In mice transgenic for IGF1 under keratin-14 promoter, lifespan is decreased and the rates of aging and thymus involution are accelerated

Original findings and discussion thereof

Figure 1 shows that, in the cohort of female K14/mIGF1 mice compared with WT FVB/N mice, an accelerated age-dependent thymus involution is paralleled by an accelerated age-dependent decrease in serum thymulin titer. The divergences between the trends seen in the two cohorts lead to initially small differences, which increase to statistical significance at later ages. At the same time, body weights and their changes with age are virtually identical in both cohorts, so as spleen weights, the latter being constant through the adult lifespan.

Since keratin-14 is known to be expressed in the thymus [15] (but not in the spleen and lymph nodes (https://www.proteinatlas.org/ENSG00000186847-KRT14/tissue) it is reasonable to hypothesize that IGF1 gene expression driven by keratin-14 promoter takes place in the thymus, not only in the skin of K14/mIGF1 mice. No direct data about IFG1 expression in the thymus, unlike the skin [14], of K14/mIGF1 mice are available so far. However, the expression of both IGF1 and IGF1R in unmodified murine and human thymus epithelium has been demonstrated [23,24]. Thus, if the local IGF1 expression in the thymus is altered being driven by keratin-14 promoter, the alteration is likely to produce effects via IGF1R. Our finding that the effects are manifested as accelerated thymus involution is quite counterintuitive since exogenous IGF1 administration has been shown [25,26] to increase thymus weight by expanding thymus epithelium.

Whatever the cause of the accelerated thymus involution in K14/mIGF1 mice, their survival pattern is consistent with accelerated aging as suggested by the survival curves of K14/mIGF1 and WT FVB/N mice, which are compared in Figure 2. The numerical estimates of their lifespan and survival parameters are presented in Table 1.

The involvement of thymus involution in aging and in the development of age-associated immunologic and neuroendocrine disorders in mice is long recognized (reviewed in [27–29]). However, the available evidence mostly shows how aging influences the thymus. There is very limited if any experimental data showing how interferences with the rate of thymus involution are translated into changes in the rate of aging.

The causes of accelerated thymus involution in K14/mIGF1 mice must relate somehow to IGF1 expression driven by keratin-14 promoter. Serum IGF1 has been shown to be unaltered in K14/mIGF1 compared with WT FVB/N mice [14]. However, even if serum IGF1 were increased because of IGF1 overexpression driven by keratin-14 promoter, which is known to take place in the skin of K14/mIGF1 mice [14], still the available evidence [25,26] is consistent with that, in adults, this would enhance thymic functions and increase lifespan. Therefore, the accelerated aging of K14/mIGF1 mice is likely associated with not the systemic effects of altered IGF1 signaling but rather with the accelerated thymus involution. Indirect evidence (see above) suggests the hypothesis that the acceleration may relate to the local IGF1 expression driven by keratin-14 promoter in thymus epithelial cells.

Another feature of K14/mIGF1 compared with WT FVB/N mice is the increased incidence of skin papillomata (Table 2). Increased susceptibility to papilloma was also observed in the transgenic mice that express IGF1 under keratin-1 or keratin-5 gene promoter [30,31]. The distributions of papillomata and other spontaneous tumors over the lifespans of K14/mIGF1 and WT FVB/N mice is shown with shade-coded points in Figure 2.

An increase in the lifelong prevalence of skin carcinomas in K14/mIGF1 vs. FVB/N mice is conspicuous but statistically insignificant, so as other differences in lifelong oncological indices between the two strains. A noteworthy observation is the predominance of lung cancer among tumors found in WT FVB/N mice, which is consistent with findings noted by other authors [32]. A lowered proportion of lung carcinomas among all tumors in K14/mIGF1 mice is insignificant statistically.

Further insight into relationships between spontaneous carcinogenesis and aging may be obtained by comparing survival patterns upon their censoring for cases not associated with postmortem tumor detection. The results are presented in Figure 3.

In the presence case, the Kaplan-Meyer plots show the probabilities of not dying without having a detectable tumor by a certain age. These probabilities decrease when tumors are initiated earlier and/or grow faster. This is what occurs in K14/mIGF1 mice as follows from that differences between censored plots related to K14/mIGF1 and WT FVB/N mice are significant according to the log-rank test (p<0.001) irrespective of whether papillomata are taken into account.

