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[Preprint]. 2024 Apr 8:rs.3.rs-4207678. [Version 1] doi: 10.21203/rs.3.rs-4207678/v1

Adam19 Deficiency Impacts Pulmonary Function: Human GWAS Follow-up in Mouse

Huiling Li 1, John House 2, Cody Nichols 3, Artiom Gruzdev 4, James Ward 5, Jian-Liang Li 6, Annah Wyss 7, Ezazul Haque 8, Matthew Edin 9, Susan Elmore 10, Beth Mahler 11, Laura Degraff 12, Min Shi 13, Darryl Zeldin 14, Stephanie London 15
PMCID: PMC11042436  PMID: 38659817

Abstract

Purpose

Over 550 loci have been associated with human pulmonary function in genome-wide association studies (GWAS); however, the causal role of most remains uncertain. Single nucleotide polymorphisms in a disintegrin and metalloprotease domain 19 (ADAM19) are consistently related to pulmonary function in GWAS. Thus, we used a mouse model to investigate the causal link between Adam19 and pulmonary function.

Methods

We created an Adam19 knockout (KO) mouse model and validated the gene targeting using RNA-Seq and RT-qPCR. Contrary to prior publications, the KO was not neonatal lethal. Thus, we phenotyped the Adam19 KO.

Results

KO mice had lower body weight and shorter tibial length than wild type (WT). Dual-energy X-ray Absorptiometry indicated lower soft weight, fat weight, and bone mineral content in KO mice. In lung function analyses using flexiVent, compared to WT, Adam19 KO had decreased baseline respiratory system elastance, minute work of breathing, tissue damping, tissue elastance, and forced expiratory flow at 50% forced vital capacity but higher FEV0.1 and FVC. Adam19 KO had attenuated tissue damping and tissue elastance in response to methacholine following LPS exposure. Adam19 KO also exhibited attenuated neutrophil extravasation into the airway after LPS administration compared to WT. RNA-Seq analysis of KO and WT lungs identified several differentially expressed genes (Cd300lg, Kpna2, and Pttg1) implicated in lung biology and pathogenesis. Gene set enrichment analysis identified negative enrichment for TNF pathways.

Conclusion

Our murine findings support a causal role of ADAM19, implicated in human GWAS, in regulating pulmonary function.

Keywords: meltrin beta, RNA-Seq, lung function, flexiVent, spirometry, inflammation

Introduction

Spirometric measures of lung function are routinely used in clinical medicine to diagnose chronic obstructive pulmonary disease (COPD) and monitor its severity along with asthma and other lung diseases. Lower function is related to mortality independently of other risk factors [1]. Human genome-wide association studies (GWAS) have identified genetic variants in over 550 genes related to pulmonary function [2]. Among these, variants in a disintegrin and metalloproteinase domain 19 (ADAM19) have been consistently associated with forced expiratory volume in the first second (FEV1) [3, 4], the ratio of FEV1 to forced vital capacity (FVC) [13, 58], peak expiratory flow (PEF) [3, 4], and COPD [9, 10]. However, while GWAS is powerful for identifying genetic associations, it cannot assign causality. Therefore, we followed up on these human GWAS findings using mouse models.

ADAM19 protein is primarily membrane-bound in various tissues and is expressed in the lung [11, 12]. It functions by shedding proteins, such as tumor necrosis factor (TNF), from the cell membrane by activating the catalytic site in its exon 11 [1315]. Shed proteins can trigger signal transduction and regulate inflammation and other pathological processes [1618].

The original study of genetic disruption of Adam19 in mice showed it to be essential for cardiac development [19]; mice deficient in Adam19 exons 10–12 exhibited severe cardiac defects, with only 5% surviving to postnatal day 8. Therefore, expecting early lethality and lack of specific ADAM19 antibodies, we created a reporter mouse by replacing exons 6 and 7 in Adam19 with a tdTomato red gene construct. We expected the heterozygous reporter mouse to be viable and thus usable to visualize the tissue distribution of ADAM19 and study the role of Adam19 in organogenesis, especially of the lungs. Mice with homozygous Adam19-tdTomato alleles are equivalent to Adam19 knockout (KO); surprisingly, they were viable. Thus, we performed RNA sequencing (RNA-Seq) and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to validate the knockout of Adam19. We confirmed the knockout and measured pulmonary function in adult Adam19 KO mice and WT controls. We also measured body weight, tibial length, and body composition. Further, given the involvement of Adam19 in inflammation, we examined whether genetic deficiency of Adam19 affects airway responsiveness and the immune cell profile of bronchoalveolar lavage fluid (BALF) following LPS administration. Some of the results from these studies were previously presented as an abstract [20].

Materials and Methods

Detailed methods are in the online supplementary information.

Adam19 Gene Targeting Scheme and Murine Studies

Adam19 exons 6 and 7 were replaced with an in-frame tdTomato construct. The homozygous Adam19-tdTomato allele is equivalent to the Adam19 KO (Fig. 1A).

Figure 1. Gene targeting scheme (A) for Adam19-tdTomato allele and validation by RNA-Seq (B).

