Screening of liver disease in alpha-1 antitrypsin deficiency (AATD) is usually carried out with liver enzymes, with low sensitivity. We conducted a multicenter cross-sectional study aiming to describe the utility of transient elastography for the identification of liver disease in patients with AATD. A total of 148 AATD patients were included. Among these, 54.7% were Pi*ZZ and 45.3% were heterozygous for the Z allele. Between 4.9% and 16.5% of patients had abnormal liver enzymes, without differences among genotypes. Liver stiffness measurement (LSM) was significantly higher in Pi*ZZ individuals than in heterozygous Z (5.6 vs. 4.6 kPa; p = 0.001). In total, in 8 (5%) individuals LSM was >7.5 kPa, considered significant liver fibrosis, and ≥10 kPa in 3 (1.9%) all being Pi*ZZ. Elevated liver enzymes were more frequently observed in patients with LSM > 7.5 kPa, but in 5 out of 8 of these patients all liver enzymes were within normal range. In patients with AATD, the presence of abnormal liver enzymes is frequent; however, most of these patients do not present significant liver fibrosis. Transient elastography can help to identify patients with liver fibrosis even with normal liver enzymes and should be performed in all Z-allele carriers to screen for liver disease.
Keywords: alpha1-antitrypsin deficiency; liver disease; transient elastography
Alpha1-antitrypsin deficiency (AATD) is caused by a specific mutation of the SERPINA 1 gene which results in abnormal production and low circulating levels of alpha1-antitrypsin (AAT). It is one of the most common genetic diseases in adulthood and is associated with an increased risk of developing pulmonary emphysema and liver disease [[
AAT is a protein synthesized and secreted mainly by hepatocytes, the main function of which is to protect lung tissue from damage caused by proteolytic enzymes such as neutrophil elastase [[
The Z variant presents an alteration in its tertiary structure that facilitates misfolding of the protein and gives rise to the spontaneous formation of polymers, leading to the accumulation of the protein in the endoplasmic reticulum of the hepatocytes [[
Currently there is no non-invasive gold standard technique for the screening and early diagnosis of liver disease in patients with AATD [[
Recently, there has been increasing interest in the use of elastographic methods, such as transient elastography, for screening liver disease in AATD patients [[
This was a multicenter cross-sectional study including patients older than 18 years with mild, moderate, and severe AATD (Pi*MS, SS, MZ, SZ, ZZ, and rare variants) consecutively recruited from the outpatient Pneumology Clinics of three AATD reference centers in Spain (Vall d'Hebron University Hospital, Barcelona, University Hospital Complex of Vigo, and Hospital Clínico San Carlos, Madrid) from 1 April 2017 to 1 January 2020. As part of the assessment of patients with AATD, all of them were offered blood analysis, full lung function tests, and transient elastography, and the only exclusion criterion was to refuse to sign informed consent. The study was approved by the Vall d'He- bron Hospital Ethics Committee (Barcelona, Spain), number PR(AG)335/2016, and all patients provided written informed consent.
During the first visit, a complete physical examination was performed in all patients with special interest in signs of chronic liver disease such as splenomegaly, jaundice, or palmar erythema. Sociodemographic and clinical characteristics were collected and other parameters such as body mass index (BMI), lung function tests (forced expiratory volume in the first second (FEV1), FEV1/forced ventilatory capacity (FVC), and carbon monoxide transfer coefficient (KCO)), comorbidities, treatments, and AAT augmentation therapy were reported. Diagnosis of chronic obstructive pulmonary disease (COPD) was established when the post-bronchodilator FEV1/FVC ratio was below 0.7.