Taken together, our findings suggest that, in mice, the acceleration of thymus involution and of the associated decrease in serum thymulin will shorten lifespan because of accelerated aging rather than increased initial mortality rate (Table 1 and Figure 2). The accelerated aging is manifested, in particular, in accelerated tumor initiation and/or growth (Figure 3). This conclusion per se does not depend on any assumptions concerning the cause of accelerated thymus involution. In the present case, the cause must relate somehow to IGF1 expression driven by keratin-14 promoter. Below it will be shown that the present case of modified IGF1 signaling differs drastically, with regard to murine survival patterns, from published cases of altered IGF1 signaling where either other promoters were used to modify IGF1 expression or IGF1R expression was altered.

Comparative analysis of original and published survival data

Differentiating changes in the initial viability, which in the Gompertz model (GM) is captured, in an inverse manner, by the initial mortality μ₀, and in the rate of its decline (the rate of aging, γ) is essential for understanding the effects of interventions into lifespan [17,19,20]. It will be shown below that, in this regard, the K14/mIGF1 model is strikingly different from other models used to study the effects of interventions in IGF1 signaling on lifespan in mice.

The artifactual component of correlation between GM parameters [20–22] makes it a tricky matter to distinguish the contributions of changes in the initial mortality and in the rate of aging to changes in lifespan. Figure 4 shows the estimates of μ₀ (logarithmic ordinate) vs. γ (linear abscissa) extracted from published survival curves related to the parent (control) strains of mice used to alter IGF1 signaling by gene engineering (references are provided in the legend to Figure 5). A linear correlation between lnμ₀ and γ is apparent. However, the respective regression of lnμ₀ on γ is almost parallel to the two other regressions shown in Figure 4, one of which is derived from data on several murine strains bred in a single laboratory (http://www.jax.org/research-and-faculty/research-labs/the-harrison-lab/gerontology/available-data), and the other, from data on several samples of female 129/Sv mice all drawn from a single general population [20]. The latter regression is 100% artifactual. Therefore, the other two must comprise significant artifactual components.

To distinguish between real and apparent changes in GM parameters, we employed the approach suggested and thoroughly discussed in [20], where it was used to differentiate the effects of calorie restriction and of drugs believed to mimic it. In essence, when a change in μ₀ is associated with a reciprocal change in γ, the latter is valid only if it is different from what the artifactual regression of lnμ₀ on γ would suggest. Ideally, for each particular population of a specific murine strain and gender, this regression must be derived from a series of control samples (as it is in the case of 129/Sv mice in Figure 4) or the randomization of a sufficiently large control sample into several subsamples. However, because all regression lines in Figure 4 are almost parallel, their general trend may be used as a reference.

Applying this approach to data about transgenic mice in which IGF1 signaling is modified in different ways (Figure 5) suggests that the difference between K14/mIGF1 and WT FVB/N mice is unique in that the respective vector (thick dashed gray line at the top of Figure 5A) is parallel to the γ axis. In this regard, the K14/mIGF1 vs. WT FVB/N case stands out of all other cases irrespective of a possible interpretation of the patterns presented in Figure 5. A plausible interpretation is that the decrease in the lifespan of K14/mIGF1 mice is completely attributable to accelerated aging. The magnitude of the decrease is reflected more by the deviation of the vector from the slope that reflects the artifactual relationships between the estimates of GM parameters, rather than by the length of the vector. Among all cases analyzed in this way earlier [20], only calorie restriction was associated with that the orientations of the respective vectors were almost parallel to the γ axis, albeit the direction of the vectors was reciprocal to that related to K14/mIGF1 vs. WT FVB/N mice. Calorie restriction is generally believed to slow down aging. This observation strengthens the conclusion that accelerated aging is largely responsible for the significant decrease in the lifespan of K14/mIGF1 mice.

Another case of a significant deviation of the corresponding vector from the artifactual slope relates to mice in which IGF1 overexpression is confined to the heart and muscles and, with that, is associated with increased circulating IGF1 [8], that is with enhanced systemic IGF1 effects. A marked increase in the median lifespan in this case (the thick hollow vector in the top left corner of Figure 5A) is brought about by decreases in both, the initial mortality (μ₀) and the rate of aging (γ). As far as the respective vector clearly deviates from the reference (artifactual) regression, changes in both of the parameters must be real and unidirectional and, thus, must be associated with a marked change in lifespan, although the vector is much shorter than that related to K14/IGF1 vs. WT FVB/N mice. Because the effects of increased IGF1 signaling brought about by elevated blood IGF1 must be beneficial for the thymus [25,26], decelerated aging in this case may be partially attributed to decelerated thymus involution, whereas decreased initial mortality, to the systemic effects of increased IGF1 signaling. The latter proposal is prompted by the observation that the systemic changes in IGF1 signaling that are brought about by interferences with IGF1R expression influence μ₀ rather than γ (see Figure 5B and its discussion below).

