Macrophages Contribute to Pulmonary Hypertension Associated With Sickle Cell Disease

ABSTRACT

Pulmonary hypertension (PH) is a fatal sequela in sickle cell disease (SCD) patients and occurs with greater prevalence compared to the general population. Macrophages (Mϕ) are one of the first immune cells to be recruited to the lungs in mouse models of PH, including SCD‐PH, and a key cell type that contribute toward disease progression. Here, we first determined if phenotypic difference exist between control (C57BL/6) and Berkeley‐SS (Berk‐SS, SCD) mouse pulmonary Mϕs and, if so, how chronic moderate hypoxic exposure (~8,000 ft, Pb ~568 mmHg for 10 weeks) altered molecular and metabolic pathways. Next, we aimed to determine if the microenvironment of the Berk‐SS lung is primed for Mϕs recruitment compared to the C57BL/6 lung. Using precision cut lung slice (PCLS), we determined PCLS from Berk‐SS mice have significant increases in adhesion molecules associate with Mϕ recruitment and recruit splenic Mϕs at a greater rate compared to control mice. We confirmed these results in an acute hypoxic exposure (18,000 ft for 3 days) experiment and our results suggest that Berk‐SS mice recruit more interstitial Mϕ with a pro‐inflammatory phenotype when compared to C57BL/6 mice. Lastly, the depletion of Mϕ in our Berk‐SS PH model improved right ventricular function, decreased pulmonary vascular muscularization, and improved exercise tolerance. Together, these data emphasize a critical role of Mϕ pulmonary recruitment in SCD‐PH pathophysiology that is driven by inflammation.

This study investigated proteomic and metabolomic differences in pulmonary macrophages and the lung microenvironment to determine molecular pathways involved in Sickle Cell Disease associated pulmonary hypertension. We concluded that macrophages play a critical role in disease pathology by decrease pulmonary arterial muscularization.

1.

Sickle Cell Disease (SCD) is an inherited genetic disorder caused by a single point mutation in the hemoglobin (Hb) β‐gene (HBB) gene that results in the substitution of the amino acid glutamic acid for valine and sickle Hb (HbSS) [1]. When deoxygenated, HbSS polymerizes resulting in the characteristic sickling of red blood cells (RBC). Approximately 100,000 Americans live with SCD and are expected to have a current life expectancy of between 50 and 55 years of age [2, 3]. Pulmonary hypertension (PH) remains one of the most severe and untreatable end‐organ complications observed in patients with SCD. PH displays a spectrum of endotypes that include; pre‐capillary; post‐capillary; and chronic thromboembolic disease. Each type demonstrate a unique, yet not fully elucidated, mechanistic underpinnings. Hemodynamically, PH is defined as a mean pulmonary arterial pressure greater than 20 mmHg at rest as determined by right heart catheterization [4]. The World Health Organization (WHO) classifies PH into 5 major groups based on underlying etiology. Currently, PH associated with SCD is classified under WHO Group 5 due to its complex, multifactorial pathophysiology. It is hypothesized that the high prevalence of PH in patients with SCD stems from the polymerization of Hb molecules that destabilize RBC membranes. This destabilization results in an increase in both intra‐ and extravascular hemolysis – the clearance of hemolytic byproducts (Hb and heme) as well as erythrophagocytosis of damaged RBCs – leading to an overabundance of iron within Mϕs [5]. Like other types of PH, our data suggests that Mϕ are recruited to the lung microenvironment and colocalize within adventitial inflammatory niches within the pulmonary vasculature of SCD‐PH patients [6]. Although, unique to pre‐capillary SCD‐PH hemolytic byproducts, Hb and heme are potential initiators of recruited Mϕs that are loaded with iron [7], which may subsequently be released into the microenvironment [8] and contribute to the development and progression of disease. Roughly 10 percent of SCD patients will develop PH, reducing their survival by 7 years [9].

Because it is well established that Mϕ recruitment to the perivascular regions in the lung exacerbates PH [10, 11, 12, 13, 14], there is considerable interest in therapeutically targeting Mϕs migration and localized pro‐inflammatory effects. Here, we hypothesize that Mϕ recruitment plays a critical role in SCD‐PH pathology in a complex model that utilizes moderate hypoxia to drive the hemolytic disease processes in Berk‐SS mice. Previously, our lab has shown that Berk‐SS mice exposed to 8,000 ft (Pb ~568 mmHg) for 10 weeks develop indices of PH such as increased end diastolic pressure‐volume relationship, Fulton index (right ventricle divided by left ventricle and septum), right ventricular (RV) stiffness and after load with decreases in cardiac output, stroke volume, ventricular‐vascular coupling, and contractility (PMID: 40997624) (PMID: 3986) (PMID: 41538305). In these studies, we utilized C57BL/6 mice for control mice as they did not see alteration in PH disease pathology. The mechanism of how Berk‐SS mice develop PH while C57BL/6 mice do not at this altitude remains to be fully understood. Multi‐omics analyses of pulmonary Mϕ isolated from Berk‐SS mice suggest a “pro‐PH” phenotype with altered hypoxic adaptions. Data also suggested that, compared to hypoxic C57BL/6 mice, the lungs of Berk‐SS mice were primed for Mϕ recruitment, in both in vivo and ex vivo experiments. When iron loaded splenic Mϕs were co‐cultured with precision cut lung slices obtained from Berk‐SS mice, the proteomic phenotype was altered, demonstrating a cause (lungs primed for recruitment) and effect (pro‐inflammatory Mϕ phenotype) relationship. Finally, the present study depleted circulating Mϕ with clodronate in Berk‐SS mice exposed to ~15 percent oxygen (simulated 8,000 ft or Pb ~568 mmHg) for 10 weeks. Dosing with clodronate both depleted pulmonary Mϕ in Berk‐SS mice and improved indices of pre‐capillary PH progression. This was evident by normalization of right ventricular functional parameters, pulmonary vascular remodeling, and by a significant improvement in critical speed, a rigorous test of exercise performance.

2. Methods

2.1. Animals

Age‐matched (8 to 10 weeks old) female C57BL/6 and Berkeley‐SS mice (Berk‐SS) were either obtained from Jackson Laboratories (Bar Harbor, ME, USA) or our in‐house mouse colony. Mice were housed and bred in an AAALAC‐accredited and genotyped as done previously [15, 16, 17]. A total of 57 mice were used for this manuscript—34 mice (C57BL/6 n = 13, Berk‐SS vehicle control n = 12, Berk‐SS with clodronate n = 9) to evaluate cardiovascular changes and multi‐omic analysis of pulmonary Mϕs, 4 mice from each genotype (8 mice total) were used for the co‐culture studies, and 3–5 mice per genotype for acute hypoxic exposure studies. Levels of discomfort and distress were monitored daily by the in‐house animal care staff, with a veterinarian available as needed. Chronic hypoxia exposure consisted of mice housed at 8,000 feet (Pb ~568 mmHg) for 10 weeks as previously described [16, 18]. Acute hypoxia exposure was at 18,000 ft (Pb ~385 mmHg) for 3 days. All experimental procedures were conducted under the guidelines recommended by The Journal of Physiology, the National Institutes of Health, and were approved by the Institutional Animal Care and Use Committee at the University of Colorado Anschutz Medical Campus.

