Article
Pharmacology & Pharmacy
Whitaker Cohn, Mikhail Melnik, Calvin Huang, Bruce Teter, Sujyoti Chandra, Chunni Zhu, Laura Beth McIntire, Varghese John, Karen H. Gylys, Tina Bilousova
Summary: This study analyzed the composition of EVs derived from microglial cells in the brains of AD patients, revealing significant changes in certain markers in AD EVs compared to normal cases, indicating a potential role for EVs in the progression of AD.
FRONTIERS IN PHARMACOLOGY
(2021)
Review
Biochemistry & Molecular Biology
Lei Wu, Xinqiang Xie, Tingting Liang, Jun Ma, Lingshuang Yang, Juan Yang, Longyan Li, Yu Xi, Haixin Li, Jumei Zhang, Xuefeng Chen, Yu Ding, Qingping Wu
Summary: Aging is closely related to human diseases, but its biological mechanism remains unclear. This review summarizes multi-omics methods and highlights the importance of integrating different omics technologies to reveal the interactions among aging molecules from a multidimensional perspective. The findings provide new insights into the discovery of aging biomarkers, understanding the mechanism of aging, and identifying novel targets for antiaging interventions.
Article
Biochemistry & Molecular Biology
Maxime Francois, Avinash Karpe, Jian-Wei Liu, David J. Beale, Maryam Hor, Jane Hecker, Jeff Faunt, John Maddison, Sally Johns, James D. Doecke, Stephen Rose, Wayne R. Leifert
Summary: The metabolomic and proteomic basis of mild cognitive impairment (MCI) and Alzheimer's disease (AD) is not well understood. This study examined the plasma samples of individuals with MCI or AD, as well as age- and gender-matched cognitively normal individuals, to identify cellular pathways and biomarkers associated with the diseases. The analysis revealed specific proteins that distinguish AD from MCI and cognitively normal groups, and identified various metabolic pathways affected in AD. These findings contribute to the understanding of the diseases and may be useful for future clinical trials.
Review
Chemistry, Medicinal
S. Akila Parvathy Dharshini, Nela Pragathi Sneha, Dhanusha Yesudhas, A. Kulandaisamy, Uday Rangaswamy, Anusuya Shanmugam, Y-h. Taguchi, M. Michael Gromiha
Summary: The development of drugs for Alzheimer's disease is challenging due to the progressive deterioration of neurons and the heterogeneity of the disease. Single-cell RNA sequencing technologies help identify cell type-specific biomarkers for selecting therapeutic targets. This review also highlights the use of machine learning techniques in Alzheimer's disease research.
CURRENT TOPICS IN MEDICINAL CHEMISTRY
(2022)
Article
Biology
Nima Zafari, Parsa Bathaei, Mahla Velayati, Fatemeh Khojasteh-Leylakoohi, Majid Khazaei, Hamid Fiuji, Mohammadreza Nassiri, Seyed Mahdi Hassanian, Gordon A. Ferns, Elham Nazari, Amir Avan
Summary: The burden and increasing trend of colorectal cancer in young adults highlight the importance of understanding its mechanisms, identifying new markers, and improving treatments. Precision medicine is a global trend, and the discovery of biomarkers and therapeutic targets is a step towards this trend. Multi-omics data and integrated analysis are being explored for personalized colorectal cancer management, but data integration and analysis present challenges. This review summarizes the application of statistical and machine learning techniques to analyze multi-omics data and their contribution to the discovery of diagnostic and prognostic biomarkers and therapeutic targets, as well as discusses the future clinical management of colorectal cancer.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Microbiology
Carlos G. Gonzalez, Robert H. Mills, Qiyun Zhu, Consuelo Sauceda, Rob Knight, Parambir S. Dulai, David J. Gonzalez
Summary: By utilizing a multi-omics approach, this study identified distinct molecular profiles between colonic and ileal Crohn's disease (CD) subtypes, suggesting separate pathologies associated with the two disease locations. Colonic CD displayed similarities to ulcerative colitis, while ileal CD showed a unique profile characterized by bile acid-driven changes. These findings highlight the power of multi-omics in discovering biomarkers and understanding the underlying biology of inflammatory bowel diseases.
