The collection of fecal material and developments in sequencing technologies have enabled standardised and non-invasive gut microbiome profiling. Microbiome composition from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterised due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a well-phenotyped and representative population cohort from Finland (n = 7211). We report robust taxonomic and functional microbiome signatures related to the Enterobacteriaceae family that are associated with mortality risk during a 15-year follow-up. Our results extend previous cross-sectional studies, and help to establish the basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status.
Prostate cancer is one of the most common and heritable human cancers. Our aim was to find germline biomarkers that can predict disease outcome. We previously detected predisposing signals at 2q37, the location of the prostate specific ANO7 gene. To investigate, in detail, the associations between the ANO7 gene and PrCa risk and disease aggressiveness, ANO7 was sequenced in castration resistant tumors together with samples from unselected PrCa patients and unaffected males. Two pathogenic variants were discovered and genotyped in 1769 patients and 1711 unaffected males. Expression of ANO7 vs. PrCa aggressiveness was investigated. Different databases along with Swedish and Norwegian cohorts were used for validation. Case-control and aggressive vs. nonaggressive association analyses were performed against risk and/or cancer aggressiveness. The ANO7 mRNA level and patient survival were analyzed using expression data from databases. Variant rs77559646 showed both risk (OR 1.40; p = 0.009, 95% CI 1.09-1.78) and association with aggressive PrCa (Genotype test p = 0.04). It was found to be an eQTL for ANO7 (Linear model p-values for Finnish patients p = 0.009; Camcap prostate tumor p = 2.53E-06; Stockholm prostate tumor cohort p = 1.53E-13). rs148609049 was not associated with risk, but was related to shorter survival (HR 1.56; 95% CI 1.03-2.36). High ANO7 expression was independently linked to poor survival (HR 18.4; 95% CI 1.43-237). ANO7 genotypes correlate with expression and biochemical relapse, suggesting that ANO7 is a potential PrCa susceptibility gene and that its elevated expression correlates with disease severity and outcome.
The collection of fecal material and developments in sequencing technologies have enabled cost-efficient, standardized, and non-invasive gut microbiome profiling. As a result, microbiome composition data from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterized due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a large, well-phenotyped, and representative population cohort (n = 7211, FINRISK 2002; Finland). We report specific taxonomic and functional signatures related to the Enterobacteriaceae family in the human gut microbiome that predict mortality during a 15-year follow-up. These associations can be observed both in the Eastern and Western Finns who have differing genetic backgrounds, lifestyles, and mortality rates. Our results supplement previously reported cross-sectional associations, and help to establish a methodological and conceptual basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status. These findings could serve as a solid framework for microbiome profiling in clinical risk prediction, paving the way towards clinical applications of human microbiome sequencing aimed at prediction, prevention, and treatment of disease.
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