Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: (a) Two different study populations were used: the Arivale cohort and the Osteoporotic Fractures in Men (MrOS) cohort. (b) Each of these two study populations were further subdivided into two groups; the Arivale cohort was split based on the microbiome vendor used to collect and process samples while the MrOS cohort separated into Discovery and Validation groups based on the batch in which the samples were run (discovery samples were processed in the initial batch, validation samples were processed several years later). (c) We profiled the microbiomes from these four study populations beginning with the Arivale cohort and validating our findings across the additional populations. (d) Our analysis pipeline further explored associations between the identified gut microbial aging pattern, lifestyle factors, and host physiology in the combined Arivale cohort, as well as health metrics and mortality in the combined MrOS cohort.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques: Biomarker Discovery

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: (a) Boxplots showing gut microbiome uniqueness measures calculated using the ASV-level (grey) and genus-level (blue) Bray-Curtis dissimilarity metric across the adult lifespan across the Arivale cohort, adjusted for vendor. Asterisks indicate significant differences relative to the youngest <30 group, from a linear regression model adjusted for vendor, sex, BMI, and Shannon diversity (ASV-level: (50–59) P=3.52e-02, (60–69) P=1.88e-05, (70–79) P=1.47e-09, (80+) P=1.12e-02, genus-level: (40–49) P=7.15e-02, (50–59) P=3.57e-03, (60–69) P=4.33e-07, (70–79) P=8.16e-09, (80+) P=7.90e-03, two-sided). Also shown is the distribution of uniqueness calculated using the Bray-Curtis metric on both the ASV and genus level. (b) Spearman correlation coefficients for measures of Bray-Curtis uniqueness with age in individuals whose stool samples were processed by vendor A or B, as well as an additional external dataset (The American Gut Project). (c) Boxplots showing gut microbiome uniqueness scores calculated using the ASV-level Bray-Curtis across early, mid and late adulthood in the American Gut Project dataset. Asterisks indicate significant differences relative to the youngest <30 group, from a linear regression model adjusted for sex and Shannon diversity ((50–59) P=2.77e-09, (80+) P=2.95e-02). In both (A) and (C), box plots represent the interquartile range (25th to 75th percentile, IQR), with the middle line demarking the median; whiskers span 1.5 × IQR, points beyond this range are shown individually. (d) Percent of variance explained in genus-level Bray-Curtis uniqueness by a diverse number of demographic and lifestyle factors, as well as a subset of clinical laboratory tests.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques:

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: (a) Age ß-coefficients and corresponding P-values from OLS models predicting Bray-Curtis uniqueness at the ASV- and genus-level in the American Gut Project (AGP) and two vendors in the Arivale cohort. In the AGP dataset, the analysis was performed on all samples, and then repeated on the subset of samples who had available sex and BMI data for covariate adjustment. P-values reported are derived from OLS linear regression models and result from a two-sided hypothesis. (b) Spearman correlations of different ß-diversity metrics with age on both the ASV- and genus-level independently in each vendor used for gut microbiome processing in the Arivale cohort.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques: Derivative Assay

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: ‘pvalue’ corresponds to the unadjusted P-Value of the ß-coefficient (B-coef column) for each analyte from an OLS model adjusted for gut microbiome vendor. ‘r_squared’ reflects the percent of variance explained beyond microbiome vendor for each analyte independently for the Genus-level Bray-Curtis measure. ‘age_adjusted_coeff’ and ‘age_adjusted_corr_pvalue’ correspond to the ß-coefficient and the Bonferroni corrected P-Value (two-sided) for each analyte predicting Genus-level Bray-Curtis Uniqueness, adjusting for gut microbiome vendor and age. The ‘age_adj_coeff (ASV-level)’ and the ‘age_adj_corr_pvalue (ASV-level)’ correspond to analysis done on the ASV-level Bray-Curtis Uniqueness measure, where models were adjusted for vendor and age. ‘Missing’ shows the number of missing observations for each analyte. Values highlighted in red are statistically significant after multiple-hypothesis correction (Bonferroni P-Value<0.05, two-sided).

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques:

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: (a) A plot of -log10 p-values for each of the 653 plasma metabolites measured in the Arivale cohort, from OLS regression models predicting genus-level Bray-Curtis uniqueness adjusted for microbiome vendor, sex, age, age , a sex*age interaction term, BMI, and Shannon diversity. Metabolites are color-coded by their super-family. All metabolites above the light red line are significant after multiple-hypothesis correction (Bonferroni P<0.05, two-sided), while the blue line indicates the unadjusted P-value threshold. Asterisks (*) indicate metabolites that were confidently identified on the basis of mass spectrometry data, but for which no reference standards are available to verify the identity. (b) Spearman correlation coefficients for each of the metabolites significantly associated with genus-level Bray-Curtis uniqueness after adjusting for covariates and multiple-hypothesis correction (Bonferroni P<0.05 two-sided). (c) Spearman correlation coefficients for each of the metabolites significantly associated with the ASV-level Bray-Curtis uniqueness measure after adjusting for covariates and multiple-hypothesis correction (Bonferroni P<0.05 two-sided). For both subfigures b) and c), bars are color-coded as in a). (d) Scatter plot of genus-level Bray-Curtis Uniqueness and the strongest metabolite predictor, phenylacetylglutamine, adjusted for vendor. (e) Scatter plot of ASV-level Bray-Curtis uniqueness and the strongest metabolite predictor, phenylacetylglutamine, adjusted for vendor. The lines shown are the y∼x regression lines, and the shaded regions are 95% confidence intervals for the slope of the line. The p-values reported in (d) and (e) are a result of two-sided statistical tests.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques: Clinical Proteomics, Mass Spectrometry