Article
Biochemistry & Molecular Biology
Xingxin Pan, Brandon Burgman, Erxi Wu, Jason H. Huang, Nidhi Sahni, S. Stephen Yi
Summary: Effective and precise classification of glioma patients for their disease risks is critical to improving early diagnosis and patient survival. However, a robust framework for integrating multi-omics data types to efficiently and precisely predict survival prognosis is still lacking. Additionally, effective therapeutic targets for treating glioma patients with poor prognoses are urgently needed.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2022)
Article
Medicine, Research & Experimental
Junling Pang, Xianmei Qi, Ya Luo, Xiaona Li, Ting Shu, Baicun Li, Meiyue Song, Ying Liu, Dong Wei, Jingyu Chen, Jing Wang, Chen Wang
Summary: Silicosis is a severe occupational lung disease with limited treatment options, leading to an urgent need for effective drugs to slow its progression. This study revealed significant metabolic alterations, specifically upregulation of arachidonic acid (AA) pathway metabolites PGD(2) and TXA(2) in silicosis lungs. The antagonist Ramatroban showed promise in alleviating pulmonary inflammation, fibrosis, and cardiopulmonary dysfunction in a silicosis mouse model, suggesting it as a potential therapeutic drug for silicosis.
Article
Neurosciences
Dun Li, Hongxi Yang, Mingqian Lyu, Ju Wang, Weili Xu, Yaogang Wang
Summary: This study identified therapeutic targets and biological mechanisms of acupuncture therapy (AT) in treating dementia through integrated analysis. The results demonstrated that AT improved Alzheimer's disease (AD) and vascular dementia (VaD) by modulating synaptic function, immunity, inflammation, and apoptosis. This study provides valuable clues for complementing and combining pharmacotherapy.
JOURNAL OF ALZHEIMERS DISEASE
(2023)
Article
Biochemistry & Molecular Biology
Lan Wei, Jingjing Gao, Liangzhi Wang, Qianru Tao, Chao Tu
Summary: Clinicians have conducted a study to understand the molecular basis of diabetic kidney disease (DKD) and its potential treatment targets. Through the use of different analysis techniques, they identified molecular and protein changes in DKD, including accumulation of extracellular matrix, activation of inflammatory microenvironment, oxidative stress, and lipid metabolism disorders. The study also found that specific signaling pathways and kinases play crucial roles in the pathogenesis of DKD. Targeting these molecules and pathways could be a promising approach for DKD treatment.
HUMAN MOLECULAR GENETICS
(2023)
Article
Genetics & Heredity
Nandan P. Deshpande, Stephen M. Riordan, Claire J. Gorman, Shaun Nielsen, Tonia L. Russell, Carolina Correa-Ospina, Bentotage S. M. Fernando, Shafagh A. Waters, Natalia Castano-Rodriguez, Si Ming Man, Nicodemus Tedla, Marc R. Wilkins, Nadeem O. Kaakoush
Summary: This study comprehensively assessed the esophageal microenvironment in patients with gastro-esophageal reflux disease and metaplasia, identifying bacterial strain-specific signatures with high relevance to disease progression.
Review
Oncology
Timothy I. Shaw, Bi Zhao, Yuxin Li, Hong Wang, Liang Wang, Brandon Manley, Paul A. Stewart, Aleksandra Karolak
Summary: This article discusses the role of cancer-specific alternatively spliced events (ASE) in cancer pathogenesis and proposes an integrated multi-omics strategy to mine ASE as potential targets for therapeutic development. The article provides an overview of current multi-omics strategies in characterizing ASEs using transcriptome, proteome, and protein structure prediction algorithms, discusses the limitations and knowledge gaps associated with each technology and informatics analytics, and explores future directions for the full integration of multi-omics data in ASE target discovery.
FRONTIERS IN ONCOLOGY
(2022)
Article
Cell Biology
Min Seo Kim, Minku Song, Beomsu Kim, Injeong Shim, Dan Say Kim, Pradeep Natarajan, Ron Do, Hong-Hee Won
Summary: Drug targets with genetic support have a higher likelihood of success in clinical trials. This study introduces a genetic-driven approach that prioritizes drug targets for dyslipidemia based on causal inferences. By conducting multiomics and multi-trait analyses, the study identifies 30 potential therapeutic targets, with a 22-fold higher likelihood of being approved or under investigation compared to targets identified through genome-wide association studies. The results demonstrate the promise of the genetic driven approach for target prioritization and informing about adverse effects and repurposing opportunities.
