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. Author manuscript; available in PMC: 2025 Aug 4.
Published in final edited form as: Neurobiol Dis. 2025 Jul 7;213:107024. doi: 10.1016/j.nbd.2025.107024

Reduction of sphingomyelinase activity associated with progranulin deficiency and frontotemporal dementia

Nicholas R Boyle a, Stephanie N Fox a, Aniketh S Tadepalli a, Nicholas T Seyfried b, Thomas Kukar c, Eliana M Ramos d, Alissa L Nana e, Salvatore Spina e, Lea T Grinberg e,f, Bruce L Miller e, William W Seeley e,f, Andrew E Arrant a, Erik D Roberson a,*
PMCID: PMC12320091  NIHMSID: NIHMS2099884  PMID: 40633679

Abstract

Loss-of-function mutations affecting the lysosomal protein progranulin are a leading cause of frontotemporal dementia. Progranulin mutations cause abnormalities in lysosomal lipid processing, particularly of sphingolipids, major components of neural cell membranes that play important signaling roles in the brain. Most work in this area has focused on two classes of sphingolipids, gangliosides and cerebrosides. Here, we examined enzymes involved in metabolism of another class of sphingolipids, the sphingomyelins, in both mouse models and patients with progranulin insufficiency. Acidic sphingomyelinase activity was decreased in progranulin knockout, but not heterozygous, mice. This resulted from post-transcriptional loss of acid sphingomyelinase (Smpd1) protein. Progranulin interacted with acid sphingomyelinase in immunoprecipitation and proximity ligation assays, suggesting a co-trafficking role like progranulin plays with other lysosomal enzymes. Consistent with that hypothesis, restoring progranulin in knockout mice using AAV-progranulin gene therapy corrected acid sphingomyelinase deficits. In post-mortem brain tissue from patients with frontotemporal dementia due to heterozygous progranulin mutations, neutral, but not acidic, sphingomyelinase activity was decreased. Neutral sphingomyelinase 2 (SMPD3), the predominant neutral sphingomyelinase in the brain, was reduced in patients with progranulin mutations. A similar trend (p = 0.0586) was seen in patients with sporadic frontotemporal lobar degeneration with type A TDP-43 pathology, but not in other types of frontotemporal lobar degeneration. The reduction of neutral sphingomyelinase 2 occurred in frontal, but not occipital cortex, correlating with the selective vulnerability of frontal regions seen in FTD. These data shed light on the role of progranulin in sphingomyelin metabolism and of this pathway in frontotemporal dementia.

Keywords: Frontotemporal dementia, Frontotemporal lobar degeneration, Progranulin, Sphingomyelinase, Sphingolipid, Lysosome

1. Introduction

Frontotemporal dementia (FTD) is a common form of early-onset dementia. Between 5 and 10 % of FTD is caused by loss-of-function mutations in the progranulin (GRN) gene, resulting in haploinsufficiency of the progranulin protein (Aswathy et al., 2016; Baker et al., 2006; Gijselinck et al., 2008; Mackenzie et al., 2011). FTD-GRN is associated with frontotemporal lobar degeneration (FTLD) with type A TDP-43 pathology (FTLD-TDP-A) (Mackenzie and Neumann, 2017). Complete loss of progranulin due to homozygous GRN mutations causes neuronal ceroid lipofuscinosis type 11, a lysosomal storage disease, suggesting that progranulin has a critical role in lysosomal function (Arrant et al., 2019; Elia et al., 2019; Smith et al., 2012; Valdez et al., 2017; Valdez et al., 2020). Consistent with this idea, progranulin deficiency is associated with lysosomal abnormalities including aberrant maturation, processing, and levels of lysosomal enzymes, increased lysosomal size and number, and disruption of autophagy (Arrant et al., 2019; Elia et al., 2019; Valdez et al., 2017; Valdez et al., 2020).

Many FTD-associated lysosomal abnormalities involve aberrant lipid processing, with abnormal levels of both lipids and lipid-processing enzymes (Arrant et al., 2019; Brown et al., 2022; Chen et al., 2018; Huang et al., 2020; Jian et al., 2016a; Valdez et al., 2020; Zhou et al., 2019; Zhou et al., 2017). One of the lipid processing pathways particularly affected by progranulin deficiency is sphingolipid metabolism. Sphingolipids contain a ceramide backbone with varying headgroups that define the classes of sphingolipids, including gangliosides, cerebrosides, and sphingomyelins (Hannun and Obeid, 2018). Sphingolipids are abundant in neural cell membranes, and disorders of sphingolipid metabolism cause lysosomal storage disorders.

Activities of several sphingolipid-degrading enzymes are altered by progranulin deficiency, resulting in accumulation of multiple sphingolipid substrates, particularly gangliosides and cerebrosides (Arrant et al., 2019; Brown et al., 2022; Huang et al., 2020; Kashyap et al., 2024; Logan et al., 2021; Zhou et al., 2019). Activities of β-galactosidase and α-galactosidase are elevated in Grn−/− mice, and activity of β-hexosaminidases is elevated in the brain both in FTD-GRN patients and in Grn−/− mice (Arrant et al., 2018; Arrant et al., 2019; Davis et al., 2023). Progranulin deficiency also impairs β-glucocerebrosidase (GCase), a sphingolipid-degrading enzyme linked to several neurodegenerative diseases (Arrant et al., 2019; Davis et al., 2023; Jian et al., 2016a; but see Marian et al., 2023; Valdez et al., 2020; Zhou et al., 2019). GCase interacts with progranulin, and both activity and maturation of GCase are impaired in FTD-GRN (Arrant et al., 2019; Jian et al., 2016b; Zhou et al., 2019).

