain development using quantitative RT-PCR (qRT-PCR). Finally, we speculate that reduced myelin-associated oligodendrocytic basic protein and transmembrane proteins 260 may be linked with abnormal brain development in BTBR mice.