10.4081/btvb.2022.41
The individual roles of cholesterol pathway biomarkers (CPB) and hemostasis inhibitors with neuroimaging outcomes were previously investigated in multiple sclerosis (MS). The purpose of this extension study was to investigate potential crosstalk between plasma CPB [total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and apolipoproteins (Apo) ApoA-I, ApoAII, ApoB, ApoC-II and ApoE] and hemostasis inhibitors [heparin cofactor-II (HCII), protein C (PC), protein S (PS), thrombomodulin, ADAMTS13 and PAI-1] in a cohort of 127 MS patients, and 40 healthy individuals (HI). The associations were assessed with regressions. In MS patients, HCII was positively associated with TC, LDL-C, HDL-C and ApoA-I (p=0.028, 0.027, 0.002 and 0.027, respectively) but negatively associated with ApoCII (p=0.018). PC was positively associated with ApoC-II (p=0.001) and ApoB (p=0.016) whereas PS was associated with TC (p=0.024) and ApoE (p=0.003) in MS. The ApoC-II associations were not observed in HI. The negative association between ApoC-II and HCll was an exception amongst other positive associations between CPB and hemostasis inhibitors in MS. CPB do not modulate the PC associations with neurodegeneration in MS.
application/pdf
2785-5309
41
3
en
Murali Ramanathan
https://creativecommons.org/licenses/by-nc/4.0
Bleeding, Thrombosis and Vascular Biology
coagulation
Crosstalk between hemostasis inhibitors and cholesterol biomarkers in multiple sclerosis
Text.Serial.Journal
https://www.btvb.org/btvb
1
Original Articles
2022-10-17
2022-05-31
2022-10-17
2022-10-24
Bleed Thromb Vascul Biol
Murali Ramanathan
2022/10/17
10.4081/btvb.2022.41
Department of Pharmaceutical Sciences, State University of New York, Buffalo; Jacobs Comprehensive MS Treatment and Research Center, Department of Neurology, University at Buffalo, State University of New York, Buffalo
2785-5309
3
coagulation
en
Gveric D, Hanemaaijer R, Newcombe J, et al. Plasminogen activators in multiple sclerosis lesions: Implications for the inflammatory response and axonal damage. Brain. 2001;124(10):1978-88.
Crosstalk between hemostasis inhibitors and cholesterol biomarkers in multiple sclerosis
https://www.btvb.org/btvb/article/download/41/41
1
                                                                                                          ORIGINAL ARTICLE

Crosstalk between hemostasis inhibitors and cholesterol biomarkers
in multiple sclerosis
                                                                            Robert Parambi,1 Nicole Ziliotto,2 Francesco Bernardi,3
                                                                            Marcello Baroni,3 Richard W. Browne,4
                                                                            Dejan Jakimovski,5 Bianca Weinstock-Guttman,6 Robert
 Correspondence: Murali Ramanathan, 355 Pharmacy Building,
 Department of Pharmaceutical Sciences, State University of New             Zivadinov,5,6 Murali Ramanathan1,6
 York, Buffalo, NY 14214-8033, USA.
                                                                            1
 Tel.: 716-645-4846. Fax: 716-829-6569.                                     Department of Pharmaceutical Sciences, State University of
 E-mail: murali@buffalo.edu                                                 New York, Buffalo, USA; 2Department of Pharmacy,
                                                                            University of Pisa, Italy; 3Department of Life Sciences and
 Key words: Cholesterol; apolipoprotein; heparin cofactor II; he-           Biotechnology, University of Ferrara, Italy; 4Department of
 mostasis inhibitor; anticoagulant; coagulation; multiple sclerosis.
                                                                            Biotechnical and Clinical Laboratory Sciences, State
 Contributions: RP and NZ equally contributed to this paper; FB –           University of New York, Buffalo, USA; 5Buffalo
 Conceptualized research, manuscript editing; RWB, MB – Con-                Neuroimaging Analysis Center, Department of Neurology,
 ducted research, manuscript editing; DJ – Manuscript editing;              University at Buffalo, State University of New York, Buffalo,
 BWG, RZ – Conceptualized research, manuscript editing; MR –                USA; 6Jacobs Comprehensive MS Treatment and Research
 Conceptualized research, manuscript writing and editing.                   Center, Department of Neurology, University at Buffalo, State
                                                                            University of New York, Buffalo, USA




                                                                                             ly
 Acknowledgements: The authors thank the many individuals with
 MS who participated in this study.




                                                                                      on
 Conflict of interest: RP, NZ, FB, MB, RWB, and DJ have nothing
 to disclose. RZ: received personal compensation from EMD                   ABSTRACT
 Serono, Genzyme-Sanofi, Bristol Myers Squibb and Novartis for                   The individual roles of cholesterol pathway biomarkers




                                                                                e
 speaking and consultant fees. He received financial support for re-        (CPB) and hemostasis inhibitors with neuroimaging outcomes
 search activities from Genzyme-Sanofi, Novartis, Bristol Myers
 Squibb, Mapi Pharma, Keystone Heart, Protembis, V-WAVE Med-
 ical. RZ is part of the editorial board of the Journal of Alzheimer’s
                                                                           us
                                                                            were previously investigated in multiple sclerosis (MS). The
                                                                            purpose of this extension study was to investigate potential
                                                                            crosstalk between plasma CPB [total cholesterol (TC), low-den-
                                                                           al
 Disease, BMC Medicine, Vein and Lymphatics, and Clinical CNS
 Drugs. BWG received honoraria for serving in advisory boards and           sity lipoprotein cholesterol (LDL-C), high-density lipoprotein
                                                                            cholesterol (HDL-C) and apolipoproteins (Apo) ApoA-I, ApoA-
                                                        ci

 educational programs from Biogen Idec, Novartis, Genentech,
 Genzyme and Sanofi, Janssen, Abbvie and Bayer. She also re-                II, ApoB, ApoC-II and ApoE] and hemostasis inhibitors [heparin
                                                      er


 ceived support for research activities from the National Institutes        cofactor-II (HCII), protein C (PC), protein S (PS), thrombomod-
 of Health, National Multiple Sclerosis Society, Department of De-          ulin, ADAMTS13 and PAI-1] in a cohort of 127 MS patients,
                                                     m



 fense, and Biogen Idec, Novartis, Genentech, Genzyme and Sanofi.           and 40 healthy individuals (HI). The associations were assessed
 MR received research funding from the National Multiple Sclerosis
                                                                            with regressions. In MS patients, HCII was positively associated
                                         om