The sphingomyelins are another class of sphingolipids, whose relationship with progranulin has not been as well studied. Sphingomyelins are degraded by sphingomyelinases (Airola and Hannun, 2013; Breiden and Sandhoff, 2021; Choezom and Gross, 2022; Gorelik et al., 2016; Jenkins et al., 2009), including acid sphingomyelinase (ASMase, encoded by SMPD1) in the lysosome and neutral sphingomyelinases (nSMase1, nSMase2, and nSMase3, encoded by SMPD2, SMPD3, and SMPD4, respectively) in other cellular compartments (Jenkins et al., 2009; Shamseddine et al., 2015). Deficiency of ASMase due to recessive SMPD1 mutations causes Niemann–Pick disease (types A and B), a lysosomal storage disorder with accumulation of sphingomyelin (Horinouchi et al., 1995; Rodriguez-Lafrasse and Vanier, 1999; Wasserstein and Schuchman, 1993). Deficiency of nSMase3 due to recessive SMPD4 mutations causes a neurodevelopmental disorder with microcephaly (Magini et al., 2019). nSMase2, the predominant neutral sphingomyelinase in mammalian cells, is involved in many cellular processes including production of exosomes (Choezom and Gross, 2022; Shamseddine et al., 2015), which are important for TDP-43 clearance and are abnormal in FTD (Arrant et al., 2020; Iguchi et al., 2016).

In FTD-GRN, sphingomyelins are reported to be elevated in the frontal cortex and decreased in frontal white matter, while lysosphingomyelins (the deacylated form) are elevated in the plasma (Boland et al., 2022; Khrouf et al., 2023; Marian et al., 2023). Given these apparent abnormalities in sphingomyelin processing, we asked whether sphingomyelinases are affected by progranulin deficiency. We addressed the relationship between progranulin and sphingomyelinase activity both in mouse models of progranulin insufficiency and in brain tissue from FTD-GRN patients.

2. Results

2.1. Post-transcriptional loss of acid sphingomyelinase in Grn−/− mice

To begin investigating potential roles of sphingomyelinases in progranulin-related disease, we examined sphingomyelinase activity in brain tissue homogenates from Grn−/− mice. To measure activity of both acid and neutral sphingomyelinases, sphingomyelin hydrolysis assays were performed at acidic and neutral pH (Fig. 1A). At acidic pH, Grn−/− mice had reduced sphingomyelinase activity as early as 2–3 months of age, continuing to at least 8–10 months of age (Fig. 1B), in both sexes (Fig. S1A,B). There were no changes in Grn+/− mice.

Fig. 1.

Fig. 1.

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Post-transcriptional loss of ASMase in Grn−/− mice. A, Sphingomyelinases hydrolyze sphingomyelin to produce ceramide, with acid sphingomyelinase acting at low pH and neutral sphingomyelinases acting at neutral pH. B, Sphingomyelinase activity at acidic pH in frontal cortex lysates at 2–3 and 8–10 months of age was unchanged in Grn+/− mice and decreased in Grn−/− mice (2-way ANOVA, effect of genotype, F(2,51) = 52.87, p < 0.0001; **** p < 0.0001 by Sidak’s post-hoc test). C, Loss of acid sphingomyelinase protein (Smpd1) in Grn−/− brains from a published proteomics dataset (Huang et al., 2020) (2-way ANOVA, effect of genotype, F(1,12) = 25.22, p = 0.0003; * p < 0.05, ** p < 0.01 by Sidak’s post-hoc test). D, RT-qPCR showed that Smpd1, the transcript encoding ASMase, was unchanged in Grn−/− mice (ANOVA, F(2,12) = 0.4003, p = 0.6787) E, Sphingomyelinase activity assay at neutral pH was not different in the frontal cortex of Grn−/− mice at 2–3 or 8–10 months (2-way ANOVA, F(2,74) = 0.2110, p = 0.8102; effect of genotype F(1,74) = 0.006784, p = 0.9346). F—H, No difference in any of the major neutral sphingomyelinase proteins, nSMase1, nSMase2, or nSMase3 in a published proteomics dataset (Huang et al., 2020) (F, 2-way ANOVA, effect of genotype, F(1,12) = 0.5173, p = 0.4858; G, 2-way ANOVA, effect of genotype, F(1,12) = 0.3628, p = 0.5581; H, 2-way ANOVA, effect of genotype, F(1,12) = 1.111, p = 0.3126) (Huang et al., 2020).

We then asked if this reduction of acidic sphingomyelinase activity in Grn−/− mice was caused by a loss of ASMase protein. Due to the lack of reliable murine ASMase antibodies, we analyzed a published proteomics dataset that used quantitative mass spectrometry to profile Grn−/− brains (Huang et al., 2020). In this dataset, ASMase protein (Smpd1) was decreased in Grn−/− mice, and the magnitude of the decrease was similar to that of the enzymatic activity deficit we observed (Fig. 1C). To determine if ASMase deficiency was due to transcriptional downregulation, we performed RT-qPCR. Smpd1 mRNA was unchanged in Grn−/− (and Grn+/−) mice (Fig. 1D). These findings indicate a post-transcriptional loss of ASMase in the brains of Grn−/− mice.

To determine if there were similar changes in nSMases, we investigated sphingomyelinase activity at pH 7.4. nSMase activity was unchanged in Grn+/− or Grn−/− mice (Fig. 1E), in both sexes (Fig. S1C,D). In agreement with the activity data, there were also no deficiencies in any of the neutral sphingomyelinase species in Grn−/− mice in the published proteomics dataset (Fig. 1F–H) (Huang et al., 2020). Thus, the changes in sphingomyelinase activity in Grn−/− brains are unique to ASMase.

2.2. Progranulin interacts with acid sphingomyelinase but not neutral sphingomyelinase 2

Interactions with progranulin appear to be critical for proper trafficking and maturation of some lysosomal enzymes. Progranulin interacts with many of the enzymes that exhibit abnormal levels in Grn−/− mice and patients with FTD-GRN, including GCase and cathepsin D (Arrant et al., 2019; Beel et al., 2017; Butler et al., 2019a; Butler et al., 2019b; Valdez et al., 2020; Zhou et al., 2019). Hypothesizing a similar mechanism for the reduction of ASMase, we asked if progranulin interacts with sphingomyelinases.