Figure 1

A. Adam19 WT: Endogenous wild-type locus. Adam19 Flox: Adam19 conditional null (“flox”) allele with exon 6 and 7 floxed by LoxP sites (solid yellow triangles). Adam19-tdTomato: Adam19 mutant allele in which exons 6 and 7 are replaced by the tdTomato construct, disrupting Adam19 gene expression. Homozygosity for Adam19-tdTomato alleles is equivalent to Adam19 knockout (KO). Each blue box represents an exon; the exon number is underneath. pA: polyA; hygroR: Hygromycin Resistance. CAG: CMV enhancer, chicken beta-Actin promoter, and rabbit beta-Globin splice acceptor site. B. Read densities of Adam19 exons and junctions in WT and KO mice by RNA-Seq analysis. The blue boxes represent exons. In the Adam19 KO, exons 6 and 7 were replaced by the tdTomato construct and showed minimal transcript expression from exon 8 through the end of the Adam19 gene. Bold orange or bold purple regions represent aggregate sequence read depth across the Adam19 WT (left panel) or KO (right panel) gene locus. Light orange or light purple arcs indicate sequence reads whose alignments represent observed splice junctions. The arc width indicates the aggregate number of junction reads. No in-frame splicing events were detected from exon 5 to any downstream Adam19 exons. n=3 mice per genotype per heart or lung tissue.

Mice in this study were all males aged 9–13 weeks with 129S6/SvEvTac background, confirmed by MiniMUGA genome genotyping arrays [21], performed by Transnetyx, Inc. (Cordova, TN). The use of animals followed NIH guidelines and was approved by the NIEHS Animal Care and Use Committee.

RNA-Seq and RT-qPCR

Strand-specific RNA-Seq was conducted on Illumina NextSeq. Sequence coverage was visualized with sashimi plots [22]. The absence of Adam19 transcript in KO was validated by both RNA-Seq and RT-qPCR.

Differential Gene Expression and Gene Set Enrichment Analysis

RNA transcript reads were quantified versus GENCODE vM33 comprehensive transcripts (mm39) using Salmon 1.10.0 [23]. Differential gene expression was performed by limma-voom 3.54.2 [24], using thresholds for false discovery rate (FDR)-adjusted p < 0.05, fold change ≥ 1.5, and a group mean normalized transcript abundance ≥ 6 in at least one sample group.

We used the gene set enrichment analysis (GSEA) [25] to identify significantly enriched pathways (FDR p < 0.25) for genes differentially expressed between Adam19 WT and KO by RNA-Seq datasets. The analysis was conducted using the Broad Molecular Signature Database (MSigDB, v2023.2.Mm) hallmark gene sets collection.

Embryo Organogenesis

E18.5 embryos were collected, sectioned sagittally (5 μm thickness), and stained with hematoxylin and eosin. A pathologist (SAE) evaluated the tissue sections, focusing on the cellular structure of the heart, lung, valves (heart, aortic, and pulmonary), adrenal glands, and diaphragm.

Assessment of Body Weight, Tibia Length, and Body Composition

Body weight was measured using a top-loading scale with an accuracy of 0.01 g. Tibia length was measured with a ruler with an accuracy of 0.1 cm. Body composition parameters [26] were assessed using the Faxitron Dual-energy X-ray Absorptiometry (DXA) imaging system.

Pulmonary Function Parameter Measurements in Mice

Pulmonary function parameters were measured using flexiVent FX2 with a negative pressure-driven forced expiratory extension. Baseline measurements and responses to methacholine doses were assessed [27, 28]. For LPS experiments, mice received LPS or saline via oropharyngeal aspiration (OPA). After four hours, lung function parameters were measured using the same flexiVent procedure.

Immune Cell Profile and Cytokine Analysis in BALF in LPS Exposed Mice

BALF was collected from each mouse by rinsing the airways [27]. We counted cells using an automated cell counter and determined the percentage of different immune cell types from cytospin slides. For LPS experiments, mice received LPS or saline via OPA and were euthanized after 4 hours. BALF was then collected and analyzed as described above. Cytokine concentrations (IL-1b, IL-2, IL-6, KC, MCP-1, MIP-1a, MIP-1b, and TNF-a) were determined using a custom Bio-Plex Pro Mouse Cytokine 8-plex assay.

Statistical Analyses

We conducted linear regression analyses to assess genotype differences in body weight, body composition parameters, and tibia length. Genotype differences in lung function parameters were analyzed at baseline using a general linear model, and the maximum response to methacholine doses (normalized to response to PBS aerosol) was analyzed using a linear mixed-effect model with a random intercept. Differences in dose-response slope changes by LPS were assessed between genotypes. All lung function parameters were adjusted for body weight. Changes in cell counts of each immune cell type (except eosinophils present in just one mouse) across genotypes following LPS exposure were analyzed using linear regression. Linear regression with a robust sandwich estimator was used for cytokine data analysis. We used R version 4.2.2 to run statistical analyses and plots.

Results

Gene Targeting Scheme and Validation for Adam19 KO Mouse

We replaced the Adam19 exons 6 and 7 with the dTomato red gene open reading frame and anti-sense Hygromycin resistance (HygroR) cassette (Fig. 1A). RNA-Seq confirmed the absence of Adam19 transcript encoding the active catalytic site of the functional protein. In both heart and lung, Adam19 mRNA expression was minimal from exon 8 through 23 in KO mice (Fig. 1B and S1). Small amounts of exon 5 to exon 8 splicing transcripts were observed in the lung but not the heart in KO mice (Fig. 1B).

The detailed gene transcript structure in the heart and lung (WT and KO), derived from RNA-Seq analysis, is shown in Fig. S1 (available via the NIEHS-hosted track hub in the UCSC Genome Browser using the URL:https://bit.ly/adam19tdt). The RNA-Seq data discussed here were deposited in NCBI’s Gene Expression Omnibus [29] under the accession number GSE183318 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE183318, reviewer token: ubgnmiignvgnbix).

