Уровень амилиновой сыворотки у пациентов с множественным склерозом: перекрестное исследование сечения.

1. Introduction

Multiple sclerosis (MS) is a complex, chronic, immune-mediated disorder of the central nervous system (CNS) characterized by neuroinflammation, demyelination, axonal injury, and progressive neurodegeneration. It affects both white and gray matter and is a major cause of neurological disability among young adults. [ 1 - 4 ]

Amylin is a pancreatic beta (β)-cell hormone co-secreted with insulin that regulates postprandial glucose homeostasis, gastric emptying, glucagon secretion, and satiation. [ 5 - 12 ] Circulating concentrations of amylin are associated with insulin secretion, nutritional status, and adiposity. [ 10 , 13 - 16 ] Amylin also acts within several regions of the CNS via calcitonin receptor–receptor activity-modifying protein complexes, supporting an interface between peripheral metabolic regulation and central homeostatic signaling. [ 17 - 27 ]

Most evidence linking amylin to neurological disease comes from studies of type 2 diabetes mellitus (T2DM) and Alzheimer disease (AD), in which altered amylin homeostasis has been associated with protein aggregation, impaired amyloid clearance, neuroinflammation, and neuronal injury. [ 28 - 46 ] These observations cannot be directly extrapolated to MS. Nevertheless, amylin-related receptor signaling and shared peptide-degrading pathways involving neprilysin, endothelin-converting enzyme, and insulin-degrading enzyme (IDE) may intersect with processes relevant to MS, including microglial activation, immune regulation, oxidative stress, demyelination, and neurodegeneration. [ 47 ] These potential mechanisms remain hypothetical and have not been established in human MS.

To the best of our knowledge, serum amylin levels have not previously been systematically investigated in patients with MS. The present study therefore aimed to compare serum amylin levels between patients with MS and healthy controls, examine differences across MS phenotypes, and evaluate the association between serum amylin and MS status, while accounting for relevant anthropometric, metabolic, and biochemical variables.

2. Materials and methods

2.1. Ethical review

The research received approval from the Non-Invasive Clinical Research Ethics Committee of Pamukkale University, Denizli, Turkey. The study complies with the World Medical Association Declaration of Helsinki.

2.2. Participants

A total of 62 patients with MS who met the 2017 McDonald criteria were recruited from Pamukkale University Hospital, Denizli, Turkey. The MS cohort comprised 33 patients with RRMS, 22 with secondary progressive MS (SPMS), and 7 with PPMS. All patients were clinically stable and in remission at the time of blood sampling and had not received corticosteroids recently. Patients with relapsing–remitting or SPMS were receiving disease-modifying therapy, whereas those with PPMS were not. In the MS cohort, patients with renal or hepatic failure, concomitant systemic inflammatory or infectious disease, or neurological disorders other than MS were excluded. Disease duration, Expanded Disability Status Scale (EDSS) scores, detailed characteristics and duration of disease-modifying treatment, relapse frequency, and the interval since the most recent relapse were not systematically available in the study dataset and therefore could not be incorporated into the analyses.

The control group comprised 63 individuals without MS, renal or hepatic failure, systemic inflammatory or infectious disease, or neurological disorders. Individuals with a family history of MS, or with documented autoimmune or infectious conditions relevant to neuroinflammatory status or the differential diagnosis of MS, including systemic lupus erythematosus, Epstein–Barr virus infection, Sjögren syndrome, and Lyme disease, were excluded from the control group.

No participant in either group had a known endocrine disorder other than diabetes mellitus (DM), and none was pregnant at the time of blood sampling.

In each group, demographic data, BMI, DM, hypertension, cardiac disease, serum glucose, thyroid-stimulating hormone (TSH), alanine aminotransferase (ALT), AST, creatinine, low-density lipoprotein cholesterol (LDL), very-low-density lipoprotein cholesterol (VLDL), high-density lipoprotein cholesterol (HDL), and triglyceride levels were assessed. DM and obesity were not exclusion criteria and were retained as metabolic variables for statistical analysis.

Written informed consent was obtained from all participants, and serum amylin levels were measured in both groups.

2.3. Blood collection

After informed consent was obtained, 5 mL blood samples were collected from the median cubital vein and placed in yellow-capped serum tubes containing a separating gel. Samples were centrifuged at 2500 × g for 20 minutes at +4°C. The resulting serum was aliquoted into Eppendorf® tubes and stored at −20°C until analysis.

2.4. Quantification of amylin

Amylin concentrations in serum samples were determined using ELISA kits from Bioassay Technology Laboratory (Biotech Ltd, Shanghai, China). Assays were conducted at 25°C on the day of analysis. Absorbances were measured at 450 nm using a BioTek ELISA reader, and concentrations were quantified using BioTek Gen5 software. The within-run coefficient of variation (CV) for amylin was <8%, and the inter-trial CV was <10%. The amylin reading range was 20 to 6000 ng/L, with a kit sensitivity of 9.49 ng/L.

