VaProS: a database-integration approach for protein/genome information retrieval

Analysis of Potential Biomarkers in Frontal Temporal Dementia: A Bioinformatics Approach

Frontal temporal dementia (FTD) is a neurological disorder known to have fewer therapeutic options. So far, only a few biomarkers are available for FTD that can be used as potential comorbidity targets. For example, genes such as VCP, which has a role in breast cancer, and WFS1, which has a role in COVID-19, are known to show a role in FTD as well. To this end, in the present study, we aim to identify potential biomarkers or susceptible genes for FTD that show comorbidities with diseases such as COVID-19 and breast cancer. A dataset from Gene Expression Omnibus containing FTD expression profiles from African American and white ethnicity backgrounds was included in our study. In FTD samples of the GSE193391 dataset, we identified 305 DEGs, with 168 genes being up-regulated and 137 genes being down-regulated. We conducted a comorbidity analysis for COVID-19 and breast cancer, followed by an analysis of potential drug interactions, pathogenicity, analysis of genetic variants, and functional enrichment analysis. Our results showed that the genes AKT3, GFAP, ADCYAP1R1, VDAC1, and C4A have significant transcriptomic alterations in FTD along with the comorbidity status with COVID-19 and breast cancer. Functional pathway analysis revealed that these comorbid genes were significantly enriched in the pathways such as glioma, JAK/STAT signaling, systematic lupus erythematosus, neurodegeneration-multiple diseases, and neuroactive ligand-receptor interaction. Overall, from these results, we concluded that these genes could be recommended as potential therapeutic targets for the treatment of comorbidities (breast cancer and COVID-19) in patients with FTD.

Two Loci Contribute to Age-Related Hearing Loss Resistance in the Japanese Wild-Derived Inbred MSM/Ms Mice

An MSM/Ms strain was established using Japanese wild mice, which exhibit resistance to several phenotypes associated with aging, such as obesity, inflammation, and tumorigenesis, compared to common inbred mouse strains. MSM/Ms strain is resistant to age-related hearing loss, and their auditory abilities are sustained for long durations. The age-related hearing loss 3 (ahl3) locus contributes to age-related hearing in MSM/Ms strain. We generated ahl3 congenic strains by transferring a genomic region on chromosome 17 from MSM/Ms mice into C57BL/6J mice. Although C57BL/6J mice develop age-related hearing loss because of the ahl allele of the cadherin 23 gene, the development of middle- to high-frequency hearing loss was significantly delayed in an ahl3 congenic strain. Moreover, the novel age-related hearing loss 10 (ahl10) locus associated with age-related hearing resistance in MSM/Ms strain was mapped to chromosome 12. Although the resistance effects in ahl10 congenic strain were slightly weaker than those in ahl3 congenic strain, slow progression of age-related hearing loss was confirmed in ahl10 congenic strain despite harboring the ahl allele of cadherin 23. These results suggest that causative genes and polymorphisms of the ahl3 and ahl10 loci are important targets for the prevention and treatment of age-related hearing loss.

Computational study of the impact of nucleotide variations on highly conserved proteins: In the case of actin

Sequencing of individual human genomes enables studying relationship among nucleotide variations, amino acid substitutions, effect on protein structures and diseases. Many studies have found general tendencies, for instance, that pathogenic variations tend to be found in the buried regions of the protein structures, that benign variations tend to be found on the surface of the proteins, and that variations on evolutionary conserved residues tend to be pathogenic. These tendencies were deduced from globular proteins with standard evolutionary changes in amino acid sequences. In this study, we investigated the variation distribution on actin, one of the highly conserved proteins. Many nucleotide variations and three-dimensional structures of actin have been registered in databases. By combining those data, we found that variations buried inside the protein were rather benign and variations on the surface of the protein were pathogenic. This idiosyncratic distribution of the variation impact is likely ascribed to the extensive use of the surface of the protein for protein-protein interactions in actin.

High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases

It is widely accepted that molecular reductionist views of highly complex human physiologic activity, e.g., the aging process, as well as therapeutic drug efficacy are largely oversimplifications. Currently some of the most effective appreciation of biologic disease and drug response complexity is achieved using high-dimensionality (H-D) data streams from transcriptomic, proteomic, metabolomics, or epigenomic pipelines. Multiple H-D data sets are now common and freely accessible for complex diseases such as metabolic syndrome, cardiovascular disease, and neurodegenerative conditions such as Alzheimer's disease. Over the last decade our ability to interrogate these high-dimensionality data streams has been profoundly enhanced through the development and implementation of highly effective bioinformatic platforms. Employing these computational approaches to understand the complexity of age-related diseases provides a facile mechanism to then synergize this pathologic appreciation with a similar level of understanding of therapeutic-mediated signaling. For informative pathology and drug-based analytics that are able to generate meaningful therapeutic insight across diverse data streams, novel informatics processes such as latent semantic indexing and topological data analyses will likely be important. Elucidation of H-D molecular disease signatures from diverse data streams will likely generate and refine new therapeutic strategies that will be designed with a cognizance of a realistic appreciation of the complexity of human age-related disease and drug effects. We contend that informatic platforms should be synergistic with more advanced chemical/drug and phenotypic cellular/tissue-based analytical predictive models to assist in either de novo drug prioritization or effective repurposing for the intervention of aging-related diseases. SIGNIFICANCE STATEMENT: All diseases, as well as pharmacological mechanisms, are far more complex than previously thought a decade ago. With the advent of commonplace access to technologies that produce large volumes of high-dimensionality data (e.g., transcriptomics, proteomics, metabolomics), it is now imperative that effective tools to appreciate this highly nuanced data are developed. Being able to appreciate the subtleties of high-dimensionality data will allow molecular pharmacologists to develop the most effective multidimensional therapeutics with effectively engineered efficacy profiles.

Biophysics at Waseda University

Biophysics in Waseda University was started in 1965 as one of the three key research areas that constitute the Physics Department. In the biophysics group, one theoretical lab and two experimental labs are now working on the cutting-edge themes on biophysics, disseminating the ideas and knowledge of biophysics to undergraduate and graduate students from the viewpoint of physics.

Toward the next step in G protein-coupled receptor research: a knowledge-driven analysis for the next potential targets in drug discovery

More than 800 G protein-coupled receptor (GPCR) genes have been discovered in the human genome. Towards the next step in GPCR research, we performed a knowledge-driven analysis of orphan class-A GPCRs that may serve as novel targets in drug discovery. We examined the relationship between 61 orphan class-A GPCR genes and diseases using the Online Mendelian Inheritance in Man (OMIM) database and the DDSS tool. The OMIM database contains data on disease-related variants of the genes. Particularly, the variants of GPR101, GPR161, and GPR88 are related to the genetic diseases: growth hormone-secreting pituitary adenoma 2, pituitary stalk interruption syndrome (not confirmed), and childhood-onset chorea with psychomotor retardation, respectively. On the other hand, the Drug Discovery and Diagnostic Support System (DDSS) tool suggests that 48 out of the 61 orphan receptor genes are related to diseases, judging from their co-occurrences in abstracts of biomedical literature. Notably, GPR50 and GPR3 are related to as many as 25 and 24 disease-associated keywords, respectively. GPR50 is related to 17 keywords of psychiatric disorders, whereas GPR3 is related to 11 keywords of neurological disorders. The aforementioned five orphan GPCRs were characterized genetically, structurally and functionally using the structural life science data cloud VaProS, so as to evaluate their potential as next targets in drug discovery.