Ranked in the topmost position among the deadliest diseases in the world, cardiovascular diseases (CVDs) are a global burden with alterations in heart and blood vessels. Early diagnostics and prognostics could be the best possible solution in CVD management. OMICS (genomics, proteomics, transcriptomics, and metabolomics) approaches could be able to tackle the challenges against CVDs. Genome-wide association studies along with next-generation sequencing with various computational biology tools could lead a new sight in early detection and possible therapeutics of CVDs. Human cardiac proteins are also characterized by mass spectrophotometry which could open the scope of proteomics approaches in CVD. Besides this, regulation of gene expression by transcriptomics approaches exhibits a new insight while metabolomics is the endpoint on the downstream of multi-omics approaches to confront CVDs from the early onset. Although a lot of challenges needed to overcome in CVD management, OMICS approaches are certainly a new prospect.
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http://dx.doi.org/10.5808/gi.21002 | DOI Listing |
Adv Biotechnol (Singap)
March 2024
State Key Laboratory of Biocontrol, Guangdong Provincial Key Laboratory of Plant Resources, School of Life Sciences, Sun Yat-Sen University, Guangzhou, 510275, China.
Plant lipids are a diverse group of biomolecules that play essential roles in plant architecture, physiology, and signaling. To advance our understanding of plant biology and facilitate innovations in plant-based product development, we must have precise methods for the comprehensive analysis of plant lipids. Here, we present a comprehensive overview of current research investigating plant lipids, including their structures, metabolism, and functions.
View Article and Find Full Text PDFmSphere
January 2025
Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Coronaviruses (CoV) emerge suddenly from animal reservoirs to cause novel diseases in new hosts. Discovered in 2012, the Middle East respiratory syndrome coronavirus (MERS-CoV) is endemic in camels in the Middle East and is continually causing local outbreaks and epidemics. While all three newly emerging human CoVs from the past 20 years (SARS-CoV, SARS-CoV-2, and MERS-CoV) cause respiratory disease, each CoV has unique host interactions that drive differential pathogeneses.
View Article and Find Full Text PDFCochrane Database Syst Rev
January 2025
Cornell Joan Klein Jacobs Center for Precision Nutrition and Health, Cornell University, Ithaca, NY, USA.
Background: Precision nutrition-based methods develop tailored interventions and/or recommendations accounting for determinants of intra- and inter-individual variation in response to the same diet, compared to current 'one-size-fits-all' population-level approaches. Determinants may include genetics, current dietary habits and eating patterns, circadian rhythms, health status, gut microbiome, socioeconomic and psychosocial characteristics, and physical activity. In this systematic review, we examined the evidence base for the effect of interventions based on precision nutrition approaches on overweight and obesity in children and adolescents to help inform future research and global guidelines.
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January 2025
Department of Biology, Pace University, One Pace Plaza, 3rd Floor, New York, 10038, NY, United States of America.
Rafflesiaceae is a family of endangered plants whose members are solely parasitic to the tropical grape vine (Vitaceae). Currently, the genetics of their crosstalk with the host remains unexplored. In this study, we use homology-based approaches to characterize micro-RNAs (miRNAs) expressed by and from published omics data.
View Article and Find Full Text PDFMethods
January 2025
Department of Computer Science and Engineering, School of Information Science and Engineering, Yunnan University, Kunming, 650504, Yunnan, China. Electronic address:
Cancer is a complex and heterogeneous disease, and accurate cancer subtyping can significantly improve patient survival rates. The complexity of cancer spans multiple omics levels, and analyzing multi-omics data for cancer subtyping is a focus of considerable attention. However, extracting complementary information from different omics data sources and adaptively integrating them remains a major challenge.
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