HA-tagged progranulin (HA-GRN) and FLAG-tagged sphingomyelinase (either ASMase or nSMase2, the predominant nSMase in the brain) were transiently transfected into HEK293T cells followed by immunoprecipitation with anti-HA antibody to pull down HA-GRN and immunoblotting with anti-FLAG to identify any co-precipitating sphingomyelinase. In cells transfected with ASMase-FLAG, there was co-immunoprecipitation ASMase with HA-GRN (Fig. 2A, S6). However, in cells co-transfected with nSMase2-FLAG, there was no co-immunoprecipitation with HA-GRN (Fig. 2A, S6). These data suggest that progranulin binds ASMase but not nSMase2. The two enzymes have little structural similarity, so this is not surprising.

Fig. 2.

Fig. 2.

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Progranulin interacts with acid sphingomyelinase but not neutral sphingomyelinase 2. A, HEK293T cells were transfected with HA-GRN (GRN) and either ASMase-FLAG (ASM) or nSMase2-FLAG (nSM2), then immunoprecipitated with anti-HA. Co-immunoprecipitation of ASMase-FLAG, but not nSMase2-FLAG, indicates progranulin binding with ASMase but not nSMase2. Full-length blot in Fig. S6. B-E, Proximity ligation assay in GRN-WT and GRN-KO HEK293 cells transfected with ASMase-FLAG or nSMase-FLAG, using anti-progranulin (endogenous) and anti-FLAG antibodies. There were numerous PLA puncta with GRN-ASMase but not with GRN-nSMase2. GRN-WT, progranulin wildtype HEK293 cells; GRN-KO, progranulin knockout HEK293 cells. Scale bar = 10 μm.

To explore this interaction in living cells, we used proximity ligation assay (PLA) for interactions between endogenous progranulin and the FLAG tag of transfected ASMase-FLAG or nSMase2-FLAG in HEK293 cells. In cells transfected with ASMase-FLAG, many GRN-FLAG PLA foci were present, indicating interactions between progranulin and ASMase (Fig. 2B). There was no PLA in control GRN-knockout HEK cells transfected with ASMase-FLAG (Fig. 2C), confirming the specificity of the interaction. In contrast, cells transfected with nSMase2 exhibited minimal PLA foci (Fig. 2D–E). Thus, both biochemical and cell-based assays indicate that progranulin interacts with ASMase but not nSMase2.

2.3. Correction of ASMase deficits by progranulin gene therapy

If the reduction of ASMase in Grn−/− mice is due to loss of critical progranulin interactions, then restoring progranulin should correct it. We tested this hypothesis using progranulin gene therapy with adeno-associated virus (AAV). AAV-Grn corrects many phenotypes of progranulin deficiency in Grn−/− mice, including abnormalities in activity of other lysosomal enzymes, such as elevated cathepsin D and reduced β-glucocerebrosidase (Arrant et al., 2018; Arrant et al., 2019). AAV-Grn was injected into the medial prefrontal cortex of Grn+/+ and Grn−/− mice and ASMase activity was assessed 8 weeks post-injection. AAV-Grn increased ASMase activity in Grn−/− mice across multiple brain regions to near wild-type levels (Fig. 3). AAV-Grn decreased ASMase activity near the injection site in wild-type mice, a finding analogous to that seen with GCase activity in AAV-Grn–injected wild-type mice (Arrant et al., 2019). These findings indicate that ASMase deficits in Grn−/− mice are reversible by replacement of progranulin.

Fig. 3.

Fig. 3.

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AAV-Grn reverses ASMase activity deficit in Grn−/− mice. AAV-Grn or AAV-GFP control was injected in the medial prefrontal cortex of 8–10-month Grn+/+ and Grn−/− mice, and acid sphingomyelinase activity was assessed in medial prefrontal cortex, motor cortex, hippocampus, and thalamus lysates after 8 weeks. ASMase activity in Grn−/− mice was increased by treatment with AAV-Grn, relative to AAV-GFP, across all brain regions (RM three-way ANOVA, effect of genotype x virus, F(1,17) = 44.26, p < 0.0001. mPFC 2-way ANOVA, genotype x virus, F(1,17) = 46.50, p < 0.0001. Motor cortex 2-way ANOVA, genotype x virus, F(1,17) = 10.49, p = 0.0048. Hippocampus 2-way ANOVA, genotype x virus, F(1,17) = 17.03, p = 0.0007. Thalamus 2-way ANOVA, genotype x virus, F(1,17) = 46.42, p < 0.0001.) For all regions, ** p < 0.01, *** p < 0.001, **** p < 0.0001 by Tukey’s multiple comparisons test). mPFC, medial prefrontal cortex.

2.4. Reduction of neutral, but not acid, sphingomyelinase activity and neutral sphingomyelinase 2 protein in the frontal cortex of FTD-GRN

These findings support a role for progranulin in regulating ASMase, with deficits when progranulin is completely absent. ASMase was not affected by partial loss of progranulin in Grn+/− mice, so we examined tissue from FTD-GRN patients with progranulin haploinsufficiency. We measured sphingomyelinase activity at both acidic and neutral pH in cortical tissue homogenates from controls and patients with pathogenic GRN mutations (FTD-GRN) (Table 1, Table S1). At acidic pH, there was no difference in sphingomyelinase activity in FTD-GRN relative to controls (Fig. 4A). Thus, like in Grn+/− mice, progranulin haploinsufficiency in patients does not reduce ASMase activity.

Table 1.

Group characteristics.

Group N Sex (%F) Age at death, years ± SD Post-mortem interval, hours ± SD
CTRL 5 2 M/3F (60) 81.2 ± 4.8 11.5 ± 10.6
FTD-GRN 12 4 M/8F (66.7) 67.4 ± 6.1 13.1 ± 7.1
S-TDP-A 7 3 M/4F (57.1) 71.4 ± 5.3 12.8 ± 6.4
S-TDP-C 7 3 M/4F (57.1) 70 ± 3.8 9.8 ± 3.5
Pick 7 3 M/4F (57.1) 68.6 ± 8 9.8 ± 3.8
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Individual case characteristics can be found in Table S1.

