Multiset sparse redundancy analysis for high‐dimensional omics data

Csala, Attila; Hof, Michel H.; Zwinderman, Aeilko H.

doi:10.1002/bimj.201700248

Cited by 9 publications

(5 citation statements)

References 18 publications

(24 reference statements)

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“…This information is crucial for examining the impact of modifications to gut flora on Rg 5 in the treatment of NAFLD. Redundancy analysis (RDA) is a multivariate statistical method primarily used to explore the relationship between multivariate response data and one or more sets of explanatory variables [ 26 ]. The results showed that at the genus level, TC, TG, LDL-C, ALT, AST, and MDA were positively correlated with Allobaulum and Lactobacillus , while being negatively correlated with Oscillospira , Bifidobacterium , and Turicibacter .…”

Section: Resultsmentioning

confidence: 99%

Ginsenoside Rg5 Activates the LKB1/AMPK/mTOR Signaling Pathway and Modifies the Gut Microbiota to Alleviate Nonalcoholic Fatty Liver Disease Induced by a High-Fat Diet

Shi,

Chen,

et al. 2024

Nutrients

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The primary objective of this investigation was to elucidate the manner in which ginsenoside Rg5 (Rg5) ameliorates nonalcoholic fatty liver disease (NAFLD) via the modulation of the gut microbiota milieu. We administered either a standard diet (ND) or a high-fat diet (HFD), coupled with 12-week treatment employing two distinct doses of Rg5 (50 and 100 mg/kg/d), to male C57BL/6J mice. In comparison to the HFD cohort, the Rg5-treated group demonstrated significant enhancements in biochemical parameters, exemplified by a substantial decrease in lipid concentrations, as well as the reduced expression of markers indicative of oxidative stress and liver injury. This signifies a mitigation of hepatic dysfunction induced by an HFD. Simultaneously, Rg5 demonstrates the capacity to activate the LKB1/AMPK/mTOR signaling pathway, instigating energy metabolism and consequently hindering the progression of NAFLD. Furthermore, we underscored the role of Rg5 in the treatment of NAFLD within the gut-microbiota-liver axis. Analysis via 16S rRNA sequencing unveiled that Rg5 intervention induced alterations in gut microbiota composition, fostering an increase in beneficial bacteria, such as Bacteroides and Akkermansia, while concurrently reducing the relative abundance of detrimental bacteria, exemplified by Olsenella. Furthermore, employing fecal microbiota transplantation (FMT) experiments, we observed analogous outcomes in mice subjected to fecal bacterial transplants, providing additional verification of the capacity of Rg5 to mitigate NAFLD in mice by actively participating in the restoration of gut microbiota via FMT. Drawing from these data, the regulation of the gut microbiota is recognized as an innovative strategy for treating or preventing NAFLD and metabolic syndrome. Consequently, these research findings suggest that Rg5 holds promise as a potential therapeutic agent for NAFLD management.

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Section: Resultsmentioning

confidence: 99%

Ginsenoside Rg5 Activates the LKB1/AMPK/mTOR Signaling Pathway and Modifies the Gut Microbiota to Alleviate Nonalcoholic Fatty Liver Disease Induced by a High-Fat Diet

Shi,

Chen,

et al. 2024

Nutrients

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“…Therefore, multiset penalized RDA enables the simultaneous analysis of multiple biomolecular variables that are dispersed over multiple omics domains, while it accounts for the hierarchical structure between the data sources. One application of multiset penalized RDA is multiset sparse redundancy analysis (multi-sRDA) (53), which facilitates variable selection. A summary of the multivariate methods reviewed in this text can be found in Table 2.…”

Section: Penalized Multi-block Redundancy Analysismentioning

confidence: 99%

Multivariate Statistical Methods for High-Dimensional Multiset Omics Data Analysis

Csala

Zwinderman

2019

Computational Biology

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This chapter covers the state-of-the-art multivariate statistical methods designed for high-dimensional multiset omics data analysis. Recent biotechnological developments have enabled large-scale measurement of various biomolecular data, such as genotypic and phenotypic data, dispersed over various omics domains. An emergent research direction is to analyze these data sources using an integrated approach to better model and understand the underlying biology of complex disease conditions. However, comprehensive analysis techniques that can handle both the size and complexity, and at the same time can account for the hierarchical structure of such data, are lacking. An overview of some of the developments in multivariate techniques for high-dimensional omics data analysis, highlighting two well-known multivariate methods, canonical correlation analysis (CCA) and redundancy analysis (RDA), is provided in this chapter. Penalized versions of CCA are widespread in the omics data analysis field, and there is recent work on multiset penalized RDA that is applicable to multiset omics data. How these methods meet the statistical challenges that come with high-dimensional multiset omics data analysis and help to further our understanding of the human condition in terms of health and disease are presented. Additionally, the current challenges to be resolved in the field of omics data analysis are discussed.

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“…The Redundancy Analysis (RDA) is based on multivariate regression and models linear combinations of explanatory variables, for example, environmental predictors, which explain linear combinations of response variables (Legendre and Legendre 1988), allowing the identi cation of traits with the greater contribution in the discrimination of genotypes in each environment. Some examples about RDA have recently been applied in works in different elds, such as health (Choi and Seo 2022), biology (Csala et al 2019), and environment (Chuang et al 2019). However, there is a need for more studies of its usefulness to bring more resolution to water stress plant breeding trials.…”

Section: Introductionmentioning

confidence: 99%

Breeding trials in water-stress conditions: identification of sensitive traits in early stages and characterization of a tropical maize public panel

Machado

Pontes

Silveira

et al. 2023

Preprint

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One of the major goals of modern agriculture is to achieve increased crop yield using less water. Despite the significant advances in genomics, a phenotypic characterization efficient is essential for the success of a modern breeding program, which wants to speed up the genetic gains by deploying selection in the early stages. Thus, this study aimed to identify which traits are most important to discriminate the maize genotypes to support early selection under contrasting water availability conditions. For this, we used a public diversity panel consisting of 360 tropical maize inbred lines, involving two conditions, well-watered (WW) and water-stress (WS), in eight trials. Evaluations were carried out in the phenological stage V6 for shoot and root traits. There was a significant variation in the panel performance, mainly for root traits under WS conditions, composing six clusters. However, the traits showed a similar pattern of clustering evidenced by principal components in WW and WS conditions. Moreover, a strong relationship was found among the roots' length, surface area, and volume. Based on this, we suggest discarding the most error-prone ones. Our results showed via Redundancy Analysis (RDA) that plant height, stalk diameter, and lateral roots length are traits more sensitive to WS and, therefore, may be considered in early selection in breeding programs aiming for water use efficiency.

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Multiset sparse redundancy analysis for high‐dimensional omics data

Cited by 9 publications

References 18 publications

Ginsenoside Rg5 Activates the LKB1/AMPK/mTOR Signaling Pathway and Modifies the Gut Microbiota to Alleviate Nonalcoholic Fatty Liver Disease Induced by a High-Fat Diet

Ginsenoside Rg5 Activates the LKB1/AMPK/mTOR Signaling Pathway and Modifies the Gut Microbiota to Alleviate Nonalcoholic Fatty Liver Disease Induced by a High-Fat Diet

Multivariate Statistical Methods for High-Dimensional Multiset Omics Data Analysis

Breeding trials in water-stress conditions: identification of sensitive traits in early stages and characterization of a tropical maize public panel

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