2.5. Study design

This observational, cross-sectional case-control study was designed to compare serum amylin levels between patients with MS and healthy controls and to investigate the association between serum amylin levels and MS status.

2.6. Statistical analysis

Statistical analyses were performed using IBM SPSS Statistics version 25.0 (IBM Corp., Armonk, NY, USA). Continuous variables were presented as mean ± standard deviation (SD), median (interquartile range [IQR]), and minimum–maximum values, whereas categorical variables were expressed as frequencies and percentages. Normality of continuous variables was assessed using the Kolmogorov–Smirnov and Shapiro–Wilk tests. Comparisons between 2 independent groups were performed using the Mann–Whitney U test. Effect size for the Mann–Whitney U test was calculated using Cohen d (Z /√N). Comparisons among 4 independent groups were performed using Kruskal–Wallis variance analysis. When a significant overall difference was detected, pairwise comparisons were conducted using the Mann–Whitney U test with Bonferron’s correction. Effect size for the Kruskal–Wallis test was calculated using epsilon-squared (ε 2 ). ROC curve analysis was performed to evaluate the discriminatory performance of serum amylin, and the area under the curve (AUC) with 95% confidence intervals (CIs) was calculated. Univariate logistic regression analysis was used to evaluate associations between demographic and laboratory variables and disease status. Variables with statistical significance in the univariate analysis were subsequently entered into a multivariable logistic regression model to identify independent predictors. Odds ratios (ORs) with 95% CIs were reported. A 2-sided P value of <.05 was considered statistically significant.

3. Results

In the patient group, 46 patients (74.2%) were female and 16 (25.8%) were male. The female-to-male ratio was 2.8, consistent with established patterns reported in the literature. The mean serum amylin level in the patient group was 234.01 ± 94.84 ng/L, whereas in the healthy control group it was 284.04 ± 110.02 ng/L. This difference was statistically significant ( P  = .003; Table 1 ).

Table 1 Comparison of serum amylin levels in healthy control and multiple sclerosis patient groups. Parameter Category Healthy control group Multiple sclerosis group
P
Gender Male 21 (33.3%) 16 (25.8%) .357 (cs = 0.850) Female 42 (66.7%) 46 (74.2%) Serum amylin level Mean ± SD 284.04 ± 110.02 234.01 ± 94.84 .003 * ( z  = -2.923) d  = 0.261 Med (IQR) 267.63 (204.7–351.67) 203.85 (170.84–269.78) Min–max 119.48–640.43 110.28–540.46 cs = chi-square test, d = Cohen d effect size for z test Z /√N, Med (IQR) = median (interquartile range, 25th–75th percentiles), SD = standard deviation, z = Mann–Whitney U test. * Statistically significant at P < .05.

Comparison of serum amylin levels in healthy control and multiple sclerosis patient groups.

cs = chi-square test, d = Cohen d effect size for z test Z /√N, Med (IQR) = median (interquartile range, 25th–75th percentiles), SD = standard deviation, z = Mann–Whitney U test.

Statistically significant at P < .05.

The patient cohort comprised 33 individuals with RRMS, 22 with SPMS, and 7 with PPMS. No significant differences in amylin levels were observed across the RRMS, SPMS, and PPMS groups. Post hoc analysis showed a statistically significant difference only between the RRMS subgroup and the healthy control group ( P  = .017; Table 2 ).

Table 2 Comparative analysis of serum amylin levels across multiple sclerosis phenotypes and healthy controls. Experimental groups Parameter Category Total Healthy control (a) Relapsing–remitting MS (b) Secondary progressive MS (c) Primary progressive MS (d)
P
Gender Male 37 (29.6%) 21 (33.3%) 7 (21.2%) 5 (22.7%) 4 (57.1%) .22 (cs = 4.410) Female 88 (70.4%) 42 (66.7%) 26 (78.8%) 17 (77.3%) 3 (42.9%) Serum amylin level Mean ± SD 259.22 ± 105.39 284.04 ± 110.02 219.35 ± 81.17 246.64 ± 109.09 263.42 ± 109.02 .017 * (kw = 10.141) (a-b) ε 2 = 0.059 Med (IQR) 231.26 (176.83–316.66) 267.63 (204.7–351.67) 198.07 (168.53–230.44) 222.92 (163.97–318.16) 216.01 (179.34–356.41) min–max 110.28–640.43 119.48–640.43 110.2–427.34 128.81–540.46 178.3–468.94 cs = chi-square test, kw = Kruskal–Wallis test, Med (IQR) = median (interquartile range, 25th–75th percentiles), MS = multiple sclerosis, SD = standard deviation, ε 2 = Epsilon-squared effect size, (a-b) = Significant difference between healthy control and relapsing–remitting MS. * P <.05 statistically significant.

Comparative analysis of serum amylin levels across multiple sclerosis phenotypes and healthy controls.

cs = chi-square test, kw = Kruskal–Wallis test, Med (IQR) = median (interquartile range, 25th–75th percentiles), MS = multiple sclerosis, SD = standard deviation, ε 2 = Epsilon-squared effect size, (a-b) = Significant difference between healthy control and relapsing–remitting MS.