FTD-GRN, GRN mutation-positive FTLD-TDP-A; AD, Alzheimer’s Disease; S-TDP-A, sporadic FTLD-TDP-A; S-TDP-C, sporadic FTLD-TDP-C; Pick, Pick’s disease.

Fig. 4.

Fig. 4.

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Reduction of neutral sphingomyelinase in FTD-GRN. Sphingomyelinase activity was measured at acidic or neutral pH in lysates from frontal cortex sections. A, Acid sphingomyelinase activity was unchanged in FTD-GRN (unpaired t-test with Welch’s correction, t(5.837) = 0.6230, p = 0.5568). B, Neutral sphingomyelinase activity was significantly decreased in FTD-GRN (unpaired t-test, t(9) = 2.665, p = 0.0258; *p < 0.05). C—D, nSMase2 protein was decreased in FTD-GRN (unpaired t-test, t(9) = 3.593, p = 0.0058; **p < 0.01). FTD-GRN, GRN mutation-positive frontotemporal dementia. B is a cropped image from a representative blot; the full-length representative blot is in Fig. S7.

We then measured neutral sphingomyelinase activity, which was unchanged in mice. Interestingly, sphingomyelinase activity at neutral pH was decreased in FTD-GRN (Fig. 4B). These data indicate that there is a reduction of sphingomyelinase activity in FTD-GRN, but likely one of the neutral sphingomyelinases is impaired rather than acidic sphingomyelinase. To better understand the basis of decreased neutral sphingomyelinase activity in FTD-GRN, we investigated levels of nSMase protein. We focused on nSMase2 because it is highly enriched in the brain and accounts for approximately 90 % of brain neutral sphingomyelinase activity (Aubin et al., 2005), and prior studies in mice indicate a potential relationship between nSMase2 and clearance of pathological TDP-43 (Iguchi et al., 2016). nSMase2 protein was decreased in FTD-GRN (Fig. 4C–D), likely accounting for the reduction in nSMase activity seen in these cases.

2.5. Neutral sphingomyelinase 2 in other forms of FTD

To determine whether nSMase2 reduction is specific to FTD-GRN, we expanded the cohort to include samples from patients with sporadic FTLD-TDP-A (the same type of TDP pathology seen in FTD-GRN), sporadic FTLD-TDP-C (the type of TDP pathology associated with semantic variant primary progressive aphasia), and FTLD-Tau Pick’s disease, as well as additional FTD-GRN cases (Table 1, Table S1).

Levels of nSMase2 were again decreased in the frontal cortex of FTD-GRN patients, consistent with the reduction of activity (Fig. 5A–B). Interestingly, there was a strong trend toward a similar degree of nSMase2 reduction in sporadic FTLD-TDP-A (p = 0.0586). In contrast, nSMase2 was unchanged in sporadic FTLD-TDP-C or Pick’s disease (Fig. 5A–B), suggesting that the changes we observed were linked to a specific form of FTLD-TDP and not to the mere presence of TDP-43 dysfunction/aggregation (as also seen in FTLD-TDP-C) or of severe neurodegeneration (as also seen in FTLD-TDP-C and Pick’s disease). We then asked if this was due to transcriptional downregulation of SMPD3, the gene encoding nSMase2, using RT-qPCR. SMPD3 mRNA levels were not decreased in either FTD-GRN or sporadic FTLD-TDP-A (Fig. 5C). Thus, the loss of nSMase2 is post-transcriptional, distinguishing this mechanism from the transcriptional upregulation of many lysosomal enzymes in FTD-GRN, likely due to lysosomal dysfunction (Davis et al., 2023). Aligned with this, transcripts for ASMase (SMPD1) were increased in FTD-GRN and sporadic FTLD-TDP-A in the frontal cortex (Fig. S2).

Fig. 5.

Fig. 5.

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Post-transcriptional loss of nSMase2 in the frontal cortex of progranulin mutation–positive and –negative FTLD-TDP-A. A-B, Western blot for nSMase2 in the frontal cortex reveals loss of nSMase2 in FTD-GRN and S-TDP-A cases (ANOVA, F(4,33) = 5.036, p = 0.0028, Tukey’s multiple comparisons *p < 0.05). C, RT-qPCR from frontal cortex for SMPD3, the gene encoding nSMase2, reveals no change in RNA in any experimental group (ANOVA, F(4,33) = 1.779, p = 0.1566). FTD-GRN, GRN mutation-positive FTLD-TDP-A; S-TDP-A, sporadic FTLD-TDP-A; S-TDP-C, sporadic FTLD-TDP-C; Pick, Pick’s disease. B is a cropped image from a representative blot; the full-length representative blot is in Fig. S8.

We then asked if the reduction of nSMase2 occurred in FTLD-TDP-A cases in a region less vulnerable to TDP-43 pathology and neurodegeneration. To address this, we measured nSMase2 in the occipital cortex from the same patients. nSMase2 was not reduced in the occipital cortex of either FTD-GRN or sporadic FTLD-TDP-A (Fig. 6A–B). We also asked if there were changes in sphingomyelinase activity in the occipital cortex. At both neutral and acidic pH, sphingomyelinase activity was unchanged in the occipital cortex of FTD-GRN and sporadic FTLD-TDP-A (Fig. 6C–D).

Fig. 6.

Fig. 6.