Blood samples were obtained for determination of liver function tests: Aspartate aminotransferase (AST), alanine aminotransferase (ALT), gamma-glutamyl transferase (GGT), alkaline phosphatase (ALP), international normalized ratio (INR), platelet count, and albumin. In addition, the Fibrosis-4 (FIB-4) score was calculated as age (years) × AST [IU/L]/(platelet count [109/L] × √ALT [IU/L]) and AST-to-platelet ratio index (APRI) as (AST [IU/L]/40 IU/L)/platelet count [109/L] × 100. Patients were classified according to the previously established FIB-4 cut-offs of <1.45 with a high negative predictive value for ruling out advanced fibrosis and >3.25 with a high specificity and a 65% positive predictive value for ruling in advanced fibrosis [[
The Enhanced Liver Fibrosis (ELF) test (Siemens Healthcare Diagnostics, Vienna, Austria) was available as a biomarker of liver fibrosis in one of the centers. The ELF test is a panel of markers that consists of 3 components: Type III procollagen peptide, hyaluronic acid, and tissue inhibitor of metalloproteinase-1. We explored the manufacturer- recommended 9.8 cut-off to rule in advanced fibrosis [[
Liver stiffness measurements (LSM) were performed in a fasting state using a Fibroscan 502 Touch (Echosens, Paris, France) using the M or XL probe as per device indication. Quality criteria used in all centers were at least 10 valid measurements and an interquartile-to-median ratio ≤ 30%. The LSM technique was carried out in accordance with the European Association for Study of the Liver (EASL) clinical guidelines [[
Results were expressed in kilopascals (kPa). Normal liver stiffness values are around 5 kPa. Transient elastography has good re-producibility and has good diagnostic performance for estimating liver fibrosis. However, the accuracy is not as good for detecting significant fibrosis compared to advanced fibrosis or cirrhosis [[
The presence of steatosis was assessed by the controlled attenuation parameter (CAP) and results were expressed in decibel per meter (dB/m). The cut-off >268 dB/m was used as an indicator of moderate steatosis, and for severe steatosis the cut-off was >280 dB/m [[
Qualitative variables were described with absolute frequencies and percentages. The description of quantitative variables was performed using the mean, standard deviation (SD) or median, and interquartile range (IQR). The Kolmogorov–Smirnov test was used to assess the normality of distributions.
Patient characteristics were compared according to genotypes and other clinical conditions. In the case of quantitative variables, the Student's t-test for normally distributed variables or the Mann–Whitney U-test if normality was not assumed was used, while ANOVA tests were performed in the case of variables with more than 2 categories. The Chi-squared test (Fisher test for frequencies < 5) was used for the comparison of categorical variables. A linear relationship between quantitative variables, in particular between surrogates of liver disease (LSM, CAP and FIB-4) and spirometric markers of airflow obstruction (FEV1(%) and FEV1/FVC), were analyzed using Spearman tests. For all the tests, p-values < 0.05 were considered statistically significant. The statistical package R Studio (V2.5.1) was used for the analyses.
A total of 148 AATD patients were included from January 2017 to December 2019. Among these, 81 (54.7%) were homozygous Pi*ZZ and 67 (45.3%) were heterozygous for the Z allele (29 Pi*SZ, 35 Pi*MZ, 1 Pi*FZ, 1 Pi*PlowellZ, 1 Pi*MmaltonZ).
The mean age was 52.5 and 57 years for heterozygous and Pi*ZZ, respectively, and 50% of the patients were male. Liver disease in infancy was reported as the cause of the diagnosis of AATD in 19.4% and 11.1% of heterozygous and homozygous patients, although there were no patients with an active diagnosis of liver disease at the time of the study. COPD was diagnosed in 22.7% of heterozygous subjects and up to 70% for Pi*ZZ patients. Consequently, the mean FEV1 (%) was significantly lower in Pi*ZZ compared with heterozygous (69% (SD: 30.5%) versus 92.9% (SD: 27.6%); p < 0.001). The baseline characteristics of the global population and the two genotype groups are shown in Table 1.
