Skip to main content
NCBI home page
Biochemistry and Biophysics Reports logoLink to Biochemistry and Biophysics Reports
. 2025 Mar 14;42:101979. doi: 10.1016/j.bbrep.2025.101979

Lack of significant ganglioside changes in Slc17a5 heterozygous mice: Relevance to FSASD and Parkinson's disease

Marya S Sabir a,b, Mahin S Hossain c, Laura Pollard d, Marjan Huizing c, William A Gahl a,c, Frances M Platt e,⁎, May Christine V Malicdan a,c,⁎⁎
PMCID: PMC11937675  PMID: 40144541

Abstract

Large population-based studies of Parkinson's disease (PD) have identified susceptibility genes, including SLC17A5. Biallelic mutations in SLC17A5, encoding the lysosomal sialic acid transporter sialin, cause the rare neurodegenerative disease, free sialic acid storage disorder (FSASD). To explore a potential biochemical link between FSASD and PD, we investigated ganglioside concentrations in a novel mouse model harboring the Slc17a5 p.Arg39Cys (p.R39C) variant. Our analysis revealed no significant alterations in ganglioside concentrations in heterozygous p.R39C mice, warranting further studies into other potential links between PD and sialin defects.

Keywords: Parkinson's disease, Salla disease, SLC17A5, Sialin, Glycosphingolipids, Mouse model

Highlights

  • •

    Large PD population studies have identified susceptibility genes, including SLC17A5.

  • •

    No impairment of gangliosides in Slc17a5 p.R39C heterozygous mice.

  • •

    Study highlights complexity of FSASD and PD connections via lysosomal dysfunction.

1. Introduction

Parkinson's disease (PD), the second most common neurodegenerative disorder, is primarily characterized by the selective degeneration of dopaminergic neurons in the substantia nigra [1], leading to motor and non-motor neurological symptoms. While aging is the greatest risk factor for PD [2,3], genetic contributions to both familial (1–2 % of cases) and sporadic forms (98–99 % of cases) of the disease have been increasingly recognized [4]. Large-scale pathway analyses using polygenic risk scores have highlighted endosomal–lysosomal dysfunction as a key biological contributor to PD [5]. Moreover, Robak et al. (2017) identified a substantial burden of rare, likely pathogenic heterozygous variants in lysosomal storage disorder genes, including SLC17A5, GBA, SMPD1, CTSD, and ASAH1, in PD cases, suggesting that these genes may contribute to disease susceptibility [6]. Among these, SLC17A5 encodes sialin (NCBI Gene: 26503), a lysosomal proton-coupled cotransporter responsible for exporting sialic acid and other acidic hexoses from lysosomes into the cytosol [[7], [8], [9], [10], [11]]. Pathogenic variants in SLC17A5 cause free sialic acid storage disorder (FSASD; MIM#269920, MIM#604369) [[12], [13], [14], [15]], a lysosomal storage disorder characterized by the accumulation of unconjugated “free” sialic acid in lysosomes, resulting in neurological dysfunction and multisystem involvement [10,16,17].

Seventeen non-synonymous SLC17A5 variants predicted to be damaging based on CADD scores were identified in both PD cases and neurologically healthy individuals [6]. Two particular variants - p.Arg39Cys (p.R39C) and c.1111+1G > A - were exclusively found in individuals with PD [6] and have also been reported in cases of lysosomal free sialic acid storage disorder (FSASD) [12,13] (Supplementary Table 1). Notably, p.R39C is a founder missense variant, present in approximately 75% of documented FSASD cases [12,13]. Additionally, three variants—p.F432S, p.G383A, and p.G237E—were detected solely in PD cases [6], though these have not been reported in FSASD.

Sialic acids, including N-acetylneuraminic acid (Neu5Ac) in humans [18,19], are negatively charged monosaccharides involved in diverse biological processes, including immune regulation, cellular interactions, and neuronal function [20]. These molecules are most concentrated in the mammalian CNS, with 65% found in gangliosides (i.e., glycosphingolipids containing sialic acid residues), 32% in glycoproteins, and 3% as free sialic acid [21]. Most sialic acids are incorporated into gangliosides, while polysialic acid is attached to glycoproteins like NCAM in the CNS [22]. The primary pathway for catabolism of sialoglycoconjugates, including gangliosides, is lysosomal degradation, where sialidases (i.e., neuraminidases) remove terminal sialic acids from glycan chains [20]. Disruption of sialic acid homeostasis can impair neuronal function, synaptic transmission, and neural plasticity [23]—critical processes that are often compromised in neurodegenerative diseases, including PD [24,25].