Follow-up analysis with RT-qPCR (TaqMan and SYBR Green assays) confirmed the absence of Adam19 mRNA expression from exon 6 through 23 in both heart and lung in the KO mice (Fig. S2), additionally validating the absence of exon 11, which encodes the active catalytic site of the ADAM19 protein [19].

Because sufficiently specific ADAM19 antibodies were unavailable, we created the Adam19-tdTomato reporter mouse model to visualize the tissue distribution of ADAM19. However, we could not detect fluorescence from the ADAM19-tdTomato fusion protein, possibly due to tdTomato protein misfolding. Nevertheless, we detected tdTomato mRNA transcripts (Fig. S2) and protein (data not shown) in the knockout lung tissue. The Adam19 transcript from the KO contains only the first five exons, representing only 12% (333 nucleotides) of the full-length Adam19 open reading frame (2760 nucleotides).

Differential Gene Expression and Gene Set Enrichment Analysis

Differential gene expression analysis revealed few significant changes in gene expression patterns in the lungs of KO compared to WT mice. We observed increased expression of pituitary tumor-transforming gene 1 (Pttg1), karyopherin subunit alpha 2 (Kpna2), and CD300 molecule like family member g (Cd300lg) in KO lungs. (Table 3). Other genes in KO that have increased expression include Rpl14-ps1, Gm21970, and Gm11131. (Table 3). The KO lungs had decreased AA465934, Gm18860, Gm12663, and Gm10184. Consistent with expectation, the WT mice did not exhibit the Adam19-tdTomato fusion gene expression.

Table 3.

Differentially Expressed Genes in Adam19 KO versus WT Mouse Lungs Based on RNA-Seqa

Gene Name Fold Change Adjusted p-valuea MGM
Rpl14-ps1 797.9 0.0247 10.64
Gm21970 396.4 0.0162 9.63
Gm11131 33.0 0.0138 6.04
Pttg1 16.3 0.0006 9.32
Kpna2 8.8 0.0291 9.10
Cd300lg 5.4 0.0474 7.47
AA465934 −15.1 0.0044 6.59
Gm18860 −32.1 0.0474 6.01
Gm12663 −55.2 0.0007 6.53
Gm10184 −426.8 0.0138 9.74

MGM means maximum group mean (the highest normalized group mean abundance for each gene)

a

Considered statistically significant if false discover rate adjusted p<0.05, the absolute value of fold change ≥h1.5 (positive fold change means increase and negative fold change means decrease), and MGM ≥G6. The table was sorted by fold change descending; n=3 per genotype.

Gene set enrichment analysis of genes differentially expressed between Adam19 KO and WT in the lung revealed enrichment for signaling pathways, including MYC_targets_v1, oxidative_phosphorylation, E2F_targets, unfolded_protein_response, protein_secretion, TNFA_signaling_via_NFkB, G2M_checkpoint, DNA_repair, and mitotic_spindle (Table S1).

Table 1.

Body composition parameter values by genotype as shown in Fig.2C-L

WT (n=10) KO (n=9)
Parameters Mean SD Mean SD p-value
Body Weight (g) 24.4 1.7 20.6 1.8 2.03e-04
Sample Area (cm 2 ) 24.0 1.3 20.9 1.6 2.18e-04
Bone Area (cm 2 ) 10.3 1.4 9.0 1.2 0.053
Total Weight (g) 26.3 1.9 22.4 1.9 0.0004
Soft Weight (g) 25.5 1.9 21.7 1.8 0.0004
Lean Weight (g) 18.3 2.5 16.4 0.9 0.056
Fat Weight (g) 7.2 1.3 5.3 1.4 0.011
Fat Percent (%) 28.3 6.2 24.3 4.5 0.135
BMC (g) 0.8 0.1 0.7 0.1 0.023
BMD (mg/cm 2 ) 75.6 3.9 72.3 3.1 0.074

SD: standard deviation; BMC: Bone Mineral Content; BMD: Bone Mineral Density = BMC/(Bone Area); Total Weight = Soft Weight + BMC; Soft Weight = Lean Weight + Fat Weight; Fat Percent = (Fat Weight)/(Soft Weight) in percentage. The p-values were based on linear regression adjusting for age.

Embryo Organogenesis

A pathologist evaluated three E18.5 KO embryos and two E18.5 WT littermates for tissue or organ abnormalities and did not identify lesions associated with tetralogy of Fallot in the heart (overriding aorta, pulmonic stenosis, ventricular septal defect, and right ventricular hypertrophy) as previously reported [19, 30] nor abnormalities in the lungs, diaphragms, and adrenal glands (Fig. S3).

Reduced Body Weight, Shorter Tibial Length, and Altered Body Composition in Adam19 KO Mice

We weighed 114 WT and 104 KO mice at 9–13 weeks. Age-adjusted body weight (Fig. 2A) was significantly lower in Adam19 KO than in WT mice. WT mice continued gaining weight through the assessment period, while the KO stopped gaining weight at nine weeks (Fig. S5). Tibia length was shorter in KO than in WT (20 KO and 24 WT) (Fig. 2B). Using DXA, we measured body composition on 10 KO and 10 WT mice 9.9 to 13.1 weeks and subsequently excluded one outlier KO. In addition to the lower body weight (Fig. 2C), compared to WT, KO had reduced sample area (Fig. 2D), bone area (Fig. 2E), total weight (Fig. 2F), soft weight (Fig. 2G), lean weight (Fig. 2H), fat weight (Fig. 2I), and bone mineral content (BMC) (Fig. 2K). There were no significant differences in %fat (Fig. 2J) or bone mineral density (BMD) (Fig. 2L). Values for body weight and body composition plotted in Figure 2 are shown in Table 1.