2.2. Macrophage Isolation

Pulmonary or splenic tissue was placed into individual 2 mL conical tubes containing 1 mL of warm digestion media (2 mg/mL of Collagenase D and 0.1% of DNase in RMPI media) and minced. Tubes were incubated at 37°C with agitation for 30 min. After, tissue was filtered through a 100 μm filter (Corning, CLS431752). HBSS was used to wash the filter and the samples spun at 3000 rpm for 10 min. The supernatant was removed and the pellet was resuspended in 1 mL of ACK buffer (150 mM NH₄Cl, 10 mM KHCO₃, 0.1 mM EDTA in deionized water) for 5–10 min at room temperature. 10 mLs of D10 media (490 mLs of DMEM + 10 mL FBS + 1% Pen/strep) was added and then spun. The supernatant was removed and the pellet was resuspended in 5 mL of warmed media. Cells were then counted and either seeded for co‐culture experiments or snap frozen for multiomics analysis. Snap frozen cells were seeded in a 6‐well plate at 1,000,000 cells/well and allowed to adhere for 2 h 37°C. Wells were then washed and cells removed on ice with EDTA. Samples were then snap frozen in liquid nitrogen for proteomic and metabolomic analysis. Co‐culture cells were counted and seeded into the top of a transwell at 100,000 cells/well and incubated at 37°C for 2 h. Wells were then washed with HBSS, fresh media was added to the transwells, and returned to the incubator for overnight incubation.

2.3. Precision Cut Lung Slices (PCLS)

Animals were anesthetized with isoflurane (5%) and humanely euthanized according to IACUC protocol via exsanguination and cervical dislocation. A small incision was then made at the neck and excess tissue separated to reveal the musculature over the trachea. Forceps exposed the trachea. Next, ~3 inches of 3.0 silk suture was threaded under the trachea. Then a small cut was made between the rungs of the trachea with spring scissors to allow for a trachea tube to be placed and secured for inflation. Lungs were inflated with 1–2 mL of 2% low temperature agarose (2% agarose to volume of DMEM). The suture was then tied of to prevent backflow of agarose. The lungs were removed from the animal and placed into a bag containing 5 mL of sterile saline and placed on ice for 20–30 min. Lungs were cut on Vibratome (World Precision Instruments, 9000SMZ) at 0.3 m/s and 500 μM thickness. Cut slices were placed in wells of a 24 well plate containing 0.5 mL of warmed DMEM + 10 FBS + 1% Pen/strep. PCLS were then placed in an incubator at standard conditions overnight.

2.4. Flow Staining for PCLS

Macrophages and PCLS were removed from the incubator, and staining solution was prepared with the hood lights off. Macrophages were stained with CD11b‐PE‐Cy7 (Biolegend, 101216) at a ratio of 1:500 4 mL D10 to 8 µL of stain. PCLS was stained with CD11b‐PE (Biolegend, 101208) at a ratio of 1:500. 100 µL of staining solution was added to macrophage transwells, and 250 µL of staining solution was added to PCLS wells. Both macrophages and PCLS were incubated with staining solution in the dark at 37°C for 1–3 h. After incubation, the staining solution was removed, both macrophages and PCLS were washed with warmed HBSS, and replenished with fresh media.

2.5. Co‐Culture of PCLS and Macrophages

After staining, transwells containing macrophages were given fresh media (200 µL) and 24‐well plates containing PCLS received 700 µL. The macrophage transwells were then moved over corresponding PCLS wells. The co‐culture plates were returned to the incubator for a 37°C incubation overnight. After, the transwells were removed and PCLS were processed into a single cell suspension. Tissue was removed from a single well and filtered through a 100 μL filter. After filtration, tubes were spun at 3200 rpm for 10 min, then the supernatant was removed. Cells were resuspended in 150 µL of 4% PFA in preparation for flow cytometry.

2.6. Metabolomic Analysis

Metabolomics analyses were performed as previously described [19]. Briefly, metabolites were extracted at 2 × 10⁶ cells per milliliter at 4°C in cold methanol/acetonitrile/water (5:3:2, v/v/v). After vortexing at 4°C for 30 min, extracts were separated from the protein pellet by centrifugation for 10 min at 10,000 g at 4°C. Ultra‐High‐Pressure Liquid Chromatography‐Mass Spectrometry analyses were performed using a Vanquish UHPLC coupled online to a Q Exactive mass spectrometer (Thermo Fisher, Bremen, Germany) using a 5 min C18 gradient in positive and negative ion modes (separate runs) as previously described. Metabolite peaks were integrated and annotated using El‐Maven with the KEGG database.

2.7. Proteomic Analysis

The protein pellets solubilized in 4% sodium dodecyl sulfate (SDS) in 100 mM triethylammonium bicarbonate (TEAB) pH 7.5 lysis buffer. The samples were digested using a 96‐well S‐Trap plate (Protifi, Huntington, NY) following the manufacturer's procedure. Samples were reduced with 10 mM DTT at 55°C for 30 min, cooled to room temperature, and then alkylated with 25 mM iodoacetamide in the dark for 30 min. Next, a final concentration of 1.2% phosphoric acid and then six volumes of binding buffer (90% methanol; 100 mM triethylammonium bicarbonate, TEAB; pH 7.1) were added to each sample. After gentle mixing, the protein solution was loaded to the 96‐well S‐Trap plate, spun at 1500 g for 2 min, and the flow‐through collected and reloaded onto the 96‐well S‐Trap plate. This step was repeated three times, and then the 96‐well S‐Trap plate was washed with 400 μL of binding buffer 3 times. Finally, 1 μg of sequencing‐grade trypsin (Promega) and 125 μL of digestion buffer (50 mM TEAB) were added onto the filter and digestion carried out at 37°C for 6 h. To elute the peptides, three stepwise buffers were applied, with 100 μL of each with one more repeat, including 50 mM TEAB, 0.2% formic acid in H₂O, and 50% acetonitrile and 0.2% formic acid in H₂O. The peptide solutions were pooled, lyophilized, and resuspended in 100 μL of 0.1% FA.

