Short telomeres in alveolar type II cells associate with lung fibrosis in post COVID-19 patients with cancer

Results

Cohort of COVID-19 patients and age-matched controls

In order to study a potential role of short telomeres in the origin of the post-viral lung fibrosis sequel presented by a percentage of COVID-19 patients, paraffin-embedded lung samples from post-COVID-19 and COVID-19-free patients were obtained from the University Hospital of Marques de Valdecilla in Santander, Spain. In all cases, lung samples corresponded to biopsies from non-tumoral areas of the lungs from lung cancer patients. The samples used for the analysis were confirmed to correspond to normal, non-tumoral tissue by using pathological analysis. Cancer patients were used owing to the fact that normal lung biopsies were readily available. A total of 35 females and 63 males of ages ranging from 42 to 84 years old were included in the study (Table 1). Nineteen patients, 5 females and 14 males, passed the COVID-19 disease previous to lung surgery, while the rest of the patients never had the COVID-19 disease. The clinical and demographic characteristics of patients under the study are summarized in Table 2. Of note, histopathological analysis of lung samples post-surgery showed that 59% of COVID-19 patients (11 out of 19) and 19% of control patients (15 out of 79) presented lung fibrosis (Tables 1, 2). It should be pointed out that none of the COVID-19 patients had fibrosis prior to SARS CoV-2 infection based on either chest radiographs or CT scans performed before infection. None of the COVID-19 patients had CT lung pannalization characteristic of the usual interstitial pneumonia. Of note, echocardiographic findings are suggestive of pulmonary hypertension in only one patient from control group.

Table 1. Control and COVID-19 patients under study.