Given that lysosomal dysfunction plays a key role in both PD and FSASD, and SLC17A5 is both a proposed genetic risk factor for PD and a known cause of FSASD, we explored potential biochemical links between these disorders by examining changes in glycosphingolipids (GSLs). Impaired GSL metabolism has been increasingly implicated in neurodegeneration associated with PD [26,27], while studies in FSASD have shown decreased ganglioside turnover in patient fibroblasts, alongside elevated lysosomal enzyme levels despite normal enzyme activity, including sialidase in some studies [[28], [29], [30], [31], [32], [33], [34]]. Since SLC17A5 is critical for lysosomal sialic acid export, its dysfunction could impact ganglioside homeostasis, potentially contributing to PD pathogenesis. However, whether heterozygous SLC17A5 variants (including p.R39C) affect ganglioside concentrations in vivo remains unknown. We therefore utilized a knock-in mouse model carrying the Slc17a5 p.R39C variant to explore ganglioside concentrations in heterozygous Slc17a5 p.R39C mice compared to wild-type mice. Additionally, given that PD is an age-related disorder and the p.R39C variant is proposed to be linked to PD risk, we investigated if aged heterozygous Slc17a5 p.R39C mice exhibit more pronounced ganglioside changes than younger mice.

To investigate whether SLC17A5 heterozygosity affects ganglioside homeostasis, we analyzed brain tissue from young and aged Slc17a5 p.R39C heterozygous mice. Given that lysosomal ganglioside processing may be disrupted in FSASD and PD, we also assessed sialidase activity and measured systemic free sialic acid concentrations as an exploratory biomarker. By examining the biochemical impact of a PD-associated SLC17A5 variant, this study provides key insights into potential lysosomal contributions to neurodegeneration.

2. Methods

2.1. Description of murine model

For this study, we utilized a knock-in mouse model carrying the human-equivalent SLC17A5 p.R39C point mutation. Briefly, we humanized the corresponding sequence in the murine genome by CRISPR-Cas12a to alter two nucleotides (Slc17a5 c.115C > T and c.117G > C) in exon 2 of the murine Slc17a5 gene (NM_172773) to generate the p.R39C murine on a hybrid background (C57BL/6J-129S1/SvlmJ) (descriptive manuscript in preparation, [35]).

At three weeks of age, homozygous mice appeared smaller than wild-type littermates and showed tremors, ataxia, and seizures, with 25% succumbing to severe symptoms by 1.5 months, and nearly 50% dying by six months due to progressive ataxia and hindlimb paralysis. In contrast, heterozygous littermates showed no symptoms and remained visually indistinguishable from wild-type mice throughout their lifespan.

2.2. Genotyping of murine model

Genotyping was performed using TaqMan-based quantitative fluorescence PCR on genomic DNA extracted from tail biopsies of 21-day-old mice. Tail samples were collected and DNA was extracted using the Extract-N-Amp kit (Sigma-Aldrich) following the manufacturer's protocol. The samples were amplified using TaqMan Genotyping Master Mix (ThermoFisher Scientific) and analyzed on an ABI 7500 instrument (Applied Biosystems). The amplification was carried out with the following primers and probes: forward primer (CTCCATCTTAATTTCAGCTCCAGTGT), reverse primer (AAACCACAGAACGCCAAAATCG), VIC probe for wild-type allele detection (VIC – CTCTGCTCGGTACAACT – NFQ), and FAM probe for mutant allele detection (FAM – CTCTGCTTGCTACAACT – NFQ). Differences in the VIC and FAM fluorescence intensities distinguished the wild-type, Slc17a5 p.R39C heterozygous, and homozygous genotypes.

2.3. Murine specimen collection

Mice were anesthetized with 1.25% tribromoethanol. Following anesthesia, a midline incision was made to expose the inferior vena cava (IVC) and urinary bladder. For the aged cohort, blood was collected from the IVC to obtain serum, transferred into 1.5 mL microcentrifuge tubes, and left to clot for 30 min. Samples were then centrifuged at 4°C for 20 min at 1500g, and the serum supernatant was transferred to fresh tubes and stored at −80°C. For the aged cohort, urine, if present, was aspirated directly from the urinary bladder using a syringe. Following blood and urine collection (if applicable), mice were perfused intracardially with 1X phosphate-buffered saline (PBS). The brain was rapidly dissected, removing the brainstem and bilateral olfactory bulbs. The left hemisphere was sectioned into the forebrain and cerebellum, flash-frozen in liquid nitrogen, and stored at −80 °C for downstream analyses.

2.4. Quantification of cellular GSLs

Glycosphingolipid (GSL) profiling in mouse forebrain and cerebellum tissues was conducted using published protocols [36]. Briefly, lipids were extracted overnight at 4°C using a chloroform-methanol mixture. GSLs were then purified using C18 columns (Telos). After elution, the GSL fractions were dried under a nitrogen stream at 42°C and digested with recombinant ceramide glycanase (rEGCase, prepared by Genscript and provided by Orphazyme) to release oligosaccharides from complex GSLs. The released glycans were fluorescently labeled with anthranilic acid (2AA), and excess 2AA was removed using DPA-6S SPE columns (Supelco). The purified 2AA-labeled oligosaccharides were separated and quantified by normal-phase high-performance liquid chromatography (NP-HPLC). A 2AA-labeled glucose homopolymer ladder (Ludger) was used to determine the glucose unit (GU) values for the HPLC peaks. Individual GSL species were identified based on their GU values (Supplementary Figs. 3A–B) and quantified by comparing the integrated peak areas to a known 2AA-labeled BioQuant chitotriose standard (Ludger). The results were subsequently normalized to protein content, which was determined using the bicinchoninic acid (BCA) assay.