2.8. Mass Spectrometry Analysis

A volume of 20 μL of each sample was loaded onto individual Evotips for desalting and then washed with 20 μL 0.1% FA followed by the addition of 100 μL of storage solvent (0.1% FA) to keep the Evotips wet until analysis. The Evosep One system (Evosep, Odense, Denmark) was used to separate the peptides on a Pepsep column (150 μm inter diameter, 15 cm) packed with ReproSil C18 1.9 μm, 120 A resin. The system was coupled to the timsTOF Pro mass spectrometer (Bruker Daltonics, Bremen, Germany) via the nano‐electrospray ion source (Captive Spray, Bruker Daltonics). The mass spectrometer was operated in PASEF mode. The ramp time was set to 100 ms and 10 PASEF MS/MS scans per topN acquisition cycle were acquired. MS and MS/MS spectra were recorded from m/z 100 to 1700. The ion mobility was scanned from 0.7 to 1.50 V s/cm². Precursors for data‐dependent acquisition were isolated within ±1 Th and fragmented with an ion mobility‐dependent collision energy, which was linearly increased from 20 to 59 eV in positive mode. Low‐abundance precursor ions with an intensity above a threshold of 500 counts but below a target value of 20,000 counts were repeatedly scheduled and otherwise dynamically excluded for 0.4 min.

2.8.1. Database Searching and Protein Identification

Raw data files' conversion to peak lists in the MGF format, downstream identification, validation, filtering, and quantification were managed using FragPipe version 13.0. MSFragger version 3.0 was used for database searches against a mouse database with decoys and common contaminants added. The identification settings were as follows: Trypsin, Specific, with a maximum of 2 missed cleavages, up to 2 isotope errors in precursor selection allowed for, 15.0 ppm as MS1, and 0.4 Da as MS2 tolerances; fixed modifications: carbamidomethylation of C (+57.021464 Da); variable modifications: oxidation of M (+15.994915 Da), acetylation of protein N‐term (+42.010565 Da), and pyrolidone from peptide N‐term Q or C (−17.026549 Da).

2.9. Interstitial Macrophage Recruitment

C57BL/6 and Berk‐SS mice (n = 3–5 per group) were continuously exposed to an oxygen level simulating an elevation of 18,000 ft elevation for 72 h (3 days). C57BL/6 served as a healthy strain of mouse without an underlying PH predisposition for comparisons to Berk‐SS mice. After 3 days, animals were anesthetized with isoflurane (4%–5%) and humanely euthanized by exsanguination and cervical dislocation. The pulmonary system was flushed with 10 mL cold PBS through the right ventricle and the descending aorta was clipped to allow for the pulmonary system to be flushed fully. Once lungs were clear of remaining RBCs, the lungs were isolated and processed into a single cell suspension for flow cytometry analysis.

2.10. Flow Cytometry Staining for Macrophage Recruitment in Acute Hypoxia Exposure

Whole lungs were digested in 1 mL HBSS (without calcium or magnesium; Sigma) containing Liberase TM (0.4 mg/mL; Sigma) and DNase I (100 U/mL; Sigma) using the GentleMACS system. The resulting digest was filtered through a 70 μm cell strainer, red blood cells were lysed (1X RBC Lysis Buffer; eBioscience; 3 min, room temperature), and cell suspensions were centrifuged (300 g, 10 min), washed, and resuspended in FA3 buffer (PBS, 1 mM EDTA, 10 mM HEPES, 1% FBS, pH 7.4) at 4°C.

Fcγ receptors were blocked with anti‐CD16/CD32 antibody (BD Biosciences) for at least 20 min. Cell suspensions were stained with Zombie Green (BioLegend) for 15 min per manufacturer's instructions, followed by 30 min incubation with the following antibody panel: anti‐mouse CD45‐AF700 (BioLegend, Clone 30‐F11, 1:100), CD64‐AF647 (BD Pharmingen, Clone X54‐5/7.1, 1:100), CD11b‐FITC (BioLegend, Clone M1/70, 1:100), CD11c‐BV421 (BioLegend, Clone N418, 1:100), MHCII‐APC‐Cy7 (Clone M5/114.15.2, 1:100), Ly6C‐BV650 (BioLegend, Clone HK1.4, 1:100), Ly6G‐BV510 (BioLegend, Clone 1A8, 1:100).

Following staining, cells were fixed (10% PFA, 30 min, 4°C), filtered through 40 μm filter cap flow tubes (Falcon), and acquired on a Cytek Aurora Instument (Cytek Biosciences) at the University of Colorado AMC Cancer Center Flow Cytometry Shared Resource Core Facility. Absolute counts were determined using 123count eBeads (Invitrogen). Data were analyzed using SpectroFlo software (Cytek Biosciences).

Lung monocytes were identified as Live, CD45‐IV‐negative (extravascular), CD45+, B220−, CD3−, Ly6G−, CD11b+, SSc^low MHCII^low and were separated based on Ly6C expression. All populations were gated using fluorescence minus one (FMO) controls.

2.11. Critical Speed

Critical speed (CS) studies were performed as previously described [15, 20, 21]. Briefly, mice completed a treadmill familiarization phase, consisting of four ~5 min runs on a rodent treadmill (Exer 3/6, Columbus Instruments, Columbus, OH, USA). Initial runs were maintained at 10–15 m/min and final runs increased speed progressively over the last minute (~30–35 m/min) to familiarize the mice with high‐speed running. Intermittent bursts of compressed room air was used to encourage running. All treadmill testing protocols were designed and conducted by experienced staff and strictly followed the guidelines set by the American Physiological Society's resource book for the design of animal exercise. The CS was determined using a modified version of the methodology used by Copp et al for rats [22] and Craig et al [23]. Each mouse performed 3–5 runs to exhaustion, in random order, at a constant speed that resulted in fatigue between 1 and 15 min (speeds ranging from 30 to 50 m/min). Each test was performed on separate days with a minimum of 24 h between tests. To start the test, the treadmill speed was increased rapidly over a 10 s period to the desired speed and timing started. Testing was terminated and time to exhaustion was measured to the nearest tenth of a second whenever the mouse could no longer maintain paces with the treadmill. A successful constant‐speed test was determined if: (1) the mouse could quickly adapt to the treadmill speed at the beginning, (2) a noticeable change in gait occurred preceding exhaustion, and (3) the animal's righting reflex was markedly attenuated when placed on their back.

2.12. Data Modeling for the Determination of CS

The CS and finite distance capacity (D’) were calculated for each mouse using the lineal 1/time model (speed = D’ x 1/time + CS) as described previously [24]. In this model, the treadmill speed used for the constant speed test is plotted as a function of the inverse of time to exhaustion and the y‐intercept of the regression line yields the CS where the slope of the line is the D’.