	Sex	Age (years)	Biopsy	Fibrosis
Controls
Control 1	Male	45	B20-4315	No
Control 2	Female	59	B20-16593	No
Control 3	Female	83	B20-20700	No
Control 4	Male	78	B21-1572	No
Control 5	Male	65	B21-2679	No
Control 6	Male	84	B21-2688	No
Control 7	Female	80	B21-470	No
Control 8	Female	62	B21-571	No
Control 9	Female	66	B21-613	No
Control 10	Female	63	B21-1042	No
Control 11	Male	54	B21-1132	No
Control 12	Female	71	B21-1599	No
Control 13	Male	60	B21-2199	Yes
Control 14	Male	78	B21-2358	Yes
Control 15	Male	66	B21-2679	No
Control 16	Female	69	B21-2739	No
Control 17	Male	68	B21-4443	No
Control 18	Male	77	B21-7920	No
Control 19	Male	73	B21-7869	No
Control 20	Male	73	B21-8659	No
Control 21	Male	69	B21-9201	No
Control 22	Female	76	B21-9647	No
Control 23	Male	64	B21-11060	No
Control 24	Male	64	B21-11606	Yes
Control 25	Female	70	B21-12024	No
Control 26	Male	68	B21-12168	Yes
Control 27	Male	72	B21-12186	Yes
Control 28	Male	73	B21-12752	No
Control 29	Male	66	B21-13359	No
Control 30	Female	66	B21-14681	No
Control 31	Female	62	B21-14588	No
Control 32	Male	58	B21-15032	No
Control 33	Female	42	B21-15986	No
Control 34	Male	59	B21- 16407	No
Control 35	Female	84	B21- 16496	No
Control 36	Male	60	B21- 18388	No
Control 37	Male	47	B21- 18468	No
Control 38	Female	50	B21- 18433	No
Control 39	Female	68	B21- 18891	No
Control 40	Female	63	B21-19598	No
Control 41	Male	66	B21-20680	No
Control 42	Male	77	B21-20835	No
Control 43	Male	72	B21-21282	No
Control 44	Male	66	B21-22922	No
Control 45	Male	66	B21-23007	No
Control 46	Male	80	B21-23575	No
Control 47	Male	70	B21-23641	No
Control 48	Female	61	B21-24222	No
Control 49	Female	72	B21-24182	No
Control 50	Male	74	B21-25026	Yes
Control 51	Female	66	B21-25449	Yes
Control 52	Male	79	B21-26566	No
Control 53	Male	72	B21-26640	No
Control 54	Female	74	B21-27377	No
Control 55	Male	73	B21-27275	No
Control 56	Male	77	B21-27490	No
Control 57	Male	68	B21-27550	No
Control 58	Female	53	B22-398	No
Control 59	Male	60	B22-1485	No
Control 60	Male	79	B22-1607	No
Control 61	Female	74	B22-2114	No
Control 62	Male	57	B22-2267	Yes
Control 63	Female	68	B22-3903	No
Control 64	Male	71	B22-4103	No
Control 65	Female	73	B22-5408	Yes
Control 66	Male	72	B22-5333	Yes
Control 67	Female	58	B22-5843	No
Control 68	Male	74	B22-5932	No
Control 69	Male	71	B22-6089	No
Control 70	Male	69	B22-6592	Yes
Control 71	Female	58	B22-7124	Yes
Control 72	Male	71	B22-7226	No
Control 73	Male	66	B22-8331	Yes
Control 74	Male	79	B22-8447	Yes
Control 75	Female	63	B22-8816	No
Control 76	Male	70	B22-9475	No
Control 77	Female	83	B22-9599	No
Control 78	Female	63	B22-9988	No
Control 79	Male	82	B22-10535	Yes
Covids
Covid 1	Female	82	B20-15688	Yes
Covid 2	Male	67	B20-9722	Yes
Covid 3	Female	69	B20-8325	Yes
Covid 4	Male	66	B21-1539	No
Covid 5	Male	73	B21-6981	No
Covid 6	Male	77	B21-10260	Yes
Covid 7	Male	65	B21-11564	Yes
Covid 8	Male	72	A21-6	Yes
Covid 9	Male	66	B21-5757	No
Covid 10	Male	79	B21-13286	Yes
Covid 11	Female	48	B21- 18230	No
Covid 12	Male	79	B21-25575	Yes
Covid 13	Male	62	B22-508	No
Covid 14	Male	64	B22-1037	Yes
Covid 15	Female	64	B22-4011	No
Covid 16	Male	76	B22-6717	Yes
Covid 17	Male	64	B22-8708	No
Covid 18	Female	84	B22-9363	Yes
Covid 19	Male	72	B22-10050	No
Results from histopathological diagnose of lung fibrosis post-surgery are indicated.

Table 2. Clinical data of patients.

Variable	COVID19	Surgical controls
Number	19	79
Gender (F/M)	5/14	35/64
Age (years)	70±9	68±9
Current smoking (yes/no)	3/16	23/56
COVID19 mild/severe	11/8	-
Pre-COVID19 lung fibrosis diagnosed by molecular imaging (yes/no)	0/19	-
Post-surgery lung fibrosis diagnosed by histopathology (yes/no)	11/8	15/64
Pulmonary Hypertension (yes/no)	0/19	1/78
Concomitant diseases (C/R/D)	6/3/2	21/24/11
CT scan with ground opacity (yes/no)	7/12	-
CT scan pulmonary effusion	13/6	-
Pulmonary function test (positive/negative)	13/6	-
Respiratory bronchiolitis	5/14	28/51
Treatment with immunosuppressants or immunomodulators (yes/no)	5/14	6/73
Patient demographic and clinical characteristics are presented as mean ± standard deviation. F, female; M, male; C, cardiovascular; R, Respiratory; D, diabetes, - not performed.

