P1234 The gut microbiome as a reporter of health, and its associations with different exposures

Abstract

Abstract Background The prevalence of metabolic and immune-mediated diseases has increased in the last century, with many of these diseases showing alterations in the gut microbial composition. We previously reported (PMID:35197084) that a large group of bacteria shows constant differential abundance (increase and decrease) across multiple diseases and can therefore provide a general indication of the host's health. We aimed to utilize a “health index” based on these bacteria to compare how different exposures are associated with this index as potential contributors to general health. Methods The gut microbial composition was derived using fecal 16S sequencing (V4), and the per-participant microbial health index was calculated. Exposures, diseases, and laboratory results were recorded at sample collection. Results 372 participants (62% males, median age 57y, Table 1) were included (the study is ongoing). Median BMI was 25 (IQR 23-28), with 9% smokers. Participants are relatively fit: only 22% reported performing physical activity less than once weekly, and the median average steps (for the 55% that reported their daily average) is 6000 steps/day (IQR 4500-8000). Subjects performing more frequent physical activity (>3 times/week) had a higher gut microbial health index (p=0.009) in comparison to less than once weekly. Subjects having no documented disease (22%) had higher indexes, and the number of diseases negatively correlated with the health index (rho=-0.19, p=0.004). A higher microbial health index (Figure 1) was found in subjects drinking >=4 coffee cups/day vs. less or no coffee (p=0.002). Interestingly, a higher percentage of eosinophils was positively correlated with a higher index (p=0.002). Lower health index was recorded in subjects who reported dietary supplements intake (p=0.01), those with above-normal levels of uric acid (p=0.02), with primary hypertension or fatty liver (p=0.02), and those taking beta-blockers (p=0.009) or glucose-lowering medications (p=0.003). The microbial health index positively correlated with Faith alpha diversity (rho=0.47). Still, in some cases, each factor was linked with different features suggesting that these microbial-based factors (diversity and health index) captured a complementary epiphenomenon of the microbiome. For example, only higher alpha diversity (but not health index) was linked with the daily bowel movement frequency (p=0.0008). Conclusion Using the gut microbial health index, we developed a methodology to assess correlations between different lifestyles, diets, and health. This approach may highlight personal modifiable factors that can be translated into risk prevention strategies for improving general health reported by microbial composition.