 Society, Department of Defense and National Institute of Neuro-
 logical Diseases and Stroke. He received funding for unrelated re-         with TC, LDL-C, HDL-C and ApoA-I (p=0.028, 0.027, 0.002
 search from Otsuka Pharmaceutical and Development. He receives             and 0.027, respectively) but negatively associated with ApoC-
 a royalty from a self-published textbook.                                  II (p=0.018). PC was positively associated with ApoC-II
                                   -c




                                                                            (p=0.001) and ApoB (p=0.016) whereas PS was associated with
 Funding: Support from Grant MS190096 from the Department of                TC (p=0.024) and ApoE (p=0.003) in MS. The ApoC-II associ-
                          on




 Defense Multiple Sclerosis Research Program for the Office of the          ations were not observed in HI. The negative association be-
 Congressionally Directed Medical Research Programs (CDMRP)
                                                                            tween ApoC-II and HCll was an exception amongst other
 to the Ramanathan laboratory is gratefully acknowledged.
                    N




                                                                            positive associations between CPB and hemostasis inhibitors in
 Availability of data and materials: All data generated or analyzed         MS. CPB do not modulate the PC associations with neurode-
 during this study are included in this published article.                  generation in MS.

 Received for publication: 31 May 2022.
 Accepted for publication: 8 September 2022.
                                                                            INTRODUCTION
 Publisher’s note: All claims expressed in this article are solely those
 of the authors and do not necessarily represent those of their affili-         Multiple sclerosis (MS) is a chronic, inflammatory, de-
 ated organizations, or those of the publisher, the editors and the re-     myelinating disease of the central nervous system (CNS)
 viewers. Any product that may be evaluated in this article or claim
 that may be made by its manufacturer is not guaranteed or endorsed         that causes progressive accumulation of disabilities. Accu-
 by the publisher.                                                          mulating evidence suggests that cardiovascular risk factors
 ©
                                                                            can contribute MS disease progression.1,2 Among the car-
  Copyright: the Author(s), 2022
 Licensee PAGEPress, Italy
                                                                            diovascular risk factors linked to MS progression, the cho-
 Bleeding, Thrombosis and Vascular Biology 2022; 1:41                       lesterol pathway biomarkers (CPB), which can cause
 doi:10.4081/btvb.2022.41                                                   sustained inflammation at the vascular endothelium, have
 This work is licensed under a Creative Commons Attribution-
                                                                            been linked to poorer clinical prognosis.3
 NonCommercial 4.0 International License (CC BY-NC 4.0).                        Cholesterol is an essential component of myelin and
                                                                            cellular membranes of the CNS and it plays a role in cel-

                                             Bleeding, Thrombosis and Vascular Biology 2022; 1:41
16                                                      R. Parambi et al.




lular signaling, synapse development, and neurogenesis.4            MS, greater levels of HDL-C and the HDL-associated
Low-density lipoprotein-cholesterol (LDL-C) particles               lipoproteins ApoA-I and A-II are associated with better
transport cholesterol to tissues but also mediate pro-              global brain perfusion; ApoC-II and ApoE were associ-
atherogenic mechanisms by supplying cholesterol to ar-              ated with lower GM perfusion.22 A hyper-coagulable state
terial walls.5 High-density lipoprotein-cholesterol                 combined with perturbed fibrinolysis can contribute to
(HDL-C) particles, which mediate cholesterol reverse                neurodegeneration in MS.23
transport from tissues and inhibit LDL-C oxidation, have                The pathophysiological mechanisms by which CPB
anti-atherogenic properties.5                                       modulate MS disease progression are not well understood.
    In MS, higher LDL-C and total cholesterol (TC) have             The purpose of this study was to extend prior work on the
been associated with disability.6,7 LDL-C increases were            individual roles of CPB6,7 and hemostasis biomarkers14,15
associated with a greater number of new lesions whereas             to include potential crosstalk and interdependence be-
increases in HDL-C and its signature apolipoprotein                 tween them. In this study, we hypothesize that both CPB
(Apo) ApoA-I were associated with less gray matter (GM)             and hemostasis inhibitors might act in concert to promote
and cortical atrophy.8 Evidence for smaller LDL-C parti-            MS disease progression in a well-characterized cohort of
cles and an altered HDL-C structure has been reported in            MS patients with both classes of biomarkers.
relapsing-remitting (RR) MS.9 ApoC-II, which is found




                                                                                            ly
on triglyceride-rich lipoproteins such as chylomicrons, is




                                                                                     on
exchanged between lipoproteins and is essential for re-             MATERIALS AND METHODS
moval of cholesterol from tissues.10 ApoC-II and ApoE               Study population
are induced by oxysterol signaling and exhibit adverse as-




                                                                                e
sociations with MS progression.11                                       The study protocol was approved by the University
    There is an increasing scientific rationale for exploring
the inter-dependencies between cholesterol pathway dys-
                                                                            us
                                                                    at Buffalo Human Subjects and Institutional Review
                                                                    Board. Written informed consent was collected from all
                                                                    participants.
regulation and the coagulation cascade in order to explain
                                                                  al
clinical progression in MS.12 The extrinsic and intrinsic               The clinical data for this observational, cross-sectional
                                                      ci

coagulation pathways merge at thrombin and lead to fib-             sub-study was obtained from CEG study at the MS Center
rinogen activation that results in fibrin clots. Fibrinogen         at the State University of New York at Buffalo.8 Patients
                                                    er


deposition, which is capable of activating microglia lead-          with MS and healthy individuals (HI) were assessed and
                                                                    provided the blood samples. This sub-study involved MS
                                                   m



ing to macrophage recruitment and activation, is fre-
quently found in MS lesions.13 Previous work from our               patients and HI between 18 and 75 years of age with CPB
                                          om




group on the hemostasis inhibitors heparin cofactor II              and hemostasis biomarkers available.
(HCII), plasminogen activator inhibitor-1 (PAI-1), protein              All MS patients were assessed by a neurologist and
C (PC), protein S (PS), a disintegrin and metallopro-               their disability was ascertained on the Expanded Disabil-
                                     -c




teinase with a thrombospondin type 1 motif-13                       ity Status Scale (EDSS) scale. RRMS and progressive MS
                                                                    (PMS) disease was assigned based on disease history and
                             on