Progressive telomere shortening with age in lung parenchyma

To address the potential role of telomere length in COVID-19 associated lung pathologies, we analyzed telomere length in a single-cell manner in lung cells from the lung parenchyma by using Quantitative telomere Fluorescence In Situ Hybridization (Q-FISH), a technique that allows quantification of individual telomere fluorescence spots per interphasic nuclei in tissue sections, which in turn serve to quantify telomere length [31]. To distinguish between ATII and non-ATII cells in the lung parenchyma, we combined the Q-FISH technique with an immunofluorescence staining using specific antibody against prosurfactant protein C (pro-SPC), a bona fide marker of ATII cells. First, we represented the distribution of the mean telomere spot intensity per nucleus in ATII and non-ATII cells from each control and COVID-19 samples (Supplementary Figure 1). Linear regression analysis between average of mean telomere spot intensity per nucleus and patient’s age, revealed a significant telomere shortening with increasing age in both ATII and non-ATII lung cells, something that has been described for other cell types previously but not for lung cell populations in humans [32–35] (Figure 1A, 1B). In agreement with telomere shortening with increasing patient age in lung cells, we also observed statistically significant increase in the abundance of short telomeres (ie, telomere fluorescence below 20^th percentile of all telomeres in control samples) and a significant decrease in the abundance of long telomeres (ie, telomere fluorescence above 80^th percentile of all telomeres in control samples) only in ATII cells but not in non-ATII cells (Figure 1C–1F). This observation could be explained by the fact that the progenitor nature of ATII cells could lead to a higher proliferative history compared to non-ATII cells within the lung parenchyma and a consequently higher rate of telomere shortening associated to cell division with age. Consistent with this notion, we found a higher rate of decrease of telomere length, a higher rate of increase in the abundance of short telomeres, as well as a higher rate of decrease in the abundance of long telomeres with age in ATII cells compared with non-ATII cells in the linear regression models (Figure 1A–1F).

Figure 1. Progressive telomere shortening with age in lung cells. (A–F) Linear regression and Pearson correlation analyses between telomere intensity in pro-SPC positive (A) and pro-SPC negative cells (B), between percentage of short telomeres in pro-SPC positive (C) and pro-SPC negative cells (D), and between percentage of long telomeres in pro-SPC positive (E) and pro-SPC negative cells (F) and age in lung section from patients under study including control and COVID-19 samples. The Pearson r coefficient and the P value are indicated.

COVID-19 patients present shorter telomeres in ATII cells than age-matched controls

In order to assess the potential correlation between telomere length in lung tissue and COVID-19 disease, we compared the average mean telomere intensity per nucleus of COVID-19 patients with that of controls both in ATII and non-ATII cells within the lung parenchyma (Figure 2A–2H). We performed the analysis in age-matched individuals within an age interval from 62 to 84 year old in which most of COVID-19 patients are found (18 out of 19 COVID-19 samples). First, we used the Kolmogorov-Smirnov (KS) test to assess whether the cumulative frequency distribution of patient’s age from control and COVID-19 groups were different. The KS test revealed similar age distribution in control and COVID-19 patients ruling out bias in the potential differences in telomere length due to different ages between both groups (Figure 2A).

Figure 2. COVID-19 patients present shorter telomeres in the alveolar type II cells than controls. (A) Box and Whisker plot representation of control and COVID-19 patients’ age within 62 and 84 years old. Differences in age distributions between both control and COVID-19 sample groups was analyzed by Kolmogorov-Smirnov test. The p-value is indicated. (B) Representative images of telomere quantitative fluorescence in situ hybridization (q-FISH) combined with immunofluorescence against Pro-SPC in a control and a COVID-19 lung samples. (C–H) Box and Whisker plot representation of mean telomeric spot intensity per nucleus (C, F), percentage of long telomeres above 80^th percentile (D, G) and percentage of short telomeres below 20^th percentile (E, H) in alveolar type II (ATII) (C–E) and in non-ATII cells (F–H) in lung sections from control and COVID-19 patients within 62 and 84 year-old age interval. Statistical significance in (C–H) was assessed using unpaired Student’s t test with Welch’s correction and the p-value is indicated. The percent increase or decrease between control and COVID-19 samples are indicated in each plot.