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No reduction of SMases in the occipital cortex of FTD-GRN or FTLD-TDP-A. A-B, Western blot for nSMase2 in the occipital cortex demonstrates no significant difference in nSMase2 in FTD-GRN or S-TDP-A (Kruskal-Wallis, Kruskal-Wallis statistic = 2.636, p = 0.2676; CTRL vs. FTD-GRN p = 0.5434; CTRL vs. S-TDP-A p > 0.9999). C, Neutral sphingomyelinase activity in the occipital cortex is unchanged in FTD-GRN or S-TDP-A (Brown-Forsythe ANOVA, F(2,17.76) = 4.327, p = 0.0295; CTRL vs. FTD-GRN p = 0.7322, CTRL vs. S-TDP-A p = 0.0885 by Dunnett’s multiple comparisons test). D, Similarly, acid sphingomyelinase activity in the occipital cortex is unchanged in FTD-GRN or S-TDP-A (ANOVA, F(2,21) = 0.2063, p = 0.8152). FTD-GRN, GRN mutation-positive FTLD-TDP-A; S-TDP-A, sporadic FTLD-TDP-A. B is a cropped image from a representative blot; the full-length representative blot is in Fig. S9.

Finally, we previously described a unique case (#10 in Table S1) of a progranulin mutation carrier with a clinical diagnosis of dementia with Lewy bodies who died with pronounced Lewy body pathology and only early-stage, anatomically restricted FTLD-TDP-A pathology, suggesting that the FTD-GRN was still presymptomatic (Arrant et al., 2019). Interestingly, this case had the highest nSMase2 level in the frontal cortex of the FTD-GRN cases, at about the median level of controls (Fig. S3). While it is a single case, the finding is consistent with the idea that reduction of nSMase2 is not an invariable effect of progranulin insufficiency but rather emerges in the presence of active FTLD-TDP-A pathology.

3. Discussion

In this study, we examined the effects of progranulin insufficiency on sphingomyelinases in both mouse models and human patients. Grn−/− mice, completely deficient of progranulin, had reduced acidic sphingomyelinase activity due to post-transcriptional loss of ASMase protein, starting at an early age (Fig. 1). This is likely related to a role for direct progranulin–ASMase interactions (Fig. 2), since replacing progranulin by gene therapy restored normal ASMase levels (Fig. 3). In FTD-GRN, which is caused by haploinsufficiency of progranulin, there was no reduction of acidic sphingomyelinase activity but there was reduction of neutral sphingomyelinase activity (Fig. 4). This corresponded with posttranscriptional loss of neutral sphingomyelinase 2 protein, selectively in more affected regions (Fig. 4–6). The loss of nSMase2 appears to be a feature of FTLD-TDP-A, both FTD-GRN and sporadic (although the latter just missed statistical significance), but not of other forms of FTLD (Fig. 5).

Reduction of ASMase in Grn−/− mice mirrors certain other lysosomal enzymatic abnormalities seen in these mice, such as reduction of GCase. GCase is a lysosomal enzyme that is impaired in Grn−/− mice and also in patient-derived cortical neurons and tissue from FTD-GRN cases (Arrant et al., 2019; but see Marian et al., 2023; Valdez et al., 2020; Zhou et al., 2019). Progranulin deficiency results in incomplete GCase glycosylation, a process that occurs primarily in the endoplasmic reticulum and Golgi, suggesting that extra-lysosomal progranulin–GCase interactions are necessary for the delivery of mature GCase to the lysosome (Arrant et al., 2019). In progranulin-deficient mice, the reductions in GCase and ASMase share thematic characteristics. GCase and ASMase are both post-transcriptionally deficient in Grn−/− mice but not Grn+/− mice, they both colocalize with progranulin by PLA, and they both co-immunoprecipitate with progranulin in a neutral pH buffer (Arrant et al., 2019; Jian et al., 2016a; Zhou et al., 2019). In addition, progranulin gene therapy by AAV-Grn increases the activities of both GCase and ASMase in Grn−/− mice and somewhat reduces the activities of both GCase and ASMase in Grn+/+ mice (Arrant et al., 2019).

Why then is there no reduction of ASMase activity in FTD-GRN? Since ASMase is only reduced in Grn−/− mice, in which progranulin is completely absent, the remaining functional copy of progranulin in Grn+/− mice and in FTD-GRN seems to be sufficient for proper levels of ASMase. The fact that GCase activity, unlike ASMase activity, is reduced in FTD-GRN (Arrant et al., 2019; Valdez et al., 2020; Zhou et al., 2019) suggests some divergence in mechanism, with GCase more sensitive to partial loss of progranulin than ASMase, which is only affected by complete loss of progranulin in mice. Our data predict that there would be reduction of ASMase in CLN11, the form of neuronal ceroid lipofuscinosis caused by homozygous loss-of-function progranulin mutations. Another potential explanation is that any ASMase deficiency in FTD-GRN is compensated for by upregulation of the ASMase gene, SMPD1 (Fig. S2), which may be induced as a homeostatic mechanism due to lysosomal dysfunction in FTD-GRN. In any event, we observed no loss of acid sphingomyelinase activity in FTD-GRN.

Rather, these FTD-GRN cases have a reduction of neutral sphingomyelinase activity which seems to be related to a loss of the most abundant nSMase, nSMase2. The reduction of nSMase2 is interesting for several reasons. First, it does not seem to be an immediate consequence of progranulin insufficiency, as no change was observed in Grn+/− or Grn−/− mice (Fig. 1), nor in less affected regions of the brain in FTD-GRN (Fig. 6), nor in the brain of an apparently pre-symptomatic progranulin mutation carrier (Fig. S3). Interestingly, reduction of nSMase2, although not reaching statistical significance, strongly trended toward a similar magnitude of reduction in affected (but not less affected) regions of the brain in sporadic FTLD-TDP-A (but not in other forms of FTLD). Thus, reduction of nSMase2 appears to only be present in affected regions of the brain in individuals with FTLD-TDP-A, whether sporadic or due to progranulin mutation. Therefore, it seems that reduction of nSMase2 is a downstream feature of FTLD-TDP-A pathogenesis, whether caused by progranulin insufficiency or other factors.