(ADAMTS13) and thrombomodulin (TM), identified po-
tential dysregulation of hemostasis markers in MS.14,15             clinical characteristics of patients and disease course
    These hemostasis inhibitors are key regulators of the           guidelines.24 The primary-progressive MS (PPMS) and
                         N




coagulation cascade. HCII inhibits thrombin at sites of             secondary-progressive MS (SPMS) patients were com-
vascular injury and is associated with reduced arterial             bined into a progressive MS (PMS) group.
plaque thickness in elderly individuals with atheroscle-                Trained project coordinators utilized a structured ques-
rotic disease.16,17 These sites are enriched with dermatan          tionnaire and collected information regarding use of disease
sulfate (DS), a type of glycosaminoglycan (GAG), that is            modifying treatment (DMT), presence of cardiovascular
synthesized and secreted by smooth muscle cells.18 DS               comorbidities such as hypertension and hyperlipidemia and
and heparin are the main GAGs that enhance the in-                  use of cardiovascular-based medications. Body mass index
hibitory function of HCII. PC inhibits factors Va and VIIIa         (BMI) was calculated as the ratio of weight in kilograms to
in plasma, and this mechanism is enhanced in the pres-              the square of the height in meters.
ence of its cofactor PS.19 Thrombin bound to TM activates
                                                                    Cholesterol and hemostasis biomarkers
PC by proteolysis. PAI-1 inhibits tissue-type plasminogen
activator, and thus fibrinolysis.                                       CPB, apolipoprotein and hemostasis components
    Elevated levels of lipids and/or apolipoproteins are            measured were made on ethylenediaminetetraacetic acid
known to have procoagulant and atherogenic effects.20,21            (EDTA) plasma samples from individuals in the non-
The progression of arterial plaques occurs at a confluence          fasted state. Study samples were collected within 30 days
of inflammatory cells, lipid accumulation and the extra-            of the clinical visit. Plasma samples were stored at -80°C
cellular matrix and can impede blood flow to tissues. In            until use.

                                     Bleeding, Thrombosis and Vascular Biology 2022; 1:41
                          Crosstalk between hemostasis inhibitors and cholesterol biomarkers in multiple sclerosis                                17



   The assay methods for the CPB: cholesterol (TC,                             sion are shown in table. To avoid false positives, bootstrap
HDL-C and LDL-C), apolipoprotein (ApoA-I, ApoA-II,                             analyses (1000 sample size), which is more robust to out-
ApoB, ApoC-II and ApoE) and hemostasis inhibitors                              liers, was used to confirm significance of findings.
(HCII, PC, PS, TM, ADAMTS13 and PAI-1) have been                                   The BPV, GMV and NCV MRI measures in MS pa-
described in publications from our group.14,15,25                              tients were analyzed as dependent variables in multiple
                                                                               regression analyses that included PC and adjusted for age,
MRI-derived measures of brain volume                                           gender, BMI, and MS disease status. To assess whether
                                                                               the PC associations were abrogated in the presence of
    The associations of PC with quantitative MRI-derived
                                                                               CPB, regression analyses were conducted with individual
measures of brain parenchymal volume (BPV), gray mat-
                                                                               CPB as an additional predictor.
ter volume (GMV) and neocortical volume (NCV) were
assessed. The MRI acquisition and analysis protocols pre-
viously described.26
                                                                               RESULTS
Statistical analyses                                                           Demographic and clinical characteristics
    All analyses were conducted on SPSS (IBM Inc., Ar-                             The demographic and clinical characteristics of the MS,




                                                                                                   ly
monk, USA, version 26.0) statistical program. A p-value                        RRMS, PMS and HI groups are displayed in Table 1. The




                                                                                          on
of less than 0.05 was considered statistically significant.                    demographic characteristics were similar in the MS
    The Fisher exact test was used to assess differences in                    (n=127) and HI (n=40) groups. The MS patients had a
the frequency of binary categorical variable such as gen-                      mean age of 54 years (SD=11.6), disease duration of 21




                                                                                      e
der and statin use in MS vs HI and RRMS vs PMS. The                            years (SD=10.8), and median EDSS score of 3.5
Student’s t-test was performed to assess differences in
age, BMI, and disease duration in years and Mann-Whit-
                                                                            us (IQR=2.0–6.0).
                                                                                   The majority of MS patients were prescribed disease-
ney U test was used to assess differences in EDSS.                             modifying therapy (DMT); 16% (n=20) were not on any
                                                                    al
    The hemostasis biomarker levels were log trans-                            DMT. Among the DMT, interferon-β (n=39, 31.2%) was
                                                     ci

formed to reduce skew. Multiple linear regression was                          most frequent, followed by glatiramer acetate (n=37,
performed with the hemostasis biomarkers assessed (ei-                         29.6%), oral DMTs (n=16, 12.8%), natalizumab (n=7,
                                                   er


ther HCII, PC, PS, TM, or PAI-1) as the dependent vari-                        5.6%) and off-label medication (n=6, 4.8%).
                                                  m



able. The individual CPB biomarkers (TC, HDL-C and                                 The RRMS (n=78) and PMS (n=49) groups had sim-
LDL-C, ApoA-I, ApoA-II, ApoB, ApoC-II and ApoE),                               ilar gender ratio (70.5% vs 73.5% females, p=0.84), BMI
                                        om




age, gender, BMI, and MS disease status were considered                        (27.9 kg/m2 vs 27.3 kg/m2, p=0.50), and statin use (14.1%
predictors of interest. The slope and p-values from regres-                    vs 18.5% patients, p=0.62).
                                  -c
                          on




Table 1. Demographic, clinical and characteristics of healthy individuals and multiple sclerosis patients.
                    N




