Baseline characteristics and circulating angiogenesis markers
A total of 317 MS participants were included in this study where 130 (41%) had RRMS (n = 102 RRMS; n = 28 CIS), and 187 had PMS (n = 137 SPMS; n = 50 PPMS); matched to 43 healthy controls (mean age 42.1 ± 12.1 years). As expected, the PMS group was older (53.1 ± 7.3; p < 0.001 vs. other groups) and had higher EDSS scores (6.5, range 3.5–8.5; p < 0.001 vs. RRMS/CIS cohort) compared to the RRMS/CIS group (43.1 ± 9.9 mean age, 1.5 (range 0-6.5) EDSS). Sex was similar (% female) for controls (69.8%), RRMS/CIS (71.5%), and PMS (64.7%). Full baseline characteristics can be found in Supplementary Table 1.
At baseline, ETN-1, PLGF, FGF-1, FGF-2, G-CSF and IL-8 were undetectable in > 33% of all samples and were thus excluded from further analysis (see above in methods). In participants with MS, several of the angiogenic markers were positively correlated with each other while none displayed negative correspondence (Fig. 1A). BMP9, endoglin, and follistatin positively correlated with age, while EGF negatively associated with age (Fig. 1B).
Circulating angiogenesis markers are dysregulated across MS phenotypes and correlate with clinical disability
When analyzing angiogenesis markers at baseline, EGF (p < 0.01) and leptin (p < 0.05) were increased in RRMS patients compared to controls; there was a trend towards higher levels of HGF, VEGF-C, and VEGF-D in RRMS patients that did not reach significance (Fig. 2). None of the markers were meaningfully different between PMS patients and controls. However, across phenotypes, EGF was elevated in RRMS compared to PMS (p < 0.0001), while endoglin and follistatin were higher in PMS compared to RRMS (p < 0.0001 and p < 0.01 respectively, Fig. 2).
To further assess the distinct angiogenic signature across MS phenotypes, we separated PMS patients into PPMS and SPMS subgroups. EGF levels remained significantly higher in RRMS compared to both PPMS/SPMS subsets (p < 0.0001). Endoglin levels were elevated in PPMS (p < 0.0001) and SPMS (p < 0.001) compared to RRMS. Interestingly, follistatin levels were exclusively higher in PPMS patients compared to both RRMS (p < 0.0001) and SPMS (p < 0.0001). Finally, HB-EGF was higher in PPMS when compared to SPMS (p < 0.05) (Supplementary Fig. 1). No other angiogenic markers were different across phenotypes.
Finally, to delineate if angiogenic markers were associated with disability, baseline markers were compared to baseline EDSS scores. BMP9, endoglin, follistatin, and VEGF-A were positively correlated with EDSS, while EGF negatively correlated with EDSS (Fig. 3). Interestingly, this pattern (along with higher circulating levels of EGF in RRMS and endoglin/follistatin in PMS) was similar to the trends seen with age; wherein endoglin, and follistatin positively correlated and EGF was negatively associated with age (Fig. 1B). PMS patients tend to be older, and EDSS also tends to increase with age. To account for this all models were adjusted for age. After adjusting, baseline angiogenic levels remained the same and disability results were maintained for BMP9, EGF, and endoglin. There remained a trend towards correlation for follistatin which did not reach significance (p = 0.07). Table 1 summates relevant results from this study.
Table 1
Selected angiogenic markers are dysregulated in the serum and central nervous system in multiple sclerosis
Marker | Serum | CNS* | Age correlation | Disability correlation | Other |
EGF | ↑ in RRMS | ↑ in NAWM/WML across all phenotypes | (-) | (-) | |
Endoglin | ↑ in PMS | ↑ in WML (PMS); ↓ in NAWM/WML (RRMS) | (+) | (+) | |
Follistatin | ↑ in PPMS | ↑ in NAWM (PMS) | (+) | (+)** | ↑ in poor remyelinators |
HB-EGF | ↑ in PPMS | ↑ in NAGM/GML (PMS), ↓ in WML (PMS) | | | ↑ in active MS; ↓ with DMT |
Leptin | ↑ in RRMS | ↓ in NAWM (RRMS), ↑ in GML (RRMS) | | | |
*based on transcriptomic datasets (compared to MS normal appearing brain and controls). **Positive disability correlation with follistatin did not reach significance after adjusting for age (p = 0.07). DMT = disease modifying therapy; EGF = epidermal growth factor; GML = grey matter lesion; HB-EGF = heparin binding-epidermal growth factor; MS = multiple sclerosis; NAGM = normal appearing grey matter; NAWM = normal appearing white matter; PMS = progressive multiple sclerosis; PPMS = primary progressive multiple sclerosis; RRMS = relapsing-remitting multiple sclerosis; WML = white matter lesions |
Circulating angiogenesis markers correlate with inflammatory activity
Of the 130 RRMS/CIS patients, 67 (51.5%) experienced inflammatory disease activity within 1-year before blood draw (defined as a clinical relapse or new T2 lesions on MRI). There were no sex differences between active and non-active groups. Active RRMS patients were younger (38.8 ± 9.3 years vs. 47.7 ± 8.3 years, p < 0.001) and had lower EDSS scores (1.5 (0.5) vs. 2.0 (1.5), p = 0.015). The only significant angiogenesis marker between groups was HB-EGF, which was higher in active RRMS compared to non-active RRMS (95.7 (61.1) pg/mL vs. 63.3 (35.3) pg/mL respectively, p < 0.01) (Table 1).