Figure 2. Adam19 KO mice have reduced body weight, shorter tibia length, and altered body composition.

Figure 2

A. Body weight measured using a top-loading scale (WT: n=114, KO: n=104). B. Tibia length measured using a ruler (WT: n=24, KO: n=20). C: Body weight of mice for measuring body composition. D-L: Body composition parameters obtained using Dual-energy X-ray Absorptiometry (WT: n=10, KO: n=9). Total weight = soft weight + bone mineral content (BMC), soft weight = lean weight + fat weight, Fat % = fat weight/soft weight in percentage, BMD = bone mineral density = BMC/bone area. p values < 0.05 for differences in the parameter by genotype are displayed (A-L).

Pulmonary Function Parameters Altered in Adam19 Deficient Naïve Mice.

We measured baseline lung function in 37 mice (22 WT and 15 KO). Adam19 KO mice exhibited reduced elastance of the respiratory system (Ers), minute work of breathing (mWOB), tissue damping (G), and tissue elastance (H) (Fig. 3A). Additionally, forced expired flow at 50% FVC (FEF50) was lower in the KO compared to WT mice (Fig. 3B). However, KO had higher FEV0.1 and FVC (Fig. 3B). No genotype differences were observed in resistance of the respiratory system (Rrs) or Newtonian resistance (RN) (Fig. 3A) nor FEV0.1/FVC, PEF or FEV_ PEF (Fig. 3B). Additionally, airway responsiveness to methacholine did not differ by genotype (Fig. S6). The means and standard deviations of lung function parameters are shown in Table 2.

Figure 3. Adam19 deficiency alters (A) baseline mechanics and (B) spirometry parameters determined by flexiVent.

Figure 3

n=22 for WT, n=15 for KO. Rrs=resistance of the respiratory system; Ers=elastance of the respiratory system; mWOB=minute work of breathing (the work required to breath-in on a minute basis); J=joule (one joule is the work required to move 1 liter of gas through a 10-cmH2O pressure gradient). RN=Newtonian resistance; G=tissue damping; H=tissue elastance; FEV0.1=forced expiratory volume in 0.1 s; FVC=forced vital capacity; FEV0.1/FVC = the ratio of FEV0.1 over FVC in %; FEF50=Forced expiratory flow at 50% FVC; PEF=Peak expiratory flow; FEV_PEF=Forced expiratory volume at peak expiratory flow. p<0.05 for differences in the parameter by genotype are displayed.

Table 2.

Mean and standard deviation of baseline lung function values by genotype as shown in Fig. 3

WT (n=22) KO (n=15)
Parameters Mean SD Mean SD p-value
Mechanics
Rrs (cmH2O.s/mL) 0.79 0.13 0.71 0.08 0.0542
Ers (cmH2O/mL) 36.98 6.33 31.64 3.37 0.0016
mWOB (J/L.min) 125.36 9.94 112.83 5.77 0.0064
Rn (cmH2O.s/mL) 0.20 0.06 0.22 0.06 0.8867
G (cmH2O/mL) 6.44 1.09 5.73 0.73 0.0169
H (cmH2O/mL) 33.13 5.27 27.9 3.52 0.0007
Spirometry
FEV0.1 (mL) 0.81 0.10 0.84 0.06 0.0218
FVC (mL) 0.90 0.12 0.93 0.09 0.0104
FEV0.1/FVC (%) 90.18 2.77 90.23 3.61 0.4564
FEF50 (mL/s) 20.61 4.63 15.97 3.20 0.0172
PEF (mL/s) 30.10 3.88 30.42 1.85 0.653
FEV_PEF (mL) 0.24 0.08 0.22 0.04 0.7124
Age and Weight
Age (wk) 10.2 0.7 10.5 0.7 0.205
Body Weight (g) 23.3 2.0 21.3 2.5 0.0118

SD-Standard Deviation; Rrs=resistance of the respiratory system; Ers=elastance of the respiratory system; mWOB=minute work of breathing (the work required to breathe in on a minute basis); J=joule (one joule is the work required move 1 liter of gas through a 10-cmH2O pressure gradient); RN=Newtonian resistance; G=tissue damping; H=tissue elastance; FEV0.1=forced expiratory volume in 0.1 s; FVC=forced vital capacity; FEV0.1/FVC = the ratio of FEV0.1 over FVC in %; FEF50=Forced expiratory flow at 50% FVC; PEF = Peak expiratory flow; FEV_PEF=Forced expiratory volume at peak expiratory flow.

Airway responsiveness to methacholine attenuated in Adam19 Deficient Mice exposed to LPS.

Adam19 has been shown to promote inflammation in prior literature [17, 18, 31]. Therefore, we assessed genotype differences in airway responsiveness induced by LPS. We did not detect differences in LPS effects (vs. saline) across genotypes for baseline lung function parameters (Fig. S7). However, LPS-induced differences (vs. saline) in the slope estimates for the methacholine dose-response curves were lower in KO than WT for tissue damping (G) and tissue elastance (H) (Fig. 4).

Figure 4. Adam19 deficient mice have reduced airway responsiveness to methacholine following LPS exposure.