Thirty-two patients (21.6%) had abnormal liver enzymes. The distribution of values showed significant differences only in AST values, which were significantly higher in Pi*ZZ patients (29.2 UI/L (SD: 15.4) vs. 25.0 UI/L (SD: 8.0; p = 0.029). The most frequent pattern was an elevation in GGT (14.9% of patients). Pi*ZZ patients had a higher FIB-4 score compared to heterozygous Z (1.6 (SD: 0.8) vs. 1.2 (SD:0.5); p < 0.001). Only 5 patients had FIB-4 > 3.25 and all were Pi*ZZ. The APRI score was higher in Pi*ZZ patients than in heterozygous Z (0.35 (SD: 0.18) vs. 0.27 (SD: 0.09); p = 0.007), but most of the patients had APRI values < 0.5, excluding advanced fibrosis or cirrhosis, and only one Pi*ZZ patient had an APRI score > 1.0. The ELF score was obtained in 52 patients (27 Pi*ZZ and 25 Pi*Z patients). Pi*ZZ had significantly higher values compared to Pi*Z phenotypes (8.6 (SD: 0.8) vs. 8 (SD: 0.6); p = 0.007). Only 1 Pi*ZZ patient showed values above the cut-off of 9.8 (Table 2).
The mean LSM was significantly higher in Pi*ZZ individuals than in heterozygous Z (5.6 (SD: 2.5) kPa vs. 4.6 (SD:1.2) kPa, respectively; p = 0.007). In total, LSM was >7.5 kPa in 8 (5%) individuals and ≥10 kPa in 3 (1.9%), all being Pi*ZZ (Figure 1). By lowering the cut-off of LSM to >7.1 kPa as suggested in other studies [[
Using the LSM > 8.45 kPa cut-off of the study by Clark et al. [[
Almost one-third of the patients had severe steatosis according to CAP values > 280 dB/m, with no significant differences between homozygous and heterozygous patients. (Table 2).
Pi*ZZ individuals with LSM > 7.5 kPa were older and had a higher BMI. Two-thirds consumed alcohol, and all had COPD (versus 67% in patients with LSM ≤ 7.5 kPa; p = 0.097).
Elevated liver enzymes were more frequently observed in patients with LSM > 7.5 kPa. Twenty-five percent of patients with LSM > 7.5 kPa had elevated AST values compared to 2.7% in patients with LSM ≤ 7.5 kPa (p = 0.048), and 37.5% of patients with LSM > 7.5 kPa had elevated GGT compared to 14.1% of patients with LSM ≤ 7.5 kPa (p = 0.120) (Table 3, Figure 2). Conversely, 11/61 patients (18%) had at least one elevated liver enzyme but with normal LSM values (LSM < 6 kPa). Correlations between LSM and liver enzymes were only significant, albeit weakly, between LSM and AST (0.311 (p < 0.001)), and LSM and GGT (0.389 (p < 0.001)).
Among the 8 patients with LSM > 7.5, 3 had GGT above the normal limit and 1 also had a FIB-4 score > 3.25 (Figure 3). The FIB-4 score (2.2 (SD: 0.7) versus 1.5 (SD: 0.8); p = 0.032), as well as CAP measurement (317.9 (SD: 48) dB/m vs. 249.6 (SD: 56.5) dB/m; p = 0.004), were also higher in Pi*ZZ patients with LSM > 7.5 kPa (Table 3). Severe steatosis, with CAP > 280 dB/m, was present in 6 patients (75%) with LSM > 7.5 kPa compared to 20 patients (27.4%) with LSM < 7.5 kPa (p = 0.041).
The APRI was higher in Pi*ZZ patients with LSM > 7.5 kPa than in those with LSM ≤ 7.5 kPa (0.56 vs. 0.33, p < 0.001). The APRI had a significant correlation with LSM (r = 0.353, p = 0.030).
Fifty-seven Pi*ZZ patients (70.4%) had COPD. Pi*ZZ patients with COPD were older and more frequently had a history of smoking compared with non-COPD individuals. As expected, they had worse lung function with a lower FEV1 (1.6 (SD: 0.8) L vs. 3.5 (SD: 1) L; p < 0.001) and KCO (%) (43.7% (SD: 30.8%) vs. 68% (SD: 30.4%); p = 0.003).
