Maximum Reproductive Lifespan Correlates with CD33rSIGLEC Gene Number: Implications for NADPH Oxidase-derived Reactive Oxygen Species in Aging

Abstract

Humans and orcas are among the very rare species that have a prolonged post-reproductive lifespan (PRLS), during which the aging process continues. Reactive oxygen species (ROS) derived from mitochondria and from the NADPH-oxidase (NOX) enzymes of innate immune cells are known to contribute to aging, with the former thought to be dominant. CD33-related-Siglecs are immune receptors that recognize self-associated-molecular-patterns and modulate NOX-derived-ROS. We herewith demonstrate a strong correlation of lifespan with CD33rSIGLEC gene number in 26 species, independent of body weight or phylogeny. The correlation is stronger when considering total CD33rSIGLEC gene number rather than those encoding inhibitory and activating subsets, suggesting that lifetime balancing of ROS is important. Combining independent lines of evidence including the short half-life and spontaneous activation of neutrophils, we calculate that even without inter-current inflammation, a major source of lifetime ROS exposure may actually be neutrophil NOX-derived. However, genomes of human supercentenarians (>110yrs) do not harbor a significantly higher number of functional CD33rSIGLEC genes. Instead, life-span correlation with CD33rSIGLEC gene number was markedly strengthened by excluding the post-reproductive lifespan of humans and orcas (R²=0.83; p<0.0001). Thus, CD33rSIGLEC modulation of ROS likely contributes to maximum reproductive lifespan, but other unknown mechanisms could be important to PRLS.

Introduction

Aging is a complex biological process varying widely between species, being influenced by numerous interacting factors (1–6). Logically, aging also impacts maximum lifespan, a number that also varies widely between species. One contributor to aging appears to be reactive oxygen species (ROS), originating from two major sources: mitochondria (a relatively constant source in most cell types) (7) and from NADPH Oxidase (NOX) enzymes (8–12). Prominent among the latter is phagolysosomal NOX2, a membrane bound enzyme that generates ROS primarily for pathogen killing (13, 14), and prominently expressed in innate immune cells of the myeloid lineage (predominantly neutrophils, which are typically thought of as more episodic sources of ROS, during inflammation) (9, 10, 15). While high levels of ROS cause organelle injury, DNA damage, protein misfolding, cell demise, promote aging, low levels mediate important cell signaling pathways (such as mTOR or Wnt). Indeed, mildly increasing ROS promotes longevity in standard multicellular models of aging (such as C. elegans) (16, 17). There is now compelling evidence that ROS contribute to aging in many organisms (18). Notably, calorie restriction, perhaps the most robust method for extending life span across species, decreases ROS production during aging in lower organisms as well as in mammals (19). Also, overexpressing antioxidants such as catalase in mice decreases ROS and extends lifespan (20). Thus, a fine balance between production and turnover of ROS appears necessary to limit cell injury and extend lifespan (21, 22).

Mitochondria are generally considered the primary source of ROS involved in aging (6). ROS produced by mitochondria are a byproduct of normal functioning of the electron transport chain and inhibitors of respiratory chain such as rotenone have been shown to suppress the ability of hormones and cytokines to produce ROS in various cell types (2, 23). While mitochondrial ROS can be physiologically regulated, it is estimated that less than 2% of mitochondrial O₂ consumption is converted to the ROS, superoxide. In contrast, the phagolysosomal NOX enzyme expressed by innate immune cells generates high levels of ROS for pathogen killing (13) and converts nearly 100% of consumed oxygen to superoxide. NOX is also a major source of superoxide in synaptosomes with minor contributions from synaptosomal mitochondria which lead to cognitive decline (24). However, all cells in the body have mitochondria that are constantly producing ROS due to electron leakage. Therefore, it is generally assumed that mitochondria are the major source of total baseline and lifetime ROS production with episodic innate immune inflammation also contributing to lifetime damage and aging (20, 25–27). Moreover, we have recently shown that while neutrophils are indeed quiescent in the blood stream, they immediately begin to produce ROS when they are separated away from the erythrocyte and plasma glycoproteins (28), which present a high density of sialic acid bearing Self-Associated Molecular Patterns (SAMPs) (29). Such separation from SAMPs would also occur in vivo when neutrophils naturally exit the bloodstream, and it is therefore likely that they emit ROS before undergoing apoptosis and clearance by tissue macrophages (30), even in the absence of active inflammation. These kinds of data support the hypotheses of Finch and colleagues that somatic cell resilience to agents such as ROS determines species differences in longevity during repeated infections and traumatic injuries in the natural environment (31). Complementary to this hypothesis, species-specific control of ROS may further contribute to differences in lifespan. Of course, other aspects of recurrent and/or chronic innate immune activation may also contribute to “inflammaging”.