Figure 4

The maximum response to methacholine at each dose was expressed as a percentage of the maximum response at PBS. Means and standard errors of means are indicated as bar lines. Rrs=resistance of the respiratory system; Ers=elastance of the respiratory system; mWOB=minute work of breathing; RN=Newtonian resistance; G=tissue damping; H=tissue elastance; BL=baseline; PBS=phosphate buffered saline. *p values ≤ 0.05 are shown for the genotype difference of the slope difference of the response to methacholine following LPS exposure (vs. saline). n=13 for WT-Saline, n=20 for WT-LPS, n=14 for KO-Saline, n=21 for KO-LPS

Immune Cell Differential Analysis in BALF in Mice Following LPS Exposure

As expected, counts of total cells and neutrophils increased in WT and KO mice following LPS exposure. However, the degree of increase in neutrophil counts was lower in KO than in WT (46% fewer cells, p=0.032, Fig. 5C). Similarly, the degree of increase in total cells was lower in the KO compared to WT (Fig. 5A). These results suggest that the Adam19 KO mice show reduced responsiveness to LPS compared to WT regarding immune cell profiles. There were no genotype differences in LPS-induced changes in macrophage or lymphocyte counts (Fig. 5B, 5D).

Figure 5. Analysis of differential immune cell counts in bronchoalveolar lavage fluid (BALF) in mice following LPS exposure.

Figure 5

Increases in neutrophil number (C) induced by LPS (vs. saline) were lower in Adam19 KO than in WT mice (46% fewer cells, p=0.032). The degree of increase in total cells (A) following LPS (vs. saline) was lower in KO (the ratio of the LPS effect between the KO and WT = 0.61, 95% confidence interval (CI) = 0.36–1.02, p=0.058). No genotype differences of LPS effects were identified for macrophages (B) and lymphocytes (D). SAL=saline, WT: n=10 (SAL), 10 (LPS); KO: n=7 (SAL), 8 (LPS).

Cytokine Analysis in BALF in Naïve and LPS Exposed Mice

As expected, we observed increases in several inflammatory cytokines in response to LPS vs. saline (IL-6, KC, MCP-1, MIP-1a, MIP-1b, and TNF-a); these did not differ by genotype (Fig. S8). IL-1b and IL-2 levels in all mice were below the detection range (not shown).

Discussion

Adam19 has been consistently associated with pulmonary function in human GWAS. However, GWAS alone cannot establish causality. Mouse models are useful in investigating the causal role of loci identified in GWAS in pulmonary function. We successfully generated a novel Adam19 knockout mouse model and confirmed gene disruption through RNA-Seq and RT-qPCR analysis. Contrary to previous publications, our KO mice are viable and generally healthy, without the lethal cardiac abnormalities reported in earlier studies [19, 30].

We considered factors potentially contributing to the discrepancy in the viability of our KO compared to prior work [19, 30]. Firstly, methods for producing the knockout differed between studies. Kurohara et al. [19] replaced exons 10 through 12 with an antisense Neomycin resistance cassette, and Zhou et al. [30] introduced a gene trap 3’ of exon 14. We replaced exons 6 and 7 with an in-frame tdTomato construct.

Second, genetic disruption of a multi-exon locus, like Adam19, may generate novel transcript variants through alternative splicing, some of which may result in a neomorph that rescues ADAM19 deficiency. In contrast, others may be potentially toxic in the absence of ADAM19. Our RNA-Seq analysis was designed to detect alternative splice variants but identified no alternative Adam19 splice variants and no active transcription from exons 8 through 23. Interestingly, we detected a novel splice variant in the lung, splicing from exon 5 to exon 8. However, this transcript led to a near-immediate nonsense mutation. Thirdly, the remaining gene structure in a knockout might influence its interaction with other genes or proteins, leading to different functional consequences. Our knockout mice expressed only the first five exons of Adam19, which do not include the sequences that encode the active catalytic sites of ADAM19. Transcriptions of exons 8 through 23 were nearly absent, providing confidence that no functional ADAM19 metalloproteinase domains were formed. While both genetic constructs in previous studies [19, 30] disrupt metalloprotease function, they may have generated truncated ADAM19 proteins that could interact with other proteins in a non-productive or dominant-negative manner.

Additional explanations for differences in the viability of the KO across studies include differences in the genetic background of the mouse lines used. Our Adam19-deficient allele was generated in 129S ES cells and subsequently maintained on the 129S6/SvEvTac background, whereas the other studies used mice with a mixed genetic background of 129Sv and C57BL6/J [19, 30]. Further, in the prior work, there was variability in the penetrance of the observed cardiac phenotypes. In Kurohara’s ADAM19-deficient line, some mice survived to adulthood without severe cardiac defects besides enlarged hearts [19]. Partial penetrance of lethal phenotypes is common, so this phenotype variability is not surprising. However, it does suggest that the genetic disruption of Adam19 is more complex than initially envisioned during our gene targeting design.

We do not know why our Adam19-deficient mice were viable without the noticeable cardiac defects observed in prior work [19, 30]. However, all available evidence and data strongly indicate that we had a functional knockout of the canonical ADAM19 protein. Our knockout mice unlikely retained ADAM19 activity, given that exons 1 to 5 only encode for the first 111 of 920 amino acids of canonical ADAM19 protein but none of the active sites of metalloproteinase domains. In addition, Adam19’s first five exons appear to have higher expression in heart and lung samples in KO than wildtype, possibly caused by either a feedback mechanism attempting to compensate for functional loss of Adam19 or by the absence of appropriate 3’ UTR elements for the consistent transcript turnover in mutant samples or both.