The reduction of nSMase2 in FTD-GRN and sporadic FTLD-TDP-A is also interesting because nSMase2 is not a lysosomal enzyme, unlike ASMase. Although they both have sphingomyelinase activity, there are many differences between ASMase and nSMase2. While ASMase is a lysosomal enzyme classically associated with ceramide salvage and lipid catabolism (Kitatani et al., 2008), nSMase2 is localized to the Golgi and plasma membrane with highest expression in the brain (Shamseddine et al., 2015). It plays an important role in neurotrophin signaling, and the protective effects of NGF and BDNF can be blocked by nSMase2 inhibitors (Candalija et al., 2014). It is also linked to production of extracellular vesicles (EVs), which is driven by the ceramide generated by sphingomyelin hydrolysis (Trajkovic et al., 2008). This is intriguing given the potential role of exosomes in neurodegenerative disease. FTD-GRN patients have elevated levels of EVs both in brain and plasma (Arrant et al., 2020), so downregulation of nSMase2 could be a compensatory pathway induced to decrease exosome production.

We found reduction of nSMase2 in FTD patients with TDP-43 pathology, but the causal directionality of this relationship remains unclear. On one hand, accumulation of cytosolic TDP-43 could contribute to reduction of nSMase2. This idea is supported by data from rNLS8 mice, which express inducible hTDP-43 confined to the cytosolic space, and have a resulting reduction of nSMase2 following 6 weeks of hTDP-43 induction (San Gil et al., 2024), although the mechanism is unclear. Another possibility is that loss of TDP-43 function causes aberrant splicing of SMPD3 mRNA, leading to a reduction of the production of protein, although we were unable to find evidence of this in published databases of TDP-43 mis-splicing (Brown et al., 2022; Polymenidou et al., 2011). While we did not detect a difference in total SMPD3 RNA in our FTLD-TDP-A cases, splicing variants would likely not be detected by traditional qPCR. On the other hand, regional reduction of nSMase2 could contribute to development of TDP-43 pathology. Likely related to the role of nSMase2 in the generation of EVs, inhibition of nSMase2 has been reported to accelerate TDP-43 accumulation in cells due to impaired EV-mediated clearance (Iguchi et al., 2016). Thus, reduction of nSMase2 activity in FTLD-TDP-A may contribute to the intracellular accumulation of TDP-43. Conversely, as inhibitors of nSMase2 activity reduce exosome-mediated release of TDP-43 (Iguchi et al., 2016), small-molecule activators of nSMase2 might lead to increased TDP-43 clearance via exosomes.

Striking similarity in findings between FTD-GRN and sporadic FTLD-TDP-A is emerging as a common theme. The two have highly similar transcriptomic signatures (Pottier et al., 2022), loss of bis(monoacylglycero)phosphates (BMP) (Boland et al., 2022), abnormalities in lysosomal proteins and storage material (Davis et al., 2023), and the same type of TDP-43 filament in cryoEM studies (Arseni et al., 2023). We now show that they also have similar deficits in the non-lysosomal nSMase2. All of this suggests that whatever causes sporadic FTLD-TDP-A taps into the same mechanistic pathways as progranulin haploinsufficiency.

A potential limitation of this study is that the FTD-GRN group was somewhat younger than controls (Fig. S4A), since FTD tends to be a relatively early-onset dementia, but our data suggest that the modest age difference between CTRL and FTD-GRN is unlikely to explain the difference in nSMase2. First, there was also a difference in nSMase2 between FTD-GRN and sporadic TDP-C (Fig. 5A), even though those groups did not significantly differ in age (Fig. S4A). Second, although the S-TDP-C and Pick groups were also significantly younger than CTRL (Fig. S4A), they did not have a reduction in nSMase2 (Fig. 5A). Finally, and perhaps most importantly, analysis of age vs. nSMase2 correlations showed no evidence for an age effect on nSMase2 (Fig. S4B).

In summary, these data expand our understanding of abnormalities in lipid processing associated with progranulin deficiency in mice and people. Reduction of neutral sphingomyelinase 2 in regions of TDP-43 pathology demonstrates that abnormalities in lipid processing are not limited to the lysosomal abnormalities that have been clearly associated with FTD pathophysiology. This study also suggests novel potential mechanisms for both EV dysregulation and TDP-43 propagation in disease. Human neuropathology studies are not ideally suited to addressing the causality of effects, including how critical the changes in nSMase2 may be for FTD-GRN pathophysiology. Further investigation of non-lysosomal abnormalities in lipid processing in FTLD-TDP is warranted.

4. Materials and methods

4.1. Animals

Progranulin-deficient mice, originally developed in the laboratory of Dr. Robert Farese (RRID: MMRRC_036771-JAX), were maintained on a C57BL/6 J background (Filiano et al., 2013; Martens et al., 2012). Progranulin heterozygous mice (Grn+/−) were crossed to generate progranulin wild-type (Grn+/+), heterozygous, and knockout (Grn−/−) mice. The mice were bred and housed in a barrier facility accredited by the Association for Assessment and Accreditation of Laboratory Animal Care. Mice were maintained on a 12:12 light/dark cycle with lights on at 6:00 A.M. and were given ad libitum access to food and water. Males and females were used for all experiments. All experiments were approved by the Institutional Animal Care and Use Committee of the University of Alabama at Birmingham.

4.2. Sphingomyelinase activity

Sphingomyelinase activity was measured using the Amplex Red Sphingomyelinase assay kit per manufacturer protocol (Invitrogen). Briefly, assays for neutral sphingomyelinase activity were performed at pH 7.4 in buffer containing 50 mM Tris-HCl and 5 mM MgCl2, and assays for acidic sphingomyelinase were performed at pH 5.0 in 50 mM sodium acetate. For neutral sphingomyelinase activity, a one-step reaction containing both sphingomyelin and the development reagents was run for 1 h at 37 °C and fluorescence was read (Excitation 530 nm, Emission 590 nm). For acid sphingomyelinase activity, a two-step reaction was performed. Samples were incubated with sphingomyelin for 1 h, then the reaction was quenched with development reagents diluted in 100 mM Tris-HCl, pH 8.0, and allowed to incubate for another 30 min. Following this second incubation, fluorescence was measured on a BioTek Synergy 2 microplate reader. For all activity assays, 5 μg lysate was added to each well and each sample was measured in triplicate.

