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Molusky, M. M.

Publications and source records attributed to Molusky, M. M..

2 recordsLinked to original sources

Sub-optimal activity of gut microbiome functional pathways increases the odds of Irritable Bowel Syndrome in a large adult human population

Functional gastrointestinal disorders present diagnostic and therapeutic challenges, and there is a strong need for molecular markers that enable early health insights and intervention. Herein, we present an approach to assess the gut microbiome with stool-based gut metatranscriptome data from a large adult human population (n = 80,570), using irritable bowel syndrome as an example that features both an abnormal gut microbiome and a spectrum of distinct conditions. We develop a suite of eight gut microbial functional pathway scores, each of which represents the activity of a set of interacting microbial functional features (based on KEGG orthology) relevant to known gut biochemical activities. We use a normative approach within a subpopulation (n = 9,350) to define "Good" and "Not Optimal" activities for these transcriptome-based gut pathway scores. We hypothesize that Not Optimal scores are associated with irritable bowel syndrome (IBS) and its subtypes (i.e., IBS-Constipation, IBS-Diarrhea, IBS-Mixed Type). We show that Not Optimal functional pathway scores are associated with higher odds of IBS or its subtypes within an independent cohort (n = 71,220) using both the Rome IV Diagnostic Questionnaire as well as self-reported phenotypes. Rather than waiting to diagnose IBS after symptoms appear, these functional pathway scores can help to provide early health insights into molecular pathways that may contribute to IBS. These molecular endpoints could also assist with measuring the efficacy of practical interventions, developing related algorithms, providing personalized nutritional recommendations, diagnostic support, and treatments for gastrointestinal disorders like IBS. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/580548v4_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@d84aaeorg.highwire.dtl.DTLVardef@f2276org.highwire.dtl.DTLVardef@19fab7aorg.highwire.dtl.DTLVardef@1b2f738_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Microbial functional pathways based on metatranscriptomic profiling enable effective saliva-based health assessments for precision wellness

It is increasingly recognized that an important step towards improving overall health is to accurately measure biomarkers of health from the molecular activities prevalent in the oral cavity. We present a general methodology for computationally quantifying the activity of microbial functional pathways using metatranscriptomic data. We describe their implementation as a collection of eight oral pathway scores using a large salivary sample dataset (n=9,350), and we evaluate score associations with oropharyngeal disease phenotypes within an unseen independent cohort (n=14,129). As clinical validation, we show that the relevant oral pathway scores are significantly worse in individuals with periodontal disease, acid reflux, and nicotine addiction, compared with controls. Given these associations, we make the case to use these oral pathway scores to provide molecular health insights from simple, non-invasive saliva samples, and as molecular endpoints for actionable interventions to address the associated conditions. HighlightsO_LIMicrobial functional pathways in the oral cavity are quantified as eight oral scores C_LIO_LIScores are significantly worse for individuals with oropharyngeal disease phenotypes C_LIO_LIThis methodology may be generalized to other pathways and other sample types C_LIO_LIThese scores provide longitudinal health insights in a precision wellness application C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/565122v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@12fb7bdorg.highwire.dtl.DTLVardef@1c7dbf3org.highwire.dtl.DTLVardef@39700forg.highwire.dtl.DTLVardef@ebf63c_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