P <.05 statistically significant.

In univariable logistic regression analyses, age, sex, DM, hypertension, cardiac disease, BMI, serum glucose, TSH, ALT, creatinine, LDL, VLDL, HDL, and triglyceride concentrations were not significantly associated with the odds of MS (all P  > .05). By contrast, higher AST activity and serum amylin levels were associated with lower odds of MS (OR = 0.953; 95% CI, 0.912–0.995; P  = .029 and OR = 0.995; 95% CI, 0.991–0.999; P  = .01, respectively). In the multivariable logistic regression model incorporating variables significant in the univariable analyses, serum amylin level remained the only variable independently associated with MS. Higher serum amylin levels were associated with lower odds of MS (OR = 0.996; 95% CI, 0.992–0.999; P  = .02), whereas the independent association of AST activity was no longer statistically significant ( P  > .05; Table 3 ).

Table 3 Univariable and multivariable logistic regression analyses of demographic, clinical, metabolic and laboratory variables associated with multiple sclerosis status. Univariable Multivariable Variable Wald
P
Odds ratio 95% CI for OR Wald
P
Odds ratio 95% CI for OR Age 0.033 .856 1.004 0.964–1.046 – – – – Sex 0.536 .464 1.337 0.614–2.911 – – – – DM 0.069 .793 0.857 0.271–2.711 – – – – Hypertension 0.103 .749 0.800 0.204–3.130 – – – – Cardiac disease 0.000 .991 1.016 0.062–16.618 – – – – BMI 0.535 .464 0.974 0.909–1.044 – – – – Serum glucose 0.717 .397 1.007 0.991–1.022 – – – – TSH 2.278 .131 1.310 0.923–1.860 – – – – ALT 2.033 .154 0.977 0.947–1.009 – – – – AST 4.746 .029 * 0.953 0.912–0.995 3.436 .064 0.959 0.917–1.002 Creatinine 3.125 .077 0.081 0.005–1.314 – – – – LDL 0.009 .926 1.000 0.989–1.010 – – – – VLDL 2.502 .114 0.980 0.955–1.005 – – – – HDL 1.902 .166 1.021 0.992–1.051 – – – – Triglycerides 2.243 .134 0.996 0.991–1.001 – – – – Serum amylin 6.611 .010 * 0.995 0.991–0.999 5.398 .020 * 0.996 0.992–0.999 ALT = alanine aminotransferase, AST = aspartate aminotransferase, BMI = body mass index, CI = confidence interval, DM = diabetes mellitus, HDL = high-density lipoprotein cholesterol, LDL = low-density lipoprotein cholesterol, OR = odds ratio, TSH = thyroid-stimulating hormone, VLDL = very-low-density lipoprotein cholesterol. * P < .05 indicates statistical significance.

Univariable and multivariable logistic regression analyses of demographic, clinical, metabolic and laboratory variables associated with multiple sclerosis status.

ALT = alanine aminotransferase, AST = aspartate aminotransferase, BMI = body mass index, CI = confidence interval, DM = diabetes mellitus, HDL = high-density lipoprotein cholesterol, LDL = low-density lipoprotein cholesterol, OR = odds ratio, TSH = thyroid-stimulating hormone, VLDL = very-low-density lipoprotein cholesterol.

P < .05 indicates statistical significance.

Although serum amylin levels differed significantly between patients with MS and healthy controls, ROC analysis showed only modest discriminatory performance (AUC = 0.652, 95% CI, 0.553–0.750; P  = .003; see Supplemental Digital Content 1 ). These findings suggest that serum amylin reflects disease-related biological alterations but is unlikely to be sufficiently accurate as a standalone diagnostic biomarker. In univariate logistic regression analysis, higher serum amylin and AST levels were associated with lower odds of MS. In the multivariable model, after adjustment for AST, serum amylin remained the only independent variable significantly associated with MS (OR = 0.996; 95% CI, 0.992–0.999; P  = .02), whereas the effect of AST was no longer statistically significant.

Patients with MS (n = 62) and controls (n = 63) were comparable in age, height, body weight, and BMI (all P  > .05). The median age was 39 years (IQR, 34–47.25) in the MS group and 37 years (IQR, 33–47) in the control group ( P  = .705). The corresponding median BMI values were 26.1 kg/m 2 (IQR, 22.88–30.70) and 27.1 kg/m 2 (IQR, 22.90–33.60), respectively ( P  = .398). Serum glucose, TSH, ALT, AST, creatinine, LDL, VLDL, HDL, and triglyceride levels did not differ significantly between the groups (all P  > .05). The prevalence of DM (9.7% vs 11.1%; P  = .793), hypertension (6.5% vs 7.9%; P  = 1.000), and cardiac disease (1.6% vs 1.6%; P  = 1.000) was also comparable between the MS and control groups (Table 4 ).

