Morquio A Syndrome: Identification of Differential Patterns of Molecular Pathway Interactions in Bone Lesions

Abstract

Mucopolysaccharidosis type IVA (MPS IVA; Morquio A syndrome) is a rare autosomal recessive lysosomal storage disease (LSD) caused by deficiency of a hydrolase enzyme, N-acetylgalactosamine-6-sulfate sulfatase, and characterized clinically by mainly musculoskeletal manifestations. The mechanisms underlying bone involvement in humans are typically explored using invasive techniques such as bone biopsy, which complicates analysis in humans. We compared bone proteomes using DDA and SWATH-MS in wild-type and MPS IVA knockout mice (UNT) to obtain mechanistic information about the disease. Our findings reveal over 1000 dysregulated proteins in knockout mice, including those implicated in oxidative phosphorylation, oxidative stress (reactive oxygen species), DNA damage, and iron transport, and suggest that lactate dehydrogenase may constitute a useful prognostic and follow-up biomarker. Identifying biomarkers that reflect MPS IVA clinical course, severity, and progression have important implications for disease management.

Keywords: animal studies; biomarkers; mucopolysaccharidosis type IV; musculoskeletal manifestations; proteomic.

Figure 1

(A) Metabolic pathways: Reactome pathway enrichment analysis of DEPs. (B) String interaction analysis of DEPs. Colored dots represent proteins implicated in glycolysis and gluconeogenesis (red); fatty acid β-oxidation (green); the electron transport chain (yellow); TCA cycle (blue); amino acid metabolism (pink). (C) Venn diagram showing the overlap of DEPs identified using SWATH-MS and all proteins identified by DDA.

Figure 2

(A–C) Relative expression levels of DEPs (p < 0.05; FC > 3) implicated in glycolysis in UNT and WT mice. (A) TCA cycle. (B) Krebs cycle. (C) Black dots represent the SWATH-MS area values of each sample, per group. * p < 0.05.

Figure 3

(A–D) Relative expression levels of DEPs (p < 0.05; FC > 3) implicated in OXPHOS in UNT and WT mice. (A) Mitochondria complex. (B) Mitochondria complex V, ATP production. (C) β-oxidation. (D) Black dots represent the SWATH-MS area values of each sample, per group. * p < 0.05.

Figure 4

(A) Mitochondrial function: Reactome pathway enrichment analysis of DEPs related to apoptosis (I); cellular response to stress (II); DNA repair (III); iron transport (IV). (B) STRING interaction analysis of DEPs. Colored dots represent proteins related to iron transport (red); cell death (green); transport (yellow); oxidative stress (blue). (C) Venn diagram showing the overlap of DEPs identified using SWATH-MS and DDA.

Figure 5

Relative expression levels in UNT and WT mice of DEPs (p < 0.05; FC > 3) related to oxidative stress (A); iron transport (B); DNA damage prevention (C). Black dots represent the SWATH-MS area values of each sample, per group. * p < 0.05; ** p < 0.01.

Figure 6

(A) Histones, ribosomes, proteasomes, vesicular transport, and lysosomes: Reactome pathway enrichment analysis of DEPs related to lysosomes (I); and vesicular transport (II). (B) Colored dots represent proteins related to proteasomes (red); rab protein signal translation (green); small ribosomal subunits (yellow); ribosomal biogenesis (blue); lysosomes (pink). (C) Venn diagram showing the overlap of DEPs identified using SWATH-MS and DDA.

Figure 7

Relative expression levels in UNT and WT mice of DEPs (p < 0.05; FC > 3) related to histones (A); ribosomal proteins (B); vesicular transport (C); lysosomal membrane (D); whole lysosome (E). Black dots represent the SWATH-MS area values of each sample, per group. * p < 0.05; ** p < 0.01; *** p < 0.001.

Figure 8

Relative expression levels in UNT and WT mice of DEPs (p < 0.05; FC > 3) related to the cytoskeleton. Cytoskeletal proteins upregulated in WT (A) and UNT (B) mice. Black dots represent the SWATH-MS area values of each sample, per group. * p < 0.05; ** p < 0.01.

Figure 9

(A) STRING interaction analysis of DEPs. Red dots indicate proteins related to cell adhesion. (B) Venn diagram showing overlap of DEPs across the two proteomic techniques used. (C) Relative expression levels in UNT and WT mice of DEPs for proteoglycans. (D) Relative expression levels in UNT and WT mice of DEPs for collagens (p < 0.05; FC > 3) related to proteoglycans. * p < 0.05; ** p < 0.01; *** p < 0.001.

Figure 10

Relative expression levels in UNT and WT mice of DEPs (p < 0.05; FC > 3) related to fibrillar collagen (A); extracellular receptor matrix (B); extracellular matrix proteases (C); cathepsins; (D) integrins; (E); discoidin domain receptor (F). * p < 0.05; ** p < 0.01.

Figure 11

Other proteins of interest: relative expression levels of DEPs (* p < 0.05; FC > 3) in UNT and WT mice. Black dots represent the SWATH-MS area values of each sample, per group.

Figure 12

(A) Venn diagram showing the overlap of validated DEPs identified using each proteomic technique. (B) STRING interaction analysis of validated DEPs showing proteins related to ATP metabolic process (red); glycolysis and gluconeogenesis (yellow); the TCA cycle (light green); the mitochondrial membrane (blue); OXPHOS (pink); and ROS (dark green).

Figure 13

In silico validation. (A) Comparison between mouse DEPs and our previous papers in human samples [18,19]. (B) Comparison between mouse DEPs and other data sets in human bone and human bone marrow samples [20,21].

Figure 14

Proteomic dysregulation in MPS IVA. The figure highlights the main proteins, pathways, and cellular components involved.