Heterogeneous pattern of differences in respiratory parameters between elderly with either good or poor FEV₁

In advanced age, spirometric indices show a large inter-individual variability within the general population even after accounting for age and determinants like sex, height and ethnicity, and for several parameters the coefficient of variation even increases with age [1]. The relationship between the functional indices as measured in the same lung-healthy subjects has not been extensively studied. This is of interest since low spirometric values are often used as an indicator of a reduced functional state of the whole respiratory system, particularly by deriving an estimated “lung age” e.g. to support smoking cessation [2]. In fact, however, it is unclear whether this notion is adequate in the sense that various functional parameters of the lung show low values. This would have to be expected with a common process of biological aging or premature aging. To answer this question a comparison of different domains of parameters is needed. Ideally, this requires a logitudinal analysis but at least the comparison of different functional domains should be possible in a sample of age-matched elderly subjects.

We therefore investigated in subjects of advanced age who were free of lung disease according to their clinical history, whether various functional indices show parallel differences indicative of a general state of the respiratory system that could be related to aging. For this purpose we analyzed the relationships between forced expiratory volume in 1 s (FEV₁), static lung volumes, airway conductance, respiratory pump function, pulmonary gas exchange, exhaled biomarkers, systemic oxidative stress and cell-biological age, as well as general physical capacity. The study population comprised two subgroups of the KORA-Age cohort who had been selected based on their percent predicted values of FEV₁ either being at the upper or the lower end of the distribution.

Spirometry was performed in the KORA study center (Augsburg, Germany) within the frame of the KORA-Age study conducted in 2009–10 [3]. The study was approved by the Ethics Committee of the Bavarian Medical Association, and its details have been described previously [4]. Briefly, in 935 individuals aged 65–90 years from the Augsburg region spirometric measurements were performed in line with ATS/ERS recommendations [5], and 840 subjects gave their written consent to be contacted to participate in the current sub-study, for which 200 individuals were selected from the upper and lower tails of the FEV₁%pred distribution based on reference equations of the lung-healthy population of the Augsburg region [4]. Subjects were further examined at the University Hospital of the Ludwig-Maximilians-Universität in Munich: 104 with high (upper end of distribution, UED) and 96 with low (lower end of distribution, LED) FEV₁%pred. The examination focused on the respiratory system but also covered biomarkers and physical capacity. For the present analysis, current smokers and subjects with symptoms of chronic bronchitis or a respiratory infection within 3 weeks prior to examination were excluded. Non-smoking status was defined via self-report; additionally an exhaled carbon monoxide value of < 7 ppm was required [6]. These criteria led to an analysis sample of n = 72 (69% of total) in the upper and n = 51 (53%) in the lower group.

A detailed description of the methods is given in Additional file 1. According to current guidelines, the following assessments were performed and parameters obtained: spirometry (FEV₁, FVC, expiratory flow rates) [5], body plethysmography (airway conductance (Gaw), specific airway conductance (sGaw), total lung capacity (TLC_pleth), intrathoracic gas volume (ITGV), residual volume (RV)) [7, 8], determination of CO and NO uptake of the lung (transfer factors TLCO, TLNO, transfer coefficients KCO, KNO; alveolar volume (VA), TLC by helium dilution (TLC_He)) [9], measurements of mouth occlusion pressure (0.1 s after the onset of tidal inspiration (P01), peak maximal static inspiratory mouth occlusion pressure (PImax)) [10], exhaled carbon monoxide (eCO) and exhaled nitric oxide at 50 ml/s (FeNO) [11]. Furthermore, a 6-min walk test was performed [12]. The telomere length of circulating leukocytes [13] and the serum level of 8-hydroxydeoxyguanosine (8-OHdG) were assessed from samples collected in the KORA study centre in Augsburg.

In the present study we compared two subgroups from a larger population-based cohort which were selected to show FEV₁ either at the lower end (LED) or the upper end (UED) of the distribution in the whole cohort. These subgroups were selected to be lung-healthy according to clinical history, symptoms and risk factors. The broad set of parameters allowed to compare the two groups regarding a number of functional domains. Deteriorations in spirometric values are sometimes interpreted as indicators of premature aging of the lung [2] but it is not clear whether these reflect a general respiratory status that would justify the terminology of an individual (overall) “lung age”. The adequacy of this notion can only be evaluated by comparison of a broad panel of lung function parameters, preferentially in a longitudinal cohort. However, the comparison between parameters should also be possible in carefully selected individuals of a cross-sectional analysis. Our study was suited for such a comparison, as it comprised spirometry, body plethysmography, transfer factors for CO and NO, and respiratory pump function. Additionally, telomere length of peripheral blood leukocytes and 8-OHdG were included as markers of biological age and stress.

We found a difference of about 40% predicted FEV₁ between the LED and UED group. This was the result of the definition of both groups but nonetheless reflected the huge difference in FEV₁ even among lung-healthy elderly subjects. The differences in FVC and in FEV₁/FVC were smaller. On the other hand, those of the FEFs as well as airway conductance and specific airway conductance were even larger. The scales of these parameters were comparable with each other, since airway conductance was chosen instead of resistance and impairment was always associated with a reduction towards zero. The comparison with the differences in plethysmographic volume parameters was less straightforward, since in principle, although not in practice, there is no upper bound of these parameters and no commonly accepted transformation analogous to conductance. Based on the differences in scale and physiologically possible range, it is understandable that the volume parameters showed smaller differences between the two groups.