Control of neutrophil ROS production is at least partly mediated by CD33-related subfamily of Siglecs (Sialic acid-binding Ig-like lectins) (28, 32–39) encoded in the CD33rSIGLEC gene cluster, and referred to as CD33rSiglecs (40–44). Consistent with the phylogenetic distribution of sialic acids in the deuterostome lineage of animals, this gene cluster only occurs vertebrates. The CD33rSiglecs recognize endogenous sialylated glycans as SAMPs (29) and modulate myeloid cell lineage reactivity. These type I transmembrane proteins have an N-terminal immunoglobulin (Ig)-like-V-set domain mediating sialic acid (Sia) recognition, followed by a variable number of Ig-like-C-2 type domains, a transmembrane domain, and often, a cytoplasmic tail with one or more immunoreceptor tyrosine-based inhibitory motif (ITIMs). Siglecs with an ITIM motif recruit tyrosine phosphatases such as Src homology domain 2-containing tyrosine phosphatase-1 (SHP-1) dampen cell activation upon engagement of sialic acid-terminated glycans prominent on cell surface glycoproteins and glycolipids, which thus act as SAMPs (45). The less common activating Siglecs have arginine or lysine residues in their transmembrane domains that instead activate cellular immune responses by recruiting the immunoreceptor tyrosine-based activatory motif (ITAM) containing DAP-12 or DAP-10 adaptors (46). These inhibitory and activating Siglecs are prominently expressed on innate immune cells, modulating production of reactive oxygen species (ROS) (47, 48) by phagolysosomal NADPH Oxidase (NOX), which generates ROS primarily for pathogen killing (13, 14), but can also have collateral effects on host cells.

Early studies showed that CD33rSiglecs are rapidly evolving and highly variable in gene number among species such as human, chimpanzees, monkeys and mice (49). In this regard, we noted a surprising correlation between the number of CD33rSIGLEC genes and maximum lifespan in mammalian species, and suggested that this association was due to modulation of oxidative stress arising from innate immune cell activity (50). Consistent with this hypothesis, inactivation of the Siglec-E, a major CD33rSIGLEC gene in mice generated evidence for increased systemic oxidative damage (50). In addition, impaired expression of the free-radical scavenging enzyme Gstp1 in these mice leads to higher levels of oxidative adducts of lipids, proteins and DNA that accelerated aging.

Evolutionary theory predicts selection against decoupling of senescence patterns between somatic and reproductive maintenance, leading to similar aging declines in both fitness traits (51). Indeed, the classic concept of “antagonistic pleiotropy” (52) suggests that genes that support enhanced reproductive fitness in earlier periods of the lifespan can even be positively selected for even if they accelerate aging in late life success. In this regard, the existence of mid-life reproductive cessation in human females (“menopause”) has been an apparent anomaly. This unusual feature has been hypothesized to have evolved in humans because of a “Grandmother” effect i.e., the contributions that post-reproductive females make to the fitness of their children and grandchildren (53). According to this theory, grand-mothering explains increased adult survival and a longer life span and in turn, favors a longer period of prepubertal development (54) and post-menopausal females who provide alloparental care to grandchildren are suggested to have increased fitness (55, 56). In keeping with this concept, we recently reported that certain gene variants that protect against late-life cognitive decline are derived and human-specific (57), including a variant of CD33 (which encodes Siglec-3/CD33).

We here seek to determine if the suggested correlation between number of CD33rSIGLEC genes and maximum lifespan prevails when increasing the dataset of species, study the relative roles of inhibitory and activating Siglecs, ask if other gene families show similar correlations, re-evaluate the relative contribution of mitochondrial and NOX-derived ROS to lifetime exposure, and also address the relative role of CD33rSIGLEC genes in PRLS.

MATERIALS AND METHODS

Analysis of genomic sequences and gene prediction strategy.

