Effect of aging on the transcriptomic changes associated with the expression of the HERV-K (HML-2) provirus at 1q22

An estimated 8% of the human genome consists of endogenous retroviruses, which are remnants of exogenous retroviral infections that have integrated into the human germline throughout millions of years. The majority of these human endogenous retrovirus (HERV) proviruses do not contain intact open reading frames due to the accumulation of mutations, insertions, and deletions. Yet despite being seemingly harmless passengers, several studies have shown that activation of HERV proviruses is associated with various diseases, such as multiple sclerosis, rheumatoid arthritis and HIV infection (reviewed in [15]).

However, the exact immunomodulatory mechanisms of HERV activation are not known. It is clear that the original retrotranspositional mechanisms are not involved, as human ERVs have lost their infectious capacity. Therefore, it seems likely that the expressed HERV proteins (env, gag, pol) are critical in this respect [9]. HERV RNA could be recognized as a pathogen-associated molecular pattern (PAMP) by toll-like receptors, and this would induce type I interferon production contributing to the pathogenesis of autoinflammatory diseases [26].

The most recently integrated proviruses, belonging to the HERV-K (HML-2) family, are relatively well preserved and have retained considerable expression capacity [10]. Yet out of the 91 proviruses in the HERV-K family, only two, at 1q22 and at 1q23.3, are thought able to produce intact viral proteins [3]. In our previous work [16], we found the HERV-K (HML-2) at 1q22 to be significantly higher expressed (p-value < 0.05) in nonagenarian PBMCs (Peripheral Blood Mononuclear Cells) compared to young controls (Fig. 1), while expression of 1q23.3 was found to be very low. In our results, median 1q22 mRNA level in the young was 0.357 TPM (Transcripts Per Million), compared to 0.478 TPM in the old, and the mean 1q22 overexpression in the old was 1.3-fold. In this work, we have thus focused solely on the provirus at 1q22 in investigating the potential consequences of these transcriptomic changes. The provirus at 1q22 is also known as K102 and ERVK-7 [21].

In order to investigate the potential consequences of the significantly increased expression of HERV-K (HML-2) at 1q22 in PBMCs from older individuals, co-expression of the provirus with human genes was investigated utilizing Pearson’s product-moment correlation coefficient. Provirus 1q22 expression was found to correlate strongly (Pearson’s correlation coefficient ≥ 0.7) with the expression of 946 genes in nonagenarians, but with only 435 in the young controls, out of 9447 total genes. Of the genes that correlated strongly with 1q22 in either young or old individuals, only 41 correlated strongly (Pearson’s correlation coefficient ≥ 0.7) with 1q22 in both the young and the old. Highest correlating genes (Pearson’s correlation coefficient ≥ 0.95) can be seen in the supplementary file, in table S1. However, correlating the expression of one provirus to thousands of genes results in strong correlations with some genes by pure chance, even if there is no true association, and therefore it is not enough to look at individual correlations, but necessary to study these correlations as a whole.

To explore what biological processes might be affected by or be behind the transcriptomic changes, gene set enrichment analysis (GSEA) was performed based on known gene ontology (GO) functions of co-expressed genes [1, 20, 22]. Figure 2a and b show the 15 most upregulated and 15 most downregulated processes in both nonagenarians and young controls, respectively. The 20 most significantly associating GO biological processes are listed in Tables 1 and 2, in the order of significance, for both age groups. Figure 2c illustrates the strong association of 1q22 expression with genes involved in neutrophil activation in the older individuals, demonstrated by the number of highly correlating genes located at the beginning of the gene list.

To quantitatively assess the enrichment of neutrophil associated genes in the transcripts that are strongly co-expressed with 1q22, the hypergeometric test was utilized. The old individuals had 4 of the top 20 most significantly enriched GO terms involve neutrophils (Table 1), which according to the hypergeometric test results in a very low p-value of 4.96e-13, indicating significance (p-value < 0.05). This p-value signifies that the association to neutrophil function seen with 1q22 is very unlikely to be purely coincidental. For the young individuals, no significantly enriched biological processes were directly involved in neutrophil function (Table 2).

The GSEA indicated association between 1q22 and neutrophil activation was further studied by focusing on the correlations between 1q22 expression and common markers of neutrophil activation: IL-8 [29] and myeloperoxidase (MPO) [17]. The results are shown in Table 3. IL-8, also known as neutrophil chemotactic factor, had a strong and significant correlation with 1q22 in the old (Pearson’s correlation coefficient = 0.83, p-value = 0.02), but not in the young (Pearson’s correlation coefficient = 0.18, p-value = 0.70). In the old individuals, some correlation was seen between 1q22 and MPO, though this correlation was not statistically significant. MPO, along with human neutrophil elastase (HNE), is expressed in neutrophils and released to the extracellular space as part of neutrophil degranulation. The expression of HNE was below threshold (mean normalized read count < 50) and was therefore not included in analysis. Correlations between 1q22 and these genes were present only weakly in the PBMCs from young controls.

