Lower Neighborhood Socioeconomic Status Associated with Reduced Diversity of the Colonic Microbiota in Healthy Adults

Study information

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study design

cross-sectional observational, not case-control

Citation

PMID PubMed identifier for scientific articles.

26859894

DOI Digital object identifier for electronic documents.

10.1371/journal.pone.0148952

URI Uniform resource identifier for web resources.

https://pubmed.ncbi.nlm.nih.gov/26859894/

Authors

Miller GE, Engen PA, Gillevet PM, Shaikh M, Sikaroodi M, Forsyth CB, Mutlu E, Keshavarzian A

Journal

PloS one

Year

2016

In the United States, there are persistent and widening socioeconomic gaps in morbidity and mortality from chronic diseases. Although most disparities research focuses on person-level socioeconomic-status, mounting evidence suggest that chronic diseases also pattern by the demographic characteristics of neighborhoods. Yet the biological mechanisms underlying these associations are poorly understood. There is increasing recognition that chronic diseases share common pathogenic features, some of which involve alterations in the composition, diversity, and functioning of the gut microbiota. This study examined whether socioeconomic-status was associated with alpha-diversity of the colonic microbiota. Forty-four healthy adults underwent un-prepped sigmoidoscopy, during which mucosal biopsies and fecal samples were collected. Subjects' zip codes were geocoded, and census data was used to form a composite indicator of neighborhood socioeconomic-status, reflecting household income, educational attainment, employment status, and home value. In unadjusted analyses, neighborhood socioeconomic-status explained 12-18 percent of the variability in alpha-diversity of colonic microbiota. The direction of these associations was positive, meaning that as neighborhood socioeconomic-status increased, so did alpha-diversity of both the colonic sigmoid mucosa and fecal microbiota. The strength of these associations persisted when models were expanded to include covariates reflecting potential demographic (age, gender, race/ethnicity) and lifestyle (adiposity, alcohol use, smoking) confounds. In these models neighborhood socioeconomic-status continued to explain 11-22 percent of the variability in diversity indicators. Further analyses suggested these patterns reflected socioeconomic variations in evenness, but not richness, of microbial communities residing in the sigmoid. We also found indications that residence in neighborhoods of higher socioeconomic-status was associated with a greater abundance of Bacteroides and a lower abundance of Prevotella, suggesting that diet potentially underlies differences in microbiota composition. These findings suggest the presence of socioeconomic variations in colonic microbiota diversity. Future research should explore whether these variations contribute to disparities in chronic disease outcomes.

Experiment 1

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Curated date: 2022/06/11

Curator: Kaluifeanyi101

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Subjects

Location of subjects: United States of America

Host species Species from which microbiome was sampled (if applicable): Homo sapiens

Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology: Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology: socioeconomic statussocioeconomic status

Group 0 name Corresponds to the control (unexposed) group for case-control studies: High SES
Group 1 name Corresponds to the case (exposed) group for case-control studies: Low SES
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: 44 healthy participants from low-income neighborhoods with a median annual income of $20,100 and a 35% unemployment rate and neighborhoods at the high end, with a median income of $129,570 and an unemployment rate under 5%).

(Income level as a continuous variable.)

Group 0 sample size Number of subjects in the control (unexposed) group: 44
Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any): 3 months

Lab analysis

Sequencing type: 16S

Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance: Roche454

Statistical Analysis

Statistical test: Linear Regression; Spearman Correlation

Significance threshold p-value or FDR threshold used for differential abundance testing (if any): .05

Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment: age, alcohol drinking, body mass index, race, sex, smoking status

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness: decreased

Signature 1

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Source: FIGURE 3

Description: Scatter-plot of neighborhood SES and bacterial genera. Figs depict associations between neighborhood SES and Prevotella to Bacteroides ratio (upper panel), as well as the relative abundance of Prevotella (middle panel) and Bacteroides (lower panel). Specimens are biopsies excised from sigmoid mucosa.

Abundance in Group 1: increased abundance in Low SES

NCBI	Links
Prevotella

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Signature 2

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Source: FIGURE 3

Description: Scatter-plot of neighborhood SES and bacterial genera. Figs depict associations between neighborhood SES and Prevotella to Bacteroides ratio (upper panel), as well as the relative abundance of Prevotella (middle panel) and Bacteroides (lower panel). Specimens are biopsies excised from sigmoid mucosa.

Abundance in Group 1: decreased abundance in Low SES

NCBI	Links
Bacteroides

Revision editor(s): Kaluifeanyi101