2.13. Hemodynamics

Mice underwent terminal open chest right ventricular pressure measurements (RVSP) function measurements with a 1.2 F, FTE‐1212B‐4018 pressure volume catheter (Transonic Systems Inc., Ithaca, NY) inserted by direct cardiac puncture. Mice were induced inhaled isoflurane (4%–5%), and tracheal incision (~1 cm) was performed. A tracheal tube was inserted and connected to an Anesthesia Workstation or Hallowell EMC Microvent and an anesthetic plain was maintained at 1.0%–2.5% isoflurane in 100% oxygen. After which, a thoracotomy was performed exposing the heart, the pericardium was resected, and a small hole made at the base of the right ventricle with a 30 g needle for insertion of the pressure‐volume catheter. Steady state right ventricular systolic pressures (RVSPs), followed by contractility (Ees), and afterload (Ea), were captured and mice were humanely euthanized by exsanguination and cervical dislocation. Data was recorded continuously using LabScribe2 and analyzed offline.

2.14. Lung Morphology

In a subset of mice from each group the vasculature in the left lung lobe was quantified for medial thickening by using H&E‐stained scanned lung images equally divided into 100 equal segments. Images that did not have sufficient tissue in the segment were excluded and from the remaining images and 10 randomly selected segments were used for analysis. Using the program STEPanizer, a grid was overlaid on each image and was used to quantify the vasculature within each image. The percentage of vascular tissue to parenchymal tissue in the lung was calculated.

2.15. Statistical Analysis

Data are presented as a mean ± standard error of the mean (SEM). Statistical comparisons for data measurements were completed with an a priori analysis using one‐tailed Student's t test for comparisons between Berk‐SS vehicle control vs Berk‐SS macrophage depleted. An ANOVA with a multiple comparisons test was used when comparing across C57BL/6, Berk‐SS VC and Berk‐SS + Clodronate. Statistical analysis was completed using the statistical software package GraphPad (version 11). Multivariate analyses, hierarchical clustering analysis (HCA), were performed with MetaboAnalyst 6.0 [25]. Statistical significance was defined as p ≤ 0.05. Pathway analysis and network analyses were performed via Omicsnet 2.0 [26].

3. Results

Here, we investigate a mechanism for the pathology of PH associated with sickle cell disease in Berkeley (Berk‐SS) mice. Our lab has previously established that Berk‐SS mice exposed to chronic moderate hypoxia (8,000 ft or Pb ~568 mmHg for 10 weeks) have increased Fulton index, end diastolic pressure‐volume relationship, RV stiffness, and afterload which are characteristics of SCD‐PH. The control animals, C57BL/6, did not have these characteristics after chronic moderate hypoxia. We, therefore, determine what phenotypical differences are present within the pulmonary macrophages (Mϕs) of Berk‐SS mice, the proteomic landscape of Berk‐SS lungs, how this is altered with Mϕs recruitment, and finally how depletion of Mϕs alters the hemodynamics and SCD‐PH disease pathology.

3.1. Berk‐SS Pulmonary Macrophages Have Decreased Cytoskeleton Protein Expression and Increased Metabolic Processes

The critical role of Mϕs in pulmonary hypertension (PH) led us to determine if phenotypic differences existed between animals that do not have a predisposition to PH (C57BL/6) and those that do (Berkeley, Berk‐SS). Here, we isolated pulmonary Mϕs from Berk‐SS and C57BL/6 mice and utilized proteomic analysis. Of the 6,924 proteins analyzed, 446 were significantly increased in Berk‐SS mice at Denver altitude while 476 were significantly decreased (Figure 1A). A list of all proteins analyzed is shown in Supporting table 1. To further analyze these changes, volcano plot analysis was utilized to emphasize the top 4 proteins upregulated or downregulated (Figure 1B). Two of the downregulated proteins, vinculin (VCL) and calcyclin (s100a6), are associated with cytoskeletal dynamics. Mapk3 and Akt1are both vital cell signaling proteins and emphasize the altered inflammatory status of the Berk‐SS mouse [27]. The upregulated proteins are related to metabolism. Hydroxypyruvate isomerase (Hyi) has been thought to be involved in carbohydrate transportation and Ndufb5 encodes for the NADH:ubiquinone oxidoreductase subunit B5 of mitochondrial complex 1. To determine global cellular pathway changes, significantly increased or decreased genes were analyzed by gene ontology biological process (GO:BP). Both down‐ and upregulated sets had multiple pathways which associated with metabolic processes. The top three of the downregulated proteins correlated with carbohydrate metabolic process, vesicle‐meditated transport, and defense response to other organisms (Figure 1C). Upregulated processes contained many metabolic pathways including proton motive force drive mitochondrial ATP synthesis, oxidative phosphorylation, and ATP synthesis coupled electron transport (Figure 1D). To further understand which metabolic pathways were altered in pulmonary Mϕs isolated from Berk‐SS mice, metabolomic analysis was applied. As shown in Figure 1E, few metabolites were significantly different between pulmonary Mϕs Berk‐SS and C57BL/6 mice at Denver altitude (full list shown in Supporting table 2). Enrichment analysis highlighted alterations in the Warburg effect and transfer acetyl groups into the mitochondria (Figure 1F). The Warburg effect is prevalent in cancer and involves a metabolic shift from oxidative phosphorylation towards glycolysis. Our data suggests this is true with a decrease in glucose and lactate, however there is no change in pyruvate (Supporting Figure 1). Together, these data suggest phenotypic differences between Berk‐SS and C57BL/6 pulmonary Mϕs.

Figure 1.

Berk‐SS Pulmonary Macrophages have Decreased Cytoskeleton Protein Expression and Increased Metabolic Processes. (A) Venn diagram of proteomic analysis between C57BL/6 and Berk‐SS pulmonary macrophages (Mϕ). 6924 proteins were analyzed with 6,002 not statistically significant (shown in grey) Of the remaining, 446 were significantly upregulated (shown in red) and 476 were significantly decreased (shown in blue) in the Berk‐SS pulmonary Mϕ. C57BL/6 n = 6, Berk‐SS n = 6 (B) Volcano plot analysis of proteomics from C57BL/6 and Berk‐SS pulmonary Mϕ. Dots in blue were downregulated in Berk‐SS pulmonary Mϕ, while those shown in red were upregulated in Berk‐SS pulmonary Mϕ. The darker the color, the more significant the change. (C) Gene ontology biological process (GO:BP) enrichment analysis from significantly downregulated proteins in Berk‐SS pulmonary Mϕ. The size of the dots represents the number of genes involved in that pathway such as a bigger dot includes more genes from the submitted set. (D) GO:BP enrichment analysis from significantly upregulated proteins in Berk‐SS pulmonary Mϕ. (E) Volcano plot analysis of metabolomic data between C57BL/6 and Berk‐SS pulmonary Mϕs. Dots in blue were downregulated in Berk‐SS pulmonary Mϕ, while those shown in red were upregulated in Berk‐SS pulmonary Mϕ. The darker the color, the more significant the change in that specific metabolite. (F) Enrichment analysis of significantly altered (both down‐ and upregulated) metabolites. The top two pathways were the Warburg effect and transfer of acetyl groups into the mitochondria. Significance was determined by a two‐tail t test and p‐value < 0.05.