                                                   HI                      All MS                    RR-MS                      P-MS
Sample size, n                                     40                        127                        78                        49
Female, n (%)                                   30 (75.0)                 91 (71.7)                  55 (70.5)                 36 (73.5)
Age, years                                     49.2±15.3                  54.0±11.6                 49.6±11.7                 60.9±7.20
             2
BMI, kg/m                                      27.6±6.95                  27.7±5.97                 27.9±6.25                 27.3±5.55
Disease duration, years                             –                     21.0±10.8                 16.9±9.04                 27.5±10.1
EDSS, score                                         –                   3.50 (2.0-6.0)            2.00 (1.5-3.0)            6.00 (4.0-6.5)
Statin use, n (%)                              4 (10.0%)                 20 (15.7%)                 11 (14.1%)                9 (18.4%)
DMT use, n (%)
 No treatment                                       –                     20 (16.0)                   9 (11.7)                 11 (22.9)
 Interferon beta 1                                  –                     39 (31.2)                  26 (33.8)                 13 (27.1)
 Glatiramer Acetate                                 –                     37 (29.6)                  21 (27.3)                 16 (33.3)
 Natalizumab                                        –                      7 (5.60)                   5 (6.50)                  2 (4.20)
 Other                                              –                      6 (4.80)                   4 (5.20)                  2 (4.20)
 Orals*                                             –                     16 (12.8)                  12 (15.6)                 4 (8.30)
All continuous variables (age, BMI, disease duration) are mean ± standard deviation. For the ordinal EDSS, the median (inter-quartile range) is given.
HI: healthy individuals; MS: multiple sclerosis; RR-MS: relapsing-remitting multiple sclerosis; P-MS: progressive multiple sclerosis; BMI: body mass
index; EDSS: Expanded disability status scale; DMT: Disease-modifying therapy. Dimethyl fumarate, fingolimod and teriflunomides were categorized
as Orals. Interferon-beta includes AVONEX®, REBIF®, BETASERON®, EXTAVIA® and PLEGRIDY™.


                                           Bleeding, Thrombosis and Vascular Biology 2022; 1:41
18                                                               R. Parambi et al.




Associations of CPB with hemostasis biomarkers                                was negatively associated with ApoC-II (rp=-0.21,
                                                                              p=0.018). Figure 1, which graphically summarizes HCII
    Supplementary Table S1 summarizes the CPB and he-
mostasis biomarkers in HI and MS groups. Table 2 sum-                         levels vs quartiles of TC, LDL-C, HDL-C and ApoA-I
marizes the regression results of the hemostasis                              in RRMS and PMS, shows that the association patterns
biomarkers on CPB after adjusting for age, gender, BMI,                       in the PMS group were qualitatively similar to the
and MS disease status.                                                        RRMS subgroup.
    In MS patients, HCII displayed the majority of sig-                           ApoC-II was negatively associated with HCII (see
nificant associations with CPB (Table 2). HCII was pos-                       above) but positively associated to PAI-1 (r=0.30,
itively associated with TC (Partial correlation coefficient                   p=0.001) and PC (rp=0.30, p=0.001), and displayed a
rp=0.20, p=0.028), LDL-C (rp=0.21, p=0.027), HDL-C                            trend towards significance for PS and TM (Table 2). Fig-
(rp=0.28, p=0.002) and ApoA-I (rp=0.20, p=0.027). HCII                        ure 2 shows that the association patterns of hemostasis in-


Table 2. Associations between hemostasis biomarkers and cholesterol biomarkers in multiple sclerosis. The partial correlation (rp) and
p values from multiple linear regression are shown.




                                                                                                           ly
                   HCII                 PAI-1                   PC                    PS              ADAMTS13                   TM




                                                                                                   on
TC             0.20 (0.028)*         -0.026 (0.78)          0.10 (0.26)         0.21 (0.024)*          -0.057 (0.55)         0.083 (0.38)
HDL-C          0.28 (0.002)*         -0.092 (0.32)         -0.12 (0.20)           0.14 (0.14)          -0.19 (0.039)         -0.13 (0.15)
LDL-C          0.21 (0.027)*         -0.15 (0.12)          0.037 (0.69)           0.13 (0.19)          -0.048 (0.61)         0.033 (0.73)




                                                                                            e
ApoA-I         0.20 (0.027)*         -0.12 (0.18)          -0.099 (0.28)         0.17 (0.059)          -0.12 (0.207)        -0.071 (0.44)
ApoA-II
Apo B
               0.071 (0.44)
                -0.14 (0.13)
                                     0.085 (0.35)
                                     0.066 (0.47)
                                                           -0.061 (0.51)
                                                           0.22 (0.016)*
                                                                                     us
                                                                                  0.10 (0.26)
                                                                                 0.052 (0.58)
                                                                                                       -0.090 (0.33)
                                                                                                       0.036 (0.70)
                                                                                                                            -0.023 (0.81)
                                                                                                                            0.20 (0.026)*
                                                                             al
ApoC-II       -0.21 (0.018)*        0.30 (0.001)*          0.30 (0.001)*         0.18 (0.054)          -0.040 (0.66)         0.17 (0.060)
ApoE            -0.13 (0.17)          0.10 (0.26)          0.038 (0.68)         0.27 (0.003)*          0.087 (0.34)          0.10 (0.27)
                                                              ci

The partial correlation (rp) and p values for the cholesterol biomarker from multiple linear regression analyses are shown for log transformed values
                                                            er


FXII, HCII, PAI-1, PC, PS, ADAMTS13, and TM. The multiple linear regression analyses are adjusted for age, gender, body mass index, type of MS (RR
vs PMS). The p-values for each cholesterol level that were significant after performing bootstrap analyses are marked with an asterisk.
                                                           m
                                                om




Table 3. Associations of protein C with magnetic resonance imaging measures when each cholesterol pathway biomarkers was included
as a predictor.
                                          -c




                                                          GMV                        BPV                       NCV
                                                       rp (p-value)               rp (p-value)              rp (p-value)
                                  on




Protein C                                             -0.29 (0.002)*             -0.25 (0.008)*            -0.27 (0.004)*
TC                                                     0.066 (0.50)               0.010 (0.92)              0.063 (0.52)
                               N