Sequences of previously reported human and mouse CD33rSIGLECs were retrieved from NCBI (http://www.ncbi.nlm.nih.gov) and MGI (http://www.informatics.jax.org/), respectively. NCBI annotated CD33rSIGLEC genes for additional mammalian species were used as references for orthologous gene searching. Additional putative CD33rSIGLEC genes were obtained by searching available mammalian genome sequences at UCSC Genome Browser (http://genome.ucsc.edu/), Ensembl (http://www.ensembl.org), and NCBI (http://www.ncbi.nlm.nih.gov/gene), PreEnsembl (for Naked Mole Rat). As SIGLEC genes contain introns, we adopted and modified a previously established search strategy (50, 58). Firstly, the candidate genes were subjected to BLAST and BLAT to identify the genomic location of a putative CD33rSIGLEC gene in a genome with a previously reported CD33rSIGLEC as a query. In addition, gene markers such as VRK3 and KLK were also considered to locate SIGLEC gene cluster in newly and poorly annotated mammalian genomes. Secondly, the orthologous gene was selected based on alignment and phylogenetic closeness with the query CD33rSIGLEC. The above gene search strategy was also applied for predicting another ten randomly selected gene families in mammals, though the criteria used in gene structure evaluation were gene family dependent.

Definition of functional genes.

Based on previous studies on CD33rSIGLECs several characteristics were considered in order to define a gene encoding a functional SIGLEC (59). One criterion is that a Siglec protein has the characteristic amino-terminal V-set Ig-like domain capable of binding sialylated glycans. This binding activity requires a conserved arginine residue in the Ig-like V-set domain. The other criterion is that a functional Siglec protein should contain either a cytosolic tail with at least one ITIM motif or a transmembrane domain carrying a positively charged amino acid. The eventually acquired candidate CD33rSiglecs in each species were considered as true orthologs and used in our correlation analysis. Defining a functional gene using our gene prediction approach is not always clear-cut, due to the nature of incomplete genome sequences or genome sequencing errors. Thus, a few additional rules were considered during our prediction process. First, when entire exons of a gene (usually one or two) are missing due to a gap in the genome sequence but ORFs remain undisrupted in the available sequences, we treat the candidate locus as a functional gene. Second, the presence of essential arginine (R) and the cytoplasmic motif (YSEI) in putative orthologous gene were used as markers to identify functional proteins. Additionally, as discussed in the earlier study, genome coverage did not make any difference in the correlation of the number of CD33rSIGLECs and maximum life span. There is no trend that higher coverage genomes will have higher number of CD33rSIGLEC genes or vice versa. For example, human and mouse genomes have the highest coverage (>12x) out of all mammals and they contain 11 and 4 CD33rSIGLEC genes respectively. Furthermore, in our previous study, we had not included essential Arg mutated SIGLECs because of their inability to recognize Sia. However, in the present study, essential Arg-mutated Siglecs were included because of their baseline activity independent of Sia recognition.

Longevity and body weight data.

Data regarding maximum lifespan and average adult body weight for mammalian species are obtained from AnAge: the animal aging and longevity (http://genomics.senescence.info/species/) (60). Also, the reproductive age of Orca (Killer whale) was obtained from a recent study (53).

Analysis of Functional and Null alleles in Supercentenarians.

To understand the presence and absence of functional SIGLEC genes in Supercentenarians (age >110 years) and individual aged ≤ 65 as Control, we obtained the information regarding SIGLECs from recently published paper on supercentenarians (61) and compared it with the thirty-four Control genomes obtained from Personal Genomics Project (PGP), Harvard (http://www.personalgenomes.org/).

Statistical analysis.

Paired Student’s t-test was used for comparisons involving three polymorphic groups (CD33m, SIGLEC-12 and SIGLEC-16) in Supercentenarian and Control PGP cohort). Lifespan correlation analysis was performed on a linear scale using regression analysis as an add-in Data analysis toolpak in Excel. Prism program (GraphPad, La Jolla, CA) was used for the statistical analyses. Phylogeny Generalized Least-Squares (PGLS) and Felsenstein’s Independent Contrast (FIC) analysis were conducted in COMPARE 4.6b (http://www.indiana.edu/~martinsl/compare/) using a degree of freedom of 23, with three (one for calculating contrast and two for estimating the slope and the intercept) subtracted from 26 (the total number of taxa). Phylogenetic regressions controlled for the body mass were run using correlation analysis in the Mesquite software (http://mesquiteproject.org). The model included CD33rSIGLEC gene numbers as a response, and maximum lifespan and body mass as covariates.