3.2. C57BL/6 and Berk‐SS Pulmonary Macrophages Adapt Differently to Moderate Hypoxia

Next, we sought to determine phenotypic differences of pulmonary Mϕs between healthy and Berk‐SS mice in response to chronic moderate hypoxia (8,000 ft for 10 weeks). Proteomic analysis showed clear separation between normoxic and hypoxic environments in both genotypes (Figure 2A,B). Full proteomic data sets are available in Supporting tables 3 and 4. We then analyzed differences between heme synthesis and degradation proteins between all groups. Figure 2C depicts that heme synthesis proteins are increased in C57BL/6 pulmonary Mϕs after 10 weeks of moderate hypoxia. Berk‐SS pulmonary Mϕs, however, exhibited increases in both, heme synthesis and heme degradation, proteins at Denver altitude and 8,000 feet above sea level. Heme oxygenase 2 (HMOX2) is of a particular interest since it is well known to be a prominent hypoxia factor the degrades heme into biliverdin. As Figure 2D shows, HMOX2 is not expressed in the C57BL/6 pulmonary Mϕs after chronic hypoxia but remains highly expressed in the Berk‐SS pulmonary Mϕs with or without moderate hypoxic exposure, suggesting different adaptations between the two genotypes.

Figure 2.

C57BL/6 and Berk‐SS Pulmonary Macrophages Adapt Differently to Moderate Hypoxia. Heatmap analysis with hierarchical clustering of the top 25 proteomic alterations in pulmonary Mϕ isolated from C57BL/6 mice (Nx n = 6, Hx n = 6) (A) or Berk‐SS mice (Nx n = 6, Hx n = 5) (B) after 10 weeks of either normoxic (Denver altitude) or hypoxic (~8,000 ft above sea level) exposure. Red squares signal increase expression and blue squares are decreased expression. (C) Heatmap analysis of heme synthesis proteins (shown in red box) or heme degradation proteins (shown in blue box) of pulmonary Mϕ isolated from C57BL/6 and Berk‐SS mice after 11 weeks of either normoxic (Denver altitude) or hypoxic (~8,000 ft above sea level) exposure. (D) Bar graph depicting peak intensities of Heme oxygenase 2 from pulmonary Mϕ isolated from C57BL/6 and Berk‐SS mice after 11 weeks of either normoxic (Denver altitude) or hypoxic (~8,000 ft above sea level) exposure. Analysis was done in Prism 11.0.2 by 2‐way ANOVA. **p‐value < 0.004. GO:BP pathway enrichment analysis from (E) significantly downregulated proteins and (F) significantly upregulated proteins between isolated pulmonary Mϕ from C57BL/6 mice after 11 weeks of either normoxic (Denver altitude) or hypoxic (~8,000 ft above sea level) exposure. GO:BP pathway enrichment analysis from (G) significantly downregulated proteins and (H) significantly upregulated proteins between isolated pulmonary Mϕ from Berk‐SS mice after 11 weeks of either normoxic (Denver altitude) or hypoxic (~8,000 ft above sea level) exposure. Significance was determined by a two‐tail t test and p‐value < 0.05. Volcano plot analysis of alterations in metabolites in pulmonary macrophages isolated from C57BL/6 mice (I) or Berk‐SS mice (J) after 10 weeks of normoxic or hypoxic exposure. Dots in blue were downregulated in pulmonary Mϕ exposed to hypoxia, while those shown in red were upregulated in pulmonary Mϕ in hypoxia. The darker the color, the more significant the change in that specific metabolite. CP‐ catabolic processes; MP‐ metabolic processes.

We next sought to determine which pathways were altered with chronic moderate hypoxia using GO:BP analysis. In C57BL/6 animals, mRNA metabolic processes, intracellular transport, and RNA processing were decreased while fibrinolysis and regulation of coagulation and hemostasis were increased (Figure 2E,F). For Berk‐SS, again metabolic pathways were prevalent. TCA, proton motive force‐driven mitochondrial ATP synthesis, and aerobic respiration associate with significantly decreased proteins (Figure 2G) and glyceraldehyde‐3‐phosphate biosynthesis, glyceraldehyde‐3‐phosphate metabolic processes, and NADH regeneration correlated with upregulated proteins in moderate hypoxia (Figure 2H).

To further investigate the observed increases in metabolic pathways, we performed metabolomic profiling. Full data sets are available in Supporting Tables 5 and 6. In C57BL/6 mice, cysteine, hypoxanthine, and succinate levels were elevated following 10 weeks of hypoxia, consistent with previously published findings (Figure 2I [28]). In contrast, Berk‐SS mice exposed to chronic hypoxia exhibited reduced nucleotides (phosphate, diphosphate, AMP and UDP) levels, accompanied by increased glucose and lactate (Figure 2H). These alterations are indicative of enhanced glycolytic flux and a concomitant shift toward pentose phosphate pathway (PPP) activity, consistent with our proteomic data, such as mitochondrial transcription factor A (Tfam), which was significantly decreased in pulmonary macrophages from Berk‐SS mice. A loss of Tfam has been associated with increased PPP flux [29]. Together, in combination with the data from Figure 1, these data support that the pulmonary Mϕs in Berk‐SS are primed towards glycolysis instead of the citric acid cycle and have alterations in adaptation to hypoxia, possibly leading to the increase of PH rates in SCD patients.

3.3. Berk‐SS Splenic Macrophages Recruited to PCLS Increase HMOX and Inflammatory Proteins Ex Vivo

Next, we wanted to determine if the microenvironment of the Berk‐SS lung expressed adhesion factors to recruit Mϕ at higher rates and, if so, how the presence of Mϕs altered the proteomic microenvironment of the lung. To do this, we employed a novel ex‐vivo model using precision cut lung slices (PCLS) and co‐culture with splenic Mϕs. Splenic Mϕs were used to minimize immune activation processes which can occur from isolating Mϕs and PCLS from different animals. Spleen‐derived Mϕs have also shown to be protective in the lung after ischemia‐reperfusion injury [30]. Figure 3A shows volcano plot analysis between C57BL/6 and Berk‐SS PCLS. Interestingly, RNA binding motif protein 3 (Rbm3), a protein which is upregulated in cellular stress situations such as hypoxia [31], was significantly increased in Berk‐SS PCLS in normoxic conditions. We also found that two adhesion molecules, platelet endothelial cell adhesion molecule 1 (PECAM1) and melanoma cell adhesion molecule (MCAM), were significantly increased in Berk‐SS PCLS in baseline conditions (Figure 3B). Both proteins are associated with Mϕ recruitment and activation. Next, we wanted to confirm if Berk‐SS PCLS recruit splenic Mϕs more frequently than C57BL/6 utilizing our co‐culture system. Figure 3C depicts culturing Mϕs with PCLS obtained from Berk‐SS mice were recruited at nearly 2 times the rate of C57BL/6 Mϕs. Collectively, these data support the notion that lungs from Berk‐SS mice are primed for Mϕ recruitment.