We assessed a range of GSLs, including gangliosides, but due to their near-baseline levels, species such as lactosylceramide (Lac), GA2, and GA1 were unreliable for quantification and were excluded from further analysis and inclusion in “Total GSLs”. As a result, gangliosides became the primary focus of this evaluation (Supplementary Figs. 3A–B).

2.5. Quantification of neuraminidase activities

Neuraminidase (NEU) activities were measured fluorometrically using a synthetic substrate, N-acetylneuraminic acid conjugated with the fluorophore 4-methylumbelliferone (4-MU), as previously described [37]. Two assays were performed, i.e., one to quantify the combined activity of NEU1, NEU3, and NEU4 (NEU1/3/4), and another to specifically measure cytosolic NEU2 activity. Both assays were incubated at 37°C for 3.16 h. Enzyme activities were determined by comparing fluorescence to a standard curve of unconjugated 4-MU and normalized to protein content as measured by BCA assay.

2.6. Quantification of free sialic acid

Neu5Ac, the most abundant mammalian sialic acid [38], was measured and is referred to as “sialic acid” in this report. Urinary and serum concentrations of free sialic acid from mice were quantified. 25 μL of urine or serum was analyzed using UPLC-MS/MS (Waters Acquity I-Class; Xevo TQ-S MS/MS). Chromatographic separation was performed with a C18 reverse-phase column (Waters Acquity UPLC HSS T3), and detection was achieved through tandem mass spectrometry in selected reaction monitoring mode (electrospray ionization, negative ion mode). Quantification was carried out using stable isotope dilution and comparison to a standard curve. Urine free sialic acid concentrations were normalized to creatinine levels, measured by the alkaline picric acid method (Jaffé reaction). Serum free sialic acid concentrations were reported without further normalization.

2.7. Statistical analyses

Statistical analyses were conducted using an unpaired t-test between wild-type and p.R39C heterozygous mice using GraphPad Prism (GraphPad, version 10.0.3). Correlations were analyzed with Pearson correlation analysis. A two-sided p-value significance was set at 0.05.

3. Results

To investigate changes in ganglioside concentrations as a potential metabolic connection between PD and FSASD, we measured GSL levels and neuraminidase enzyme activities in both younger (mean age: 152 ± 9 days) and aged (mean age: 546 ± 70 days) wild-type and Slc17a5 p.R39C heterozygous mice (see Supplementary Table 2 for cohort details). We selected these timepoints for several reasons. First, ganglioside levels are known to change with age [26]. Second, given that PD is an age-related disorder, the inclusion of aged mice was particularly relevant. Finally, ganglioside concentrations are known to be influenced by neurodegeneration [26], which generally manifests later in life.

In the aged cohort, we also quantified free sialic acid in urine and serum using UPLC-MS/MS; no significant differences were observed between genotypes (Supplementary Fig. 1).

3.1. GSL profiling of mouse forebrain and cerebellum

Quantitative analysis of GSLs isolated from the forebrain and cerebellum of younger and aged mice heterozygous for the Slc17a5 p.R39C variant revealed no significant differences in GSL concentrations compared to wild-type controls (Fig. 1A–D). The primary brain gangliosides, GM1a, GD1a, GD1b, and GT1b [39], were present at comparable levels across both genotypes. Although no statistically significant changes were found, we noted a modest trend toward lower ganglioside concentrations in the cerebellum of aged heterozygous mice compared to wild-type controls (Fig. 1D). Given the established age-related decline in ganglioside metabolism in neurodegeneration [26], further studies in larger cohorts may be required to determine whether this trend represents a subtle biochemical effect of SLC17A5 heterozygosity.

Fig. 1.

Fig. 1

Open in a new tab

Concentrations of total GSLs, individual GSL species, and neuraminidase enzyme activities in mouse forebrain and cerebellum. GSL concentrations in heterozygous Slc17a5 p.R39C mice (pink) compared to wild-type mice (black) for: (A) younger mouse forebrain, (B) younger mouse cerebellum, (C) aged mouse forebrain, and (D) aged mouse cerebellum. Neuraminidase activity levels in (E) younger mouse forebrain and cerebellum and (F) aged mouse forebrain and cerebellum. For GSL measurements and neuraminidase enzyme screening, the younger mouse cohort consisted of 4 wild-type and 10 Slc17a5 p.R39C heterozygous mice, while the aged cohort included 2 wild-type and 9 Slc17a5 p.R39C heterozygous mice. Mean ± SEM; unpaired t-test.

3.2. Correlation of free sialic concentrations and ganglioside concentrations

We next explored whether ganglioside concentrations correlated with urinary and serum free sialic acid concentrations, as sialic acid homeostasis and ganglioside metabolism are functionally linked. No significant correlations were observed in the forebrain, but we found a borderline significant positive correlation between urinary free sialic concentrations and ganglioside concentrations in the mouse cerebellum (Supplementary Figs. 2A–D). This unexpected trend suggests that systemic sialic acid availability may influence cerebellar ganglioside metabolism, although further studies are needed to confirm this finding.