Table 4 Comparison of demographic, anthropometric, biochemical and clinical characteristics between patients with multiple sclerosis and healthy controls. Parameter Category All participants Healthy control group MS group
P
Age Mean ± SD 39.42 ± 8.61 39.29 ± 8.82 39.56 ± 8.47 .705 ( z = −0.378) Med (IQR) 39 (33–47) 37 (33–47) 39 (34–47.25) Height Mean ± SD 165.77 ± 8.11 164.83 ± 8.16 166.73 ± 8.00 .133 ( z = −1.502) Med (IQR) 164 (160–173) 163 (158–173) 165 (160.75–173) Body weight Mean ± SD 75.51 ± 14.06 75.56 ± 13.97 75.47 ± 14.26 .982 ( z = −0.022) Med (IQR) 79 (62–84.5) 79 (62–83) 79 (62–86) BMI Mean ± SD 27.70 ± 5.10 28.03 ± 5.10 27.36 ± 5.12 .398 ( z = −0.845) Med (IQR) 26.6 (22.9–31.75) 27.1 (22.9–33.6) 26.1 (22.88–30.7) Serum glucose Mean ± SD 100.22 ± 25.42 98.25 ± 16.92 102.23 ± 31.86 .945 ( z = −0.069) Med (IQR) 95 (88–102.5) 95 (88–102) 94 (88–103) TSH Mean ± SD 2.03 ± 1.24 1.85 ± 0.82 2.21 ± 1.53 .211 ( z = −1.252) Med (IQR) 1.64 (1.39–2.35) 1.60 (1.38–2.06) 1.73 (1.42–2.52) ALT Mean ± SD 21.50 ± 11.81 23.02 ± 12.17 19.97 ± 11.34 .084 ( z = −1.730) Med (IQR) 17 (14–27) 19 (14–30) 16 (13–23.5) AST Mean ± SD 19.97 ± 8.69 21.68 ± 9.68 18.23 ± 7.22 .072 ( z = −1.797) Med (IQR) 17 (14–23.5) 18 (14–30) 16 (13.75–22) Creatinine Mean ± SD 0.75 ± 0.13 0.77 ± 0.13 0.73 ± 0.13 .075 ( t  = 1.795) Med (IQR) 0.74 (0.67–0.85) 0.77 (0.68–0.86) 0.71 (0.60–0.82) LDL Mean ± SD 111.37 ± 34.53 111.65 ± 34.39 111.08 ± 34.95 .947 ( z = −0.067) Med (IQR) 106 (85–130) 107 (85–130) 106 (85–130) VLDL Mean ± SD 28.73 ± 14.30 30.75 ± 16.05 26.68 ± 12.06 .261 ( z = −1.124) Med (IQR) 27 (18–38) 28 (18–43) 26.5 (18–32.25) HDL Mean ± SD 52.14 ± 12.48 50.60 ± 12.32 53.71 ± 12.54 .119 ( z = −1.560) Med (IQR) 50 (43.5–59) 50 (42–59) 52 (45–61.5) Triglycerides Mean ± SD 135.44 ± 70.02 144.79 ± 78.65 125.94 ± 59.14 .356 ( z = −0.924) Med (IQR) 124 (85.5–173.5) 119 (83–213) 124 (86.25–148) DM Present 13 (10.4%) 7 (11.1%) 6 (9.7%) .793 (cs = 0.069) Hypertension Present 9 (7.2%) 5 (7.9%) 4 (6.5%) 1.000 (γ) Cardiac disease Present 2 (1.6%) 1 (1.6%) 1 (1.6%) 1.000 (γ) ALT = alanine aminotransferase, AST = aspartate aminotransferase, BMI = body mass index, cs = chi-square test, DM = diabetes mellitus, HDL = high-density lipoprotein cholesterol, IQR = interquartile range, LDL = low-density lipoprotein cholesterol, Med (IQR) = median (interquartile range, 25th–75th percentiles), MS = multiple sclerosis, SD = standard deviation, t = independent-samples t test, TSH = thyroid-stimulating hormone, VLDL = very-low-density lipoprotein cholesterol, z = Mann–Whitney U test, γ = Fisher exact test.

Comparison of demographic, anthropometric, biochemical and clinical characteristics between patients with multiple sclerosis and healthy controls.

ALT = alanine aminotransferase, AST = aspartate aminotransferase, BMI = body mass index, cs = chi-square test, DM = diabetes mellitus, HDL = high-density lipoprotein cholesterol, IQR = interquartile range, LDL = low-density lipoprotein cholesterol, Med (IQR) = median (interquartile range, 25th–75th percentiles), MS = multiple sclerosis, SD = standard deviation, t = independent-samples t test, TSH = thyroid-stimulating hormone, VLDL = very-low-density lipoprotein cholesterol, z = Mann–Whitney U test, γ = Fisher exact test.