Figure 3.

Berk‐SS Splenic Macrophages Recruited to PCLS Increase HMOX and Inflammatory Proteins Ex Vivo. (A) Volcano plot analysis between precision cut lung slices (PCLSs) from C57BL/6 (n = 12 PCLS, n = 4 animals) or Berk‐SS mice (n = 12 PCLS, n = 4 animals). Dots in blue were downregulated in PCLS From Berk‐SS mice, while those shown in red were upregulated in PCLS from Berk‐SS. The darker the color, the more significant the change in that specific protein. (B) Bar plots showing peak intensities from platelet endothelial cell adhesion molecule 1 (PECAM1) and melanoma cell adhesion molecule (MCAM) from PCLS of C57BL/6 or Berk‐SS mice. Data was analyzed by a two‐tail t test and p < 0.04. (C) An ex vivo, co‐culture model of Mϕ with PCLS demonstrating a greater rate of recruitment of Mϕ to PCLS in tissue from Berk‐SS mice compared to C57BL/6 mice. **p < 0.01 *** p < 0.001. (D) Heatmap analysis of the top 25 proteins between Berk‐SS PCLS with or without co‐culture with Mϕs. Red squares signal increase expression and blue squares are decreased expression. (E) Bar plots of Hmox1 and Ly6C1 between Berk‐SS PCLS and Berk‐SS PCLS co cultured with Mϕs. Analysis was done by a two‐tail t test **p < 0.007.

Finally, we wanted to determine the proteomic contribution of recruited Mϕs. To this end, we performed proteomic analysis on Berk‐SS mouse PCLS with or without Mϕs recruitment. Figure 3D shows a heatmap of the top 25 altered proteins, revealing clear separation between Berk‐SS mouse PCLS alone vs Berk‐SS mouse PCLS + Mϕs, respectively. Among the top changes, heme oxygenase 1 (Hmox1) and lymphocyte antigen 6 complex C1 (Ly6c1) were highlighted due to their biological functions within heme stress and innate immune responses. Hmox1 enzymatically degrades heme into biliverdin, CO, and iron and is recognized as an anti‐inflammatory and antioxidant marker. While Ly6c1 is classically known as pro‐inflammatory factor, although recently it has been shown that that deletion of this gene via Crispr/Cas has no significant effects on immune cell populations [32]. Both Hmox1 and Ly6c1were elevated in Berk‐SS PCLS co‐cultures with Mϕ (Figure 3E). Collectively, these findings underscore how Mϕ recruitment alters the pulmonary microenvironment in Berk‐SS mice by modulating iron handling and promoting inflammatory responses. Full data sets are available in Supporting Tables 7 and 8.

3.4. Acute Hypoxic Exposure and Macrophage Recruitment (In Vivo)

It is recognized that Mϕs are critical to the progression of human PH [10, 11, 12], and in murine models of hypoxia PH, lung recruitment of Mϕs was observed within in the first few days of hypoxic exposure [33, 34, 35]. Thus, we sought to determine if hypoxia induced Mϕ recruitment would be more pronounced in Berk‐SS compared to C57BL/6 mice. Following a 72‐h hypoxic exposure (18,000 ft, Pb ~385 mmHg), flow cytometry analysis shows significantly more pulmonary monocytes, with both LyC6 low and high markers in Berk‐SS compared to C57BL/6 mice (Figure 4A–C). These data demonstrate that lungs of Berk‐SS vs C57BL/6 mice are critically primed for increased Mϕ recruitment and subsequent development of PH.

Figure 4.

Pulmonary Macrophage Recruitment is Greater in Berk‐SS Mice. (A) Berk‐SS pulmonary monocytes increased recruitment in vivo compared to C57BL/6 mice after 3 days of exposure to hypoxia (simulated 18,000 ft, Pb ~385 mmHg). C57BL/6 Nx n = 3, Hx n = 3. Berk‐SS Nx n = 5, Hx n = 4 (B) Berk‐SS mice have increased LyC6 low in vivo compared to C57BL/6 mice after 3‐day hypoxic exposure (simulated 18,000 ft, Pb ~385 mmHg). (C) Berk‐SS mice have increased LyC6 high in vivo compared to C57BL/6 mice after 3‐day hypoxic exposure (simulated 18,000 ft, Pb ~385 mmHg). Analysis was done by a two‐way ANOVA *p‐value < 0.05 **p‐value < 0.01.

3.5. Macrophage Depletion Attenuates the Progression of PH

3.5.1. Macrophage Depletion With Clodronate

Next, we sought to determine whether Mϕ depletion attenuated PH in our Berk‐SS model of SCD‐PH. First, we completed a pilot study to confirm our administered desired dose of clodronate (6.5 mg/kg) depleted Mϕ. To this end, we evaluated splenic Mϕ 3 days post‐administration. As expected, splenic Mϕ were depleted as evidenced by a reduction in the number of F4/80 stained cells (Supporting Figure 2A). Also, we noted no significant changes in T cells (CD4), B cells (B220), or dendritic cells (CD11c) between treated and untreated mice. These data demonstrate that, at this dose, clodronate toxicity is specific to Mϕs (Supporting Figure 2B–D). We also confirmed that F4/80+ cells were depleted in the lungs of clodronate treated mice (Supporting Figure 2E). We interpreted these results as weekly administration of clodronate is sufficient to prevent pulmonary Mϕ recruitment.

3.5.2. Exercise Tolerance

To begin to understand if Mϕ depletion attenuates PH in our murine model of SCD‐PH we first assessed exercise tolerance, as determined by critical speed (CS), as a marker for disease progression. CS in pre‐clinical mouse models is the most rigorous and reproducible approach to mimic the human 6‐min walk test to assess PH effects on exercise (in)tolerance. Figure 5A shows that after 10 weeks of moderate hypoxia, Berk‐SS mice have reduced exercise tolerance as compared to C57BL/6 mice. Supporting our hypothesis, Mϕ depletion nearly returned CS to that of C57BL/6 mice (VC 21.24 ± 1.17 meters•min⁻¹ vs. Clodronate 28.05 ± 1.16 meters•min⁻¹; p = 0.0005), suggesting that Mϕ depletion attenuates PH progression compared to untreated mice.