The third case of a marked deviation of changes in GM parameters from the artifactual relationships between them is presented by data of Ashpole et al. [9]. In female mice, IGF1 downregulation at the age of 10 days increases lifespan, which is equivalent to a decrease upon upregulation, as reflected by the direction of the respective vector head in Figure 5A. This black hammerhead vector is almost perpendicular to the artifactual slope, this being consistent with increases in both, μ₀ and γ. When the same intervention starts at 5 months of age, a similar decrease in the median lifespan (considered as if occurring upon increased IGF1 signaling) is accountable for by increased μ₀. The slope of the relatively long gray hammerhead vector being close to the artifactual slope. In male mice, lifespans seem to increase upon increasing IGF1 signaling; however, the effects are small and, in terms of changes in GM parameters, are contradictory, the corresponding reciprocally directed vectors being almost parallel to the artifactual slope.

In [10], a significant decrease in lifespan upon downregulation of IGF1expression in the liver of male mice was reported. This is equivalent to an increase in lifespan upon IGF1 up-regulation (relative to, perhaps, an inappropriately low level). The respective (dotted) vector in Figure 5A suggests that the increase is caused by a decrease in μ₀, whereas the apparent increase in γ (which per se could not increase lifespan) is largely artifactual as far as the vector is parallel to the reference regression, which is completely artifactual. The magnitude of the artifact, as well as of 95% confidence limits of the estimates of GM parameters may relate to the small numbers of animals (15 and 16) in the groups compared. There was no effect on lifespan in females in this study, and the female survival plot presented in [10] is too messy to extract numerical data from it.

In Figure 5B, IGF1R⁺⁺ and IGF1R^+– mice are compared. The latter are transgenic, and the former are wild type, that is, the former are regarded as controls. However, because in the present context the consequences of enhanced IGF1 signaling is the matter of interest, all vectors shown in Figure 5B are directed towards points related to control instead of transgenic mice. Even without a detailed analysis, it is clear that the orientations of the vectors shown in Figure 5B are overtly different from the vector related to K14/mIGF1 mice in Figure 5A, no matter how the patterns seen in Figure 5 may be interpreted. Some suggestions concerning Figure 5B interpretation are given below

The gray vectors in Figure 5B relate to data reported in [12]. The authors demonstrated significant increases in the lifespan of 129/Sv mice in which systemic IGF1 signaling was attenuated by gene engineering resulting in IGF1R haploinsufficiency (IGF1R^+–). This is equivalent to decreased lifespans in IGF1R⁺⁺ vs. IGF1R^+– mice. The effect is more expressed in females. Because lifespan cannot be decreased by the deceleration of aging per se, the primary effect must be a real increase in μ₀ associated with an apparent decrease in γ, which is largely artifactual since it is not greater than the reference regressions suggest.

When the same gene-engineering approach was applied to C56BL mice, the conclusion was that upon attenuated IGF1 signaling, lifespan is increased in females only and is decreased in males [11]. Dotted vectors in Figure 5B show these effects in a reciprocal manner. However, since the effects are small, within 5%, they must be, most likely, irreproducible according to the “probability of detection” criterion introduced in [33]. In Figure 5B, the respective vectors are short and almost parallel to the reference regressions. It was confirmed subsequently [34] that decreased IGF1 signaling increases lifespan only in the females of C56BL mice. This effect is shown in Figure 5B with the black hammerhead vector. The magnitude of the effect is consistent with the marked deviation of this relatively short vector from the reference regressions. The decrease in lifespan is attributable to increased μ₀, whereas the apparent increase in γ is distinctly smaller than the reference regressions suggest. As to the lifespan of C56BL males according to data extracted from survival curves presented in [34], it seems not to depend on changes in IGF1 signaling within ranges possible upon IGF1R haploinsufficiency. Indeed, the respective vector (black arrowhead), although it is long, suggests that a decrease in μ₀ is associated with a greater than it follows from the reference regressions decrease in γ; that is, an apparent increase in the estimate of the initial mortality is compensated by an apparent decrease in the estimate of the rate of aging. The associated alteration of lifespan is so small that little, if anything, more than artifactual is presented by this case.

