Omics Studies in CKD: Diagnostic Opportunities and Therapeutic Potential DOI
Merita Rroji, Goce Spasovski

PROTEOMICS, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 11, 2024

Omics technologies have significantly advanced the prediction and therapeutic approaches for chronic kidney disease (CKD) by providing comprehensive molecular insights. This is a review of current state future prospects integrating biomarkers into clinical practice CKD, aiming to improve patient outcomes targeted interventions. In fact, integration genomic, transcriptomic, proteomic, metabolomic data has enhanced our understanding CKD pathogenesis identified novel an early diagnosis treatment. Advanced computational methods artificial intelligence (AI) further refined multi-omics analysis, leading more accurate models progression responses. These developments highlight potential care with precise individualized treatment plan .

Language: Английский

Multifluid Metabolomics Identifies Novel Biomarkers for Irritable Bowel Syndrome DOI Creative Commons
Daniel Kirk, Panayiotis Louca, Ilias Attaye

et al.

Metabolites, Journal Year: 2025, Volume and Issue: 15(2), P. 121 - 121

Published: Feb. 12, 2025

Background/Objectives: Irritable bowel syndrome (IBS) is a complex disorder affecting 10% of the global population, but underlying mechanisms remain poorly understood. By integrating multifluid metabolomics, we aimed to identify metabolite markers IBS in large population-based cohort. Methods: We included individuals from TwinsUK with and without IBS, ascertained using Rome III criteria, analysed serum (232 cases, 1707 controls), urine (185 1341 stool (186 1284 controls) metabolites (Metabolon Inc.). Results: After adjusting for covariates, multiple testing, 44 unique (25 novel) were associated including lipids, amino acids, xenobiotics. Androsterone sulphate, sulfated steroid hormone precursor, was lower odds both (0.69 [95% confidence interval = 0.56-0.85], p 2.34 × 10-4) (0.75 [0.63-0.90], 1.54 10-3. Moreover, suberate (C8-DC) higher (1.36 [1.15-1.61]; 1.84 (0.76 [0.63-0.91]; 2.30 10-3). On contrary, 32 appeared be fluid-specific, indole, 13-HODE + 9-HODE, pterin, bilirubin (E,Z or Z,Z), urolithin. The remaining 10 one fluid suggestive evidence (p < 0.05) another fluid. Finally, identified androgenic signalling, dicarboxylates, haemoglobin, porphyrin metabolism significantly over-represented compared controls. Conclusions: Our results highlight utility multi-fluid approach research, revealing distinct metabolic signatures across biofluids.

Language: Английский

Citations

1

Vitamin A carotenoids, but not retinoids, mediate the impact of a healthy diet on gut microbial diversity DOI Creative Commons
Ana M. Valdes, Panayiotis Louca, Alessia Visconti

et al.

BMC Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: Aug. 7, 2024

Abstract Background Vitamin A is essential for physiological processes like vision and immunity. A’s effect on gut microbiome composition, which affects absorption metabolism of other vitamins, still unknown. Here we examined the relationship between metagenome composition six vitamin A-related metabolites (two retinoid: -retinol, 4 oxoretinoic acid (oxoRA) four carotenoid metabolites, including beta-cryptoxanthin three carotene diols). Methods We included 1053 individuals from TwinsUK cohort with measured in serum faeces, diet history, assessed by shotgun sequencing. Results were replicated 327 women ZOE PREDICT-1 study. Five positively correlated alpha diversity ( r = 0.15 to 0.20, p < × 10 −6 ). Carotenoid compounds short-chain fatty-acid-producing bacteria Faecalibacterium prausnitzii Coprococcus eutactus. Retinol was not associated any microbial species. found that could predict circulating levels carotenoids AUCs ranging 0.66 0.74 using random forest models, but retinol (AUC 0.52). The healthy eating index (HEI) strongly all compounds, retinoids. investigated mediating role a diversity, finding significantly mediated 18 25% HEI diversity. Conclusions Our results show strong links potential pattern.

Language: Английский

Citations

4

Machine Learning Metabolomics Profiling of Dietary Interventions from a Six-Week Randomised Trial DOI Creative Commons
Afroditi Kouraki, Ana Nogal,

Weronika Nocun

et al.

Metabolites, Journal Year: 2024, Volume and Issue: 14(6), P. 311 - 311

Published: May 29, 2024

Metabolomics can uncover physiological responses to prebiotic fibre and omega-3 fatty acid supplements with known health benefits identify response-specific metabolites. We profiled 534 stool 799 serum metabolites in 64 healthy adults following a 6-week randomised trial comparing daily versus inulin supplementation. Elastic net regressions were used separately the whose change concentration discriminated between two types of supplementations. Random forest was explore gut microbiome’s contribution levels identified from matching samples. Changes 3-carboxy-4-methyl-5-propyl-2-furanpropanoate indoleproprionate accurately (area under curve (AUC) = 0.87 [95% confidence interval (CI): 0.63–0.99]), while eicosapentaenoate indicated supplementation (AUC 0.86 CI: 0.64–0.98]). Univariate analysis also showed significant increases fibre, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate, omega-3. Out these, only partly explained by changes microbiome composition 0.61 0.58–0.64] Rho 0.21 0.08–0.34]) positively correlated increase abundance genus Coprococcus (p 0.005). three The shifts microbiome, particularly Coprococcus, previously linked better health.

Language: Английский

Citations

1

Omics Studies in CKD: Diagnostic Opportunities and Therapeutic Potential DOI
Merita Rroji, Goce Spasovski

PROTEOMICS, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 11, 2024

Omics technologies have significantly advanced the prediction and therapeutic approaches for chronic kidney disease (CKD) by providing comprehensive molecular insights. This is a review of current state future prospects integrating biomarkers into clinical practice CKD, aiming to improve patient outcomes targeted interventions. In fact, integration genomic, transcriptomic, proteomic, metabolomic data has enhanced our understanding CKD pathogenesis identified novel an early diagnosis treatment. Advanced computational methods artificial intelligence (AI) further refined multi-omics analysis, leading more accurate models progression responses. These developments highlight potential care with precise individualized treatment plan .

Language: Английский

Citations

0