4. Discussion

In this cross-sectional case-control study, serum amylin levels were significantly lower in patients with MS than in healthy controls. Although serum amylin levels differed significantly between patients with MS and healthy controls, ROC analysis showed only modest discriminatory performance (AUC = 0.652). These findings suggest that serum amylin reflects disease-related biological alterations but is unlikely to be sufficiently accurate as a standalone diagnostic biomarker. In univariate logistic regression analysis, higher serum amylin and AST levels were associated with lower odds of MS. In the multivariable model, serum amylin remained the only independent variable significantly associated with MS after adjustment for AST (OR = 0.996; 95% CI, 0.992–0.999; P  = .02), whereas the effect of AST was no longer statistically significant. Phenotype-stratified analysis further refined this association. Phenotype-specific analysis indicated that the significant pairwise difference was confined to the comparison between the RRMS subgroup and healthy controls.

Patients with MS (n = 62) and controls (n = 63) were comparable in age, height, body weight, and BMI (all P  > .05). The median age was 39 years (IQR, 34–47.25) in the MS group and 37 years (IQR, 33–47) in the control group ( P  = .705). The corresponding median BMI values were 26.1 kg/m 2 (IQR, 22.88–30.70) and 27.1 kg/m 2 (IQR, 22.90–33.60), respectively ( P  = .398). Serum glucose, TSH, ALT, AST, creatinine, LDL, VLDL, HDL, and triglyceride levels did not differ significantly between the groups (all P  > .05). The prevalence of DM (9.7% vs 11.1%; P  = .793), hypertension (6.5% vs 7.9%; P  = 1.000), and cardiac disease (1.6% vs 1.6%; P  = 1.000) was also comparable between the MS and control groups.

The present study addresses an apparently unexplored aspect of MS biology by assessing serum amylin levels in patients with MS, offering preliminary evidence that altered amylin biology may be associated with MS-related pathophysiological processes.

MS is a complex inflammatory and neurodegenerative disorder of the CNS, predominantly affecting young adults. It has a higher prevalence among Caucasian females, particularly in affluent societies, making it a leading cause of disability among young and middle-aged individuals in high-income countries. [ 1 ] Globally, the incidence of MS is approximately twice as high in women as in men. [ 2 ] The disease results in lesions in white and gray matter, leading to symptoms that commonly include sensory deficits, motor and visual disturbances, vertigo, ataxia, diplopia, cognitive impairment, spasticity, and urinary dysfunction. This broad clinical spectrum underscores the marked heterogeneity of MS, in which lesion distribution and disease phenotype shape clinical expression. [ 2 - 4 ]

Amylin is a hormone secreted alongside insulin by pancreatic β-cells and plays an important role in regulating glucose homeostasis. It achieves this by inhibiting gastric emptying, reducing glucagon secretion, enhancing satiety, and regulating blood glucose. [ 5 ] In pathological conditions, amylin can become dysregulated, leading to misfolding, self-aggregation, and the formation of amyloid deposits. [ 6 ] Nevertheless, its precise role in disease pathogenesis remains unclear.

Amylin belongs to the calcitonin (CT) peptide family, which also includes CT, intermedin, alpha-CT gene-related peptide, β-CT gene-related peptide, and adrenomedullin. Members of this family are important pharmacological targets because they regulate essential homeostatic processes. [ 7 ] Amylin, a pancreatic hormone released in response to food intake, reduces appetite, gastric acid secretion, gastric emptying rate, and meal-induced pancreatic glucagon secretion. It acts as a satiety signal, thereby modulating portion size. Circulating amylin concentrations rise rapidly within minutes of food intake. The appetite-suppressing effects of amylin are dose-dependent and may be specifically blocked by amylin receptor antagonists. [ 8 - 12 ]

Homeostatic regulation of eating behavior involves both adiposity-related tonic signals and meal-associated episodic satiation signals. Adiposity signals, including leptin from adipose tissue and insulin and amylin from the pancreas, correlate with body fat and promote satiation. [ 10 ] Amylin, for instance, potentiates the satiating effects of cholecystokinin. [ 13 ] Basal plasma amylin concentrations are elevated in obesity and after exposure to a high-fat diet compared with lean controls. [ 10 , 14 - 16 ]

Chronic peripheral or central amylin administration reduces body weight and adiposity, whereas amylin antagonism increases adiposity. These findings suggest that central amylin signaling, like leptin and insulin signaling, contributes to maintaining body weight homeostasis in adults. [ 8 , 10 ] Receptor autoradiography studies have demonstrated high-affinity amylin receptor binding sites in several CNS regions, particularly within circumventricular organs such as the subfornical organ and the area postrema (AP). The AP plays a pivotal role in mediating the physiological responses to peripheral amylin, as amylin can directly activate AP neurons independently of vagal or non-vagal afferent pathways. [ 17 - 22 ] Local administration of amylin into the AP recapitulates the effects observed after peripheral amylin administration. Conversely, intra-AP administration of the amylin receptor antagonist AC187 produces opposing effects and abolishes the appetite-suppressing action of peripheral amylin, indicating that amylin signaling within the AP is essential for these central responses. [ 23 ]