Animals

Wild-type female FVB/N (WT FVB/N) and FVB/N-derived transgenic K14/mIGF1 mice [14] were donated by European Molecular Biology Laboratory Mouse Biology Unit (Monterotondo-Scalo, Rome, Italy). The mice were then housed and bred in parallel at the animal facilities of N.N. Petrov National Medical Research Center of Oncology (Saint Petersburg, Russia) and Institute of Genetic and Regenerative Medicine (Kiev, Ukraine). Cohort were established by combining animals born within one week after the date that preceded by three months the onset of the follow-up of a cohort. Five to seven mice were kept in polypropylene cages under a standard light/dark schedule (12:12) at 22±2°C with food and water ad libitum. When the numbers of mice in cohorts decreased because of deaths, the survived mice were randomly transferred to a smaller number of cages to keep 5 to 7 mice per cage throughout the whole study period, except for the last survivors. All mice were under veterinary control. All procedures were performed in conformance with European Convention for the Protection of Vertebral Animals Used for Experimental and Other Scientific Purposes, CETS No. 123, and were approved by the Ethic Committees of N.N. Petrov National Medical Research Center of Oncology and Institute of Genetic and Regenerative Medicine.

Thymus and thymulin studies

To determine changes in thymus and spleen weights and serum thymulin titers and in whole body weight, the cohorts of female WT FBN/N mice (N₀=77) and K14/mIGF1 mice (N₀=57) were established at Institute of Genetic and Regenerative Medicine. Ten mice of each cohort were sacrificed by decapitation at the age of 3 months and in every 3 months thereafter. Thymuses and spleens were dissected and weighed. Serum samples obtained by centrifugation of clotted blood were stored at –20°C. Thawed samples were filtered through Centriflo CF-25A ultrafilter (Amicon, USA) to remove the high molecular inhibitor of thymulin. Thymulin titers were determined as described in [41]. The determination method is based on the ability of thymulin to restore the sensitivity of spontaneous rosette formation by splenocytes from thymectomized mice to inhibition with azathioprine (Sigma, USA). The results were recorded as log₂(thymulin titer).

Survival and carcinogenesis studies

To determine the survival patterns of mice, WT FVB/N (N₀=69) and K14/mIGF1 (N₀=46) cohorts were followed-up at N.N. Petrov National Medical Research Center of Oncology until the natural deaths of their last members. The related procedures have been described earlier [42]. All dead animals were autopsied. Any tumors as well as tissues and organs with a suspected tumor mass were excised and fixed in 10% neutral formalin. After routine histological processing, the tissues were embedded in paraffin. Five to seven 7-mm thick histological sections were stained with hematoxylin and eosin and examined microscopically. Tumors were classified according to International Agency for Research on Cancer.

Survival analysis

Experimental and published survival data were approximated, as described in [20], with the parametric Gompertz model (GM):

$\begin{array}{l}n(t)=\underset{\Delta t\to 0}{\lim }\frac{N(t)-N(t+\Delta t)}{\Delta t}=\frac{dN(t)}{dt},\\ \mu =n(t)\times \frac{1}{N(t)}={\mu }_0\cdot e^{\gamma t},\end{array}$

where: N(t) is the number of survivors at age t; Δt is the increment of t, n(t) is the decrement of N(t) during Δt, μ(t) is the force of mortality, i.e., the decrement of N(t) during Δt relative to the number of survivors at age t; μ₀ is the initial mortality, which may be interpreted as capturing, in the inverse manner, the initial viability, and γ is the rate of aging.

Under these premises,

$N(t)=N_0-{\text{e}}^{-\frac{{\mu }_0}{\gamma }({\text{e}}^{\gamma \cdot t}-1)}$.

The basic GM model, which does not account for the age-independent mortality and for study sample heterogeneity, is appropriate when experimental samples are small [16,20]. The maximum likelihood method implemented in the TableCurve2D software tool ver. 5.1 (Systat Software Inc., San Jose, CA, fully functional trial version available at http://www.sigmaplot.co.uk/products/tablecurve2d/tablecurve2d.php) was used to fit survival data to the above equations.

To account for the artifacts that are inevitably introduced to μ₀ and γ estimates by any technique of survival data fitting to GM [22], the estimates were checked against the artifactual correlation between them as suggested in [20]. GM parameters were compared based on the overlaps of their 95% confidence intervals (CI).

Statistics

Subsets of time series data related to small age intervals were treated using Mann-Whitney test. Contingency data were compared using the exact Fisher test and/or Chi². Tabulated data are presented as means ± standard errors of the mean (with 95% CI in round brackets).

To get insight into the contribution of tumors to mortality, the Kaplan-Meier approach was applied: survival data were censored for cases not associated with the presence of a tumor upon postmortem examination. This was carried out using GraphPad Prism ver.7 software (GraphPad Software, San Diego, CA).