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Dimension reduction of microbiome data linked Bifidobacterium and Prevotella to allergic rhinitis

Komaki, Shohei, Sahoyama, Yukari, Hachiya, Tsuyoshi, Koseki, Keita, Ogata, Yusuke, Hamazato, Fumiaki, Shiozawa, Manabu, Nakagawa, Tohru, Suda, Wataru, Hattori, Masahira, Kawakami, Eiryo·2024·Scientific Reports
DOI 10.1038/s41598-024-57934-xPMC PMC10995140
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Abstract

Dimension reduction has been used to visualise the distribution of multidimensional microbiome data, but the composite variables calculated by the dimension reduction methods have not been widely used to investigate the relationship of the human gut microbiome with lifestyle and disease. In the present study, we applied several dimension reduction methods, including principal component analysis, principal coordinate analysis (PCoA), non-metric multidimensional scaling (NMDS), and non-negative matrix factorization, to a microbiome dataset from 186 subjects with symptoms of allergic rhinitis (AR) and 106 controls. All the dimension reduction methods supported that the distribution of microbial data points appeared to be continuous rather than discrete. Comparison of the composite variables calculated from the different dimension reduction methods showed that the characteristics of the composite variables differed depending on the distance matrices and the dimension reduction methods. The first composite variables calculated from PCoA and NMDS with the UniFrac distance were strongly associated with AR (FDR adjusted P = 2.4 × 10–4 for PCoA and P = 2.8 × 10–4 for NMDS), and also with the relative abundance of Bifidobacterium and Prevotella. The abundance of Bifidobacterium was also linked to intake of several nutrients, including carbohydrate, saturated fat, and alcohol via composite variables. Notably, the association between the composite variables and AR was much stronger than the association between the relative abundance of individual genera and AR. Our results highlight the usefulness of the dimension reduction methods for investigating the association of microbial composition with lifestyle and disease in clinical research.

