The incidence of chronic inflammatory diseases (CIDs) is dramatically increasing in the developed world, resulting in an increased burden of disease in childhood. Currently, there are limited effective strategies for treating or preventing these conditions. To date, myriads of cross-sectional studies have described alterations in the composition of the gut microbiota in a variety of disease states, after the disease has already occurred. We suggest that to mechanically link these microbiome changes with disease pathogenesis, a prospective cohort design is needed to capture changes that precede or coincide with disease onset and symptoms. In addition, these prospective studies must integrate microbiological, metagenomic, meta transcriptomic and metabolomic data with minimal and standardized clinical and environmental metadata that allow to correctly compare and interpret the results of the analysis of the human microbiota in order to build a system-level model of the interactions between the host and the development of the disease. The creation of new biological computational models thus constructed will allow us to finally move from the detection of simple elements of "association" to the identification of elements of real "causality" allowing to provide a mechanistic approach to the exploration of the development of CIDs.This can only be done when these diseases are studied as complex biological networks. In this chapter we discuss the current knowledge regarding the contribution of the microbiome to CID in childhood, focusing on celiac disease and inflammatory bowel disease, with the overall aim of identifying pathways to shift research from descriptive to mechanistic approaches. We then examine how some components of the microbiota, through epigenetic reprogramming, can start the march from genetic predisposition to clinical expression of CIDs, thus opening up new possibilities for intervention, through microbiota therapy targeting the manipulation of the composition and function of the microbiota, for future applications of precision medicine and primary prevention.
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http://dx.doi.org/10.1007/978-3-031-58572-2_6 | DOI Listing |
Genet Med
December 2024
Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN; Center for Digital Genomic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN. Electronic address:
Purpose: The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results. We performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) with genetic data to understand which decisions may affect performance.
View Article and Find Full Text PDFJ Eval Clin Pract
February 2025
Instituto Mexicano del Seguro Social, IMSS Hospital General de Zona Número 17, Monterrey, Nuevo León, México.
Introduction: Rheumatoid arthritis (RA) is a progressive autoimmune inflammatory disease. According to the European League Against Rheumatism (EULAR), the stages of RA progression include pre-RA, preclinical RA, inflammatory arthralgia, arthralgia with positive antibodies, arthralgia suspected of progressing to RA, undifferentiated arthritis and finally established RA. According to the Community Oriented Program for Control of Rheumatic Diseases (COPCORD), the prevalence of RA in Mexico is 1.
View Article and Find Full Text PDFNurse Educ
October 2024
Author Affiliations: The Ohio State University College of Nursing, Columbus, Ohio (Dr Hoying, Mss Terry and Gray-Bauer, and Dr Melnyk); and The University of Arizona College of Nursing, Tucson, Arizona (Dr Kelly).
Background: Nursing students experience significantly more stress related diseases when compared to non-nursing students, and the state of their mental health can result in short-term increased attrition rates and increased nursing shortages.
Purpose: A preexperimental pre-post study design was used to examine mental health and healthy behaviors among prenursing students.
Methods: Cohorts received the MINDSTRONG© program either in-person or virtually.
Purpose: To examine associations between clinical measures (self-reported and clinician-administered) and subsequent injury rates in the year after concussion return to play (RTP) among adolescent athletes.
Methods: We performed a prospective, longitudinal study of adolescents ages 13-18 years. Each participant was initially assessed within 21 days of concussion and again within 5 days of receiving RTP clearance from their physician.
Biochem Genet
December 2024
College of Medical Laboratory, Dalian Medical University, Dalian, 116044, People's Republic of China.
This study aims to establish a genetic risk assessment model based on a score of short tandem repeats (STRs) of polygenic inheritance. A total of 396 children and their biological parents were collected for STR genotyping. The numbers of tandem repeats of two alleles in one STR locus were assumed to be a quantitative genetic strength for disease incidence.
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