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: (a-c) PCoA of the MrOS discovery cohort color-coded by (a) genus-level Bray-Curtis uniqueness, (b) relative Bacteroides abundance, and (c) relative Prevotella abundance. (d) Barplot demonstrating the correlation of strongest taxa associated with genus-level gut microbiome uniqueness in the MrOS discovery cohort, color-coded by phylum. ( e) Correlation of genus-level Bray-Curtis uniqueness scores with age across the MrOS discovery and validation cohorts under different health stratifications. Also shown are age β-coefficients (slopes) with 95% confidence intervals from (OLS) linear regression models predicting genus-level Bray-Curtis uniqueness adjusted for BMI across the same stratifications. ‘Excellent’ corresponds to individuals who self-reported their health to be excellent, while ‘

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques: Biomarker Discovery

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: (a-d) Plots demonstrating the correlation coefficients between genus-level Bray-Curtis gut microbiome uniqueness and individual taxa in the (a) Discovery MrOS cohort, (b) Vendor A in the Arivale Cohort, (c) Validation MrOS cohort, (d) and vendor B of the Arivale cohort. Only correlations > |0.20|) are shown. (e) Plots demonstrating the strength of correlation between genus-level Bray-Curtis microbiome uniqueness and individual taxa in the in the AGP dataset. The strongest 20 associations are shown. (d-e) Plots demonstrating the strength of correlation between gut microbiome uniqueness and individual taxa in Vendor A of the Arivale cohort in (f) females and (g) males. (h) Scatter plot of correlation coefficients for each genus tested between males and females. The correlation of the coefficients for each genus between sexes is shown. Only genera that had less than 5% zero values and a mean greater than five counts were tested.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques: Biomarker Discovery

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: Description of health metrics used for stratification in the MrOS cohort.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques: Medications, Functional Assay

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: Uniqueness measures reported in this table were calculated at the genus level. ‘Health Stratification’ corresponds to the metric used to define healthy individuals. ‘ Spearman Rho’ reports the Spearman correlation coefficient between age and microbiome uniqueness for the specified group of participants, while the ‘pvalue’ column provides the corresponding p-value. ‘Beta_coeff’ is the BMI adjusted age beta-coefficient predicting uniqueness across the same stratifications as the ‘Spearman Rho’ column. ‘Coef_pvalue’ provides the p-value corresponding to the age Beta-coefficient from linear regression models. ‘Sample_size’ is the number of participants in each stratification while the last column “Healthy (yes=1/no=0)” specifies whether the group of participants is the healthy subgroup (yes(1)), or the remainder of the cohort (No(0)). Significant p-values (P<0.05, two-sided) are highlighted in red. No multiple hypothesis correction was performed.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques:

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: (a-e) Plots demonstrating the strength of Spearman correlation between age and gut microbiome measures at different taxonomic resolutions. (a) The blue/red panel corresponds to the calculated Weighted UniFrac (ß-diversity) uniqueness score at the genus level, while (b) the grey/green and (c) grey/yellow panels correspond to Shannon diversity and Observed species (α-diversity measures) at the ASV level, respectively. Significant correlations (two-sided) are indicated with asterisks. Exact correlation coefficients and corresponding p-values for (a) are provided in . (d-e) The same plots as in (b-c), with α-diversity calculated at the genus level. (f) Comparison of ASV level and genus-level analysis in healthy aging in the MrOS cohort. Barplots represent correlation coefficients comparing age and uniqueness at the ASV level across composite healthy MrOS individuals, and the remainder of the cohort in both the discovery and validation groups. (g) ß -coefficients for age from OLS regression models predicting genus-level Bray-Curtis uniqueness in healthy composite individuals and remainder of the cohort, adjusted individually for the most commonly reported supplements and medications in the MrOS cohort.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques: Comparison, Biomarker Discovery, Medications

Journal: Nature metabolism

Article Title: Gut microbiome pattern reflects healthy aging and predicts survival in humans

doi: 10.1038/s42255-021-00348-0

Figure Lengend Snippet: Associations between gut microbiome measures and mortality in the MrOS cohort.Unadjusted, age, clinical site and batch adjusted and multivariable adjusted Hazard Ratios (HR) and the 95% confidence intervals (95%CI) of relative Bacteroides abundance, genus level Bray-Curtis and Weighted UniFrac uniqueness scores, as well as the same metrics calculated at the ASV level, from Cox Proportional Hazard Regression models evaluating mortality risk in all community-dwelling MrOS participants (n=706) and exclusively community-dwelling MrOS participants 85+ years old (n=256). Multivariable models were adjusted for age, clinical site, BMI, self-perceived health, diagnosis of congestive heart failure, and batch in which stool samples were processed. Both relative Bacteroides abundance and The Bray-Curtis uniqueness measures were scaled and centered prior to mortality analysis. Significant HRs are bolded and colored in red ( P≤0.05, two-sided). HR and 95%CI reported have not been corrected for multiple hypothesis testing.

Article Snippet: These observations are strengthened by the presence of similar age-related trends across two independent microbiome vendors, and three demographically distinct cohorts (Arivale, MrOS, AGP).

Techniques: Biomarker Discovery