Protein C                                             -0.30 (0.002)*             -0.25 (0.010)*            -0.27 (0.006)*
HDL-C                                                  0.015 (0.87)               -0.085 (0.37)             0.031 (0.75)
Protein C                                             -0.30 (0.001)*             -0.25 (0.008)*            -0.27 (0.005)*
LDL-C                                                 0.043 (0.66)                -0.003 (0.98)             0.041 (0.68)
Protein C                                            -0.30 (0.002) *             -0.25 (0.009)*            -0.26 (0.007)*
ApoA-I                                                  0.11 (0.25)               0.018 (0.85)               0.11 (0.23)
Protein C                                             -0.30 (0.001)*             -0.25 (0.008)*            -0.27 (0.004)*
ApoA-II                                                 0.11 (0.25)               0.098 (0.30)               0.13 (0.17)
Protein C                                             -0.31 (0.001)*             -0.25 (0.007)*            -0.27 (0.003)*
ApoB                                                   -0.13 (0.16)               0.17 (0.08)                0.13 (0.17)
Protein C                                             -0.32 (0.001)*            -0.28 (0.002) *            -0.29 (0.002)*
ApoC-II                                                 0.12 (0.21)                0.15 (0.11)               0.13 (0.18)
Protein C                                             -0.32 (0.001)*             -0.29 (0.002)*            -0.29 (0.002)*
ApoE                                                   0.047 (0.63)               0.039 (0.68)              0.050 (0.60)
Protein C                                             -0.30 (0.001)*             -0.25 (0.007)*            -0.27 (0.004)*
The partial correlation (rp) and p-values for Protein C (logarithm transformed) and cholesterol pathway biomarkers from multiple linear regression
analyses are shown for GMV, BPV, and NCV. BPV: Whole brain volume; GMV: Gray matter volume; NCV: Cortical volume; PC: Protein C. The multiple
linear regression analyses are adjusted for age, gender, body mass index, type of MS (RR vs PMS). The p-values that were significant are marked with
an asterisk.


                                           Bleeding, Thrombosis and Vascular Biology 2022; 1:41
                     Crosstalk between hemostasis inhibitors and cholesterol biomarkers in multiple sclerosis                           19



hibitors with ApoC-II quartiles were generally similar in           the associations of PC with BPV, GMV and NCV were
the PMS and RRMS groups.                                            abrogated by including CPB as predictors. Table 3 sum-
    ApoB levels were positively associated with PC                  marizes the regression results for PC without CPB and for
(rp=0.22, p=0.016) and TM (rp=0.20, p=0.026) whereas                PC and individual CPB when both were included as pre-
TC (rp=0.21, p=0.024) and ApoE were associated with PS.             dictors. The inclusion of CPB did not affect the strength
    The hemostasis-cholesterol biomarker associations               of any of the associations of PC with BPV, GMV and
that were significant in MS patients were not observed in           NCV, which is consistent with the possibility that the PC
HI (Supplementary Table S2).                                        associations do not contain mediating influences from the
                                                                    CPB investigated.
Effects CPB on the associations of protein C with MRI
measures of brain volume
                                                                    DISCUSSION AND CONCLUSIONS
    In our earlier report, we found that greater PC was as-
sociated with lower BPV and GMV as assessed by quan-                   In this research, we investigated the associations be-
titative MRI.26 We therefore investigated whether or not            tween CPB and a panel of hemostasis inhibitors in MS




                                                                                      ly
                                                                               on
                                                                         e
                                                                  us
                                                           al
                                              ci
                                            er
                                           m
                                  om
                            -c
                     on
                N




                                                                                              A: HCII levels in the lowest, 2nd, 3rd, and
                                                                                              highest quartiles of total cholesterol in RR-
                                                                                              MS (left) and P-MS (right). B: HCII levels
                                                                                              in the lowest, 2nd, 3rd, and highest quartiles
                                                                                              of Apolipoprotein AI (ApoA-I) in RR-MS
                                                                                              and P-MS. C: HCII levels in the lowest, 2nd,
                                                                                              3rd, and highest quartiles of low-density
                                                                                              lipoprotein cholesterol (LDL-C) in RR-MS
                                                                                              and P-MS. D: HCII levels in the lowest, 2nd,
                                                                                              3rd, and highest quartiles of high-density
                                                                                              lipoprotein (HDL-C) in RR-MS and P-MS.
                                                                                              The bars represent mean values and the er-
                                                                                              rors bars are standard errors of the mean.

Figure 1. Dependence of heparin cofactor II (HCII) plasma concentrations on cholesterol pathway biomarker level quartiles in
relapsing-remitting multiple sclerosis (RR-MS) and progressive MS (P-MS) patients.


                                     Bleeding, Thrombosis and Vascular Biology 2022; 1:41
20                                                     R. Parambi et al.




patients. We found that HCII was positively associated                 In the context of cardiovascular disease, hypercholes-
with TC, LDL-C, HDL-C, and ApoA-I but negatively                   terolemia and apolipoproteins including ApoC-II and
associated with ApoC-II. ApoC-II was also associated               Apo-E are associated with shorter coagulation times and
with PC and PAI-1 and showed association trends with               higher levels of procoagulant proteins.20,21 From this sim-
PS and TM. Additional hemostasis biomarker-CPB as-                 plistic vantage point, we expected greater CPB levels to
sociations included: PC with ApoB, TM with ApoB, and               be associated with lower levels of hemostasis inhibitors.
PS with TC, and ApoE. The associations found in MS                 We were therefore surprised to find positive associations
were not observed in HI. Notably, the strength of the as-          for TC and LDL-C with HCII, which is a hemostasis in-
sociations of PC with BPV, GMV and NCV were not                    hibitor and has anticoagulant activity. Given our results,
weakened when Apo-CII, ApoB and other CPB were in-                 we were particularly interested in studies of lipid associ-
cluded as a predictor. These results build on and substan-         ations of HCII, in HI and other diseases but there was a
tially extend our earlier work14,15,26 on hemostasis               paucity of information.17 It is also noteworthy that PC
markers in MS by including the clinically relevant focus           antigen has negative rather than positive associations with
on CPB.                                                            MRI measures of brain volume.26 This raises the possibil-




                                                                                           ly
                                                                                    on
                                                                              e
                                                                           us
                                                                 al
                                                    ci
                                                  er
                                                 m
                                         om
                                   -c
                            on
                        N




                                                                                           A: HCII concentration in the lowest, 2nd,
                                                                                           3rd, and highest quartiles of ApoC-II in RR-
                                                                                           MS (left) and P-MS (right). B: PAI-1 con-
                                                                                           centration in the lowest, 2nd, 3rd, and highest
                                                                                           quartiles of ApoC-II in RR-MS and P-MS.
                                                                                           C: PC concentrations in the lowest, 2nd, 3rd,
                                                                                           and highest quartiles of ApoC-II in RR-MS
                                                                                           and P-MS. The bars represent mean values
                                                                                           and the errors bars are standard errors of
                                                                                           the mean.