3.3. Neuraminidase activity in mouse brain

To determine whether sialin dysfunction impacts lysosomal sialidase activity, we measured NEU1/3/4 and cytosolic NEU2 activities in brain homogenates from heterozygous p.R39C and wild-type mice at both younger and aged timepoints. NEU1/3/4 and NEU2 activities remained unchanged in p.R39C heterozygous mice relative to wild-type controls (Fig. 1E–F). However, neuraminidase activity levels were significantly higher in the aged cohort compared to the younger cohort in both genotypes (Fig. 1E–F).

These results indicate that heterozygous Slc17a5 p.R39C mice do not exhibit major defects in lysosomal ganglioside processing, at least under basal conditions. However, the age-dependent increase in sialidase activity warrants further investigation, particularly in the context of age-related neurodegeneration and PD pathogenesis.

4. Discussion

Given the proposed role of SLC17A5 as both a genetic risk factor for Parkinson's disease and a monogenic cause of FSASD, our study aimed to explore potential links between these neurodegenerative disorders by analyzing ganglioside concentrations and sialic acid homeostasis. While ganglioside concentrations has been increasingly implicated in neurodegeneration [26,26,27,40], our results do not show a significant effect of Slc17a5 heterozygosity on brain ganglioside levels (including GM1a, GD1a, GD1b, and GT1b) in mice. The absence of significant changes in ganglioside concentrations, even in aged heterozygous mice, suggests that the p.R39C variant alone may not trigger GSL accumulation or substantial alterations in lysosomal glycosphingolipid processing. However, this does not exclude a pathogenic role for SLC17A5 variants in PD, as additional genetic or environmental stressors may be required to reveal impacts on lysosomal function, as seen in gba point mutation mouse models of PD [41].

Interestingly, urinary free sialic acid concentrations correlated positively with cerebellar ganglioside concentrations in aged mice, likely suggesting a possible age-related regulation of sialic acid metabolism and ganglioside turnover. While this finding may be incidental, it warrants further investigation, particularly given the high concentration of sialic acid in the brain and their role in neuronal stability [42,43]. Future studies should also measure Neu5Gc, the predominant sialic acid in peripheral tissues of young and aged mice and correlate these levels with brain gangliosides where Neu5Ac predominates [44].

Since ganglioside catabolism occurs via lysosomal neuraminidases [20], we assessed neuraminidase activities (NEU1/3/4 and NEU2) in the p.R39C heterozygous model. Consistent with the GSL findings, no significant differences were observed between genotypes at either time point, reinforcing the idea that Slc17a5 heterozygosity alone does not impair lysosomal ganglioside degradation. Interestingly, neuraminidase activity was higher in aged mice, consistent with prior reports of age-related enzymatic shifts [45].

Several studies have underscored the role of lysosomal dysfunction in PD susceptibility and pathogenesis, with particular emphasis on β-glucocerebrosidase, the enzyme encoded by the GBA1 gene [46,47]. Recent evidence suggests that ganglioside metabolism may play a distinct role in the pathophysiology of PD, particularly in the context of GBA1-related lysosomal dysfunction. Measurement of brain gangliosides across idiopathic PD, PD-GBA, and neurologically healthy controls reveals slightly elevated ganglioside concentrations in the idiopathic PD group, and a more pronounced and statistically significant increase in the PD-GBA group [48], implicating a role of ganglioside in disease progression [50]. This is likely because GBA1 is central to the lysosomal catabolism of the GSL, glucosylceramide whereas SLC17A5 is not directly involved in glycosphingolipid metabolism, which may explain the lack of significant changes in ganglioside concentrations in our mouse model. To gain a clearer understanding of these differences, further studies are needed to compare human brain samples from idiopathic PD and controls with those from PD-SLC17A5, a group that includes PD patients carrying SLC17A5 variants.

This study has limitations, including limited availability of wild-type mice for the aged cohort due to constraints in breeding heterozygous mice, which reduced statistical power. While we observed no statistical significance, we cannot rule out the possibility that a larger sample size could reveal biochemical alterations. Next, while the younger cohort included both male and female mice, the aged cohort only included male mice to mirror the disproportionate incidence of PD in aging males [2].

Our study focused on global ganglioside levels in mouse brain tissues as an initial approach to assess broad changes, but did not distinguish between plasma membrane-bound and lysosomal ganglioside pools. Subcellular fractionation could provide additional critical insights, and emerging technologies like tagless Lyso-IP [49] hold promise for addressing this limitation. Further, our study focused on ganglioside concentrations at only two specific timepoints and two specific brain regions in the p.R39C heterozygous mice. Expanding this approach to additional timepoints and PD-relevant brain regions, such as the substantia nigra or basal ganglia, could uncover more localized or progressive changes in ganglioside homeostasis. Additionally, while we focused on ganglioside concentrations, future studies could incorporate flux analysis and a broader screening of lysosomal hydrolases involved in GSL catabolism. Future studies may also benefit from using a heterozygous Slc17a5 knock-out model [50] to remain SLC17A5 variant-agnostic. Beyond gangliosides, oligosaccharide profiling could offer complementary insights into sialic acid metabolism in FSASD and PD.

