2024 Volume 71 Issue 12 Pages 1175-1181
Dipeptidyl peptidase 4 (DPP-4) inhibitors are new antidiabetic drugs. Their effects on the respiratory system remain unclear. This study aimed to determine the association between DDP-4 inhibitors and acute respiratory failure (ARF) among patients with type 2 diabetes mellitus (T2DM). A meta-analysis was performed by searching the PubMed, Embase, and CENTRAL databases up to July 3rd, 2024, to identify randomized controlled, double-blind, and placebo controlled-cardiovascular outcomes trials (CVOTs) that enrolled participants with T2DM. A total of 6,532 studies were initially retrieved; ultimately, 5 large CVOTs enrolling 47,714 adult T2DM patients were included in the meta-analysis. Overall, there were a nonsignificant increase in the risk of ARF in the DDP-4 inhibitor group compared with the placebo group (RR, 1.72; 95% CI, 0.59 to 4.97; p = 0.319). This is the first meta-analysis to evaluate the association between DDP-4 inhibitors and ARF among T2DM patients. In general, these findings suggest that DPP-4 inhibitors may slightly, but non-significantly, increase the risk of ARF in T2DM patients. As few studies are available and few ARF events occurred, further well-designed large-scale studies need to be performed.
Diabetes mellitus is a chronic metabolic disorder characterized by hyperglycemia that leads to damage to many organs due to micro- and macrovascular dysfunction [1]. The lung is an organ with an abundant alveolar-capillary network that may be affected by diabetic microvascular impairment. Cohort studies have shown that patients with diabetes are at increased risk of asthma, chronic obstructive pulmonary disease (COPD), pulmonary fibrosis, pneumonia, and acute respiratory distress syndrome [2, 3]. These lung diseases can develop into acute respiratory failure (ARF)—a devastating condition characterized by acute and progressive hypoxemia [4]—as an advanced stage or acute worsening state [5]. Moreover, cigarette smoke exposure may further aggravate this process [6].
Dipeptidyl peptidase 4 (DDP-4) is a serine peptidase that cleaves a wide range of substrates, including growth factors, chemokines, and peptides. In particular, cleaving glucagon-like peptide-1 (GLP-1) leads to decreased insulin secretion [7]. DPP-4 inhibitors are new oral hypoglycemic agents for the treatment of type 2 diabetes mellitus (T2DM) through preventing DPP-4 cleaving GLP-1. However, the role of DPP-4 inhibitors in lung diseases is unclear. In particular, there is no evidence regarding the direct relationship between DPP-4 inhibitors and ARF. A retrospective cohort study suggested that DPP-4 inhibitors significantly decreased the risk of asthma development in patients with T2DM [8]. A meta-analysis [9] and a retrospective, observational study [10] showed that DDP-4 inhibitors may decrease the mortality rate of patients with COVID-19 and T2DM. Nevertheless, a summary of the product characteristics of sitagliptin has indicated that interstitial lung disease is an adverse reaction [11]. And a case-control study indicated that users of DPP-4 inhibitors reported an increase in infections, particularly upper respiratory tract infections [12]. Other cohort studies revealed that DPP-4 inhibitors were not clearly associated with a decreased or increased risk of COPD exacerbations [13] or pneumonia [14].
Given the abovementioned controversial results, a meta-analysis of cardiovascular outcomes trials (CVOTs) was conducted to determine the association between DDP-4 inhibitors and the risk of ARF among patients with T2DM.
This meta-analysis was performed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines (PRISMA) [15]. The PubMed, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) electronic databases were searched up to July 3rd, 2024, to identify randomized controlled, double-blind, placebo-controlled CVOTs.
Two reviewers independently screened all the studies, and any disagreements were resolved by discussion with a third reviewer. Two reviewers independently extracted data from the included studies, including author names, year of publication, ClinicalTrials.gov ID, number of patients, patient characteristics, intervention, and median follow-up (years). Studies were retrieved and managed using EndNote (Version X9; Clarivate, available at www.endnote.com).