Figure 2. Dependence of hemostasis biomarker concentrations on apolipoprotein C-II level quartiles in relapsing-remitting mul-
tiple sclerosis (RR-MS) and progressive (P-MS) patients.


                                    Bleeding, Thrombosis and Vascular Biology 2022; 1:41
                     Crosstalk between hemostasis inhibitors and cholesterol biomarkers in multiple sclerosis                21



ity that MS neurodegeneration can be facilitated when                    We postulate that the nexus of interactions between
there is dysregulation of a key anticoagulation biomarkers          lipoprotein lipase (LPL) function, GAG and CPB could
such as PC. Our results do not support a role for CPB in            be a potential biomolecular pathway that could plausibly
the PC associations with MRI measures.                              explain many of our results, particularly those related to
     However, studies have investigated the lipid associa-          HCII and ApoC-II. LPL is present in the vascular endothe-
tions of PS, PC and PAI-1 in HI, which provided a frame-            lium of brain capillaries and also in several CNS tissues
work for comparative assessment of our findings in MS.              including the hippocampus, cortical areas and the dentate
In a study of HI from south-eastern England, TC was                 gyrus, which is an area of neurogenesis.34 ApoC-II is a co-
found to be associated with PS (and PC) levels.27 In com-           factor that activates triglyceride hydrolysis by LPL. LPL
parison, we found an association between TC and PS but              also interacts with ApoE-rich lipoproteins of the brain and
did not find evidence for the TC-PC association.27 In               its interactions with circulating HDL, LDL and VLDL at
Japanese women, PS was found to be associated with TC,              the vascular endothelium facilitate lipoprotein particle up-
LDL-C, ApoA-II, ApoC-II and ApoE;28 in our MS group,                take.34 GAGs are important for tethering LPL in the brain
we found associations of PS with TC and ApoE and a                  because the glycosylphosphatidylinositol-anchored high-
trend with ApoC-II. HDL-C and ApoA-I, the signature                 density lipoprotein binding protein 1 (GPI-HBP1) that
apolipoprotein of HDL particles, increase PS and PC an-             tethers LPL in heart, skeletal muscle and adipose tissue




                                                                                      ly
ticoagulant activities.29 We could not estimate PS or PC            capillaries is absent on brain capillaries.35 The anticoagu-




                                                                               on
activity because the plasma samples available were anti-            lant activities of HCII are enhanced as a result of interac-
coagulated with EDTA. We found a trend (p=0.059) be-                tion with GAGs such as heparan sulfate and dermatan
tween PS levels and ApoA-I. Kim et al. found                        sulfate that tether LPL.36 LDL-C stimulates GAG secre-




                                                                         e
associations of PC levels with TC and LDL-C in a sample             tion by vascular smooth muscle cells37 but this effect is
of Korean HI.20 We identified an association of PC with
ApoB, the signature apolipoprotein of LDL, but did not
                                                                  usantagonized by HDL-C. The positive associations be-
                                                                    tween LDL-C and ApoB, which are proatherogenic, with
find evidence for the association between PC with TC or             HCII and PC respectively, in MS patients may represent
                                                           al
LDL-C in MS patients. PAI-1 was increased in active MS              a hemostatic regulatory mechanism for slowing vascular
                                              ci

compared to stable MS30 and PAI-1 levels in Japanese HI             changes caused by prothrombotic and atherosclerotic
were found to be associated with TC, ApoB and ApoC-                 pathophysiological process.18
                                            er


II.31 In our MS group, we found the association between                  The pathogenic role of macrophages, which express
                                           m



ApoC-II with PAI-1. We surmise that our PS, PC and PAI-             LPL, in the inflammation at the atherosclerotic lesion is
1 results are partially concordant with findings reported           well established.38 However, macrophages are a partic-
                                  om




in the literature for HI.                                           ularly important immune cell type in MS pathogenesis
     While our study provides information on the associa-           because they are capable of extravasation across the
tions of CPB with hemostasis inhibitors, it has limitations.        blood-brain barrier;39 they modulate immune milieu in
                            -c




For example, we did not measure oxidized LDL-C which                active lesions toward inflammatory phenotypes by pre-
                     on




is important in both atherogenesis32 and also in MS.33              senting antigens and toward anti-inflammatory pheno-
While the associations of CPB levels with HC-II were not            types by phagocytosing myelin debris.40,41 Macrophages
statistically significant, the plots of HC-II vs CPB quar-          express LPL42,43 and also upregulate the LPL cofactor
                 N




tiles (Supplementary Figure S1) were qualitatively similar          ApoC-II in response to activation of the liver X receptor
to those observed in MS. The ApoC-II associations with              transcription factor.44 Pathological evidence indicates ac-
hemostasis inhibitors found in MS were not present in HI            tivation of LXR by macrophages in active MS lesions.45
(Supplementary Table S2 and Supplementary Figure S2).               In the experimental allergic encephalitis model of MS,
Our study had a cross-sectional design and only a limited           PC activation resulted in a reduction in activated
number of HI, which may have limited the statistical                macrophages and increases in the inflammatory markers
power to detect associations between CPB and hemostasis             tumor necrosis factor-α and intercellular adhesion mol-
inhibitors. While the findings are consistent with the pos-         ecule-1.46 In MS, PAI-1 was found to be localized in
sibility that CPB can contribute to dysregulated levels of          perivascular mononuclear cells and foamy macrophages
hemostasis inhibitory biomarkers, the possibility that the          in lesions.47 We hypothesize that CPB aggravate inter-
associations are simply correlations unrelated to causation         actions between activated endothelial cells and
cannot be formally precluded. We did not have follow-up             macrophages/monocytes in the inflammatory MS patho-
hemostasis inhibitor measurements, which could have en-             physiological milieu that can contribute to hemostasis
abled us to assess whether changes in PC (and other he-             and endothelial barrier dysfunction.
mostasis inhibitors) abrogated the associations of HDL-C                 In conclusion, our results of CPB and hemostasis in-
biomarkers changes with GMV and NCV atrophy over 5-                 hibitors in MS provide evidence for crosstalk between
years follow-up.8                                                   these important homeostatic pathways.