Figure 5.

Exercise Tolerance and Right Ventricular Function. (A) Exercise tolerance, as measured by critical speed, is decreased in Berk‐SS mice after 10 weeks of moderate hypoxia (simulated 8,000 ft, Pb ~568 mmHg, n = 9) when compared to C57BL/6 controls (n = 9). Weekly administration of clodronate (to deplete macrophages) increased significantly exercise tolerance (n = 9). Hematocrits (B) and heart rate (C) were not significantly altered between SCD‐PH (Berk‐SS VC) and macrophage depleted SCD‐PH (Berk‐SS Clod). (D) Cardiac output was significantly increased by ~29% with macrophage depletion (7.83 ± 0.45 mL•min^‐1 in VC vs 10.11 ± 0.91 in clodronate, p = 0.04). (E) Berk‐SS Clod increases stroke volume ~19% (19.01 ± 0.92 in VC vs 21.79 ± 1.82 μL, p = 0.09). (F) Macrophage depletion increased contractility (Ees) by ~50% (VC 0.72 ± 0.09 meters•min^‐1 vs. Clod 1.08 ± 1.13 meters•min^‐1; p = 0.03). (G) Ventricular‐to‐vascular coupling ratio (VVCR), driven by increase in contractility, is significantly increased in Berk‐SS Clod compared to Berk‐SS VC and returned to that of a C57BL/6 control mouse (VC 0.50 ± 0.08 vs Clod. 0.77 ± 0.11; p = 0.07). (H) RV stiffness (EDPVR), (I) ejection fraction, or (J) afterload (Ea) were not altered with macrophage depletion. White bars are C57BL/6 mice. Red Bars are vehicle control (VC) Berk‐SS mice. Blue bars macrophage depleted Berk‐SS mice. *p‐value < 0.05, ***p < 0.001, ****p < 0.0001, WT n = 13, Berk‐SS VC n = 12, Berk‐SS Clod n = 9 for hemodynamics.

3.5.3. Red Blood Cell Production

Due to exercise tolerance being driven by an increase in oxygen carrying capacity, which can be a result of improving either anemia or cardiopulmonary function (increased cardiac output), we evaluated red blood cell volume and heart rate. Clodronate did not affect the hematocrit or heart rate, suggesting that improvement in exercise tolerance was not a consequence of greater oxygen delivery from an improvement in anemia/hemolysis with a subsequent increase in hematocrit (Figure 5B,C).

3.5.4. Right Ventricular Hemodynamics

Since the improvement in exercise tolerance was not driven by an attenuation of hemolysis, we sought to understand how Mϕ reduction in Berk‐SS mice improved exercise tolerance by measuring PH characteristics – right ventricular (RV) hemodynamics. We found that Mϕ depletion in Berk‐SS mice increased cardiac output by 29% (7.83 ± 0.45 mL•min⁻¹ in VC vs 10.11 ± 0.91 in clodronate, p = 0.04; Figure 5D). This improvement was driven by a 19% increase in stroke volume (19.01 ± 0.92 in VC vs 21.79 ± 1.82 μL, p = 0.09, Figure 5E) and 50% increase in contractility (Ees) (VC 0.72 ± 0.09 meters•min⁻¹ vs. Clod 1.08 ± 1.13 meters•min⁻¹; p = 0.03 Figure 5F). Further, the ventricular‐to‐vascular coupling ratio (VVCR; Ees/Ea), a value demonstrating efficiency of blood flow from the right ventricle to the pulmonary artery, returned to that of C57BL/6 mice (VC 0.50 ± 0.08 vs Clodronate 0.77 ± 0.11; p = 0.07, Figure 5G). This process changing from an “uncoupled to coupled” heart was driven primarily by an improvement in contractility (Ees). Despite these improvements, Mϕ depletion to did not alter right ventricle stiffness (EDPVR), ejection fraction, or afterload (Ea) (Figure 5H–J).

3.5.5. Cardiopulmonary Function and Pulmonary Vascular Medial Thickening

Subsequently, we examined cardiac function indices to determine if the improvements in right ventricular function were a consequence of a healthier pulmonary vasculature. Congruent with an increase in cardiac output, pulmonary vascular resistance (PVR) was reduced by ~25% in Berk‐SS treated mice compared to VC cohorts (4.01 ± 0.23 VC vs 3.05 ± 0.24 Wood units; p = 0.01; Figure 6A). Additionally, further supporting the notion that Mϕ depletion improved cardiac function by preventing changes in the pulmonary vasculature, there was a reduction in pulmonary medial thickening in Berk‐SS treated mice compared to VC (Figure 6B,C). To this point, our study demonstrates Berk‐SS Mϕ's have a high affinity towards lung recruitment and play a critical role in the development and progression cardiopulmonary dysfunction in our Berk‐SS model of SCD‐PH, possibly through increasing medial thickening after recruitment.

Figure 6.

Pulmonary Function and Muscularization. (A) Pulmonary vascular resistance is decreased by ~25% in Berk‐SS Clod compared to Berk‐SS VC (4.01 ± 0.23 VC vs 3.05 ± 0.24 Wood units). (B) Micrographs of hematoxylin and eosin staining to show pulmonary medial thickening in SCD‐PH (Berk‐SS VC) and macrophage depleted SCD‐PH (Berk‐SS Clod). Berk‐SS Clod visually has significantly decreased medial thickening. (C) Quantification of pulmonary medial thickening in SCD‐PH (Berk‐SS VC) and macrophage depleted SCD‐PH (Berk‐SS Clod) emphasizing the decrease of pulmonary medial thickening in Berk‐SS Clod. White bars are C57BL/6 mice. Red Bars are vehicle control (VC) Berk‐SS mice. Blue bars macrophage depleted Berk‐SS mice. *p‐value < 0.05.

4. Discussion

It is well established that Mϕs play a critical role in the development and progression of pre‐capillary PH [6, 36, 37]. However, it is unique to SCD‐PH that pulmonary macrophage accumulation demonstrates erythrophagocytes with high iron content [16, 17, 38]. We hypothesized that the pulmonary adventitial microenvironment in a mouse model of SCD‐PH is uniquely primed for Mϕ recruitment and that disrupting this process attenuates PH. Supporting this hypothesis, data from both in vivo and ex vivo models demonstrate that greater numbers of Mϕs are recruited to the lungs of Berk‐SS mice compared to C57BL/6 mice. Furthermore, ten weeks of Mϕ depletion in moderately hypoxic Berk‐SS mice improved their exercise tolerance and right ventricular function. These findings suggest a critical role of phenotypically distinct Mϕs in SCD‐PH. This observation is supported by the multi‐omic phenotype analysis of recruited Mϕs obtained from in vivo studies, that demonstrated that Mϕ from Berk‐SS compared to C57BL/6 have a more robust “pro‐PH” phenotype. Concurrently, proteomic analysis from ex vivo PCLS further revealed that recruited Mϕs directly alters the lung phenotype demonstrating a cause (primed lungs) and effect (altered Mϕ phenotype) relationship. Collectively, these data suggest that both the microenvironment of the lung and Mϕs from Berk‐SS mice contribute to the development of PH.