Regarding the liver study, no differences were observed in transaminase levels, but the FIB-4 score was higher in COPD patients (1.7 (SD: 0.8) vs. 1.2 (SD: 0.8); p = 0.046). More individuals in the COPD group had a LSM > 7.5 kPa (14% vs. 0%; p = 0.097) and they also had higher CAP values (265.9 (SD: 58.3) dB/m vs. 233.5 (SD: 55.8) dB/m; p = 0.023) (Table 3). Significant, albeit weak, correlations were found between FIB-4 and FEV1 (mL) (r = −0.350, p = 0.002), and CAP and FEV1 (mL) and FEV1(%) (r = −0.391, p < 0.001 and r = −0.306, p = 0.006, respectively). No significant correlations were found between LSM or ELF and measures of airflow obstruction.
In our study population, we found that 10% of Pi*ZZ individuals had transient elastography results suggestive of liver fibrosis, but none of the heterozygous individuals reached the suggested threshold. Although individuals with higher LSM had higher transaminase levels and FIB-4 scores, normal levels of these biomarkers did not reliably rule out liver disease, since some of the patients with normal values had high LSM values. All patients with high LSM also had COPD.
Transient elastography is a non-invasive tool that has proven to be useful in the diagnosis of liver fibrosis of different etiologies. More recently, its utility has also been explored in AATD-related liver disease with promising results [[
Ten percent of Pi*ZZ patients in our cohort had LSM > 7.5 kPa, similar to the prevalence of liver fibrosis reported in initial studies in AATD patients, which varied from 10–15% in clinical studies [[
In our cohort, Pi*MZ individuals had lower values of LSM compared to Pi*ZZ individuals. The mean LSM was 4.7 kPa for the 34 Pi*MZ patients included. None of these patients had values above 7.5, and only one had LSM = 7.5 kPa. In this patient, other co-factors for liver disease such as obesity, alcohol consumption, or metabolic syndrome were not found. The incidence of liver disease could be higher in heterozygous Z than in the general population, although some authors have hypothesized that while the Pi*MZ genotype acts as a disease modifier, it is not sufficient per se to trigger clinically relevant liver impairment [[
Liver enzymes have often been used to screen liver disease in AATD in clinical practice [[
The relationship between lung and liver disease in individuals with AATD is controversial. The first series of patients with the deficiency suggested that lung and liver disease rarely coexisted in AATD, and liver disease was more frequently reported in AATD never smokers compared to smokers [[
Our study had some limitations. First, the identification of liver fibrosis was only made by transient elastography as we did not perform liver biopsies. However, as there are no specific treatments for AATD liver disease to date, the performance of an invasive diagnostic technique in otherwise asymptomatic patients may not be justified. Second, this was a cross-sectional study, and data on the evolution of LSM over time were not available. Third, the design of our study did not allow us to investigate a causal relationship between AATD and liver alterations. Our sample size was not big enough for a multivariate analysis adjusted for known confounders of increased liver fibrosis. However, the study had some strengths: We recruited individuals from three reference centers, and, considering that AATD is a rare disease, we reported information from a large series of patients with homozygous and heterozygous AATD.
In conclusion, the results of this study support the assessment of liver disease in all AATD Pi*ZZ individuals and heterozygous Pi*Z individuals with additional liver risk factors. Transient elastography has been shown to be a valuable tool to screen for AATD liver disease, and collaboration between hepatologists and pneumologists is crucial for providing the best care to AATD patients. Due to the poor correlation between liver enzymes and other serum biomarkers and the underlying liver disease, all Z-allele carriers, even those with normal serum biomarker values, should be screened with transient elastography. Since AATD is a rare disease, international collaboration in large registries is needed to investigate the best screening strategy for lung and liver disease [[
Graph: Figure 1 Comparison of mean LSM values by phenotype.
Graph: Figure 2 All individuals from the cohort with liver enzymes above the highest level of normal based on LSM values. UPN: Upper limit of normal for GGT: >38 IU/L in females and >55 IU/L in males.
Graph: Figure 3 Relation between elevated GGT, FIB4, and LSM in Pi*ZZ patients. GGT: Gamma-glutamyl transferase; FIB-4: Fibrosis 4; LSM: Liver stiffness measurement; UPL: Upper limit of normal (according to sex-specific cut-offs: for GGT: >38 IU/L in females and >55 IU/L in males).
