This mini-review explores the potential of precision medicine and personalized nutrition in addressing health challenges faced by perimenopausal women, focusing on the role of genetic polymorphisms in key metabolic pathways. Specifically focus on the single nucleotide polymorphisms (SNPs) in the COMT, FUT2, and MTHFR genes, which influence neurotransmitter metabolism, gut microbiota composition, and folate homeostasis, respectively. These polymorphisms are critical in modulating hormonal fluctuations, metabolic imbalances, and nutrient absorption during perimenopause. The review highlights the impact of COMT rs4680 on stress response and mood disorders, FUT2 rs602662 and rs601338 on vitamin B12 absorption and cortisol metabolism, and MTHFR rs1801133 and rs1801131 on homocysteine levels and cardiovascular risk. Furthermore, the integration of machine learning in precision medicine is discussed, offering insights into how genetic data can optimize personalized interventions. This approach enables targeted nutritional and therapeutic strategies to mitigate the metabolic and psychological effects of perimenopause. Overall, this review underscores the importance of incorporating genetic testing into preventive care for perimenopausal women to enhance quality of life and promote healthy aging.
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http://dx.doi.org/10.1016/j.clinsp.2024.100549 | DOI Listing |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11664282 | PMC |
Sci Rep
December 2024
Medical Genomics Research Department, King Abdullah International Medical Research Center, King Saud bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia.
In order to plan and facilitate the culture of personalized / precision medicine in medical practices within any healthcare institution, it is requisite for healthcare professionals like clinicians to have a clear understanding and approach towards the practices of personalized genetic testing. This nationwide cross-sectional study aimed to measure the perceptions and knowledge of clinicians towards personalized genetic testing and assess their current practices of personalized genetic testing in clinical settings through an online self-administered questionnaire in Saudi Arabia. The results of the study revealed that almost two-fifths of participants were responsible for ordering genetic tests directly (39.
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December 2024
Laboratory Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou, 341000, China.
Warfarin is the most widely used oral anticoagulant in clinical practice. The cytochrome P450 2C9 (CYP2C9), vitamin K epoxide reductase complex 1 (VKORC1), and cytochrome P450 4F2 (CYP4F2) genotypes are associated with warfarin dose requirements in China. Accurate genotyping is vital for obtaining reliable genotype-guided warfarin dosing information.
View Article and Find Full Text PDFTheranostic drugs represent an emerging path to deliver on the promise of precision medicine. However, bottlenecks remain in characterizing theranostic targets, identifying theranostic lead compounds, and tailoring theranostic drugs. To overcome these bottlenecks, we present the Theranostic Genome, the part of the human genome whose expression can be utilized to combine therapeutic and diagnostic applications.
View Article and Find Full Text PDFBAY 2413555 is a novel selective and reversible positive allosteric modulator of the type 2 muscarinic acetylcholine (M2) receptor, aimed at enhancing parasympathetic signaling and restoring cardiac autonomic balance for the treatment of heart failure (HF). This study tested the safety, tolerability and pharmacokinetics of this novel therapeutic option. REMOTE-HF was a multicenter, double-blind, randomized, placebo-controlled, phase Ib dose-titration study with two active arms.
View Article and Find Full Text PDFNat Commun
December 2024
State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center (BIOPIC) and Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), Peking University, 100871, Beijing, China.
Deciphering how noncoding DNA determines gene expression is critical for decoding the functional genome. Understanding the transcription effects of noncoding genetic variants are still major unsolved problems, which is critical for downstream applications in human genetics and precision medicine. Here, we integrate regulatory-specific neural networks and tissue-specific gradient-boosting trees to build SVEN: a hybrid sequence-oriented architecture that can accurately predict tissue-specific gene expression level and quantify the tissue-specific transcriptomic impacts of structural variants across more than 350 tissues and cell lines.
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