In contrast, NO and CO transfer factors also decrease upon impairment, having zero as lower bound, and are in this respect comparable to the spirometric and airway conductance parameters. Despite this similarity the differences between LED and UED groups were only about 10% in case of TLCO and about 15% in case of TLNO. Both of these parameters involve lung volume, therefore the transfer coefficients which in first order correct for volume are of particular interest, as CO diffusing capacity is sensitive to changes pulmonary capillary blood volume and NO diffusing capacity to those of the diffusion barrier. Both are likely to be affected by aging processes, thus a general aging of the lung should also have effects.

Remarkably, however, the differences in KCO and KNO between the two groups were small and not significantly different from zero indicating that the differences in transfer factors were primarily due to differences in volume, i.e. of lung-mechanical nature. KCO values were also similar when using the reference values by Garcia-Rio et al. [19] for KCO (84.4%pred in UED vs. 82.9%pred in LED subjects). Moreover, the 95%-confidence intervals for the differences in transfer factors and coefficients did not overlap with those of FEV₁%pred and FVC%pred as well as airway conductance. There were no significant differences in Hb values which might have influenced the values of the CO transfer factor despite the correction for Hb. The differences in PImax they were lower than those of FEV₁ and sGAW, which showed values in a range of 30%pred or more, but still beyond 10%pred and larger than those of transfer coefficients KCO and KNO. Overall, these observations indicated a marked difference between the lung-mechanical and gas uptake domains. Regarding the concept of a general “lung age” our observations suggest that a differentiated description of functional domains is more adequate.

The difference in 6MWD between the LED and UED group was between those of mechanical and gas exchange parameters. Dyspnoea and fatigue scores could not be scaled as percent predicted, therefore their differences were not directly comparable to the other parameters. Still, the fact that they differed between the two groups, in terms of pre and post values, indicated a greater 6MWD and at the same time lower dyspnoea and fatigue in subjects of the UED group.

FeNO was included as it might indicate eosinophilic airway inflammation if elevated, or oxidative stress if decreased, but no significant differences were found. There was a small difference regarding eCO despite the fact that we had excluded current smokers and subjects with values > 6 ppm. The source of this small difference might be unreported active or passive smoking, or endogenous production related to oxidative stress [20]. However, serum 8-OHdG, as an indicator of systemic oxidative stress, was similar in the two groups. The same was true for telomere length in peripheral blood leukocytes which is often considered as a marker of biological age and/or stress but there was a tendency (p = 0.058) towards decreased telomere length in the LED group.

One might argue that the results in terms of percent predicted values simply reflected different coefficients of age-dependence in the reference equations despite the fact that the mean age was similar in the two groups. To evaluate this we inserted the measured values into the respective reference equations and solved for the age that resulted in the observed values; for non-linear equations (e.g. GLI) linear approximations within the adequate range were used. This analysis was not meaningful for all parameters as it made sense only with an obvious and monotonous relationship to age to avoid absurd individual age estimates. Figure 1 shows median values and quartiles for FEV₁, FVC, FEF_25–75, FEF₇₅, ITGV/TLC, KCO and KNO. It illustrates the large differences for mechanical versus much smaller differences for gas uptake parameters, taking into account the coefficients of age-dependence via the prediction equations.

As one of the limitations of our study, we did not measure individual rates of ageing. Still, the cross-sectional analysis used by us allowed for the comparison of different functional domains. Naturally, it is not possible to decide whether the differences between the two groups existed from the beginning, i.e. from young age, or whether they developed over time [21], e.g. due to environmental factors and cigarette smoke exposure. Therefore, an interpretation of our data in terms of “aging” or “premature aging” is not straightforward, since even telomere length might also have been shorter from the beginning. This objection does, however, not compromise the aim of our study which was the analysis of the notion “lung age” that is commonly derived from spirometry alone. The sample size of n = 123 did not allow to adjust for a broad variety of potential confounders; we therefore present only pairwise comparisons. Adjustment for weight or sex did not markedly change the results. Furthermore, it was not possible to directly compare all parameters, either because no reference values were available, or because, e.g. for ITGV, pathological changes can occur in both directions and scales were different. Our study has the strength of a broad panel of high-quality assessments that allowed direct comparisons in the same subjects. This aspect seems particularly important in view of the marked differences between the functional domains.

Two groups of elderly, lung-healthy subjects were chosen from the lower and upper end of the distribution of FEV₁%predicted from a population-based sample. The differences of lung function parameters between groups depended on the functional domain. While those of FEV₁, FVC and (specific) airway conductance were large, those of KCO and KNO transfer coefficients were small and not significantly different from zero. Therefore, the differences in lung-mechanics associated with the selection of the two groups were not in parallel with those in gas uptake. Using the respective prediction equation, a “functional age” is often computed for FEV₁, especially for pedagogical purposes. When adopting this approach for other parameters, the differences between groups translated into corresponding differences in the “functional ages”. This again underlined that the notion of a unique “lung age” is ill-founded, at least when referring to functional indices, and a differentiated description should be preferred.