Our Adam19 KO animals exhibited several notable phenotypic differences compared to their WT littermates, including reduced body weight, decreased tibia length, and altered body composition. Inoue et al. reported that Adam19 was involved in osteoblast differentiation in mice [32], which may help explain why our Adam19 knockouts have shorter tibias. Weerasekera et al. demonstrated a correlation between high ADAM19 expression in human peripheral blood mononuclear cells and BMI, relative fat, and TNF levels [31]. They also observed increased Adam19 mRNA and ADAM19 protein in the liver tissue of mice fed a high-fat diet (HFD). In contrast, neutralizing ADAM19 protein with its antibody resulted in weight loss, reduced white fat accumulation, and decreased TNF protein levels in the liver of HFD-fed mice. These published findings provide insights into our observations of smaller body sizes, reduced body weight, and altered body compositions. In addition, our differential gene expression and GSEA results revealed some supporting clues. Kpna2 is associated with body weight and BMI in human GWAS [33]. We observed decreased Kpna2 expression in our KO. Decreased Cd300lg expression is associated with increased intramyocellular lipid content and reduced fasting forearm glucose uptake by regulating metabolism in humans [34]. Our knockout mice had increased Cd300lg expression, indicating its role in reducing body weight and composition. Our GSEA exhibited the enrichment of differentially expressed genes in multiple pathways related to cell proliferation and metabolism, which could partially explain the anthropometric phenotype in our KO. Collectively, our data support the role of ADAM19 in regulating growth and body weight development.

From human GWAS, it is impossible to predict the direction of effect that knocking out Adam19 would have on lung function in mice. Human GWAS have identified hundreds of single nucleotide polymorphisms (SNPs) in or near ADAM19, significantly associated with lung function [2, 3, 5, 7, 9, 10, 3537]. Although the minor alleles of sentinel SNPs have been associated with lower FEV1/FVC and FEV1 and increased risk of COPD, the minor allele of other genome-wide significant variants was associated with higher FEV1/FVC and FEV1 [2, 3, 5, 7, 9, 10, 3537]. Hundreds of ADAM19 variants also implicate significant expression quantitative trait loci in lung tissue from Genotype-Tissue Expression (GTEx), with associations including increased and decreased expression depending on the variant (the GTEx Portal: https://gtexportal.org/home/ was accessed 30 September 2023). Given the large number of ADAM19 variants associated with lung function, gene expression, and the range of effects for individual SNPs, it is impossible to identify a single causal variant or the overall direction of effect across associated variants. This is a known limitation of GWAS [38], highlighting the importance of follow-up research using mouse models.

Critical to comparison with human GWAS, the Adam19 KO mice also displayed altered baseline pulmonary function parameters, namely decreased elastance of the respiratory system, minute of work of breathing, tissue damping, tissue elastance, and declined forced expiratory flow at 50% forced vital capacity, as well as increased FEV0.1 and FVC. Because our KO had a lower body weight, which may affect lung function, we adjusted all statistical analyses of lung function parameters for weight. Our data provide compelling evidence for the causal role of ADAM19 in pulmonary function, confirming the findings observed in human GWAS. However, the precise molecular mechanisms underlying these observations remain unknown. ADAM19 cleaves NEUREGULIN-1 (NRG1), an erythroblastic leukemia viral oncogene homolog (ERBB) receptor tyrosine kinases ligand. ERBB receptor ligands NRG1 and epidermal growth factor affect fetal surfactant synthesis in the developing mouse lungs [39].

Moreover, ADAM19 has been implicated in non-proteolytic functions, such as regulating neuromuscular junctions in murine embryos through Eph family receptor-interacting proteins (EPHRIN)-A5/EPHRIN-A4 signaling [40]. In addition, the cytoplasmic tail of ADAM19 has several Src homology 3 (SH3) binding sites that regulate protein-protein interactions. ADAM19 binds strongly to the scaffolding protein tyrosine kinase substrate with five SH3 domains and the Src tyrosine kinase, potentially influencing cytoskeletal functions that impact cell motility, contractility or tissue development [41]. Therefore, disruption of ADAM19 may have important effects on lung development, neuromuscular functions, tissue elastance, contractility, or other unidentified signaling processes.

Our differential gene expression findings also lead to the direction of genes related to lung physiology and pathology. For example, increased Kpna2 expression may contribute to altered lung function, consistent with publications that KPNA2 genetic variation is associated with FEV1/FVC in human GWAS [2] and plays a role in lung cancer [42]. Our KO had increased Pttg1 expression. Pttg1 is involved in cell cycle regulation [43] and the development of lung cancer [44], suggesting its role in the lungs.

Given our observation of reduced neutrophil infiltration in BALF following LPS exposure in the Adam19 knockout, we investigated whether airway responsiveness to methacholine differs between KO and WT mice following LPS administration. Notably, our knockout mice showed decreased tissue damping and tissue elastance response to methacholine following LPS exposure compared to WT, indicating an attenuated response to inflammation. ADAM19 facilitates the release of TNF from the cell membrane, promoting an inflammatory response and contributing to the development of inflammatory diseases [17, 18, 31, 45]. Our GSEA identified the enrichment of downregulated differentially expressed genes in TNF signaling pathways in our Adam19 KO mice. This is consistent with these previous findings [17, 18, 31, 45] and helps explain the reduced lung functional response to the inflammation in our knockout mice.

In summary, we created a viable whole-body Adam19 knockout and used this model to examine the role of Adam19 in lung function, following up on findings from human GWAS implicating this gene. In addition to smaller body size, the lack of functional Adam19 resulted in reduced respiratory system elastance, minute work of breathing, tissue elastance, forced expiratory flow at 50% FVC, and increased FEV0.1 and FVC. These data provide evidence to support a causal role for Adam19 in regulating pulmonary function development. Pathway analysis of genes differentially expressed after disruption of Adam19 implicates pathways crucial in lung inflammation, including TNF signaling pathways. Although our study is limited to a descriptive scope and a definitive understanding of mechanisms underlying our findings requires further investigation, our novel Adam19 KO murine model could be helpful in future studies to dissect the role of this gene in lung function.