Table 1 Baseline characteristics of the patients included by AAT genotype.
ZZ ( Heterozygous Z Age 57.0 (14.4) 52.5 (14.5) 0.051 1 Sex, men 41 (50.6%) 34 (50.7%) 0.985 2 BMI 25.1 (3.9) 24.0 (7.0) 0.398 1 Smoking exposure: 0.010 2 Active 43 (53.1%) 22 (32.8%) Former smoker 7 (8.6%) 16 (23.9%) Never smoker 31 (38.3%) 29 (43.3%) Alcohol consumption 19 (23.5%) 19 (28.4%) 0.991 2 Diabetes mellitus 0 (0%) 2 (3.0%) 0.203 2 Hypertension 14 (17.5%) 16 (23.9%) 0.453 2 AAT levels, mg/dL 33.3 (61.9) 71.9 (20.8) <0.001 1 Reason for diagnosis: 0.002 2 Liver disease 9 (11.1%) 13 (19.4%) Lung disease 52 (64.2%) 23 (34.3%) Family study 17 (21.0%) 28 (41.8%) Other 3 (3.7%) 3 (4.5%) COPD 57 (70.4%) 15 (22.7%) <0.001 2 Asthma 5 (7.8%) 14 (21.2%) 0.056 2 Neonatal jaundice 6 (7.4%) 3 (4.5%) 0.513 2 FVC, L 3.6 (1.5) 3.9 (1.1) 0.197 1 FVC, % 90.0 (28.5) 99.8 (19.8) 0.033 1 FEV1, L 2.1 (1.2) 3.0 (1.2) <0.001 1 FEV1, % 69.0 (30.5) 92.9 (27.6) <0.001 1 FEV1/FVC 0.6 (0.2) 0.7 (0.2) 0.001 1 KCO, % 51.0 (32.5) 58.9 (36.7) 0.231 1
Table 2 Results of blood analysis and transient elastography in patients with different AAT genotypes.
ZZ ( Heterozygous Z Laboratory findings Platelet count, ×109/L 222 (59) 239 (61) 0.074 1 INR 1.0 (0.2) 1.0 (0.1) 0.067 1 Bilirubin, mg/dL 0.8 (0.5) 0.7 (0.3) 0.158 AST, IU/L 29.2 (15.4) 25.0 (8.0) 0.029 1 AST > ULN 4 (4.9%) 4 (6%) 0.869 2 ALT, IU/L 26.6 (22.6) 26.1 (13.4) 0.967 1 ALT > ULN 6 (7.4%) 5 (7.5%) 0.952 2 ALP, IU/L 78.2 (29.6) 81.8 (21) 0.412 1 ALP > ULN 6 (7.4%) 2 (3%) 0.294 2 GGT, IU/L 36.2 (33.9) 31.1 (29.4) 0.336 1 GGT > ULN 13 (16.5%) 9 (13.6%) 0.637 2 Albumin, g/dL 4.3 (0.6) 4.4 (0.3) 0.044 1 Cholesterol, mg/dL 207 (35) 198 (36) 0.161 FIB-4 1.6 (0.8) 1.2 (0.5) <0.001 FIB-4 < 1.45 38 (47.5%) 51 (78.5%) <0.001 2 FIB-4 > 3.25 5 (6.2%) 0 0.065 2 APRI 0.35 (0.18) 0.27 (0.09) <0.001 1 APRI < 0.5 67 (83) 64 (91) 0.023 2 APRI > 1.0 1 (1.2) 0 0.956 ELF, n = 60 8.6 (0.8) 8 (0.6) 0.007 1 Transient elastography LSM 5.6 (2.4) 4.6 (1.2) 0.001 1 LSM > 7.5 kPa 8 (9.9%) 0 0.040 2 LSM ≥ 10 kPa 3 (3.7%) 0 CAP 256 (59) 253 (50) 0.252 1 CAP 268–280 dB/m 7 (8.6%) 4 (6%) 0.807 2 CAP > 280 dB/m 26 (32.1%) 21 (31.3%)
Table 3 Comparison between Pi*ZZ individuals based on liver stiffness (LSM) and diagnosis of chronic obstructive pulmonary disease (COPD).
