Clinical Scorecard: The Role of Gut Microbiome in Promoting Healthy Aging Among Individuals With and Without HIV
At a Glance
Category
Detail
Condition
Aging-related comorbidities and gut microbiome alterations in people with and without HIV
Key Mechanisms
Gut microbiome diversity and composition changes with age influence immunity, inflammation, and metabolism, impacting healthy aging
Target Population
Adults with and without HIV infection
Care Setting
HIV clinical care and aging research cohorts
Key Highlights
Older age is associated with increased gut microbiome diversity and uniqueness, with specific genera (Akkermansia, Streptococcus) increasing and others (Prevotella, Faecalibacterium) decreasing.
An aging-related microbiome score based on 18 genera correlates with age independent of demographic, behavioral, and cardiometabolic factors.
Certain microbiota, such as Faecalibacterium, are linked to reduced frailty, while others like Streptococcus associate with higher mortality risk (VACS index).
Guideline-Based Recommendations
Diagnosis
Use 16S rRNA gene sequencing of stool samples to assess gut microbiome diversity and composition in aging individuals with and without HIV.
Management
Consider gut microbiome composition as a factor in managing aging-related comorbidities in people with HIV.
Monitor specific gut genera associated with healthy or unhealthy aging to inform interventions.
Monitoring & Follow-up
Assess frailty using the Fried frailty phenotype and mortality risk using the Veterans Aging Cohort Study (VACS) index in conjunction with microbiome profiling.
Risks
Recognize that altered gut microbiome in people with HIV may contribute to increased aging-related comorbidities and mortality risk.
Patient & Prescribing Data
Women and men with and without HIV infection enrolled in longitudinal cohort studies
Gut microbiome features vary by age and HIV status; microbiome-targeted strategies may support healthy aging but require further research.
Clinical Best Practices
Perform sex-stratified analysis when evaluating gut microbiome data due to differing microbiome characteristics.
Exclude confounding factors such as pregnancy and transgender status to facilitate clear interpretation of microbiome-aging relationships.
Use comprehensive covariate adjustment including demographic, behavioral, and cardiometabolic factors in microbiome-aging studies.
Incorporate longitudinal stool sample collection and repeated measures to capture dynamic microbiome changes with aging.
by Brandilyn A Peters, Xiaonan Xue, David B Hanna, Yi Wang, Zheng Wang, Anjali Sharma, Michelle Floris-Moore, Deborah Konkle-Parker, Maria L Alcaide, Anandi N Sheth, Elizabeth F Topper, Kathleen M Weber, Phyllis C Tien, Daniel Merenstein, Elizabeth Vásquez, Yue Chen, Matthew J Mimiaga, Valentina Stosor, Todd T Brown, Kristine M Erlandson, Stephanie M Dillon, Noha S Elsayed, Mykhaylo Usyk, Christopher C Sollecito, Robert C Kaplan, Robert D Burk, Qibin Qi
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