The inclusion criteria were as follows: 1) CVOTs involving patients who had been diagnosed with T2DM; 2) DDP-4 inhibitors were compared with placebo; and 3) studies reporting adverse events of ARF, defined by one MedDRA preferred term (“acute respiratory failure”). The data were retrieved from the “Serious Adverse Events” section on Clinicaltrials.gov. The risk of bias of the included randomized clinical trials was evaluated using the revised Cochrane risk of bias, version 2 (RoB 2) tool [16]. The pooled risk ratio (RR) and 95% CI were calculated using a random effects model. Heterogeneity between studies was assessed using the I2 statistic. Subgroup analyses were performed according to multiple variables, including age, sex, proportion of current smokers, race, estimated glomerular filtration rate (eGFR), proportion of individuals with hypertension, proportion of individuals with prior heart failure, baseline HbA1c, baseline BMI, duration of diabetes, and median follow-up. The publication bias was evaluated by funnel plots as well as Egger’s test. A p value <0.05 was considered to indicate statistical significance. The meta-analysis was conducted, and forest plots were created using STATA software (Version 15; Stata Corp., College Station, TX).
In the initial search, 6,532 potential reports were identified from the databases as follows: PubMed (n = 2,128), Embase (n = 3,373), and CENTRAL (n = 1,031). After eliminating duplicate records (n = 1,932) and screening the titles and abstracts, 246 records remained for full-text analysis. A total of 224 records did not meet the eligibility criteria and 17 records cannot be retrieved. Ultimately, 5 CVOTs fulfilled the inclusion criteria and were included in this meta-analysis [17-21] (Fig. 1). Table 1 summarizes the included trials with a description of the populations, intervention, median follow-up and risk of bias. These trials were conducted at multiple centers, and a total of 47,714 adult patients who were diagnosed with T2DM and cardiovascular disease or who were at high risk for cardiovascular disease were included. The mean age of the included patients was 64.2 years, the mean percentage of females was 32.3%, the mean proportion of current cigarette smokers was 12.6%, and the mean baseline HbA1c% and baseline body mass index were 7.8% and 30.5 kg/m2, respectively. Patients were randomly allocated to receive DDP-4 inhibitor treatment (23,899 patients) or a matching placebo (23,815 patients). The median duration of follow-up ranged from 1.8 years to 3 years. The risk of bias for each individual trial was judged as low risk.
| Study | NCT | Name | No. of patients | Populations | Intervention | Age (years) | Female sex (%) | Current cigarette smoker (%) | Baseline HbA1c (%) | Baseline BMI (kg/m2) | Duration of diabetes (years) | Median follow-up (years) | Risk of bias* |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Scirica 2013 [17] | NCT01107886 | SAVOR-TIMI 53 | 16,492 | T2DM patients with a history of or were at risk for CV events | Saxagliptin | 65.1 | 33.1 | 13.5 | 8 | 31.2 | 10.3 | 2.1 | Low |
| White 2013 [18] | NCT00968708 | EXAMINE | 5,380 | T2DM patients with either an acute myocardial infarction or unstable angina requiring hospitalization within the previous 15 to 90 days | Alogliptin | 61 | 32.1 | 13.6 | 8 | 28.7 | 7.2 | 1.5 | Low |
| Green 2015 [19] | NCT00790205 | TECOS | 14,671 | T2DM patients with established CV disease | Sitagliptin | 65.5 | 29.3 | 11.4 | 7.2 | 30.2 | 11.6 | 3 | Low |
| Gantz 2017 [20] | NCT01703208 | OMNEON | 4,192 | T2DM patients with established CV disease | Omarigliptin | 63.6 | 29.7 | 14.4 | 8 | 31.3 | 12 | 1.8 | Low |
| Rosenstock 2019 [21] | NCT01897532 | CARMELINA | 6,979 | T2DM patients with high CV risk | Linagliptin | 65.9 | 37.1 | 10.2 | 7.9 | 31.3 | 14.8 | 2.2 | Low |
T2DM, type 2 diabetes mellitus; CV, cardiovascular; BMI, body mass index.
*Risk of bias of each trial was judged as low risk, some concerns, or high risk according to the revised Cochrane risk of bias, version 2 (RoB 2) tool.