Despite the limitations, this study represents the first attempt to investigate a biochemical connection between PD and FSASD in the context of SLC17A5 heterozygosity, given its association with both disorders. Although lysosomal dysfunction is a prominent feature of both conditions, our findings do not support a shared pathomechanism involving changes in ganglioside concentrations in heterozygous p.R39C carriers. Collectively, this study underscores the complexity of age-related metabolic changes in the brain and highlights the necessity for further studies to clarify the genetic overlap between these disorders in larger PD case-control studies.

CRediT authorship contribution statement

Marya S. Sabir: Writing – review & editing, Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Mahin S. Hossain: Writing – review & editing, Methodology, Investigation. Laura Pollard: Writing – review & editing, Investigation, Data curation. Marjan Huizing: Writing – review & editing, Data curation. William A. Gahl: Writing – review & editing, Supervision, Funding acquisition. Frances M. Platt: Writing – review & editing, Supervision, Resources, Funding acquisition, Formal analysis, Conceptualization. May Christine V. Malicdan: Writing – review & editing, Supervision, Resources, Project administration, Investigation, Formal analysis, Conceptualization.

Funding

This work was supported in part by the National Institutes of Health Intramural Research Program of the National Human Genome Research Institute. MSS received a graduate fellowship from the National Institutes of Health Oxford-Cambridge Scholars Programme. The Salla Treatment and Research foundation awarded a grant to Greenwood Genetic Center (LP) for sialic acid quantification.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors would like to thank Ms. Carla Ciccone (NIH/NHGRI) for her assistance with sample shipments. We would also like to acknowledge the NHGRI Mouse Transgenic Core for their assistance in generating the mice used in this study.

Footnotes

Appendix A

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbrep.2025.101979.

Contributor Information

Frances M. Platt, Email: frances.platt@pharm.ox.ac.uk.

May Christine V. Malicdan, Email: maychristine.malicdan@nih.gov.

Appendix A. Supplementary data

The following are the Supplementary data to this article:

Multimedia component 1
mmc1.docx (25.5KB, docx)
Multimedia component 2
mmc2.pdf (198.7KB, pdf)

graphic file with name mmcfigs1.jpg

Open in a new tab

Supplementary Figure 1. Free sialic acid concentrations in urine and serum. Free sialic acid (Neu5Ac) concentrations in heterozygous Slc17a5 p.R39C aged mice compared to wild-type controls in (A) urine and (B) serum. The urine screening cohort included 2 wild-type and 7 Slc17a5 p.R39C heterozygous mice, while the serum screening cohort comprised 2 wild-type and 8 Slc17a5 p.R39C heterozygous mice. Urine values normalized to mg creatinine. Mean ± SEM; unpaired t-test with p-values as indicated.

graphic file with name mmcfigs2.jpg

Open in a new tab

Supplementary Figure 2. Correlation of urinary and serum free sialic acid concentrations with ganglioside concentrations in aged heterozygous Slc17a5 p.R39C mouse brain. Correlation of urinary free sialic concentrations with brain ganglioside concentrations in (A) forebrain and (B) cerebellum. Correlation of serum free sialic concentrations with brain ganglioside concentrations in (C) forebrain and (D) cerebellum. The urine analyses included 2 wild-type and 7 Slc17a5 p.R39C heterozygous mice, while the serum analyses comprised 2 wild-type and 8 Slc17a5 p.R39C heterozygous mice. Pink circles indicate p.R39C variant carriers and black circles represent wild-type mice. Data were analyzed using Pearson correlation analysis with r and p-values as indicated in each panel.

graphic file with name mmcfigs3.jpg

Open in a new tab

Supplementary Figure 3. HPLC profiles of mouse brains. HPLC analysis of GSLs in the mouse brain, showing overlayed chromatographic traces for both the forebrain and cerebellum in (A) the younger cohort and (B) the aged cohort. GSL species highlighted in red were unreliably detected due to near-baseline levels and were therefore excluded from the downstream analyses. The GSL species highlighted in green represent the primary gangliosides found in the adult brain.

Data availability

Data will be made available on request.