Peripheral amylin-mediated stimulation of AP neurons is thought to recruit a forebrain-projecting neuroaxis comprising the nucleus tractus solitarius, lateral parabrachial nucleus, and central nucleus of the amygdala. [ 24 , 25 ] Amylin may also engage mesolimbic dopaminergic regions, including the ventral tegmental area and nucleus accumbens, which contain high-affinity amylin-binding sites and components of the amylin receptor complex. [ 24 , 25 ] Pathological overeating has been proposed to compensate, at least in part, for reduced activity within mesolimbic and nigrostriatal dopaminergic pathways. This concept aligns with the view that the reinforcing properties of food intake may drive feeding behavior beyond homeostatic energy requirements, thereby contributing to excessive weight gain and the development of obesity. [ 26 , 27 ] Amylin and amylin receptor agonists may modulate dopaminergic signaling by affecting ventral tegmental area neurons, attenuating phasic dopamine responses in the nucleus accumbens and consequent reductions in food intake. [ 27 ]

The physiological actions of amylin require preservation of its soluble monomeric form, enabling the hormone to reach target organs and cells after release from pancreatic β-cells. In pathological states such as T2DM, however, amylin may self-aggregate, forming insoluble amyloid deposits. The transition from soluble, functional amylin to aggregated amyloid species may be associated with toxic effects on peripheral and central organ systems and cellular structures. [ 28 ]

Under homeostatic conditions, monomeric amylin remains soluble and adopts a natively unfolded conformation, with aggregation limited by interactions with insulin and proinsulin within secretory vesicles. [ 29 ] Increased amylin concentrations within pancreatic islet cells may promote aggregation and fibril formation, during which β-sheet-rich structures are stabilized predominantly by hydrogen bonding between β-strands. [ 29 , 30 ] The propensity of amylin to form pancreatic amyloid deposits, together with the cytotoxic properties of aggregated amylin species, shows mechanistic parallels with amyloid-β (Aβ), which is generated through the proteolytic processing of amyloid precursor protein (APP) in the CNS. APP is a type I transmembrane glycoprotein that is abundant in the human CNS and is widely distributed across cellular compartments, including the Golgi apparatus, plasma membrane, mitochondria, and endoplasmic reticulum. [ 31 ] Aβ oligomers are considered among the most neurotoxic amyloid species and have been implicated in mitochondrial dysfunction, oxidative stress, impaired synaptic plasticity, altered intracellular signaling, and neuronal death. These processes may establish a self-reinforcing pathological cycle that favors further Aβ generation through amyloidogenic processing, particularly under disease conditions. Under physiological conditions, APP is processed predominantly through the secretory pathway. [ 28 , 31 - 33 ]

Physiological homeostasis depends on the balance between Aβ peptide production and clearance. Apolipoprotein E (APOE) and IDE play important roles in this process, partly through interactions with Aβ peptides that may limit their aggregation. Established AD risk factors, including the APOE ε4 polymorphism, may impair Aβ clearance and promote plaque formation, while metabolic disturbances, particularly those associated with T2DM, may further disrupt amyloid clearance pathways. T2DM has also been linked to IDE deficiency, which may favor the aggregation of amyloidogenic proteins, including Aβ and amylin-derived amyloid. Accordingly, IDE hypofunction may represent a mechanistic link between metabolic disorders such as T2DM and increased AD risk through effects on Aβ plaque formation. [ 34 - 37 ] Evidence indicates that amylin-derived amyloid is present in pancreatic islets and the temporal lobe of patients with T2DM and AD, where it co-localizes with Aβ deposits. [ 38 , 46 ] These observations suggest that metabolic dysfunction and aging may contribute to CNS amylin accumulation. Amylin has therefore been proposed as a “second amyloid” in AD, with studies showing co-localization of amylin and Aβ in AD plaques and cerebral vessel walls. [ 38 - 40 ] Whether brain amylin is produced locally or derives from the systemic circulation remains unclear; however, experimental evidence that intravenous amylin fibrils can enhance pancreatic amyloid deposition supports the possibility of a systemic contribution. [ 38 , 40 ]

Recent studies suggest that reduced systemic amylin concentrations may exacerbate AD-like pathology. [ 41 , 42 ] One study demonstrated that chronic administration of non-amyloidogenic amylin or pramlintide attenuated neuropathological alterations and cognitive impairment in an AD mouse model, reduced Aβ plaque burden, and enhanced Aβ clearance, as reflected by increased Aβ1–42 levels in cerebrospinal fluid and serum. [ 41 ] Similarly, pramlintide improved AD-related deficits in SAMP8 mice, a model of sporadic AD. In addition, individuals with mild cognitive impairment or AD have been reported to exhibit lower circulating amylin levels than control subjects. [ 41 , 42 ] These findings suggest that reduced peripheral amylin concentrations may contribute to neurological and cognitive deficits in mild cognitive impairment and AD. [ 41 , 42 ] This association may be related to competition between amylin and Aβ for binding to the CNS calcitonin receptor (CTR) complexed with receptor activity-modifying protein 3 (RAMP3). In hypoamylinaemia, Aβ preferentially binds to the CTR–RAMP3 complex, thereby promoting Aβ oligomerisation and plaque formation. Restoration of amylin levels through exogenous non-amyloidogenic amylin or amylin analogues may prevent Aβ binding to CTR–RAMP3, reduce Aβ oligomerisation, and potentially enhance Aβ clearance through the cerebral vasculature. [ 43 - 45 ] Hypoamylinaemia therefore appears to be associated with, and may promote, pathological amyloid formation in the CNS. Although these observations provide a relevant neurodegenerative context, their direct applicability to MS remains uncertain because the immunopathological and demyelinating architecture of MS differs substantially from that of AD.