Many of the biological processes enriched in the PBMCs from the old individuals are related to neutrophil activation and function (Fig. 2a and Table 1). This association between 1q22 expression and neutrophil function is not present in the samples from young controls. In addition to the differences between age groups in the number of directly neutrophil involving GO terms, the GSEA results for the old contain many GO terms that are indirectly related to neutrophil function, such as terms describing granulocyte and leukocyte activity as well as more general immune system functions. Elevated levels of neutrophil activation in old individuals have already been previously reported. For example, in a time series study spanning 15 years, Samson et al. found that the numbers of neutrophils and monocytes increased with age, correlating with frailty and CRP trajectories [18].

It is known that neutrophils are crucial in the first line of defense against infectious agents and that several of their functional activities are affected by aging [7]. As host cells for viruses, neutrophils are suboptimal, as they are both short-lived and terminally differentiated. However, internalization of viruses during infection does occur, for example with the West Nile virus, which is reported to replicate within neutrophils [2].

Though many of the weapons in the neutrophil’s arsenal are specifically for bacteria, neutrophils still play an important indirect role in viral infection defense by influencing the behavior of other cell subsets [19]. It is this indirect relationship between neutrophils and viruses that may explain why the results indicate enrichment of neutrophil-associated functions in PBMC samples that should not contain more than trace amounts of neutrophil-derived RNA. Though neutrophils are absent from the samples, the effects exerted by lymphocytes on neutrophils and by neutrophils on lymphocytes can still be seen in gene expression from the lymphocyte-containing PBMC samples. For example, neutrophil chemotaxis and activation can be induced by lymphocyte-produced IL-8 [29]. In the results of this work, IL-8 expression was found to strongly correlate with 1q22 expression in the old, yet not in the young, which could be seen as another link between 1q22 expression and neutrophil activation.

Based on the results of this work, it could thus be speculated that a chronic activation of neutrophils by HERVs is leading to the functional exhaustion of neutrophils as part of the aging-associated decline of immune capacity, i.e., immunosenescence. Additionally, as the expression of various HERVs have been shown to be increased in several diseases of autoimmune and autoinflammatory nature, HERV expression could be leading to increased production of pro-inflammatory mediators and in this way potentiating age-associated inflammation, referred to as “inflammaging”. It would therefore be of interest to analyze HERV-associated biological processes in cases of autoimmune or autoinflammatory disease.

If HERVs were indeed causing activation of neutrophil-associated mechanisms, they would not be the only viruses to do so. Dunning et al. [6] described a comparable change in the analysis of the blood transcriptome in patients with long-lasting and severe influenza infection. This change from the “anti-viral” transcriptomic signature (including the effects of type-I interferons) to the “anti-bacterial” signature (e.g. neutrophil-mediated) is similar to that we observed in the HERV-K 1q22 expressing PBMC from the older individuals. However, Dunning et al. [6] saw a rise in transcripts associated with the GO term “response to bacterium”, while that GO term was not enriched in our data. Additionally the transcripts that we found to most strongly correlate with 1q22 in young and in old separately (Supplementary file, Table S1) had no overlap with the transcripts that Dunning et al. describe to be associated with the GO terms “response to virus” or “response to bacterium”. The difference in results could be explained by Dunning et al. having sequenced whole-blood samples, as opposed to the PBMC samples used in this work. In our results, the association with neutrophils does not come from a general response to bacterium, rather we see a more specific co-expression with transcripts associated with neutrophil activation.

As a limitation of this work, the cell types involved in this provirus 1q22 associated processes cannot be determined based on this PBMC derived data, as the correlating transcripts could be derived from different cell types. A natural next step in this line of research would therefore be to investigate this association between 1q22 and neutrophils in datasets from specific cell types.

The results of this work suggest that the biological processes associated with the expression of HERV-K (HML-2) provirus at 1q22 are different in the blood of young and old individuals. The number of genes strongly correlating with the expression of the provirus is higher in the PBMC from the old individuals compared to the young, and the associated GO biological processes differ between the age groups. The strong association that was found in the older individuals between neutrophil activity and the expression of HERV-K (HML-2) provirus at 1q22 could be explained by a chronic activation of neutrophils by HERVs, leading to the functional exhaustion of neutrophils as part of immunosenescence. Expression f this provirus could also be leading to increased production of pro-inflammatory mediators, thus potentiating inflammaging. Taken as a whole, these findings offer insight into potential effects of altered HERV expression in older individuals. Investigation of provirus 1q22 expression associated biological functions in specific cell types and in conditions of autoimmune or autoinflammatory disease could further elucidate the consequences of its expression.

This work extends the bioinformatic analyses done on our Vitality 90+ dataset that we have previously presented in [16]. Below are again described the sample collection and RNA sequencing protocols used, followed by the new analyses that have been performed as part of this work.