CELL REPORTS MEDICINE
(2023)
Article
Multidisciplinary Sciences
Lea Maitre, Mariona Bustamante, Carles Hernandez-Ferrer, Denise Thiel, Chung-Ho E. Lau, Alexandros Siskos, Marta Vives-Usano, Carlos Ruiz-Arenas, Dolors Pelegri-Siso, Oliver Robinson, Dan Mason, John Wright, Solene Cadiou, Remy Slama, Barbara Heude, Maribel Casas, Jordi Sunyer, Eleni Z. Papadopoulou, Kristine B. Gutzkow, Sandra Andrusaityte, Regina Grazuleviciene, Marina Vafeiadi, Leda Chatzi, Amrit K. Sakhi, Cathrine Thomsen, Ibon Tamayo, Mark Nieuwenhuijsen, Jose Urquiza, Eva Borras, Eduard Sabido, Ines Quintela, Angel Carracedo, Xavier Estivill, Muireann Coen, Juan R. Gonzalez, Hector C. Keun, Martine Vrijheid
Summary: Environmental exposures during early life have a significant impact on lifelong health, but the molecular effects underlying these exposures are poorly understood. In the HELIX project, researchers investigate the associations between individual exposomes and multi-omics profiles in a cohort of 1301 mother-child pairs. The findings reveal potential biological responses and sources of exposure, with pregnancy exposures primarily affecting child DNA methylation changes and childhood exposures affecting features across multiple omics layers, such as the serum metabolome.
NATURE COMMUNICATIONS
(2022)
Article
Oncology
Giuseppe Fiorentino, Roberto Visintainer, Enrico Domenici, Mario Lauria, Luca Marchetti
Summary: Modern profiling technologies have made significant progress in precision medicine and disease management. The integration of multiple omics data types for patient classification, as demonstrated by MOUSSE, shows potential advantages in identifying meaningful phenotype groups. MOUSSE, a new unsupervised multi-omics integration tool, outperforms other algorithms in clustering patients based on survival for various cancer types and extracts relevant biological features associated with patient survival.
Article
Biochemistry & Molecular Biology
R. Sai Swaroop, P. S. Akhil, Pradhan Sai Sanwid, Prasad Bandana, Rao K. Raksha, Manjunath Meghana, Choudhary Bibha, Venketesh Sivaramakrishnan
Summary: Amyotrophic Lateral Sclerosis (ALS) is a progressive and incurable neurodegenerative disease involving motor neurons. Biomarker identification and finding therapeutic targets can help manage the disease. An integrative analysis of transcriptomic datasets revealed deregulation in fatty liver disease, oxidative phosphorylation, and ribosome-associated pathways in ALS patients and transgenic mice datasets. Further analysis showed that oxidative phosphorylation is a major deregulated pathway, and mitochondrial electron transport chain inhibitors reduced amyloidogenesis. This study highlights the importance of mitochondrial oxidative phosphorylation as a potential therapeutic target for ALS.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Biochemistry & Molecular Biology
Sai Krishna Srimadh Bhagavatham, Sujith Kumar Pulukool, Sai Sanwid Pradhan, R. Saiswaroop, Ashwin Ashok Naik, Datta V. M. Darshan, Venketesh Sivaramakrishnan
Summary: Rheumatoid Arthritis (RA) is a chronic systemic autoimmune disease. This study aimed to identify the critical pathways involved in RA pathophysiology through the analysis of transcriptomics, proteomics, and metabolomics datasets. The analysis revealed that SNPs associated with RA were categorized into pathways driving immune response and cytokine production. Further analysis identified gene expression and metabolic pathways with potential implications for RA.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Biochemistry & Molecular Biology
G. Siva Sankari, Remya James, Febby Payva, Venketesh Sivaramakrishnan, T. V. Vineeth Kumar, Subbarao Kanchi, K. S. Santhy
Summary: SLC20A1/PiT1 is a sodium-dependent inorganic phosphate transporter that is associated with disease and has deleterious nsSNPs. Protein modeling and MD simulations were performed to evaluate the impact of these SNPs on protein structure and function. The results show that SNPs can lead to structural perturbations and potentially affect the function of SLC20A1.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Biotechnology & Applied Microbiology
Sai Sanwid Pradhan, K. Raksha Rao, Meghana Manjunath, R. Saiswaroop, Durga Prasad Patnana, Kanikaram Sai Phalguna, Bibha Choudhary, Venketesh Sivaramakrishnan
Summary: Huntington's disease is an incurable neurodegenerative disease caused by the expansion of the polyglutamine tract in the protein Huntingtin. A study was conducted to analyze the pathways modulated by vitamin B-6, B-12, and folate in relation to Huntington's disease using transcriptomic, metabolomic, and cofactor-protein network approaches. The results showed significant overlap between the pathways affected by these vitamins and those observed in HD patients and model systems. Additionally, treatment with vitamin B-6, B-12, or folate in a yeast model of HD showed impaired aggregate formation and modulation of various metabolic pathways. Knockout of specific genes also resulted in increased aggregates, which were mitigated by vitamin treatment. These findings suggest a potential role for vitamin B-6, B-12, and folate in preventing protein aggregation and their implications for HD.