A potential mechanistic link between amylin and MS may involve both receptor-mediated signaling and shared neuropeptide catabolic pathways. Amylin may exert central effects through amylin receptors, which participate in signaling cascades relevant to inflammation, energy metabolism, and synaptic plasticity. Owing to its structural homology with amylin, calcitonin gene-related peptide may also bind amylin 1a receptors with high affinity and potentially reinforce physiological amylin signaling. Beyond these receptor-mediated effects, amylin, calcitonin gene-related peptide, adrenomedullin, and Aβ share catabolic pathways involving neprilysin, endothelin-converting enzyme, and IDE, all of which have been implicated in regulating inflammatory and degenerative processes within the CNS. Neprilysin may be particularly relevant to MS, as experimental evidence suggests that its catabolism of vasoactive peptides, including members of the amylin peptide family, may attenuate disease severity in experimental autoimmune encephalomyelitis. [ 47 ] Collectively, these observations provide a plausible biological framework through which amylin-related signaling and metabolism might intersect with inflammation, glial dysfunction, neuronal survival, and neurodegenerative processes in MS; however, the precise contribution of amylin to MS pathophysiology remains to be established.

Taken together, amylin occupies a biologically complex position at the interface between peripheral metabolic regulation and CNS signaling. In its soluble physiological form, amylin contributes to postprandial satiation, glucagon regulation, gastric emptying, and body-weight homeostasis, while its actions within the AP and interconnected forebrain and mesolimbic pathways extend its influence to central homeostatic and dopaminergic signaling. [ 7 - 27 ] By contrast, dysregulation of amylin homeostasis and the transition from soluble monomeric amylin to aggregated amyloid species may be associated with cytotoxicity and with molecular processes that overlap with Aβ-related pathology, including impaired amyloid clearance, mitochondrial dysfunction, oxidative stress, synaptic disruption, and neuronal injury. [ 28 - 46 ] Amylin receptor signaling and the shared catabolic pathways of amylin, calcitonin gene-related peptide, adrenomedullin, and Aβ, involving neprilysin, endothelin-converting enzyme, and IDE, further provide a biologically plausible interface with inflammatory, metabolic, glial, and neurodegenerative processes relevant to MS. [ 47 ] Within this biological context, serum amylin levels were significantly lower in patients with MS than in healthy controls in our study. This finding supports an association between lower circulating amylin homeostasis and MS-related biological processes, potentially at the interface between metabolic–neuroendocrine signaling and the inflammatory, glial, and neurodegenerative pathways implicated in MS; however, the cross-sectional design precludes any inference regarding directionality or causality. Importantly, BMI and DM did not differ significantly between the patient and control groups. Similarly, no statistically significant between-group differences were observed in age, body weight, serum glucose, TSH, ALT, AST, creatinine, LDL, VLDL, or HDL. Accordingly, the reduction in serum amylin levels observed in our study occurred in the absence of significant differences in the principal anthropometric, metabolic, and biochemical variables evaluated, although residual confounding attributable to unmeasured metabolic factors cannot be excluded.

Higher serum amylin levels were associated with lower odds of MS, and this association remained statistically significant after adjustment for AST. The significant phenotype-specific difference was confined to the comparison between the RRMS subgroup and healthy controls. Although this pattern may be considered within the broader context of peripheral immune activation and neuroinflammation in relapsing disease, the cross-sectional design, limited subgroup sizes, and the absence of contemporaneous inflammatory, immunological, radiological, demyelination-related, and receptor-level measures preclude mechanistic interpretation or causal inference. Accordingly, these findings support an association between altered circulating amylin concentrations and MS but do not establish whether amylin is directly involved in neuroinflammation, demyelination, immune regulation, or neurodegenerative processes. Clarification of these potential biological links will require longitudinal studies incorporating detailed metabolic, inflammatory, immunological, radiological, and disease-activity measures.