Then, we compared the mean telomere intensity per nucleus in ATII cells in both control and COVID-19 patients and found a significant 6% lower mean telomere fluorescence intensity in ATII cells from COVID-19 patients compared to those from controls (Figure 2C). In accordance with this, we also found a significant 42% decrease in the abundance of long telomeres above the 80^th percentile in the telomeres of control samples (Figure 2D). We also found a 30% increase in the abundance of short telomeres below 20^th percentile of control samples although this difference did not reach statistical significance (Figure 2E). Interestingly, although we also observe a similar trend in telomere length, long and short telomere abundance in non-ATII cells, none of these comparisons reached statistical significance (Figure 2F–2H). These observations support the fact that SARS-Cov2 mainly infects ATII cells, and thus can lead to increased turn-over of the remaining progenitor ATII cells in an attempt to regenerate the COVID-19 induced lung damage, which in turn accelerates telomere shortening in these cells. Short/dysfunctional telomeres in ATII cells impair lung damage repair and are sufficient to trigger interstitial pulmonary fibrosis in mouse models [17].

COVID-19 patients present lung fibrosis

In line with the above, a potential outcome of SARS-CoV-2 infection is the induction of fibrosis-like phenotypes in the lung, suggesting that the viral infection maybe exhausting the regenerative potential of lung tissue [36–39]. Indeed, histopathological analysis of lung samples post-surgery showed that the incidence of lung fibrosis was 3-fold higher among COVID-19 than in control patients, 59% and 19%, respectively (Table 2). We further analyzed the lung fibrotic pathologies in a subset of our patient cohorts by performing Masson trichrome and Sirius red staining for histological evaluation of collagen fibers and by immunohistochemical staining of α-smooth muscle actin (SMA), a marker of activated fibroblasts and myofibroblasts that secrete extracellular components required for wound repair [40]. Quantitative analysis of Masson trichrome, Sirius red and SMA revealed that histopathologically diagnosed with pulmonary fibrosis post-surgery in control and COVID-19 patient cohorts present significant higher collagen depots and increased presence of activated fibroblasts and/or myofibroblasts as compared to control lungs (Figure 3A–3D).

Figure 3. Collagen depots in patients diagnosed with lung fibrosis post-surgery. (A) Representative images of Masson trichrome, Sirius red (polarized light and bright field) and smooth muscle actine (SMA) staining in non-fibrotic and fibrotic lungs. (B–D) Quantification of Masson trichrome (B), Sirius red (C) and SMA (D) positive stained lung area in non-fibrotic (NF) and fibrotic (F) lung samples. The samples analyzed correspond to Control 1-23 and COVID-19 1-9 (Table 1). Statistical significance was assessed using Student’s t test and the p-value is indicated.

We next compared telomere length and the percentage of long and short telomeres in ATII cells in histopathological diagnosed fibrotic and no-fibrotic patients within the age range of 62- to 84-year-old (Table 1 and Figure 4). The results clearly showed that non-fibrotic COVID-19 patients showed a 7-fold higher rate of telomere shortening than their age-matched non-fibrotic controls (Figure 4A). In contrast, the rate of telomere shortening was similar when comparing fibrotic controls with fibrotic COVID-19 patients (Figure 4B). Non-fibrotic COVID-19 patients present shorter mean telomere length, increased percentage of short telomeres and lower percentage of long telomeres in ATII cells as compared to age-matched non-fibrotic control patients (Figure 4C–4G), supporting the notion that short telomeres are a risk factor for SARS-CoV2 infection [23, 25, 26]. It should be pointed out that the difference in short telomeres between non-fibrotic COVID-19 and control patients is even observed in a COVID-cohort younger than its correspondent control-cohort (mean age of 66 and 71 in COVID-19 and controls, respectively) (Figure 4C). No significant differences were detected in mean telomere length and the percentage of long/short telomeres between fibrotic control and fibrotic COVID-19 cohorts (Figure 4D–4F), in agreement with the notion that short telomeres associate with pulmonary fibrosis [14, 15].