4.3. RT-qPCR

RNA was extracted from brain tissue using RNeasy mini kit (Qiagen). Extracted RNA concentration was measured by Nanodrop and cDNA was generated using the iScript cDNA synthesis kit (Bio-Rad). Primer sequences for each gene were purchased from IDT’s PrimeTime qPCR primers and were validated by efficiency testing with acceptable efficiencies between 90 and 110 %. Primer sequences: SMPD1 (primer 1: GAGAGAGATGAGGCGGAGA, primer 2: CTGGCTCTATGAAGCGATGG), SMPD3 (primer 1: GGTCCTGAGGTGTGCTTC, primer 2: TCTTTGCCAGCCGCTAC), HPRT1 (primer 1: GCGATGTCAATAGGACTCCAG, primer 2: TTGTTGTAGGATATGCCCTTGA). qPCR was performed on a Bio-Rad CFX96 Real Time PCR Detection System (RRID: SCR_018064).

4.4. Generation of GRN knockout HEK-293 cells

The entire coding sequence (CDS) of the GRN gene was deleted from HEK-293 cells by transfection with constructs expressing Cas9 and sgRNAs targeting areas 5′ and 3′ to the GRN coding sequence (CDS) (Fig. S5) to delete the sequence between the sgRNAs (Bauer et al., 2015). The sgRNA sequences were: 5′ – GCAAAGTACCAAGGAACGTC, 3′ – CCCTCGGGACCCCACTCGGA, and were designed with the online tool at crispr.mit.edu (Ran et al., 2013). For control cells, an sgRNA targeting LacZ (TGCGAATACGCCGGGGCGAT) was used (Savell et al., 2019). All sgRNAs were cloned into the pX330-U6-Chimeric_BB-CBh-hSpCas9 vector (RRID: Addgene_42230) (Konermann et al., 2013). HEK-293 cells were co-transfected with equivalent amounts of each GRN sgRNA plasmid or the same total amount of the LacZ sgRNA plasmid, as well as the pAcGFP-N1 plasmid (Takara #632469) to monitor transfection efficiency. Transfected cells were flow-sorted to isolate cells exhibiting strong GFP fluorescence. Single cells were then isolated by limiting dilution and clonal cell lines were expanded and genotyped for GRN deletion using the following primers: Forward (5′ to GRN CDS) – AGACTCCACTGGCCACCATA, WT Reverse (in CDS) – CTCCTCTGGCCAATCCAAGAT, KO Reverse (3′ to GRN CDS) – GAGGGGATGGCAGCTTGTAA (Fig. S5).

4.5. Cell culture

HEK293T cells (RRID: CVCL_0063) and GRN-WT and GRN-KO HEK293 cells were cultured in DMEM (Corning) supplemented with 10 % fetal bovine serum (R&D Systems) and 100 units/mL penicillin and 100 μg/mL streptomycin (Gibco) in 5 % CO2 at 37 °C. For transient transfections, plasmids containing the relevant constructs were diluted in Opti-MEM (Gibco) and incubated with Fugene (Promega) for 15 min at room temperature before being directly added to the wells. Plasmids expressing FLAG-tagged human ASMase (Origene RC219758), FLAG-tagged human nSMase2 (Origene RC218441), and HA-tagged human progranulin (derived from Origene RC202139) were used.

4.6. Co-immunoprecipitation

HEK293T cells were transiently transfected for 48 h and then lysed in buffer containing 50 mM Tris pH 7.5, 150 mM NaCl, 5 mM EDTA, 1 % Triton X-100, and 0.1 % deoxycholate. Bicinchoninic acid (BCA) assay with bovine serum albumin (BSA) standards was performed to determine protein concentration for co-IP. Briefly, 100 μg of each sample was precleared with protein G Dynabeads (Invitrogen) for 30 min and then incubated with 1–2 μg primary antibody for 12–16 h at 4 °C. Then, samples were incubated with fresh protein G Dynabeads for 4 h at 4 °C, washed three times in buffer, and denatured with 10× Reducing Agent (Invitrogen) and 4× LDS (Invitrogen) at 70 °C for 10 min.

4.7. Western blotting

Samples were prepared in 10× Reducing Agent (NuPAGE) and 4× LDS (NuPAGE), denatured at 70 °C for 10 min, run down a 4–12 % bistris gel, transferred to an Immobilon-FL PVDF (Millipore-Sigma) membrane, blocked in protein-free TBS blocking buffer (Pierce), and probed overnight with primary antibody except for GAPDH, which was probed for 2 h at room temperature. The following antibodies were used: HA (1:1000, rabbit monoclonal, C29F4, #3724, Cell Signaling Technology, RRID: AB_1549585), FLAG (1:1000, mouse monoclonal, F3165, Sigma-Aldrich, RRID: AB_259529), nSMase2 (1:1000, mouse monoclonal, G-6, #sc-166,637, Santa Cruz Biotechnology, RRID: AB_2270817), GAPDH (1:5000, mouse monoclonal, 6C5, #MAB374, MilliporeSigma, RRID: AB_2107445). Blots were then probed with species-matched IRdye-conjugated secondary antibodies (RRIDs: AB_621847, AB_621848, AB_10706161, AB_2713919) and scanned on an Odyssey scanner (RRID: SCR_023765). Relative intensity of bands was measured using Image Studio Lite software (RRID: SCR_013715). For human samples, two slices from opposed sides of each tissue block were taken, and the two slices were averaged for analysis.