                                     Bleeding, Thrombosis and Vascular Biology 2022; 1:41
22                                                             R. Parambi et al.




                                                                                 tor II: discovery, properties, and role in controlling vascular
REFERENCES                                                                       homeostasis. Semin Thromb Hemost 2011;37:339-48.
                                                                           18.   Aihara K-i, Azuma H, Akaike M, et al. Heparin Cofactor II
 1. Kappus N, Weinstock-Guttman B, Hagemeier J, et al. Car-
                                                                                 as a Novel Vascular Protective Factor Against Atheroscle-
    diovascular risk factors are associated with increased lesion
                                                                                 rosis. J Atheroscler Thromb 2009;16:523-31.
    burden and brain atrophy in multiple sclerosis. J Neurol
                                                                           19.   Griffin JH, Zlokovic BV, Mosnier LO. Activated protein C,
    Neurosurg Psychiatry 2016;87:181-7.
                                                                                 protease activated receptor 1, and neuroprotection. Blood
 2. Jakimovski D, Topolski M, Genovese AV, et al. Vascular as-
    pects of multiple sclerosis: emphasis on perfusion and car-                  2018;132:159-69.
    diovascular comorbidities. Expert Rev Neurother                        20.   Kim JA, Kim JE, Song SH, et al. Influence of blood lipids on
    2019;19:445-58.                                                              global coagulation test results. Ann Lab Med 2015;35:15-21.
 3. Zhornitsky S, McKay KA, Metz LM, et al. Cholesterol and                21.   Orsi FA LW, Van der Laarse A, Ruhaak LR, et al. Associa-
    markers of cholesterol turnover in multiple sclerosis: rela-                 tion of apolipoproteins C-I, C-II, C-III and E with coagula-
    tionship with disease outcomes. Mult Scler Relat Disord                      tion markers and venous thromboembolism risk. Clin
    2016;5:53-65.                                                                Epidemiol 2019;11.
 4. Hussain G, Wang J, Rasul A, et al. Role of cholesterol and             22.   Jakimovski D, Zivadinov R, Dwyer MG, et al. High density
    sphingolipids in brain development and neurological dis-                     lipoprotein cholesterol and apolipoprotein A-I are associated
    eases. Lipids Health Dis 2019;18:26.                                         with greater cerebral perfusion in multiple sclerosis. J Neu-




                                                                                                        ly
 5. Kontush A, Chapman MJ. Functionally Defective High-                          rol Sci 2020;418.
    Density Lipoprotein: A New Therapeutic Target at the                   23.   Ziliotto N, Bernardi F, Jakimovski D, et al. Coagulation




                                                                                                on
    Crossroads of Dyslipidemia, Inflammation, and Atheroscle-                    Pathways in Neurological Diseases: Multiple Sclerosis.
    rosis. Pharmacol Rev 2006;58:342-74.                                         Front Neurol 2019;10.
 6. Tettey P, Simpson S, Taylor B, et al. An adverse lipid profile         24.   Lublin FD, Reingold SC, Cohen JA, et al. Defining the clin-




                                                                                          e
    and increased levels of adiposity significantly predict clini-               ical course of multiple sclerosis. The 2013 revisions. Neu-
    cal course after a first demyelinating event. J Neurol Neu-
    rosurg Psychiatry 2017;88:395-401.
 7. Weinstock-Guttman B, Zivadinov R, Mahfooz N, et al.
                                                                           25.     us
                                                                                 rology 2014;83:278-86.
                                                                                 Browne RW, Jakimovski D, Ziliotto N, et al. High-density
                                                                                 lipoprotein cholesterol is associated with multiple sclerosis
                                                                         al
    Serum lipid profiles are associated with disability and MRI                  fatigue: A fatigue-metabolism nexus? J Clin Lipidol
    outcomes in multiple sclerosis. J Neuroinflammation                          2019;13:654-63.e1.
                                                            ci

    2011;8:127.                                                            26.   Ziliotto N, Zivadinov R, Jakimovski D, et al. Relationships
                                                                                 Among Circulating Levels of Hemostasis Inhibitors,
                                                          er


 8. Murali N, Browne RW, Fellows Maxwell K, et al. Choles-
    terol and neurodegeneration: longitudinal changes in serum                   Chemokines, Adhesion Molecules, and MRI Characteristics
                                                         m



    cholesterol biomarkers are associated with new lesions and                   in Multiple Sclerosis. Front Neurol 2020;11.
    gray matter atrophy in multiple sclerosis over 5 years of fol-         27.   Maccallum PK, Cooper JA, Martin J, et al. Associations of
                                               om




    low-up. Eur J Neurol 2020;27:188-e4.                                         protein C and protein S with serum lipid concentrations. Br
 9. Jorissen W, Wouters E, Bogie JF, et al. Relapsing-remitting                  J Haematol 1998;102:609-15.
    multiple sclerosis patients display an altered lipoprotein pro-        28.   Otsuka Y, Ueda M, Nakazono E, et al. Relationship between
                                         -c




    file with dysfunctional HDL. Sci Rep 2017;7:43410.                           plasma protein S levels and apolipoprotein C-II in Japanese
10. Isshiki M, Hirayama S, Ueno T, et al. Apolipoproteins C-II                   middle-aged obese women and young nonobese women.
                                 on




    and C-III as nutritional markers unaffected by inflammation.                 Blood Coagul Fibrinolysis 2018;29:39-47.
    Cli Chim Acta 2018;481:225-30.                                         29.   Griffin JH, Kojima K, Banka CL, et al. High-density
11. Fellows Maxwell K, Bhattacharya S, Bodziak ML, et al.                        lipoprotein enhancement of anticoagulant activities of
                            N