LSM ≤ 7.5 LSM > 7.5 No COPD COPD Age 56.2 (14.5) 64.9 (11.4) 0.076 46.2 (14.5) 61.6 (11.7) <0.001 1 Sex, men 37 (50.7%) 4 (50%) 1.00 11 (45.8%) 30 (52.6%) 0.752 2 BMI 24.6 (3.4) 29.0 (5.3) 0.056 24.2 (3.7) 25.4 (3.9) 0.186 1 Smoking exposure: 0.527 <0.001 2 Active 37 (50.7%) 6 (75%) 7 (29.2%) 36 (63.2%) Former smoker 7 (9.6%) 0 (0%) 0 (0%) 7 (12.3%) Never smoker 29 (39.7%) 2 (25%) 17 (70.8%) 14 (24.6%) Alcohol consumption 16 (24.2%) 3 (60%) 0.115 5 (25%) 14 (27.2) 1.000 2 Hypertension 10 (13.9%) 4 (50%) 0.028 1 (4.2%) 13 (23.2%) 0.054 2 COPD 49 (67.1%) 8 (100%) 0.097 0 57 (100%) 0.001 2 Neonatal jaundice 6 (8.2%) 0 (0%) 1.000 4 (16.7%) 2 (3.5%) 0.060 2 FEV1, % 70.4 (30.7) 56.4 (27.3) 0.205 99.6 (13.1) 56.2 (26.3) <0.001 1 Laboratory findings: Platelet count, ×109/L 224 (60) 202 (49) 0.267 210 (48) 226 (62) 0.214 1 INR 1.0 (0.2) 1.1 (0.1) 0.378 1.0 (0.1) 1.1 (0.2) 0.040 1 Bilirubin, mg/dL 0.8 (0.5) 0.6 (0.2) 0.262 1.0 (0.9) 0.7 (0.2) 0.143 1 AST, UI/L 27.2 (10.1) 47.6 (34.7) 0.141 27.2 (10.6) 30.0 (16.9) 0.375 1 AST > ULN * 2 (2.7%) 2 (25%) 0.048 1 (4.2%) 3 (5.3%) 0.675 2 ALT, UI/L 24.2 (14.2) 48.8 (55.8) 0.254 25.5 (14.4) 27.1 (25.3) 0.719 1 ALT > ULN * 4 (5.5%) 2 (25.0%) 0.108 3 (12.5%) 3 (5.3%) 0.226 2 ALP, UI/L 78.5 (30.9) 75.9 (14.8) 0.816 70.3 (31) 81.4 (28.7) 0.130 1 ALP > ULN * 6 (8.5%) 0 (0%) 1.000 2 (8.3%) 4 (7.0%) 1.000 2 GGT, UI/L 31.8 (19.3) 75.6 (84.1) <0.001 33.2 (22.2) 37.2 (37.7) 0.685 1 GGT > ULN * 10 (14.1%) 3 (37.5%) 0.120 5 (20.8%) 8 (14%) 0.589 2 Albumin, g/dL 4.3 (0.6) 4.4 (0.3) 0.615 4.5 (0.3) 4.2 (0.6) 0.004 1 Cholesterol, mg/dL 206 (35) 208 (39) 0.901 205 (39) 207 (34) 0.824 1 FIB-4 1.5 (0.8) 2.2 (0.7) 0.032 1.3 (0.8) 1.7 (0.8) 0.046 1 FIB-4 < 1.45: 37 (50.7%) 1 (12.5%) 0.059 15 (62.5%) 23 (40.4%) 0.077 2 FIB-4 > 3.25: 4 (5.5%) 1 (12.5%) 0.418 1 (4.2%) 4 (7%) 1.000 2 APRI 0.33 (0.1) 0.56 (0.3) <0.001 0.35 (0.17) 0.35 (0.19) 0.992 1 Transient elastography LSM 5.0 (1.1) 10.8 (4.6) 0.009 5.3 (1.1) 5.7 (2.8) 0.361 1 CAP 249 (56) 318 (48) 0.004 233 (56) 266 (58) 0.023 1 LSM > 7.5 kPa: 0 8 (100%) NA 0 8 (14.0%) 0.097 2
Conceptualization, M.P., A.N., C.E., M.M., and M.B.; methodology, M.P., A.N., and C.E.; formal analysis, C.E.; investigation, M.P., A.N., C.E., M.T.-D., J.L.R.-H., M.C., R.T.-P., I.B., F.R.-F., J.G., M.M., and M.B.; resources, M.T.-D., J.L.R.-H., M.C., R.T.-P., J.G., and M.M.; data curation, M.P., A.N., C.E., M.T.-D., J.L.R.-H. and E.R.; writing—original draft preparation, M.P., A.N., M.M., and M.B.; writing—review and editing, C.E., M.T.-D., J.L.R.-H., M.C., R.T.-P., I.B., F.R.-F., and J.G.; supervision, J.G., M.M., and M.B.; project administration, M.M.; funding acquisition, M.T.-D., J.L.R.-H., M.C., and M.M. All authors have read and agreed to the published version of the manuscript.