4.8. Proximity ligation assay

Glass coverslips were coated in a solution of poly-d-lysine and laminin in sterile water. Cells grown on glass coverslips were transfected as described above with the respective constructs and after 48 h were fixed for 30 min in a mixture of 4 % paraformaldehyde and 4 % sucrose in 1× PBS. Cells were then permeabilized for 20 min in 0.025 % Triton X-100 in 1× PBS, then blocked for 1 h with 5 % (w/v) bovine serum albumin in 1× PBS. Cells were probed overnight with primary antibodies to human progranulin (0.04 μg/mL, goat polyclonal, R&D systems #AF2420, RRID: AB_2114489) and DYKDDDDK (FLAG) tag (1:25000, rabbit monoclonal, D6W5B, Cell Signaling Technology, RRID: AB_2572291) in 5 % bovine serum albumin in 1× PBS. Duolink PLA was performed per manufacturer instructions. Briefly, the primary was removed, and Duolink PLA probes specific to the species of the primary antibodies were added for 60 mins at 37 °C (Rabbit plus Sigma-Aldrich Cat# DUO92002, RRID:AB_2810940 and Goat minus Sigma-Aldrich Cat# DUO92006, RRID:AB_2943059). PLA reagents were removed, and ligation reagents were added for 30 min at 37 °C. Then, ligation reagents were removed and amplification reagents were added for 100 min at 37 °C. The amplification reagents were removed and samples were incubated in secondary antibodies (1:1000, donkey anti-rabbit IgG Alexa Fluor 647 RRID: AB_2536183, and 1:1000, donkey anti-goat IgG Alexa Fluor 594 RRID: AB_2535864) for 60 min in the dark at ambient temperature. Coverslips were mounted with Prolong Diamond (ThermoFisher) on Colorfrost slides (Fisher) and imaged at 20× on an epifluorescent microscope (Nikon) and CCD camera (Nikon). All images were processed with ImageJ (RRID: SCR_003070).

4.9. AAV administration

The effects of AAV-Grn on ASMase activity in Grn+/+ and Grn−/− mice was measured in medial prefrontal cortex, motor cortex, hippocampus, and ventral posteromedial/posterolateral samples from mice used in a previous study of AAV-Grn (Arrant et al., 2019). 3–6-month-old mice were injected with AAV-GFP or AAV-Grn and euthanized for analysis 4 weeks later. The right hemisphere of the brain was flash frozen and manually subdissected prior to lysis in 50 mM Tris pH 7.5, 150 mM NaCl, 5 mM EDTA, 1 % Triton X-100, and 0.1 % deoxycholate.

4.10. Patient brain samples

Post-mortem samples from the inferior orbital gyrus and the inferior occipital cortex were provided by the Neurodegenerative Disease Brain Bank at the University of California, San Francisco. Brains were donated with the consent of the patients or their surrogates in accordance with the Declaration of Helsinki and the research was approved by the University of California, San Francisco Committee on Human Research. All cases were screened for GRN mutations, and clinical and neuropathological diagnosis were made using standard diagnostic criteria as previously described (Arrant et al., 2019). Two tissue sections were taken from each block. They were measured independently and averaged for each of the experiments using these samples.

4.11. Statistical analysis

For figures containing mouse data (Figs. 1 and 3), n is defined as one mouse. The datasets in Fig. 1B–C and 1F–H were assessed with 2-way ANOVA and, for those reaching statistical significance, were further compared using Sidak’s post-hoc test. Fig. 1D–E were assessed with one-way ANOVA. Acid sphingomyelinase activity data in Fig. 3 were analyzed by three-way repeated measures (RM)-ANOVA matching brain regions within mouse. As the data had a significant interaction effect between virus and genotype, the brain regions were independently assessed using two-way ANOVA. Significant interactions were followed by Sidak’s post-hoc test to determine the virus effect within genotypes. Data in Fig. 4 were analyzed by unpaired t-test, and Welch’s correction was applied when samples had unequal variance (Fig. 4A). Western blot data of nSMase2 protein in Fig. 5 were analyzed using one-way ANOVA; data reaching statistical significance were further assessed with Tukey’s post hoc test (Fig. 5A). For occipital cortex nSMase2 protein data in Fig. 6A, Kruskal-Wallis test was performed due to the non-normal distribution of the data. For the data on SMase activity at pH 7.4 in Fig. 6C, Brown-Forsythe ANOVA was performed due to unequal variance with normal distribution of the data. One-way ANOVA was performed for Fig. 6D. For the SMPD1 mRNA data in Fig. S2, Kruskal-Wallis test was performed followed by Dunn’s post-hoc test. Data were analyzed using GraphPad Prism (RRID:SCR_002798) with α set at 0.05; error bars in bar plots represent mean ± SEM.

Supplementary Material

1

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.nbd.2025.107024.

Funding statement

This work was supported by the Bluefield Project to Cure Frontotemporal Dementia and NIH grants F30AG071114, K00AG068428, R00AG056597, RF1AG079318, R01NS105971 and P30AG086401. Human tissue samples were provided by the Neurodegenerative Disease Brain Bank at the University of California, San Francisco, which receives funding support from NIH grants P01AG019724 and P30AG062422, the Consortium for Frontotemporal Dementia Research, and the Tau Consortium.

Footnotes

CRediT authorship contribution statement

Nicholas R. Boyle: Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Stephanie N. Fox: Writing – review & editing, Visualization, Funding acquisition, Data curation. Aniketh S. Tadepalli: Data curation. Nicholas T. Seyfried: Writing – review & editing, Data curation. Thomas Kukar: Writing – review & editing, Data curation. Eliana M. Ramos: Writing – review & editing, Project administration. Alissa L. Nana: Writing – review & editing, Resources, Project administration. Salvatore Spina: Writing – review & editing, Resources, Project administration. Lea T. Grinberg: Writing – review & editing, Project administration, Methodology. Bruce L. Miller: Writing – review & editing, Resources, Project administration, Funding acquisition. William W. Seeley: Writing – review & editing, Project administration, Methodology, Funding acquisition. Andrew E. Arrant: Writing – review & editing, Validation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Erik D. Roberson: Writing – review & editing, Writing – original draft, Visualization, Supervision, Resources, Project administration, Methodology, Funding acquisition, Formal analysis, Conceptualization.

Declaration of competing interest

No authors declare competing interests.

Data availability

Data will be made available on request.

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Supplementary Materials

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NIHMS2099884-supplement-1.docx (2.4MB, docx)

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