Abstract
BackgroundAgeing is associated with an impaired immune response and shares many physiological alterations observed in HIV chronic infection; therefore, we hypothesised that people living with HIV exhibit a premature ageing phenotype, reflected by age-related changes in the plasma proteome. MethodsWe profiled the plasma proteome in two cohorts of virally suppressed people living with HIV, the 2000HIV cohort (n=65; median age 53 years [IQR 45–60]; 91% male [n=597] and 8% female [n=59]) and the 200HIV cohort (n=218; 52 years [45–59]; 91% [n=199] and 9% [n=19]), and in 100 age-matched and sex-matched people without HIV, the 200FG cohort (n=100; 50 years [38–59]; 75% [n=75] and 25% [n=25]). Patients were recruited from the following Dutch HIV Treatment Centres: Radboudumc (Nijmegen), ErasmusMC (Rotterdam), Onze Lieve Vrouwe Gasthuis (Amsterdam), Elisabeth-TweeSteden Ziekenhuis (Tilburg). Clinical information was collected from all participants using standard questionnaires and interviews on lifestyle, health, and clinical symptoms, and samples from blood, urine, saliva and stool were obtained for further analytical measurements. We characterised the proteins that are associated with chronological age and explored the extent to which the plasma proteome predicts age in people with or without HIV. Using a multiplex proximity extension assay (Olink Proteomics), the relative abundance of 1472 proteins was assessed across four different panels (inflammatory, cardiometabolic, neurology, and oncology). The cohort of people without HIV was used to build a prediction model for age, based on elastic net regression and using a common proteomic signature between people living with HIV and people without HIV. FindingsThe number of proteins significantly associated with age was 569 in the 2000 HIV cohort, 322 in the 200 HIV cohort, and 101 in the 200FG cohort (adjusted p<0·05). 78 proteins were common to all cohorts and some of these proteins (LTBP2, EDA2R, WNT9A, NEFL, SCARF2, KLK4, GDF15, CXCL14, HAVCR1, and GFAP) are involved in immune-related processes and secretory senescence-associated phenotype. The correlation between proteomic age prediction and chronological age was 0·92 in 200FG, 0·82 in 2000 HIV, and 0·8 in 200 HIV (p<0·001). According to this proteomic-age predictive model, people living with HIV showed an increased inflammatory age compared with people without HIV. InterpretationThis targeted proteomics analysis showed a common proteomic signature of chronological age in people with HIV and people without HIV. This proteomic signature of age could predict premature ageing in people with HIV, which warrants further investigation of its role in the development of inflammatory comorbidities and disease severity. FundingViiV Healthcare.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.