This research was funded by Grifols through an unrestricted grant from the Catalan Center for Research in Alpha-1 antitrypsin deficiency of the Vall d'Hebron Research Institute (VHIR) in the Vall d'Hebron Barcelona Hospital Campus, Barcelona, Spain; from the Madrid Center for Research in Alpha-1 antitrypsin deficiency of the Hospital Clínico San Carlos, Madrid, Spain; from the Galicia Center for Research in Alpha-1 antitrypsin deficiency of the University Hospital Complex of Vigo, Spain; as well as a research grant from Fundació Catalana de Pneumologia (FUCAP).
The study was approved by the Vall d'Hebron Hospital Ethics Committee (Barcelona, Spain), number PR(AG)335/2016 (28 October 2016).
Informed consent was obtained from all subjects involved in the study.
Data are available from the authors upon request.
Myriam Calle received speaking or consulting fees from Boehringer Ingelheim, Grifols, Chiesi, CSL Behring, AstraZeneca, GlaxoSmithKline, Menarini, Gebro Pharma, Zambon, and Novartis. There is no real or perceived conflict of interest between these sources and the present paper. Juan Luis Rodríguez-Hermosa received speaking fees from Boehringer Ingelheim, GlaxoSmithKline, Grifols, CSL Behring, Zambon, and Gebro Pharma. There is no real or perceived conflict of interest between these sources and the present paper. Cristina Esquinas received speaker fees from CSL Behring. Marc Miravitlles received speaker or consulting fees from AstraZeneca, Bial, Boehringer Ingelheim, Chiesi, Cipla, CSL Behring, Laboratorios Esteve, Gebro Pharma, Kamada, GlaxoSmithKline, Grifols, Menarini, Mereo Biopharma, Novartis, pH Pharma, Rovi, TEVA, Spin Therapeutics, Verona Pharma, and Zambon, and research grants from Grifols. Miriam Barrecheguren received speaker fees from Grifols, Menarini, CSL Behring, and GSK, and consulting fees from GSK, Novartis, Boehringer Ingelheim, and Gebro Pharma. The remaining authors report no conflict of interest.
Mònica Pons was the recipient of a Rio Hortega contract in the 2018 Strategic Action Health Call from the Instituto de Salud Carlos III for the years 2019–2020. Alexa Núñez was the recipient of a Rio Hortega contract in the 2019 Strategic Action Health Call from the Instituto de Salud Carlos III for the years 2020–2022. We thank Ignacio Martín Granizo and Montserrat Figueira Alvarez for their collaboration in the elastography in the University Hospital Complex of Vigo.
By Mònica Pons; Alexa Núñez; Cristina Esquinas; María Torres-Durán; Juan Luis Rodríguez-Hermosa; Myriam Calle; Ramón Tubio-Pérez; Irene Belmonte; Francisco Rodríguez-Frías; Esther Rodríguez; Joan Genescà; Marc Miravitlles and Miriam Barrecheguren
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