    Oxysterols and apolipoproteins in multiple sclerosis: a 5                    plasma protein S and activated protein C. Journal Clin Invest
    year follow-up study[S]. J Lipid Res 2019;60:1190-8.                         1999;103:219-27.
12. Mandoj C, Renna R, Plantone D, et al. Anti-annexin anti-               30.   Onodera H, Nakashima I, Fujihara K, et al. Elevated Plasma
    bodies, cholesterol levels and disability in multiple sclerosis.             Level of Plasminogen Activator Inhibitor-1 (PAI-1) in Pa-
    Neurosci Lett 2015;606:156-60.                                               tients with Relapsing-Remitting Multiple Sclerosis. Tohoku
13. Davalos D, Mahajan KR, Trapp BD. Brain fibrinogen dep-                       J Exp Med 1999;189:259-65.
    osition plays a key role in MS pathophysiology - Yes. Mult             31.   Iida K, Tani S, Atsumi W, et al. Association of plasminogen
    Scler 2019;25:1434-5.                                                        activator inhibitor-1 and low-density lipoprotein heterogene-
14. Ziliotto N, Bernardi F, Jakimovski D, et al. Hemostasis bio-                 ity as a risk factor of atherosclerotic cardiovascular disease
    markers in multiple sclerosis. Eur J Neurol 2018;25:1169-                    with triglyceride metabolic disorder: a pilot cross-sectional
    76.                                                                          study. Coron Artery Dis 2017;28:577-87.
15. Ziliotto N, Zivadinov R, Baroni M, et al. Plasma levels of             32.   Li D, Mehta JL. Oxidized LDL, a critical factor in athero-
    protein C pathway proteins and brain magnetic resonance                      genesis. Cardiovasc Res 2005;68:353-4.
    imaging volumes in multiple sclerosis. Eu J Neurol                     33.   Palavra F, Marado D, Mascarenhas-Melo F, et al. New
    2020;27:235-43.                                                              Markers of Early Cardiovascular Risk in Multiple Sclerosis
16. Aihara K-i, Azuma H, Takamori N, et al. Heparin Cofactor                     Patients: Oxidized-LDL Correlates with Clinical Staging.
    II Is a Novel Protective Factor Against Carotid Atheroscle-                  Dis Markers 2013;34:567162.
    rosis in Elderly Individuals. Circulation 2004;109:2761-5.             34.   Wang H, Eckel RH. Lipoprotein lipase in the brain and nerv-
17. Rau JC, Mitchell JW, Fortenberry YM, et al. Heparin cofac-                   ous system. Annu Rev Nutr 2012;32:147-60.


                                          Bleeding, Thrombosis and Vascular Biology 2022; 1:41
                       Crosstalk between hemostasis inhibitors and cholesterol biomarkers in multiple sclerosis                      23



35. Goulbourne CN, Gin P, Tatar A, et al. The GPIHBP1-LPL             42. Chang HR, Josefs T, Scerbo D, et al. Role of LpL (Lipopro-
    complex is responsible for the margination of triglyceride-           tein Lipase) in Macrophage Polarization In Vitro and In
    rich lipoproteins in capillaries. Cell Metab 2014;19:849-60.          Vivo. Arterioscler Thromb Vasc Biol 2019;39:1967-85.
36. Pratt CW, Whinna HC, Church FC. A comparison of three             43. Babaev VR, Fazio S, Gleaves LA, et al. Macrophage
    heparin-binding serine proteinase inhibitors. J Biol Chem             lipoprotein lipase promotes foam cell formation and ather-
    1992;267:8795-801.                                                    osclerosis in vivo. J Clin Invest 1999;103:1697-705.
37. Wosu L, McCormick S, Kalant N. Interaction of high and            44. Wolska A, Dunbar RL, Freeman LA, et al. Apolipoprotein
    low density lipoproteins on glycosaminoglycan secretion by            C-II: New findings related to genetics, biochemistry, and
    human vascular smooth muscle cells and fibroblasts. Can J             role in triglyceride metabolism. Atherosclerosis 2017;
    Biochem Cell Biol 1984;62:984-90.
                                                                          267:49-60.
38. Xu H, Jiang J, Chen W, et al. Vascular Macrophages in Ath-
                                                                      45. Mailleux J, Vanmierlo T, Bogie JF, et al. Active liver X re-
    erosclerosis. J Immunol Res 2019;2019:4354786.
                                                                          ceptor signaling in phagocytes in multiple sclerosis lesions.
39. Ladewig G, Jestaedt L, Misselwitz B, et al. Spatial diversity
                                                                          Mult Scler 2018;24:279-89.
    of blood-brain barrier alteration and macrophage invasion
    in experimental autoimmune encephalomyelitis: a compar-           46. Verbout NG, Yu X, Healy LD, et al. Thrombin mutant
    ative MRI study. Exp Neurol 2009;220:207-11.                          W215A/E217A treatment improves neurological outcome
40. Grajchen E, Hendriks JJA, Bogie JFJ. The physiology of                and attenuates central nervous system damage in experimen-
    foamy phagocytes in multiple sclerosis. Acta Neuropathol              tal autoimmune encephalomyelitis. Metab Brain Dis




                                                                                        ly
    Commun 2018;6:124.                                                    2015;30:57-65.




                                                                                 on
41. Wouters E, Grajchen E, Jorissen W, et al. Altered                 47. Gveric D, Hanemaaijer R, Newcombe J, et al. Plasminogen
    PPARgamma Expression Promotes Myelin-Induced Foam                     activators in multiple sclerosis lesions: Implications for the
    Cell Formation in Macrophages in Multiple Sclerosis. Int J            inflammatory response and axonal damage. Brain 2001;




                                                                           e
    Mol Sci 2020;21.                                                      124:1978-88.

                                                                    us
                                                               al
                                                 ci
                                               er
                                              m
                                     om
                               -c
                       on
                  N




                                        Bleeding, Thrombosis and Vascular Biology 2022; 1:41
