Cellular aging dynamics after acute malaria infection: A 12-month longitudinal study

Abstract

Accelerated cellular aging and reduced lifespan have recently been shown in birds chronically infected with malaria parasites. Whether malaria infection also affects cellular aging in humans has not been reported. Here, we assessed the effect of a single acute Plasmodium falciparum malaria infection on cellular aging dynamics in travelers prospectively followed over one year in Sweden. DNA and RNA were extracted from venous blood collected at the time of admission and repeatedly up to one year. Telomere length was measured using real-time quantitative PCR, while telomerase activity and CDKN2A expression were measured by reverse transcriptase (RT)-qPCR. Our results show that acute malaria infection affects cellular aging as reflected by elevated levels of CDKN2A expression, lower telomerase activity, and substantial telomere shortening during the first three months postinfection. After that CDKN2A expression declined, telomerase activity increased and telomere length was gradually restored over one year, reflecting that cellular aging was reversed. These findings demonstrate that malaria infection affects cellular aging and the underlying cellular mechanism by which pathogens can affect host cellular aging and longevity need to be elucidated. Our results urge the need to investigate whether repeated malaria infections have more pronounced and long-lasting effects on cellular aging and lifespan (similarly to what was observed in birds) in populations living in malaria endemic areas.

Keywords: Plasmodium falciparum; CDKN2A; Malaria; Telomerase; Telomeres; cellular aging.

Figure 1

Telomere length dynamics in blood of travelers followed over one year after successful treatment of Plasmodium falciparum malaria (n = 38). (a) Telomere length dynamics after single acute malaria infection in peripheral blood; each gray circle represents the telomere measurement of individual sample, solid black lines represent the mean at each sampling point, and error bars denote the 95% CI. (b) Telomere length, as predicted from the mixed models; solid gray line denotes the mean telomere length and shaded gray areas denote the 95% CI of the model predictions when adjusted for covariates. Black dots denote the observed mean telomere length at each time point (pooled data at approximate measurement day), and error bars denote the 95% CI of the mean. Number on each error bar represents the sample size at each measurement time point

Figure 2

Relationship between telomere length and telomerase expression in blood of subset of travelers with RNA samples (n = 8, observations = 39) followed over one year after a successfully treated Plasmodium falciparum malaria infection. (a) Dynamics of telomerase expression level (log) after single acute malaria infection in peripheral blood; each gray circle represents the telomerase expression of individual sample, solid black lines represent the mean at each sampling point, and error bars denote the ± SE. (b) Pearson correlation (adjusted for cluster‐robust standard errors) between telomerase expression and telomere length. (c) Telomere length, telomerase expression level (log), and CDKN2A level (log) at the respective sampling time points. Bars represent the mean values and error bars denote the ± SE

Figure 3

Relationship between telomere length and telomerase expression in blood of subset of travelers with RNA samples (n = 8, observations = 39) followed over one year after a successfully treated Plasmodium falciparum malaria infection. (a) Dynamics of CDKN2A level (log) after single acute malaria infection in peripheral blood; each gray circle represents the CDKN2A expression of individual sample, solid black lines represent the mean at each sampling point, and error bars denote the ± SE. (b) Pearson correlation (adjusted for cluster‐robust standard errors) between CDKN2A and telomere length