References

  • 1.Poewe W., Seppi K., Tanner C.M., Halliday G.M., Brundin P., Volkmann J., Schrag A.E., Lang A.E. Parkinson disease. Nat. Rev. Dis. Primers. 2017;3 doi: 10.1038/nrdp.2017.13. [DOI] [PubMed] [Google Scholar]
  • 2.Van Den Eeden S.K., Tanner C.M., Bernstein A.L., Fross R.D., Leimpeter A., Bloch D.A., Nelson L.M. Incidence of Parkinson's disease: variation by age, gender, and race/ethnicity. Am. J. Epidemiol. 2003;157:1015–1022. doi: 10.1093/aje/kwg068. [DOI] [PubMed] [Google Scholar]
  • 3.Wright Willis A., Evanoff B.A., Lian M., Criswell S.R., Racette B.A. Geographic and ethnic variation in Parkinson disease: a population-based study of US Medicare beneficiaries. Neuroepidemiology. 2010;34:143–151. doi: 10.1159/000275491. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Blauwendraat C., Nalls M.A., Singleton A.B. The genetic architecture of Parkinson's disease. Lancet Neurol. 2020;19:170–178. doi: 10.1016/S1474-4422(19)30287-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Bandres-Ciga S., Saez-Atienzar S., Kim J.J., Makarious M.B., Faghri F., Diez-Fairen M., Iwaki H., Leonard H., Botia J., Ryten M., Hernandez D., Gibbs J.R., Ding J., Gan-Or Z., Noyce A., Pihlstrom L., Torkamani A., Soltis A.R., Dalgard C.L., American Genome C., Scholz S.W., Traynor B.J., Ehrlich D., Scherzer C.R., Bookman M., Cookson M., Blauwendraat C., Nalls M.A., Singleton A.B., C. International Parkinson Disease Genomics Large-scale pathway specific polygenic risk and transcriptomic community network analysis identifies novel functional pathways in Parkinson disease. Acta Neuropathol. 2020;140:341–358. doi: 10.1007/s00401-020-02181-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Robak L.A., Jansen I.E., van Rooij J., Uitterlinden A.G., Kraaij R., Jankovic J., International Parkinson's Disease Genomics C., Heutink P., Shulman J.M. vol. 140. 2017. pp. 3191–3203. (Excessive Burden of Lysosomal Storage Disorder Gene Variants in Parkinson's Disease Brain). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Blom H.J., Andersson H.C., Seppala R., Tietze F., Gahl W.A. Defective glucuronic acid transport from lysosomes of infantile free sialic acid storage disease fibroblasts. Biochem. J. 1990;268:621–625. doi: 10.1042/bj2680621. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Courville P., Quick M., Reimer R.J. Structure-function studies of the SLC17 transporter sialin identify crucial residues and substrate-induced conformational changes. J. Biol. Chem. 2010;285:19316–19323. doi: 10.1074/jbc.M110.130716. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Mancini G.M., Beerens C.E., Aula P.P., Verheijen F.W. Sialic acid storage diseases. A multiple lysosomal transport defect for acidic monosaccharides. J. Clin. Investig. 1991;87:1329–1335. doi: 10.1172/JCI115136. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Morin P., Sagne C., Gasnier B. Functional characterization of wild-type and mutant human sialin. EMBO J. 2004;23:4560–4570. doi: 10.1038/sj.emboj.7600464. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Pietrancosta N., Anne C., Prescher H., Ruivo R., Sagne C., Debacker C., Bertrand H.O., Brossmer R., Acher F., Gasnier B. Successful prediction of substrate-binding pocket in SLC17 transporter sialin. J. Biol. Chem. 2012;287:11489–11497. doi: 10.1074/jbc.M111.313056. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Aula N., Salomaki P., Timonen R., Verheijen F., Mancini G., Mansson J.E., Aula P., Peltonen L. The spectrum of SLC17A5-gene mutations resulting in free sialic acid-storage diseases indicates some genotype-phenotype correlation. Am. J. Hum. Genet. 2000;67:832–840. doi: 10.1086/303077. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Verheijen F.W., Verbeek E., Aula N., Beerens C.E., Havelaar A.C., Joosse M., Peltonen L., Aula P., Galjaard H., van der Spek P.J., Mancini G.M. A new gene, encoding an anion transporter, is mutated in sialic acid storage diseases. Nat. Genet. 1999;23:462–465. doi: 10.1038/70585. [DOI] [PubMed] [Google Scholar]
  • 14.Adams D., Wasserstein M. In: GeneReviews((R)) Adam M.P., Feldman J., Mirzaa G.M., Pagon R.A., Wallace S.E., Bean L.J.H., Gripp K.W., Amemiya A., editors. 1993. Free sialic acid storage disorders. Seattle (WA) [PubMed] [Google Scholar]
  • 15.Huizing M., Hackbarth M.E., Adams D.R., Wasserstein M., Patterson M.C., Walkley S.U., Gahl W.A., Consortium F. Free sialic acid storage disorder: progress and promise. Neurosci. Lett. 2021;755 doi: 10.1016/j.neulet.2021.135896. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Sagne C., Gasnier B. Molecular physiology and pathophysiology of lysosomal membrane transporters. J. Inherit. Metab. Dis. 2008;31:258–266. doi: 10.1007/s10545-008-0879-9. [DOI] [PubMed] [Google Scholar]