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Figure 1 Enterotypes and distribution of gut microbial composition. (a) Principal coordinate analysis plots based on the Jensen-Shannon divergence. The left panel shows the top 1 (x-axis) and 2 (y-axis) composite variables, while the right panel shows the top 1 (x-axis) and 3 (y-axis) composite variables. The dot colour indicates the enterotype calculated from the same Jensen-Shannon divergence matrix. (b) Relative abundances of representative genera by enterotype.
Figure 1 Enterotypes and distribution of gut microbial composition. (a) Principal coordinate analysis plots based on the Jensen-Shannon divergence. The left panel shows the top 1 (x-axis) and 2 (y-axis) composite variables, while the right panel shows the top 1 (x-axis) and 3 (y-axis) composite variables. The dot colour indicates the enterotype calculated from the same Jensen-Shannon divergence matrix. (b) Relative abundances of representative genera by enterotype.CC BY · PubMed Central
Figure 2 Distribution of the gut microbial community using different dimension reduction methods. (a) principal component analysis (PCA), (b) PCA on the centered log-ratio (CLR) transformed abundance matrix, (c, d) principal coordinate analysis with the Bray–Curtis dissimilarity (BCD) and the UniFrac distance, (e) non-negative matrix factorization, (f–h) non-metric multidimensional scaling with the Jensen-Shannon distance, BCD, and UniFrac distance. The top panel shows the top 1 (x-axis) and 2 (y-axis) composite variables, while the bottom panel shows the top 1 (x-axis) and 3 (y-axis) composite variables. The colour of the point indicates the log-transformed P/B ratio.
Figure 2 Distribution of the gut microbial community using different dimension reduction methods. (a) principal component analysis (PCA), (b) PCA on the centered log-ratio (CLR) transformed abundance matrix, (c, d) principal coordinate analysis with the Bray–Curtis dissimilarity (BCD) and the UniFrac distance, (e) non-negative matrix factorization, (f–h) non-metric multidimensional scaling with the Jensen-Shannon distance, BCD, and UniFrac distance. The top panel shows the top 1 (x-axis) and 2 (y-axis) composite variables, while the bottom panel shows the top 1 (x-axis) and 3 (y-axis) composite variables. The colour of the point indicates the log-transformed P/B ratio.CC BY · PubMed Central
Figure 3 Comparison and characterisation of composite variables. (a) Pairwise Spearman's rank correlations between composite variables. X- and y-axes were ordered based on hierarchical clustering. Highly correlated pairs (Spearman's rank correlation > 0.8) are indicated by asterisks (*). (b) Spearman's rank correlations between composite variable and genus-level relative abundance. Non-significant pairs (FDR-adjusted P value > 0.05) are shown as white cells. NMF: non-negative matrix factorization, P/B ratio: Prevotella-Bacteroides ratio, PC: principal component, CLR: centered log-ratio transformed, PCo: principal coordinate, NMDS: non-metric multidimensional scaling, JSD: Jensen-Shannon divergence, BCD: Bray–Curtis dissimilarity, UniF: UniFrac distance.
Figure 3 Comparison and characterisation of composite variables. (a) Pairwise Spearman's rank correlations between composite variables. X- and y-axes were ordered based on hierarchical clustering. Highly correlated pairs (Spearman's rank correlation > 0.8) are indicated by asterisks (*). (b) Spearman's rank correlations between composite variable and genus-level relative abundance. Non-significant pairs (FDR-adjusted P value > 0.05) are shown as white cells. NMF: non-negative matrix factorization, P/B ratio: Prevotella-Bacteroides ratio, PC: principal component, CLR: centered log-ratio transformed, PCo: principal coordinate, NMDS: non-metric multidimensional scaling, JSD: Jensen-Shannon divergence, BCD: Bray–Curtis dissimilarity, UniF: UniFrac distance.CC BY · PubMed Central
Figure 4 Associations of microbial composition with nutrient intakes and AR via composite variables. Circles indicate the top 3 composite variables calculated using different dimension reduction methods. Significant associations (FDR adjusted P value < 0.05) of the composite variables with genus-level abundance, nutrient intake, and the symptom of AR are shown. The line thickness represents -log10(P value) and the line color indicates the direction of association (coefficient). Orange and blue line indicate positive and negative associations, respectively. (a–c) Principal coordinate analysis (PCoA) with the Jensen-Shannon divergence (JSD) the Bray–Curtis dissimilarity (BCD), and the UniFrac distance; (d) principal component analysis (PCA); (e) PCA with the centered log-ratio (CLR) transformed abundance matrix; (f–h) non-metric multidimensional scaling (NMDS) with the JSD, BCD, and the UniFrac distance; (i) non-negative matrix factorization, and (j) Prevotella to Bacteroides ratio. ALC: alcohol, CHO: carbohydrate, K: potassium, MG: magnesium, NAC: niacin, NDF: insoluble dietary fibre, SFA: saturated fat, TDF: total dietary fibre, VB1: thiamin, VB6: vitamin B6, WDF: soluble dietary fibre.
Figure 4 Associations of microbial composition with nutrient intakes and AR via composite variables. Circles indicate the top 3 composite variables calculated using different dimension reduction methods. Significant associations (FDR adjusted P value < 0.05) of the composite variables with genus-level abundance, nutrient intake, and the symptom of AR are shown. The line thickness represents -log10(P value) and the line color indicates the direction of association (coefficient). Orange and blue line indicate positive and negative associations, respectively. (a–c) Principal coordinate analysis (PCoA) with the Jensen-Shannon divergence (JSD) the Bray–Curtis dissimilarity (BCD), and the UniFrac distance; (d) principal component analysis (PCA); (e) PCA with the centered log-ratio (CLR) transformed abundance matrix; (f–h) non-metric multidimensional scaling (NMDS) with the JSD, BCD, and the UniFrac distance; (i) non-negative matrix factorization, and (j) Prevotella to Bacteroides ratio. ALC: alcohol, CHO: carbohydrate, K: potassium, MG: magnesium, NAC: niacin, NDF: insoluble dietary fibre, SFA: saturated fat, TDF: total dietary fibre, VB1: thiamin, VB6: vitamin B6, WDF: soluble dietary fibre.CC BY · PubMed Central

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Metadata

Authors
Komaki, S., Sahoyama, Y., Hachiya, T., Koseki, K., Ogata, Y., Hamazato, F., Shiozawa, M., Nakagawa, T., Suda, W., Hattori, M., & Kawakami, E.
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2024-04-05
Volume
14
Issue
1
ISSN
2045-2322
DOI
10.1038/s41598-024-57934-x
PMC
PMC10995140
Cited by
13
References
1
Language
en
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