Eighty-one patients (62.3%) were treated with a DMT at the time of blood draw. The majority of stable RRMS participants were on a DMT, compared to active RRMS participants (n = 56/63 (88.9%) vs. n = 25/67 (37.3%) respectively, p < 0.001). Neither EDSS nor sex were different between treated and untreated groups, but DMT patients were significantly older (45.7 ± 9.1 years vs. 38.9 ± 9.6 years respectively, p = 0.001). Of the patients on DMTs, 50 (61.7%) were treated with a “lower efficacy” agent. There was no significant difference when stratifying angiogenesis markers according to DMT category (not shown). Intriguingly, HB-EGF levels were lower in people treated with a DMT (90.94 (57.1) pg/mL vs. 66.15 (47.3) pg/mL respectively, p < 0.01), the only significant difference found amongst biomarkers studied (Table 1). Using a linear regression model, HB-EGF levels were modestly associated with inflammatory disease activity independent of age/EDSS/DMT use (1.012 (95% CI 1.001–1.023), p = 0.037).
Transcriptomic changes are consistent with angiogenesis dysregulation in the MS CNS
To establish if angiogenic dysregulation exists in the CNS in MS, we performed a meta-analysis of published transcriptomic datasets. Our search yielded a total of 17 studies included in the meta-analysis, 16 including brain/choroid plexus samples and one with spinal cord samples (Supplementary Fig. 2). The selected datasets along with the associated study, population, and transcriptomic profiling method are listed in Supplementary Table 2.
All studied angiogenic biomarkers were identified in at least one dataset. In the MS normal appearing brain, a significant difference was observed in the expression of EGF, endoglin, follistatin, HB-EGF, HGF, leptin and VEGF-A in at least one dataset (Fig. 4). Generally speaking, leptin was decreased across datasets in the MS normal appearing brain compared to controls, while HGF was increased. Endoglin and VEGF-A were differentially expressed across datasets but meaningfully downregulated in at least one study; while EGF, follistatin and HB-EGF were differentially expressed across datasets but significantly upregulated in at least one study (Fig. 4). No observable differences were found in the expression of ANGPT2, BMP9, and VEGF-C/D.
Angiogenic differences in MS demyelinating lesions compared to MS normal appearing brain or controls
When focusing specifically on demyelinating lesions (compared to controls or MS normal appearing brain), a significant difference in the expression of EGF, endoglin, HB-EGF, HGF, leptin, and VEGF-A/C/D was found in at least one dataset (Fig. 5). EGF and HGF were primarily increased across datasets, and significantly upregulated in 2 or more studies. Endoglin, HB-EGF, leptin, and VEGF-A/C were differentially expressed across datasets, but meaningfully upregulated or downregulated in one or more studies. Only 2 studies identified VEGF-D, with one finding a downregulation in VEGF-D, and the other finding a non-significant upregulation (Fig. 5). No observable differences were found in the expression of AGPT2, BMP9 or follistatin.
Angiogenic differences across MS phenotypes and brain regions
Significant DEGs were then categorized according to disease phenotype/region described in each study (Supplementary Table 2). Several markers were dysregulated in all MS phenotypes. EGF was upregulated in at least one study in the NAWM/WML of all MS phenotypes. Similarly, HGF was upregulated in the NAWM and both WML/GML in MS. VEGF-A was upregulated in GML and downregulated in NAWM/WML.
Several angiogenic markers were only significantly changed in a specific MS phenotype: HB-EGF was downregulated in WML and upregulated in NAGM/GML, but only in PMS. Follistatin was exclusively upregulated in PMS NAWM. VEGF-C/D were only significantly different in PMS WML, with the former upregulated and the latter downregulated. Leptin was upregulated in GML and downregulated in NAWM, but only in RRMS. Finally, endoglin was downregulated in RRMS NAWM/WML but upregulated in PMS WML. Table 1 summates transcriptomic data for relevant angiogenic molecules.
Angioneurins are associated with remyelination and disability outcomes in clinical trial cohorts
A proportion of MS participants in this study were involved in pilot or phase-2 trials. In the RRMS cohort, sixteen patients were included in a pilot trial of domperidone, a potential remyelinating agent (Clinicaltrials.gov identifier NCT02493049, see above in methods). Longitudinal MRIs were obtained at baseline, week 16, and week 32 (Supplementary Fig. 3A). Percent change in lesion FA was used to group participants into “poor remyelinators” and “good remyelinators” based on if they were in the bottom or top 50th percentile change in FA at the above timepoints (Supplementary Fig. 3B). Angiogenesis markers were measured at the above timepoints, and follistatin was significantly higher in participants with poor remyelination (Supplementary Fig. 3C, Table 1). No significant differences were found with the other angiogenesis markers, or with demographic variables between these two groups (not shown).
Another subset of PPMS participants (n = 39) participated in a phase-2 HCQ futility trial (Clinicaltrials.gov identifier NCT0291)(18). As described above in methods, this population was divided into responders (those with no disability worsening) and non-responders (those with disability worsening) based on if they experienced a ≥ 20% worsening on the T25FWT or the NHPT between baseline and 18 months of follow-up(19). Baseline age, sex, and levels of disability (NHPT, T25FW, EDSS) were not observably different between responders and non-responders. Baseline follistatin levels were significantly higher in responders compared to non-responders (not shown); no other baseline angiogenic marker was different between the 2 groups.
After 6 months of hydroxychloroquine treatment, most of the angiogenic markers remained stable (not shown). Interestingly, ANGPT2 (p < 0.01), endoglin (p < 0.0001), and leptin (p < 0.001) were all increased, while VEGF-A (p < 0.01) decreased during this period (Fig. 6A). When separating the aforementioned angiogenic markers into HCQ responders and non-responders, there were significant changes in the responder group exclusively: with a decrease in follistatin and an increase in endoglin and leptin levels (Fig. 6B).