The results of the individual studies and combined analysis are displayed in Fig. 2. In the SAVOR-TIMI 53 study, ARF was observed in 0.14% of patients in the saxagliptin group and 0.04% of patients in the placebo group, with a RR of 3.97 (95% CI, 1.12 to 14.05). A RR of 3.47 (95% CI, 0.72 to 16.70) was found in the EXAMINE trial when comparing the incidence of ARF between the alogliptin (0.26%) and placebo (0.07%) groups. In the OMNEON trial, the omarigliptin group also demonstrated a nonsignificantly higher risk of ARF than with the placebo group (RR, 6.02; 95% CI, 0.73 to 49.98). However, in the TECOS study, there was a nonsignificant decrease in the risk of ARF between the sitagliptin (0.01%) and placebo (0.07%) arms, resulting in a RR of 0.20 (95% CI, 0.02 to 1.71). Similarly, the linagliptin group demonstrated a small but not significantly decreased risk of ARF compared with the placebo group (RR, 0.82; 95% CI, 0.34 to 1.97) in the CARMELINA trial. According to the pooled analysis of all 5 studies, ARF was observed in 0.15% of patients in the DDP-4 inhibitor arm and 0.09% of patients in the placebo arm. There was a small but nonsignificant association between DDP-4 inhibitor use and the risk of ARF (RR, 1.72; 95% CI, 0.59 to 4.97; p = 0.319). A subgroup analysis stratified by the proportion of current cigarette smokers revealed a RR of 4.09 (95% CI, 1.68 to 10.00; p = 0.002) when pooling data from studies with higher proportions of cigarette smokers and comparing the incidence of ARF between the DPP-4 inhibitors and placebo groups. Conversely, a RR of 0.58 (95% CI, 0.18 to 1.89, p = 0.364) was found when pooling data from studies with lower proportions of cigarette smokers (Supplementary Fig. 1).
The RoB 2 tool indicated that all 5 trials had a low risk of bias. There was statistical heterogeneity across the trials (I2 = 61.0%). Results of the extensive subgroup analyses revealed that the disparity in smoking prevalence among studies might be one of the sources of the heterogeneity (Supplementary Fig. 1). There was no evidence of publication bias in the meta-analysis based on the funnel plot (Supplementary Fig. 2) or Egger’s test (p > 0.05).
To the best of our knowledge, this is the first meta-analysis to evaluate the risk of ARF associated with DDP-4 inhibitors involving patients with T2DM. Five large CVOTs with a total of 47,714 adult T2DM patients were included in this study. Overall, our study demonstrated that there was a small but not significant increase in the incidence of ARF associated with DPP-4 inhibitor use compared with that associated with placebo.
Consistently, adverse event data from the DrugCentral2023 database (https://drugcentral.org/) revealed that DPP-4 inhibitors were associated with a risk of interstitial lung disease. Similarly, data from the FDA adverse event reporting system suggest increased reporting of pneumonia for DPP-4 inhibitor users compared with other noninsulin antidiabetic drug users [22]. A retrospective cohort study showed that compared with sodium glucose cotransporter 2 inhibitor use, DPP-4 inhibitors were associated with a significantly higher risk of pneumonia and pneumonia mortality [23]. Nonetheless, a meta-analysis of CVOTs revealed no effect of DPP-4 inhibitors on the risk of respiratory infection [24] or asthma incidence [25]. Cohort studies revealed that DPP-4 inhibitors were not clearly associated with the risk of COPD exacerbation [13] or pneumonia [14]. However, these studies did not directly clarify the relationship between DPP-4 inhibitors and ARF. The results of this study showed that the RR of ARF between the DPP-4 inhibitor treatment group and the placebo group was 1.72, which indicated a small correlation between DPP-4 inhibitor treatment and ARF; however, this difference was not statistically significant.
The mechanisms underlying the increased risk of ARF associated with DPP-4 inhibitor treatment are unclear. DPP-4 expressed in the respiratory tract might play a deleterious role in the lung since DPP-4 upregulation has been found in the lungs of smokers, COPD patients [26], and asthma patients [27]. DPP-4 exacerbates endothelial inflammation and enhances endothelial cell permeability and participates in the pathogenesis of acute lung injury/acute respiratory distress syndrome [28]. Moreover, a study in mice revealed that prolonged DPP-4 activity inhibition increased the levels of DPP-4 protein in the lung and increased the plasma levels of inflammatory markers [29]. Considering that DPP-4 might play a deleterious role in the lung, one potential mechanism might be that systemic inhibition of DPP-4 activity results in compensatory increases in DPP-4 protein expression and limited promotion of proinflammatory states in the lung.