Figure 4. Higher rate of telomere shortening with age in COVID-19 patients. (A, B) Linear regression analyses between telomere intensity in pro-SPC positive cells and age in lung section from control and COVID-19 patients not presenting lung fibrosis (A) or being histopathologically diagnosed with lung fibrosis (B) post-surgery. The slope of the linear regression is shown. (C) Mean age of control and COVID-19 patients within 62 and 84 year-old interval presenting or not lung fibrosis post-surgery. (D–F) Mean telomeric spot intensity per nucleus (D), percentage of long telomeres above 80^th percentile (E) and percentage of short telomeres below 20^th percentile (F) in alveolar type II in lung sections from control and COVID-19 patients within 62 and 84 year-old age interval. Statistical significance in (C–F) was assessed using unpaired Student’s t test and the p-value is indicated.

Decreased number of alveolar type II cells in the lungs of COVID-19 patients

As the SARS-CoV-2 virus in known to infect mainly ATII cells [29, 41], we set to analyze the percentage of ATII cells in control and COVID-19 samples by immune staining of Pro-surfactant protein C (Pro-SPC) as a specific marker of ATII cells. The results clearly show a significant lower number of ATII cells in COVID-19 patients compared to control lung samples (Figure 5A, 5B). Since ATII cells constitute the alveolar regenerative stem cells, this observation supports the notion that SARS-CoV-2 infection induces a regenerative/proliferative response that leads to further telomere shortening in ATII cells that may contribute to ATII exhaustion.

Figure 5. Decreased number of alveolar type II cells in the lungs of COVID-19 patients. (A, B) Representative images of prosurfactant protein C (pro-SPC) immunostaining, a marker of alveolar type II cells (ATII) (A) and quantification of pro-SpC positive cells in the lungs of control and COVID-19 patients (B) Statistical significance was assessed using Student’s t test and the p-value is indicated.

Abbreviations

ATI: alveolar type I cells; ATII: alveolar type II cells; IPF: Idiopathic pulmonary fibrosis; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; COVID-19: coronavirus disease 2019; ACE2: angiotensin-converting enzyme 2; Q-FISH: Quantitative telomere Fluorescence In Situ Hybridization; SMA: a-smooth muscle actin; pro-SPC: prosurfactant protein C.

Author Contributions

MAB was the chief investigator of the study. MSRD, SNG, JSOC and AVR were the clinical team that performed the pathological, surgical and pneumology studies. PM performed experimental work and analyzed the data. RSV and AS contributed to experimental work. PM, MAB and AVR wrote the paper.

Acknowledgments

We are indebted to D. Megias for confocal microscopy analysis. The authors wish to thank BioBanco service, especially R. Madureira, from Hospital Universitario Valdecilla, Santander for its expertise.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Ethical Statement and Consent

The Clinical Research Ethics Committee of the University Hospital of Marques de Valdecilla approved the study (INNVAL-20/34). All participants in the registry gave written informed consent prior to participation and the study complied with the Declaration of Helsinki.

Funding

Research in the Blasco Lab is funded by Fundación Botín and Banco Santander (Spain); Agencia Estatal de Investigación (AEI/MCI/10.13039/501100011033) with the project RETOS SAF2017-82623-R, cofunded by European Regional Development Fund (ERDF), “A way of making Europe”; Comunidad de Madrid with the Synergy Project COVIDPREclinicalMODels-CM and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 882385) through the project ERC-AvG SHELTERINS. The CNIO, certified since 2011 as Severo Ochoa Centre of Excellence by AEI/MCI/10.13039/501100011033, is supported by the Spanish Government through the Instituto de Salud Carlos III (ISCIII). Research in the Villar Lab is funded by Agencia Estatal de Investigación RTI2018-095214-B-I00, Gobierno de Cantabria SUBVTC-2021-0011, Fomento de la transferencia de conocimiento en la Comunidad Autónoma de Cantabria 2020UCI22-PUB-000 and by Fundación IDIVAL INNVAL20/34. The sponsors did not have any input or contributions in the development of the research and manuscript.

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