Article
Cell Biology
Saiswaroop Rajaratnam, Akhil P. Soman, Kanikaram Sai Phalguna, Sai Sanwid Pradhan, Meghana Manjunath, Raksha Kanthavara Rao, Rajesh Babu Dandamudi, Sai Krishna Srimadh Bhagavatham, Sujith Kumar Pulukool, Sriram Rathnakumar, Sai Kocherlakota, Ashish Pargaonkar, Ravindra P. Veeranna, Natarajan Arumugam, Abdulrahman I. Almansour, Bibha Choudhary, Venketesh Sivaramakrishnan
Summary: Amyotrophic lateral sclerosis (ALS) is a fatal disease that affects motor neurons and is currently incurable. Multi-omics studies on both patients and model systems have shed light on the various molecular pathways involved in the disease, with yeast models proving to be particularly valuable in understanding gene amyloid interactions.
Article
Biochemistry & Molecular Biology
Sai Sanwid Pradhan, Sai Swaroop R., Sai Phalguna Kanikaram, Datta Darshan V.m., Ashish Pargaonkar, Rajesh Babu Dandamudi, Venketesh Sivaramakrishnan
Summary: Huntington's disease is caused by an expanded polyglutamine tract in the protein Huntingtin. Metabolomic analysis of a yeast model of HD showed significant changes in metabolic pathways between logarithmic and stationary phase cells. The arginine biosynthesis pathway was found to be common in stationary phase yeast and HD patients, and its modulation affected the aggregation of mutant HTT.
JOURNAL OF BIOMOLECULAR STRUCTURE & DYNAMICS
(2023)
Article
Endocrinology & Metabolism
Sriram Rathnakumar, Naga Sai Visweswar Kambhampati, R. Saiswaroop, Sai Sanwid Pradhan, G. Ramkumar, Nirmala Beeraka, Gopi Krishna Muddu, Sandeep Kumar, Sai Kiran Javvaji, Ashish Parangoankar, Venketesh Sivaramakrishnan, Sai Sathish Ramamurthy
Summary: This study identified molecular signatures associated with different phases of dengue through integrated clinical and metabolomic analysis. The findings have significant implications for dengue research.
Article
Materials Science, Multidisciplinary
Sriram Rathnakumar, Seemesh Bhaskar, Pradeep Kumar Badiya, Venketesh Sivaramakrishnan, Venkatesh Srinivasan, Sai Sathish Ramamurthy
Summary: We synthesized electrospun PVA nanofibers doped with Titania nanoparticles (NPs) for plasmon-coupled fluorescence studies and obtained enhanced effects, with the highest enhancements achieved using TiCN-doped nanofibers (about 150-fold). Nanofibers showed greater and highly polarized emission enhancements compared to 2D thin films, which exhibited dual polarizations at higher concentrations of PVA. These results suggest that 1D nanofibers can serve as green and low-cost alternatives to 2D nano thin films.
MRS COMMUNICATIONS
(2023)