  • 17.Wreden C.C., Wlizla M., Reimer R.J. Varied mechanisms underlie the free sialic acid storage disorders. J. Biol. Chem. 2005;280:1408–1416. doi: 10.1074/jbc.M411295200. [DOI] [PubMed] [Google Scholar]
  • 18.Chou H.H., Hayakawa T., Diaz S., Krings M., Indriati E., Leakey M., Paabo S., Satta Y., Takahata N., Varki A. Inactivation of CMP-N-acetylneuraminic acid hydroxylase occurred prior to brain expansion during. human evolution Proc Natl Acad Sci U S A. 2002;99:11736–11741. doi: 10.1073/pnas.182257399. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Zhu W., Zhou Y., Guo L., Feng S. Biological function of sialic acid and sialylation in human health and disease. Cell Death Dis. 2024;10:415. doi: 10.1038/s41420-024-02180-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Schnaar R.L., Gerardy-Schahn R., Hildebrandt H. Sialic acids in the brain: gangliosides and polysialic acid in nervous system development, stability, disease, and regeneration. Physiol. Rev. 2014;94:461–518. doi: 10.1152/physrev.00033.2013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Brunngraber E.G., Witting L.A., Haberland C., Brown B. Glycoproteins in Tay-sachs disease: isolation and carbohydrate composition of glycopeptides. Brain Res. 1972;38:151–162. doi: 10.1016/0006-8993(72)90596-3. [DOI] [PubMed] [Google Scholar]
  • 22.Lunemann J.D., von Gunten S., Neumann H. Targeting sialylation to treat central nervous system diseases. Trends Pharmacol. Sci. 2021;42:998–1008. doi: 10.1016/j.tips.2021.09.002. [DOI] [PubMed] [Google Scholar]
  • 23.Wang B. Sialic acid is an essential nutrient for brain development and cognition. Annu. Rev. Nutr. 2009;29:177–222. doi: 10.1146/annurev.nutr.28.061807.155515. [DOI] [PubMed] [Google Scholar]
  • 24.Picconi B., Piccoli G., Calabresi P. Synaptic dysfunction in Parkinson's disease. Adv. Exp. Med. Biol. 2012;970:553–572. doi: 10.1007/978-3-7091-0932-8_24. [DOI] [PubMed] [Google Scholar]
  • 25.Popescu B.O., Batzu L., Ruiz P.J.G., Tulba D., Moro E., Santens P. Neuroplasticity in Parkinson's disease. J. Neural Transm. 2024;131:1329–1339. doi: 10.1007/s00702-024-02813-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Wallom K.L., Fernandez-Suarez M.E., Priestman D.A., Te Vruchte D., Huebecker M., Hallett P.J., Isacson O., Platt F.M. Glycosphingolipid metabolism and its role in ageing and Parkinson's disease. Glycoconj. J. 2022;39:39–53. doi: 10.1007/s10719-021-10023-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Te Vruchte D., Sturchio A., Priestman D.A., Tsitsi P., Hertz E., Andreasson M., Markaki I., Wallom K.L., Platt F., Svenningsson P. Glycosphingolipid changes in plasma in Parkinson's disease independent of glucosylceramide levels. Mov. Disord. 2022;37:2129–2134. doi: 10.1002/mds.29163. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Renlund M., Chester M.A., Lundblad A., Parkkinen J., Krusius T. Free N-acetylneuraminic acid in tissues in Salla disease and the enzymes involved in its metabolism. Eur. J. Biochem. 1983;130:39–45. doi: 10.1111/j.1432-1033.1983.tb07114.x. [DOI] [PubMed] [Google Scholar]
  • 29.Fois A., Balestri P., Farnetani M.A., Mancini G.M., Borgogni P., Margollicci M.A., Molinelli M., Alessandrini C., Gerli R. Free sialic acid storage disease. A new Italian case. Eur. J. Pediatr. 1987;146:195–198. doi: 10.1007/BF02343235. [DOI] [PubMed] [Google Scholar]
  • 30.Baumkotter J., Cantz M., Mendla K., Baumann W., Friebolin H., Gehler J., Spranger J. N-Acetylneuraminic acid storage disease. Hum. Genet. 1985;71:155–159. doi: 10.1007/BF00283373. [DOI] [PubMed] [Google Scholar]
  • 31.Nakano C., Hirabayashi Y., Ohno K., Yano T., Mito T., Sakurai M. A Japanese case of infantile sialic acid storage disease. Brain Dev. 1996;18:153–156. doi: 10.1016/0387-7604(95)00142-5. [DOI] [PubMed] [Google Scholar]
  • 32.Pitto M., Chigorno V., Renlund M., Tettamanti G. Impairment of ganglioside metabolism in cultured fibroblasts from Salla patients. Clin. Chim. Acta. 1996;247:143–157. doi: 10.1016/0009-8981(95)06243-2. [DOI] [PubMed] [Google Scholar]
  • 33.Mendla K., Baumkotter J., Rosenau C., Ulrich-Bott B., Cantz M. Defective lysosomal release of glycoprotein-derived sialic acid in fibroblasts from patients with sialic acid storage disease. Biochem. J. 1988;250:261–267. doi: 10.1042/bj2500261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Chigorno V., Tettamanti G., Sonnino S. Metabolic processing of gangliosides by normal and Salla human fibroblasts in culture. A study performed by administering radioactive GM3 ganglioside. J. Biol. Chem. 1996;271:21738–21744. doi: 10.1074/jbc.271.36.21738. [DOI] [PubMed] [Google Scholar]