Molecular mechanisms of SCD‐PH remain incompletely understood, however the present study demonstrates Mϕ depletion with clodronate liposomes improves critical speed, RV metrics and pulmonary muscularization and is in congruent with previous hemolytic PH models from our lab [6]. In the current study, the improvement in RV function is most likely due to a healthier, less remodeled pulmonary vasculature. This is evidenced by the decrease in pulmonary arterial thickening and pulmonary vascular resistance. Ntkokou et al also reported Mϕ depletion reduced pulmonary muscularization in a murine PH model through a Mϕ derived plate‐derived growth factor B (PDGF‐B) mechanism [39]. While not within the scope of our study, it will be important to understand if a Mϕ dependent PDGF‐B pathway is driving pulmonary vascular disease in our model as well. The alterations in metabolites from Berk‐SS and C57BL/6 pulmonary Mϕ was a noteworthy and appears to be consistent with a chronically altered immune system [27] accompanied by increased oxidative stress in SCD patients [38, 40, 41].

While it is recognized that Mϕ's are critical to other types of PH disease progression, such as hypoxia [42, 43, 44] and schistosomiasis induced PH [45], our study now confirms that Mϕs are a key cell type in a Berk‐SS mouse model of SCD‐PH. More data is emerging that suggests Mϕ involvement is universal across multiple forms of PH and that SCD‐PH is associated with iron rich Mϕs. This information suggests new therapeutic targets to attenuate SCD‐PH, such as blocking Mϕ recruitment to the lung or the blocking of downstream processes, such as iron transport into the lung microenvironment. Further, understanding how Mϕ drives pulmonary vascular disease may also lead to therapeutic options focusing on adaptive immune cells (B and T cells) which are directly influenced by Mϕs and implicated in various forms PH [46].

Here, we utilized a low dose of clodronate liposomes compared to other preclinical studies investigating Mϕ depletion in PH. We rationalized this dose on the basis that Berk‐SS mice are immunocompromised, which may be detrimental to their overall health when exposed to common pathogens in the colony. Despite this, our dose remained effective at attenuating PH. Future studies will need to be conducted with a higher dose of clodronate to determine whether a higher depletion rate of Mϕ and dendritic cells further protects against PH progression at the expense of severely immunocompromising Berk‐SS mice.

In conclusion, pulmonary Mϕs from Berk‐SS mice exhibit a distinct phenotype compared to those from C57BL/6 mice. Functionally, Mϕ are recruited to the lung at higher rates and exist in a reactive metabolic state. Weekly doses of clodronate for 10 weeks corrected cardiopulmonary dysfunction and pulmonary vascular remodeling. Hemodynamic assessment revealed improvements in cardiac output, stroke volume, pulmonary vascular resistance, myocardial contractility, and ventricular‐vascular coupling. We propose that the reduction in pulmonary vascular muscularization, resulting from Mϕ depletion with clodronate, permits downstream improvements in cardiac function. Taken together, these data emphasize that specific Mϕ subsets represent an important cellular driver of SCD‐PH pathogenesis.

5. Clinical Relevance

The World Health Organization currently classifies SCD‐PH as group 5 pulmonary hypertension, which remains the “catch‐all” category for PH. Our recent paper, “Iron, arginine, and redox metabolism in peripheral blood mononuclear cells distinguishes sickle cell disease and pulmonary hypertension,” identified metabolic and proteomic differences between PH and SCD‐PH. With continued studies such as ours, we may be able to identify novel therapeutics for patients with SCD‐PH, for whom traditional PH medicines are ineffective.

Author Contributions

Concept or design – Christina Lisk, Gemlyn George, Paul W. Buehler, David C Irwin. Acquisition of the data – Francesca Cendali, Natalie Westover, Delaney Swindle, Daniel Colon Hidalgo, Christina Lisk, Nishant K. Rana, Saini Setua, Monika Dzieciatkowska, Angelo D'Alessandro. Analysis of the data – Christina Lisk, Natalie Westover, Delaney Swindle, Daniel Colon Hidalgo, Christina Lisk, Melissa J. Lucero, Monika Dzieciatkowska, Christy S. Niemeyer, David C Irwin, Eva Nozik. Interpretation of the data – Christina Lisk, Francesca Cendali, Daniel Colon Hidalgo, Monika Dzieciatkowska, Christina Lisk, Kathryn Hassel, Kurt Stenmark, Paul W. Buehler, David C Irwin, Eva Nozik. Drafting the work – Christina Lisk, Francesca Cendali, Natalie Westover, Daniel Colon Hidalgo, Gemlyn George, Christy S. Niemeyer, Angelo D'Alessandro, David C Irwin. Critically reviewing the work – Francesca Cendali, Delaney Swindle, Daniel Colon Hidalgo, Melissa J. Lucero, Nishant K. Rana, Saini Setua, Christina Lisk, Monika Dzieciatkowska, Kathryn Hassel, Christy S. Niemeyer, Kurt Stenmark, Angelo D'Alessandro, Paul W. Buehler, David C Irwin, Eva Nozik. Final approval and agreement to be accountable for all aspects of the work – Christina Lisk, Francesca Cendali, Natalie Westover, Delaney Swindle, Daniel Colon Hidalgo, Christina Lisk, Melissa J. Lucero, Nishant K. Rana, Gemlyn George, Saini Setua, Monika Dzieciatkowska, Kathryn Hassel, Christy S. Niemeyer, Kurt Stenmark, Angelo D'Alessandro, Paul W. Buehler, David C Irwin, Eva Nozik.

Ethics Statement

All experimental procedures were conducted under the guidelines recommended by The Journal of Physiology, the National Institutes of Health, and were approved by the Institutional Animal Care and Use Committee at the University of Colorado Anschutz Medical Campus.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Sharing

The data that support the findings of this study are available in the supplementary material of this article.

Supporting information

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Supporting File 10

Lisk C., Cendali F., Westover N., et al., “Macrophages Contribute to Pulmonary Hypertension Associated With Sickle Cell Disease,” Pulmonary Circulation 16 (2026): e70413, 10.1002/pul2.70413.

Data Availability Statement

The data that supports the findings of this study are available in the supplementary material of this article.