Infection and telomere length: A systematic review

Abstract

Background: Infections may increase the risk of age-related diseases such as dementia. Accelerated immunological ageing, measurable by telomere length (TL), may be a potential mechanism. However, the relationship between different infections and TL or telomere attrition remains unclear. This systematic review synthesises existing evidence on whether infections contribute to TL or telomere attrition and highlights research gaps to inform future studies.

Objective: To summarise the literature on associations between infections and telomere length or attrition.

Methods: We conducted comprehensive searches across six databases (MEDLINE, EMBASE, Web of Science, Scopus, Global Health, Cochrane Library) from inception to 22 May 2025, using concepts of infections, TL, and study type. Two researchers independently screened studies, extracted data, and assessed risk of bias (ROB) using the ROBINS-E tool. Meta-analysis was unfeasible due to heterogeneity, so a narrative synthesis was conducted. Studies were grouped by infection type, telomere measurement assay, cell type, and statistical approach. A GRADE assessment was performed to evaluate evidence quality.

Results: Our searches identified 10,349 studies, of which 73 met eligibility criteria. Most (59) were cross-sectional and most were published after 2000, with the earliest from 1996. Most studies were from the USA (17). HIV was the most frequently studied infection (35 studies), with 79% (excluding overlapping samples) reporting an association between HIV and reduced TL or increased telomere attrition. Findings for other infections, including herpesviruses and Human Papillomavirus were more variable. Variation in infection type, measurement assay, cell type, and statistical approach made cross-study comparisons challenging. Most studies had a high ROB, mainly due to unmeasured confounding. The GRADE assessment rated evidence quality as very low.

Conclusions: Our review highlights a potential link between HIV and TL and telomere attrition. More robust longitudinal studies with standardised measurements and better confounder control are needed, particularly for non-HIV infections. PROSPERO (ID:CRD42023444854).

Fig 1. PRISMA flow diagram showing how studies were selected for the systematic review.

NB- The ‘Records screened’ stage refers to title and abstract screening and the ‘Reports assessed for eligibility’ stage relates to full-text screening. Figure adapted from Page et al. (2021), PRISMA 2020 flow diagram [94].

Fig 2. Risk of Bias by Domain Across 105 Exposure–Outcome Relationships. D1-confounding, D2-measurement of the exposure, D3- selection of participants into the study (or into the analysis), D4-post-exposure interventions, D5- missing data, D6- measurement of the outcome, D7- selection of the reported result.

Fig 3. Forest plot of HIV studies presenting difference in mean telomere length.

The difference in means relates to mean in infected group minus mean in control group. 1- Results are from univariate analysis only. *−95% Confidence interval calculated from available data. **- Effect estimate and 95% confidence interval calculated from available data.

Fig 4. Forest plot of CMV studies presenting difference in mean telomere length.

The difference in means relates to mean in infected group minus mean in control group. *−95% Confidence interval calculated from available data.

Fig 5. Forest plot of HSV-1 studies presenting difference in mean telomere length.

The difference in means relates to mean in infected group minus mean in control group. *−95% Confidence interval calculated from available data.