RESULTS

Number of CD33rSIGLEC genes correlates with maximum lifespan across 26 species.

Our previous study showed a correlation between CD33rSIGLEC gene number and maximum lifespan in 14 mammalian species. To assure that this correlation was not due to chance, we have now increased the number of mammalian species to 26 (detailed in Materials and Methods). The genomic localization of Siglecs among 26 mammalian species is shown in Fig. 1 (also provided in Supplemental data are sequence files of all identified CD33rSIGLECs from all 26 species). Since these Siglecs are categorized based on ITIM or ITAM motifs present in their cytosolic tails we studied them separately or in combination for their correlation with maximum lifespan. A moderate correlation was observed with CD33rSIGLECs containing the ITIM motifs (R² = 0.42, p<0.05, Fig. 2) and with those containing ITAM motifs (R² = 0.27, p<0.05, Fig.2). However, the correlation with maximum lifespan was strongest when considering total CD33rSIGLEC gene numbers (R² = 0.58, p=<0.0001, Fig.2).

Figure 1.

Presence and ordering of CD33rSIGLEC genes in Genomes of 26 mammalian species. The numbering designation of likely orthologous of SIGLECs is indicated at the top and the respective presence and absence of the SIGLECs is shown in each species. It should be noted, mouse and rat SIGLECs were based on the most likely phylogenetic relatedness with the human SIGLECs. The phylogeny (on the right) is not scaled and common names (as well as scientific) of 26 mammalian species can be found in Supplemental Table 3.

Figure 2.

Correlation of CD33rSIGLEC genes encoding ITIM or ITAM motifs with maximum lifespan (Years). Level of significance (p value) were computed using Data analysis toolpak (add-in) in Excel.

In order to further test the correlation of maximum lifespan and other gene families, we examined ten other gene families involved in different functions viz. transcription factors (JUN-c, TRAC, ZNF621), immune regulation (IFNα1, APOL1), Cell Signalling (MAS, NPM) and Metabolic process (AMY1α, GAA, ORFAC). None of the other gene families showed strong correlations between gene number and maximum lifespan in 26 mammalian species (Supplemental Fig.1).

Correlation between CD33rSIGLEC gene number and maximum lifespan is independent of phylogeny or body weight.

Closely related species may share similar traits due to their common ancestry and/or body weight, making data from different species not necessarily statistically independent. To control for such effects, we did phylogenetic comparative analysis using Phylogeny Generalized Least-Squares (PGLS) or Felsenstein’s Independent Contrast (FIC) approaches. The correlation between CD33rSIGLECs and longevity remained robust after such phylogenetic correction (Supplemental Fig. 2, Supplemental Table 1). Moreover, the correlation also persisted after mathematical correction for body mass represented by average adult body weight, another factor known to correlate with metabolic rate and lifespan (Supplemental Table 2). Taken together, these data indicate that the correlation of the number of CD33rSIGLEC genes with maximum lifespan in mammals appears independent of phylogenetic constraints (Pagel Lambda: R² = 0.21, df=24), effects of genomic location, evolution of receptors involved in immune responses and body mass.

Estimation of Adult Reproductive Lifetime Production of Neutrophils in Humans.

So far, we have assumed that the striking correlation of the number of CD33rSIGLEC genes with maximum lifespan is related to differential modulation of life-time phagolysosomal ROS production by NOX enzymes and their regulation by Siglecs. However, as detailed in the introduction, life-time exposure to ROS is often assumed to originate largely from mitochondria, which are present in all cells in the body and represent a constant source. In contrast, ROS produced by phagolysosomal NOX enzymes originates mainly from neutrophils and other myeloid lineage phagocytes (monocytes) and are assumed to mostly originate during acute or chronic immune responses to invasive pathogens (62, 63). However, recent evidence suggests that neutrophils may spontaneously activate when they exit the circulation (64) and escape the inhibitory sialome-based milieu of the bloodstream (28). Thus, prior to rapid demise, each neutrophil likely releases some ROS, with the amount depending on potential encounters with commensal or pathogenic microbes.