Funding

This work was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01 ES 025041 to D.C.Z.; Z01 ES025045 and Z01 ES043012 to S.J.L.)

Funding Statement

This work was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01 ES 025041 to D.C.Z.; Z01 ES025045 and Z01 ES043012 to S.J.L.)

Footnotes

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Supplementary Files

This is a list of supplementary files associated with this preprint. Click to download.

Contributor Information

Huiling Li, National Institute of Environmental Health Sciences.

John House, National Institute of Environmental Health Sciences.

Cody Nichols, Whitsell Innovations, Inc..

Artiom Gruzdev, National Institute of Environmental Health Sciences.

James Ward, National Institute of Environmental Health Sciences.

Jian-Liang Li, National Institute of Environmental Health Sciences.

Annah Wyss, Beth Israel Deaconess Medical Center.

Ezazul Haque, National Institute of Environmental Health Sciences.

Matthew Edin, National Institute of Environmental Health Sciences.

Susan Elmore, National Institute of Environmental Health Sciences.

Beth Mahler, National Institute of Environmental Health Sciences.

Laura Degraff, National Institute of Environmental Health Sciences.

Min Shi, National Institute of Environmental Health Sciences.

Darryl Zeldin, National Institute of Environmental Health Sciences.

Stephanie London, National Institute of Environmental Health Sciences.