Furthermore, it has been reported that DPP-4 expression in lungs of smokers is significantly higher compared to never-smokers [26]. And many studies have underscored a strong association between cigarette smoking and an elevated risk of acute respiratory distress syndrome, which is an important and common cause of ARF [30-35]. However, despite the subgroup analysis suggested that differing proportions of current smokers might be one of the sources of the observed heterogeneity, it was challenging to further compare the incidence of ARF between smokers and never-smokers within each study due to the lack of access to individual patient data. Therefore, the actual impact of cigarette smoking on the risk of ARF associated with DPP-4 inhibitors remains uncertain and warrants further investigation.
Furthermore, the heterogeneity observed in this study may also originate from the variations in the DPP-4 inhibitors employed. While DPP-4 inhibitors have similar mechanisms of action and efficacy, they are diverse in their chemical and/or pharmacokinetic profiles, which may be associated with different adverse event profiles. First, DPP-4 inhibitors have different bioavailability ranging from ~ 30% with linagliptin to 87% with sitagliptin. In terms of metabolism, DPP-4 inhibitors generally have low potential for drug interactions, except for saxagliptin, which is metabolized mainly by CYP3A4/5, suggesting that inhibitors or inducers of CYP3A4/5 can alter its metabolism. In terms of clearance, DPP-4 inhibitors are predominantly eliminated by renal excretion, with the exception of linagliptin [36]. In particular, the selectivity of DPP-4 inhibitors is speculated to potentially correlate with adverse events. Saxagliptin has demonstrated an off-target effect with significant and concentration-dependent inhibitory effects on both DPP-8 and DPP-9 enzymes [37], which share a 26% sequence similar to that of DPP-4, and it was reported that inhibiting DPP-8/-9 produced alopecia, thrombocytopenia, reticulocytopenia, an enlarged spleen, multiorgan histopathological changes, and mortality in rats [38]. However, alogliptin, sitagliptin and linagliptin are highly selective DPP-4 inhibitors with little inhibitory activity against other members of the dipeptidyl peptidase family [36]. Notably, the ARF incidence was consistent with the selectivity of the inhibitors. In the SAVOR-TIMI 53 trial, the saxagliptin treatment group had a significantly greater incidence of ARF than did the placebo group. In the other trials, the risk of ARF was not significantly greater in the treatment group than in the placebo group. However, whether the off-target effects of DPP-4 inhibitors on DPP-8 and DPP-9 activity are related to the increased risk of ARF is unknown, and these speculations need to be further investigated in vivo and in vitro to elucidate the underlying pathophysiological mechanisms involved.
There are several strengths in this study. First, these included data are all strong evidence from 5 large, multicenter, randomized, placebo-controlled trials that balanced background therapy and other confounders. Second, the 5 included trials had a median duration of follow-up ranging from 1.8 years to 3 years with exposure to DDP-4 inhibitors that was long enough to trigger ARF. However, some potential limitations should be mentioned. First, the events of ARF were not predefined outcomes in the included CVOTs, so the actual number of ARF events could be underestimated. Second, the incidence of ARF was rare; thus, a wide range of CIs for the RR was reported, and biases in the results could not be completely avoided. Furthermore, the disparity of the proportion of current cigarette smokers between the two subgroups was subtle. Therefore, whether the proportion of current cigarette smokers is the origin of heterogeneity is not conclusive.
In summary, our findings revealed that DPP-4 inhibitor treatment was associated with an increased but not significant risk of ARF. The results of this study may offer implications for the clinical utilization of DPP-4 inhibitors for T2DM patients. It is necessary to focus on and verify the relationship between DDP-4 inhibitors and ARF through further well-designed large-scale prospective studies.
We would like to thank Huilin Tang for his critical comments and assistance in language polishing.
This work was supported by a grant from National Natural Science Foundation of China (No.82104255).
The authors have no conflicts of interest to declare.