Combining independent lines of evidence including the short half-life and spontaneous activation of neutrophils, we here calculated that even without re-current inflammation, a major source of lifetime ROS exposure may be NOX-derived. Neutrophils are produced in the bone marrow, enter the circulation and then exit into tissues. Traditional dogma maintains that these cells circulate for only a few hours. Estimated neutrophil half-lives in healthy individuals vary from 6.7 hrs to 3 days (discussed later). However, the short lifetime values are based on reinfusion of purified neutrophils, which are effectively pre-activated and might be cleared more rapidly. The debate on these different values reached a compromise with a recent estimate of T^1/2 as 1 day (65). Assuming this number is reasonably correct, how many neutrophils pass through the body of an adult human each year?

The first step is to calculate the circulating granulocyte pool (CGP) in a healthy individual of ~60Kg weight (Table 1). The average neutrophil count in circulating blood is ~5000 per μl, the typical blood volume is 5000 ml (5×10⁶ μl), giving a CGP = 5000 × 1000 × 5000 = 25 × 10⁹ cells. Taking into consideration the approximately equal marginated granulocyte pool (MGP), the total granulocyte blood pool (TGBP) is 5 × 10¹⁰ cells. Assuming a half-life of 1day, neutrophil production during an average 30-year adult reproductive life span is then 5 × 10¹⁰ × 0.5 × 30 × 365= 2.735 × 10¹⁴ cells per 30 years (Table 2). Even ignoring multiple infectious episodes during which neutrophil counts and activity may drastically increase, the number of neutrophils that pass through the body of an adult human during an adult reproductive lifetime is ~10 times the number of cells in the body (latest estimate is 3.7 × 10¹³)(66). Thus, a major source of ROS may be NOX2-derived, and this may help explain why CD33rSIGLEC gene number correlates so well with maximum life span.

Table 1.

Calculation of Blood Neutrophil turnover rate during one decade of an individual’s life. Assumes the half-life of neutrophils in circulation is 1 day (See text for discussion).

Parameter	Estimates
Blood volume	5000 ml (A)
Average Neutrophil count	5000 /μl (B)
Circulating Neutrophil pool (CGP) (A × B)	2.5 × 1010 cells (C)
Total Neutrophil Blood Pool (TGBP) 2 × C	5 × 1010 cells (D)
Half-life in Circulation (h)	1 Day
Neutrophil turnover rate per Decade (3650 days)	0.91 × 1014 cells/Decade

Table 2.

Correlation of number of CD33rSIGLEC alleles in Supercentenarians (N=11) and Personal Genomics Project (PGP) Controls (N=34). Paired T test: t=1.557 df=2, P= 0.2597, Non-significant. Calculation based on CD33m (protective allele marker), SIGLEC12P (Pseudogene) and SIGLEC16P (Pseudogene).

	Supercentenarian (22 haploid genomes)	PGP Controls (68 haploid genomes)
CD33m	5	16
SIGLEC12P	8	10
SIGLEC16P	7	14

Supercentenarians do not have unusually high number of CD33rSIGLEC genes.

Based on the findings thus far, we next sought to ask if extremely long-lived humans harbor higher numbers of CD33rSIGLEC genes. We could ask this question because of the polymorphic presence of human-specific CD33rSIGLECP pseudogene alleles in human populations in variable frequency, with overall averages of SIGLEC12P (58%) SIGLEC16P (88%) and SIGLEC14P (39%) respectively (67, 68). In addition, there is a polymorphic presence of an alternatively spliced CD33m Alzheimer’s disease protective allele, also specific to humans (57). For various technical reasons, the SIGLEC14P allele comprised of >14kb deletion is difficult to determine in standard genome sequences or in the variant call format (VCF) files available from databases. We thus explored the status of SIGLEC12P, SIGLEC16P and CD33m in Supercentenarians and Control individuals. The number of CD33rSiglec alleles was correlated between 22 Supercentenarian haploid genomes and 68 PGP control genomes, and we found no enrichment of ancestral intact alleles in Supercentenarians (Table 2).

CD33rSIGLEC gene number correlates best with maximal Reproductive Lifespan, not Total Lifespan.

The above finding in Supercentenarians appears to go against our original hypothesis, which predicted a correlation between total CD33rSIGLEC gene numbers and maximum lifespan. However, in carefully reconsidering the data (Fig.3), we noticed that only two species (out of twenty-six) fall far off the line of regression, namely humans and killer whales (orcas) (Fig. 3, R² = 0.58, p<0.0001). Notably, these are the two species that also have a prolonged PRLS. When we recalculated the regression statistics considering only reproductive lifespan of the above two species (orca and human), humans and killer whale gene numbers now fall on the line of regression, the correlation improves greatly and p value becomes highly significant (Fig. 3, R² = 0.83, p<0.0001).