Several limitations should be acknowledged. First, the total sample size was modest, comprising 125 participants across all groups, and the number of patients with PPMS was particularly limited compared with the RRMS and SPMS subgroups. This may have reduced the statistical power of phenotype-specific comparisons and limited the generalizability of the subgroup-level findings. Second, disease duration, EDSS scores, magnetic resonance imaging lesion burden, detailed characteristics and duration of disease-modifying treatment, relapse frequency, and the interval since the most recent relapse were not systematically available in the study dataset and therefore could not be incorporated into the analyses. The absence of these variables limited our ability to examine the relationship between serum amylin levels and disease burden, disability severity, radiological disease activity, treatment exposure, and recent inflammatory disease activity. Third, although several demographic, metabolic, and biochemical variables were evaluated statistically, residual confounding related to metabolic status, insulin dynamics, diet, body composition, and medication exposure cannot be fully excluded. Fourth, given the single-center design and relatively modest sample size, the generalizability of these findings to broader MS populations and other clinical settings may be limited, particularly where patient characteristics, treatment patterns, and disease-activity profiles differ. Finally, owing to the cross-sectional case-control design, the present study can demonstrate associations between serum amylin levels and MS status but cannot establish temporality or causality.

In conclusion, this cross-sectional case-control study is the first apparent evaluation of serum amylin levels in patients with MS. It demonstrated that serum amylin levels were lower in patients with MS than in healthy controls and were associated with MS status in regression analysis. The association appeared most evident in the RRMS subgroup compared with healthy controls. However, the modest ROC performance indicates that serum amylin is unlikely to serve as a standalone diagnostic biomarker on the basis of the present data. These findings should therefore be interpreted as preliminary evidence of an association between altered serum amylin levels and MS-related biological processes. Larger longitudinal studies incorporating detailed clinical, radiological, metabolic, and treatment-related data are required to clarify the biological relevance and potential clinical utility of serum amylin in MS.

Author contributions

Conceptualization: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin.

Data curation: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Ahmet Magrur Karagulmez, Esin Avci Cicek, Hande Senol.

Formal analysis: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Ahmet Magrur Karagulmez, Esin Avci Cicek, Hande Senol.

Funding acquisition: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Esin Avci Cicek.

Investigation: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Ahmet Magrur Karagulmez, Esin Avci Cicek.

Methodology: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Esin Avci Cicek.

Project administration: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin.

Resources: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Ahmet Magrur Karagulmez, Esin Avci Cicek.

Software: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Ahmet Magrur Karagulmez, Esin Avci Cicek, Hande Senol.

Supervision: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Esin Avci Cicek, Hande Senol.

Validation: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Hande Senol.

Visualization: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Hande Senol.

Writing – original draft: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Esin Avci Cicek, Hande Senol.

Writing – review & editing: Ufuk Cinkir, Levent Sinan Bir, Selma Tekin, Ahmet Magrur Karagulmez, Esin Avci Cicek, Hande Senol.

Abbreviations: AD Alzheimer disease ALT alanine aminotransferase AP area postrema APP amyloid precursor protein AST aspartate aminotransferase AUC area under the curve Aβ amyloid-β CI confidence interval CNS central nervous system CT calcitonin CTR calcitonin receptor CV coefficient of variation DM diabetes mellitus EDSS Expanded Disability Status Scale ELISA enzyme-linked immunosorbent assay HDL high-density lipoprotein cholesterol IDE insulin-degrading enzyme L litre LDL low-density lipoprotein cholesterol mL millilitre MS multiple sclerosis ng nanogram nm nanometre PPMS primary progressive MS RAMP3 receptor activity-modifying protein 3 ROC receiver operating characteristic RRMS relapsing–remitting MS SPMS secondary progressive MS T2DM type 2 diabetes mellitus TSH thyroid-stimulating hormone VLDL very-low-density lipoprotein cholesterol β beta.

Abbreviations:

Alzheimer disease

alanine aminotransferase

area postrema

amyloid precursor protein

aspartate aminotransferase

area under the curve

amyloid-β

confidence interval

central nervous system

calcitonin

calcitonin receptor

coefficient of variation

diabetes mellitus

Expanded Disability Status Scale

enzyme-linked immunosorbent assay

high-density lipoprotein cholesterol

insulin-degrading enzyme

litre

low-density lipoprotein cholesterol

millilitre

multiple sclerosis

nanogram

nanometre

primary progressive MS

receptor activity-modifying protein 3

receiver operating characteristic

relapsing–remitting MS

secondary progressive MS

type 2 diabetes mellitus

thyroid-stimulating hormone

very-low-density lipoprotein cholesterol

beta.

The authors have no conflicts of interest to declare.

The datasets generated during and/or analyzed during the current study are not publicly available, but are available from the corresponding author on reasonable request.

Supplemental Digital Content is available in the online version of this article ( http://dx.doi.org/10.1097/MD.0000000000050425 ).

How to cite this article: Cinkir U, Bir LS, Tekin S, Karagulmez AM, Avci Cicek E, Senol H. Serum amylin levels in patients with multiple sclerosis: A cross-sectional case-control study. Medicine 2026;105:35(e50425).

Contributor Information

Levent Sinan Bir, Email: leventsinanbir@yahoo.com.

Selma Tekin, Email: selmabilgintekin@gmail.com.

Ahmet Magrur Karagulmez, Email: ahmet.magrur28@gmail.com.

Esin Avci Cicek, Email: hekimesin@gmail.com.

Hande Senol, Email: handesenol@gmail.com.

References

Associated Data

Supplementary Materials