References

  • 1.Sarycheva T, Capkova N, Pajak A et al. (2022) All-cause and cardiovascular mortality in relation to lung function in the full range of distribution across four Eastern European cohorts. Sci Rep 12(1):12959. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Shrine N, Izquierdo AG, Chen J et al. (2023) Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk. Nat Genet 55(3):410–422 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Shrine N, Guyatt AL, Erzurumluoglu AM et al. (2019) New genetic signals for lung function highlight pathways and chronic obstructive pulmonary disease associations across multiple ancestries. Nat Genet 51(3):481–493 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Sinkala M, Elsheikh SSM, Mbiyavanga M et al. (2023) A genome-wide association study identifies distinct variants associated with pulmonary function among European and African ancestries from the UK Biobank. Commun Biol 6(1):49. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Hancock DB, Eijgelsheim M, Wilk JB et al. (2010) Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function. Nat Genet 42(1):45–52 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Kichaev G, Bhatia G, Loh P-R et al. (2019) Leveraging Polygenic Functional Enrichment to Improve GWAS Power. Am J Hum Genet 104(1):65–75 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.London SJ, Gao W, Gharib SA et al. (2014) ADAM19 and HTR4 variants and pulmonary function: Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium Targeted Sequencing Study. Circ Cardiovasc Genet 7(3):350–358 . [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Wain LV, Shrine N, Artigas MS et al. (2017) Genome-wide association analyses for lung function and chronic obstructive pulmonary disease identify new loci and potential druggable targets. Nat Genet 49(3):416–425 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Wilk JB, Shrine NR, Loehr LR et al. (2012) Genome-wide association studies identify CHRNA5/3 and HTR4 in the development of airflow obstruction. Am J Respir Crit Care Med 186(7):622–632 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Wyss AB, Sofer T, Lee MK et al. (2018) Multiethnic meta-analysis identifies ancestry-specific and cross-ancestry loci for pulmonary function. Nat Commun 9(1):2976. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Bu SM, Yang YJ, Miao CL et al. (2006) Developmental and hormonal regulation of meltrin beta (ADAM19) expression in mouse testes during embryonic and postnatal life. Life Sci 79(22):2112–2118 [DOI] [PubMed] [Google Scholar]
  • 12.Dijkstra A, Postma DS, Noordhoek JA et al. (2009) Expression of ADAMs (a disintegrin and metalloprotease) in the human lung. Virchows Archiv: Int J Pathol 454(4):441–449 [DOI] [PubMed] [Google Scholar]
  • 13.Blobel CP (2005) ADAMs: key components in EGFR signalling and development. Nat Rev Mol Cell Biol 6(1):32–43 [DOI] [PubMed] [Google Scholar]
  • 14.Chesneau V, Becherer JD, Zheng Y et al. (2003) Catalytic properties of ADAM19. J Biol Chem 278(25):22331–22340 [DOI] [PubMed] [Google Scholar]
  • 15.Zhong S, Khalil RA (2019) A Disintegrin and Metalloproteinase (ADAM) and ADAM with thrombospondin motifs (ADAMTS) family in vascular biology and disease. Biochem Pharmacol 164:188–204 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Wakatsuki S, Hatsuzawa K, Black RA et al. (2006) ADAM10 is a principal ‘sheddase’ of the low-a nity immunoglobulin E receptor CD23. Genes to cells: devoted to molecular & cellular mechanisms. 7(12):1293–1298 [Google Scholar]
  • 17.Franzè E, Caruso R, Stolfi C et al. (2013) High expression of the A disintegrin and metalloprotease 19 (ADAM19), a sheddase for TNF-a in the mucosa of patients with inflammatory bowel diseases. Inflamm Bowel Dis 19(3):501–511 [DOI] [PubMed] [Google Scholar]
  • 18.Zheng Y, Saftig P, Hartmann D, Blobel C (2004) Evaluation of the contribution of different ADAMs to tumor necrosis factor alpha (TNFalpha) shedding and of the function of the TNFalpha ectodomain in ensuring selective stimulated shedding by the TNFalpha convertase (TACE/ADAM17). J Biol Chem 279(41):42898–42906 [DOI] [PubMed] [Google Scholar]
  • 19.Kurohara K, Komatsu K, Kurisaki T et al. (2004) Essential roles of Meltrin beta (ADAM19) in heart development. Dev Biol 267(1):14–28 [DOI] [PubMed] [Google Scholar]
  • 20.Li H, Nichols C, Gruzdev A et al. (2020) ADAM19 and Pulmonary Function in the Mouse: Follow-Up of Human GWAS. Am J Respir Crit Care Med 201:A2386–A2386 [Google Scholar]
  • 21.Sigmon JS, Blanchard MW, Baric RS et al. (2020) Content and Performance of the MiniMUGA Genotyping Array: A New Tool To Improve Rigor and Reproducibility in Mouse Research. Genetics 216(4):905–930 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Farris S, Ward JM, Carstens KE et al. (2019) Hippocampal Subregions Express Distinct Dendritic Transcriptomes that Reveal Differences in Mitochondrial Function in CA2. Cell Rep 29(2):522–539e6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Patro R, Duggal G, Love MI et al. (2017) Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods 14(4):417–419 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Ritchie ME, Phipson B, Wu D et al. (2015) limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res 43(7):e47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Subramanian A, Tamayo P, Mootha VK et al. (2005) Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43): pp. 15545–15550 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Nagy TR, Clair AL (2000) Precision and accuracy of dual-energy X-ray absorptiometry for determining in vivo body composition of mice. Obes Res 8(5):392–398 [DOI] [PubMed] [Google Scholar]
  • 27.House JS, Li H, DeGraff LM et al. (2015) Genetic variation in HTR4 and lung function: GWAS follow-up in mouse. Faseb j 29(1):323–335 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Shalaby KH, Gold LG, Schuessler TF et al. (2010) Combined forced oscillation and forced expiration measurements in mice for the assessment of airway hyperresponsiveness. Respir Res 11:82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Edgar R, Domrachev M, Lash AE (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res, 30(1): pp. 207–10 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Zhou HM, Weskamp G, Chesneau V et al. (2004) Essential role for ADAM19 in cardiovascular morphogenesis. Mol Cell Biol 24(1):96–104 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Weerasekera L, Rudnicka C, Sang QX et al. (2017) ADAM19: A Novel Target for Metabolic Syndrome in Humans and Mice. Mediators Inflamm, 2017: p. 7281986. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Inoue D, Reid M, Lum L et al. (1998) Cloning and Initial Characterization of Mouse Meltrin β and Analysis of the Expression of Four MetalloproteaseDisintegrins in Bone Cells*. J Biol Chem 273(7):4180–4187 [DOI] [PubMed] [Google Scholar]
  • 33.Chen C-Y, Chen T-T, Feng Y-CA et al. (2023) Analysis across Taiwan Biobank, Biobank Japan, and UK Biobank identifies hundreds of novel loci for 36 quantitative traits. Cell Genomics 3(12):100436. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Støy J, Kampmann U, Mengel A et al. (2015) Reduced CD300LG mRNA tissue expression, increased intramyocellular lipid content and impaired glucose metabolism in healthy male carriers of Arg82Cys in CD300LG: a novel genometabolic cross-link between CD300LG and common metabolic phenotypes. BMJ Open Diabetes Res Care 3(1):e000095. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Hobbs BD, de Jong K, Lamontagne M et al. (2017) Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis. Nat Genet 49(3):426–432 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Soler Artigas M, Loth DW, Wain LV et al. (2011) Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function. Nat Genet 43(11):1082–1090 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Castaldi PJ, Cho MH, Litonjua AA et al. (2011) The association of genome-wide significant spirometric loci with chronic obstructive pulmonary disease susceptibility. Am J Respir Cell Mol Biol 45(6):1147–1153 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Tam V, Patel N, Turcotte M et al. (2019) Benefits and limitations of genome-wide association studies. Nat Rev Genet 20(8):467–484 [DOI] [PubMed] [Google Scholar]
  • 39.Zscheppang K, Korenbaum E, Bueter W et al. (2006) ErbB receptor dimerization, localization, and co-localization in mouse lung type II epithelial cells. Pediatr Pulmonol 41(12):1205–1212 [DOI] [PubMed] [Google Scholar]
  • 40.Yumoto N, Wakatsuki S, Kurisaki T et al. (2008) Meltrin beta/ADAM19 interacting with EphA4 in developing neural cells participates in formation of the neuromuscular junction. PLoS ONE 3(10):e3322. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Kleino I, Jarviluoma A, Hepojoki J et al. (2015) Preferred SH3 domain partners of ADAM metalloproteases include shared and ADAM-specific SH3 interactions. PLoS ONE 10(3):e0121301. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Feng HP, Liu YC, Wang CL et al. (2023) Acetylation regulates the nucleocytoplasmic distribution and oncogenic function of karyopherin alpha 2 in lung adenocarcinoma. Biochem Biophys Res Commun 659:96–104 [DOI] [PubMed] [Google Scholar]
  • 43.Bernal JA, Luna R, Espina A et al. (2002) Human securin interacts with p53 and modulates p53-mediated transcriptional activity and apoptosis. Nat Genet 32(2):306–311 [DOI] [PubMed] [Google Scholar]
  • 44.Li H, Yin C, Zhang B et al. (2013) PTTG1 promotes migration and invasion of human non-small cell lung cancer cells and is modulated by miR-186. Carcinogenesis 34(9):2145–2155 [DOI] [PubMed] [Google Scholar]
  • 45.van Loo G, Bertrand MJM (2023) Death by TNF: a road to in ammation. Nat Rev Immunol 23(5):289–303 [DOI] [PMC free article] [PubMed] [Google Scholar]

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