Figure 3.

Correlation of CD33rSIGLEC genes with Maximum or Reproductive lifespan (Years). Level of significance (p value) were computed using Data analysis toolpak (add-in) in Excel.

DISCUSSION

Since Harman first proposed that ROS are mediators of the aging process (69), much research has supported this concept. There are of course many mechanisms of aging, and reactive oxygen species (ROS) is only one contributor (6, 70). In fact, it is well documented that ROS can be beneficial as well as detrimental, and it is the balance of ROS production that apparently matters (too much is bad, too little is bad). ROS produced by phagolysosomal NADPH oxidase are prominently produced by professional phagocytes such as neutrophils and monocytes which play a central role in the innate immune response. Furthermore, our discovery of constitutive RBC suppression of neutrophils shows that as soon as neutrophils leave the bloodstream, they are very likely to release ROS, even more so than upon encountering normal commensals at mucosal interfaces (28). Because of the capacity of NOX2 to produce high levels of ROS constitutively, and the role of SIGLECs in regulating phagocyte NOX2 activity, we suggest that NOX2 is the prominent source of ROS throughout life. While other NOX isoforms such as NOX4 and NOX5 are believed to become important contributors to tissue-specific ROS production in certain disease states, neither isoform has been systematically studied in human aging, so this remains an open question (11, 12).

CD33rSIGLEC genes are expressed on innate immune cells and are variable in number among species, which further reflects the cells variability in ROS production. Of course, other functions of Siglecs might also be associated to their variation in number. For example, bacterial pathogens expressing sialic acids can engage CD33rSiglecs (71, 72) and might therefore represent strong driving forces for shaping the evolution of this class of receptors (29, 73). Our earlier study suggested that Siglec gene number of few mammalian species correlated with maximum lifespan and modulates ROS. Here we affirm this association with a larger dataset and found that total CD33rSIGLEC number in the genome correlates with maximum lifespan implicating the balanced production and destruction of ROS. However, this correlation becomes much stronger when the unusual prolonged post-reproductive lifespans of humans and orcas was taken out of the analysis, suggesting the role of CD33rSIGLECs in regulation of reproductive lifespan.

Note that apart from humans, only two known species (killer whale (Orcinus orca) and short-finned pilot whale (Globicephala macrorhynchus)) exhibit prolonged PRLS (55). Information on post-reproductive survival in long-lived species has been more limited because of the difficulty in obtaining longitudinal data, especially from populations in the wild. While there is evidence of such post reproductive lifespan in many other species, it is generally short, detectable only in few individuals and occurs mainly in captivity, in association with health promoting measures, veterinary care and absence of predation (55). This life history pattern stands in stark contrast to that of other mammalian species, wherein reduced fecundity generally coincides with somatic aging and eventually with death (55, 74). Also as discussed earlier, from the perspective of natural selection during evolution, successful reproduction with transmission of genetic material from individuals to the next generation is the key to “fitness”. Thus, the most effective way for an organism to maximize its fitness is to continue to reproduce until somatic aging leads to the end of life. This is indeed the case for the vast majority of mammals, and the time between last parturition and death is related to the overall longevity of most species (55). Thus, senescence can reduce fertility in late life, and a brief post reproductive lifespan is a common trait in many mammals (75). It has been noted that a few marine species such as beluga whale (Delphinapterus leucas), narwhal (Monodon monoceros) and false killer whale (Pseudorca crassidens) (74) do manifest a short but more significant post-reproductive lifespan. In addition, Asian elephants that share some features with humans and these whales in having large brains, being long lived and having well-defined social networks also share short post reproductive lifespans (76). Indeed, in Asian elephants having a nearby grandmother can enhance calf survival even though the grandmother may be still reproducing (77). However, the extension of life well beyond the end of the reproductive lifespan is extremely rare and is limited only to humans and two species of whales (55, 74, 78–80).