  • 35.Sabir M.S., Hackbarth M.E., Burke J.D., Garrett L.J., Elliott G., Rivas C., Springer D.A., Leoyklang P., Clark T.S., Huizing M., Gahl W.A., Malicdan M.C.V. vol. 135. 2022. p. S107. (A Novel Experimental Mouse Model to Investigate a Free Sialic Acid Storage Disorder (Salla Disease)). [Google Scholar]
  • 36.Priestman D.A., Sabir M.S., Bush R., te Vruchte D., Wallom K.L., Fernández-Suárez M.E., Platt F.M. io; 2024. Analysis of Glycosphingolipids from Animal Tissues Protocols. [Google Scholar]
  • 37.Huebecker M., Moloney E.B., van der Spoel A.C., Priestman D.A., Isacson O., Hallett P.J., Platt F.M. Reduced sphingolipid hydrolase activities, substrate accumulation and ganglioside decline in Parkinson's disease. Mol. Neurodegener. 2019;14:40. doi: 10.1186/s13024-019-0339-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Schauer R., Kamerling J.P. Exploration of the sialic acid. World Adv Carbohydr Chem Biochem. 2018;75:1–213. doi: 10.1016/bs.accb.2018.09.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Yu R.K., Tsai Y.T., Ariga T., Yanagisawa M. Structures, biosynthesis, and functions of gangliosides--an overview. J. Oleo Sci. 2011;60:537–544. doi: 10.5650/jos.60.537. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Platt F.M. The expanding boundaries of sphingolipid lysosomal storage diseases; insights from Niemann-Pick disease type C. Biochem. Soc. Trans. 2023;51:1777–1787. doi: 10.1042/BST20220711. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Farfel-Becker T., Do J., Tayebi N., Sidransky E. Can GBA1-associated Parkinson disease Be modeled in the mouse? Trends Neurosci. 2019;42:631–643. doi: 10.1016/j.tins.2019.05.010. [DOI] [PubMed] [Google Scholar]
  • 42.Sipione S., Monyror J., Galleguillos D., Steinberg N., Kadam V. Gangliosides in the brain: physiology, pathophysiology and therapeutic applications. Front. Neurosci. 2020;14 doi: 10.3389/fnins.2020.572965. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Svennerholm L. Gangliosides and synaptic transmission. Adv. Exp. Med. Biol. 1980;125:533–544. doi: 10.1007/978-1-4684-7844-0_46. [DOI] [PubMed] [Google Scholar]
  • 44.Naito-Matsui Y., Davies L.R., Takematsu H., Chou H.H., Tangvoranuntakul P., Carlin A.F., Verhagen A., Heyser C.J., Yoo S.W., Choudhury B., Paton J.C., Paton A.W., Varki N.M., Schnaar R.L., Varki A. Physiological exploration of the long term evolutionary selection against expression of N-glycolylneuraminic acid in the. Brain J Biol Chem. 2017;292:2557–2570. doi: 10.1074/jbc.M116.768531. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Hallett P.J., Huebecker M., Brekk O.R., Moloney E.B., Rocha E.M., Priestman D.A., Platt F.M., Isacson O. Glycosphingolipid levels and glucocerebrosidase activity are altered in normal aging of the mouse. brain Neurobiol Aging. 2018;67:189–200. doi: 10.1016/j.neurobiolaging.2018.02.028. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Moors T., Paciotti S., Chiasserini D., Calabresi P., Parnetti L., Beccari T., van de Berg W.D. Lysosomal dysfunction and alpha-synuclein aggregation in Parkinson's disease. Diagnostic Links Mov Disord. 2016;31:791–801. doi: 10.1002/mds.26562. [DOI] [PubMed] [Google Scholar]
  • 47.Wong Y.C., Krainc D. Lysosomal trafficking defects link Parkinson's disease with Gaucher's disease. Mov. Disord. 2016;31:1610–1618. doi: 10.1002/mds.26802. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Blumenreich S., Nehushtan T., Barav O.B., Saville J.T., Dingjan T., Hardy J., Fuller M., Futerman A.H. Elevation of gangliosides in four brain regions from Parkinson's disease patients with a GBA mutation. NPJ Parkinsons Dis. 2022;8:99. doi: 10.1038/s41531-022-00363-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Saarela D., Lis P., Gomes S., Nirujogi R.S., Dong W., Rawat E., Glendinning S., Zeneviciute K., Bagnoli E., Fasimoye R., Lin C., Nyame K., Boros F.A., Zunke F., Lamoliatte F., Elshani S., Jaconelli M., Jans J.J.M., Huisman M.A., Posern C., Westermann L.M., Schulz A., van Hasselt P.M., Alessi D.R., Abu-Remaileh M., Sammler E.M. Tagless LysoIP method for molecular profiling of lysosomal content in clinical samples. bioRxiv. 2024 doi: 10.1101/2024.05.17.594681. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Prolo L.M., Vogel H., Reimer R.J. The lysosomal sialic acid transporter sialin is required for normal CNS myelination. J. Neurosci. 2009;29:15355–15365. doi: 10.1523/JNEUROSCI.3005-09.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Multimedia component 1
mmc1.docx (25.5KB, docx)
Multimedia component 2
mmc2.pdf (198.7KB, pdf)

Data Availability Statement

Data will be made available on request.

Articles from Biochemistry and Biophysics Reports are provided here courtesy of Elsevier

RESOURCES