Based on genetic variation, it is well documented that comparison of long-lived cohorts and controls showed variation. Analysis of candidate genes such as Insulin-like Growth Factor 1 (IGF-1) and forkhead box O-3 (FOXO3) have revealed that polymorphisms in these genes are associated with extreme longevity (81, 82). In addition, genome-wide association studies have shown that the apolipoprotein e4 (APOE4) haplotype is depleted in centenarians (83–85). However, more variants that decrease gene function in the Teashirt Zinc Finger Homeobox 3 (TSHZ3) were observed in Centenarian and Supercentanarian genomes (~110 years) than control genomes (61). Considering these studies, we found that supercentenarians genomes did not contain an increased number of functional SIGLEC alleles in comparison to controls. Although the CD33 protective allele (also known as CD33m) helps reduce cognitive decline and Alzheimer’s disease, the frequency of the variant was not significantly different between supercentenarian and control genomes which supports the conclusion that CD33rSIGLECs are not involved in regulating PRLS, but instead contribute to the regulation of reproductive lifespan. A recent paper showed Older Amish individuals harbor a rare loss-of-function mutation in SERPINE1 gene that protects against effects of ageing. This mutation affects the function of plasminogen activator inhibitor-1 (PAI-1), which has a vital role in cellular senescence and is expressed at higher levels in senescent cells (86). This loss of function in “wellderly” individuals could be one of the factors that regulate PRLS. Further investigation is certainly warranted to decipher other factors regulating PRLS and future studies based on post-reproductive lifespan and correlation of genetic variants are required. The naked mole-rat appears resistant to aging with a maximal lifespan of 30 years or more (87). Despite having such an exceptional longer lifespan, the CD33rSIGLEC gene number is only appropriately higher than that of other rodents and falls on the regression line.

We have also now calculated that a very large number of neutrophils are produced and enter tissues during an adult reproductive lifespan, and their NADPH Oxidase enzyme may possibly be a major source of total life-time ROS along with whole body mitochondria. Siglecs are major regulators of ROS production by phagocytes, perhaps explaining why SIGLEC gene numbers so strongly correlated with maximum reproductive lifespan. A relevant question is how much ROS each neutrophil produces after it leaves the circulation and before it disappears. In this regard our recent work (28) shows that immediately after separation of neutrophils from the heavily sialylated RBCs and plasma proteins that suppress activation by engaging Siglecs, these cells become spontaneously activated. An additional consideration is that, in acute idiopathic or drug-induced agranulocytosis (which involves the sudden selective loss of neutrophils), tissues are rapidly invaded by “normal commensal” organisms (88). Indeed, prompt recognition of patients with neutropenic fever of any kind is a well-established imperative and the administration of empiric systemic antibiotic therapy is typically used to reduce the risk of severe sepsis (88, 89). These clinical observations suggest that at steady-state neutrophils are likely to be constantly encountering and eliminating commensal organisms that enter too deep into host tissues, likely generating ROS all the time, even in the healthy state.

In summary, the present study shows a strong correlation between CD33rSIGLEC gene number and reproductive lifespan further implicating the role of these receptors in balancing oxidative stress and modulate aging patterns and lifespan in mammals. We know of no other gene family that shows such a striking correlation with lifespan and gene number. In view of this fact, and the well-known ROS modulatory role of SIGLECs it is natural for us to focus on this aspect. The lack of correlation with post-reproductive lifespan suggests roles of other genes that are under study. The larger implication is that the study of aging phenomena in humans needs to consider the possibility that the post-reproductive period may be regulated by factors different from those gleaned from studying aging in other animals.

Supplementary Material

Supp figS1-2

Supplemental Figure 1 No correlation among Ten gene families and Maximum Lifespan in 26 mammalian species.

Supplemental Figure 2 Phylogenetic tree with its newick format used in this study.

ABBREVIATIONS

NOX

NADPH-oxidase

ROS

Reactive oxygen species

PRLS

Prolonged post-reproductive lifespan

Siglecs

Sialic acid-binding Ig-like lectins

SAMPs

Self-Associated Molecular Patterns

Sia

Sialic acid

ITIMs

Immunoreceptor tyrosine-based inhibitory motif

SHP-1

Src homology domain 2-containing tyrosine phosphatase-1

ITAM

Immunoreceptor tyrosine-based activatory motif

PGLS

Phylogeny Generalized Least-Squares

FIC

Felsenstein’s Independent Contrast

CGP

Circulating granulocyte pool

MGP

Marginated granulocyte pool

TGBP

Total granulocyte blood pool

IGF-1

Insulin-like Growth Factor 1

FOXO3

Forkhead box O-3

APOE4

Apolipoprotein e4

TSHZ3

Teashirt Zinc Finger Homeobox 3