---
title: "Disease-modifying therapies linked to better olfactory function via NK cell–microbiota interaction"
id: "frontiers-in-immunology-16-disease-modifying-therapies-are-associated-with-improved-olfactory-function-via"
canonical_url: "https://medichelpline.com/clinical-feed/frontiers-in-immunology-16-disease-modifying-therapies-are-associated-with-improved-olfactory-function-via"
content_type: "clinical_feed_article"
specialty: "Neurology"
source_name: "Frontiers in Immunology"
source_url: "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1889149"
published_at: "2026-09-14T00:00:00.000Z"
evidence_level: "Journal Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# Disease-modifying therapies linked to better olfactory function via NK cell–microbiota interaction
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/frontiers-in-immunology-16-disease-modifying-therapies-are-associated-with-improved-olfactory-function-via
- **Specialty:** [Neurology](https://medichelpline.com/clinical-feed/neurology.md)
- **Primary Source:** Frontiers in Immunology
- **Source URL:** [Original Journal Publication](https://www.frontiersin.org/articles/10.3389/fimmu.2026.1889149)
- **Published At:** 2026-09-14T00:00:00.000Z
- **Evidence Rating:** Journal Feed
## Executive GIST (TL;DR)
- The source page title reports that **disease-modifying therapies** are associated with improved **olfactory function** in people with **multiple sclerosis** through interactions involving **NK cells** and the **microbiota**. - The available source material contains only site navigation and indexing content from Frontiers in Immunology; the full article text, methods, results, and specific data were not present on the provided page content. - No study design, sample size, statistical outcomes, treatment types, timing, measures of olfactory function, or mechanistic experimental details were reported in the retrieved source excerpt. - The title implies a link between immunomodulatory treatment effects, innate immune cells (NK cells), and the mucosal or gut microbial community as mediators of olfactory improvement in MS, but specific pathways and causal evidence are not reported in the available content. - Important clinical and translational details—such as which **disease-modifying therapies** were studied, whether findings are observational or interventional, effect sizes, patient characteristics, and safety data—were not available in the provided source. - Because the extract lacked the article body, readers should consult the full published article for study methods, quantitative results, and authors’ conclusions before applying or citing these findings in clinical or research contexts. - The available information supports only a hypothesis-level statement as presented in the article title rather than a verifiable clinical conclusion based on reported evidence within the provided source.
## Clinical Analysis & Structured Key Points
Frontiers | Disease-modifying therapies are associated with improved olfactory function via NK cell- microbiota interactions in multiple sclerosis ORIGINAL RESEARCH article Front. Immunol. , 14 September 2026 Sec. Autoimmune Disorders Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1889149 Published in Frontiers in Immunology Autoimmune Disorders 7 impact factor 11.3 citescore Editor & Reviewers Edited by V O Valentyn Oksenych Reviewed by S L Shuqi Li V S Varun Suroliya Outline Figures and Tables Figure 1 View in article Figure 2 View in article Figure 3 View in article Figure 4 View in article Figure 5 View in article Table 1 Characteristics of MS patients with DMTs and without DMT . View in article Table 2 Lymphocyte subgroup test results of MS patients. View in article ORIGINAL RESEARCH article Front. Immunol. , 14 September 2026 Sec. Autoimmune Disorders Volume 17 - 2026 | https://doi.org/10.3389/fimmu.2026.1889149 Disease-modifying therapies are associated with improved olfactory function via NK cell- microbiota interactions in multiple sclerosis Z D Zhuoma Danzhen 1 Z Y Zhang Yang 1 L C Lan Chu 2 Z G Zidan Gao 1 * 1. Department of Neurology, Affiliated Hospital of Guizhou Medical University, Guizhou Medical University, Guiyang, China 2. Beijing Amcare Hospital, Jingshun Road, Chaoyang District, Beijing, China Article metrics View details Abstract Objective: To examine the associations of nasal microbiota with disease-modifying therapies (DMTs), lymphocyte subsets and olfactory function in multiple sclerosis (MS). Methods: Thirty patients with MS and 30 age- and sex-matched healthy controls (HCs) were enrolled. Patients were classified as DMT-treated (MS[DMT+]) or untreated (MS[DMT-]). Olfactory function was assessed using the University of Pennsylvania Smell Identification Test (UPSIT). Lymphocyte subsets were measured by flow cytometry, and nasal microbiota were analysed by 16S rRNA sequencing. Results: Olfactory function was lower in MS than in HCs, and better in MS(DMTs+) than in MS(DMTs−) ( p =0.016, 95% CI 0.5614 to 4.941). NK cell counts were lower in MS(DMTs+) than in MS(DMTs−) ( p =0.049, 95% CI -244.7 to -0.2109). And NK cell counts in MS(DMTs+) correlate with UPSIT ( r =-0.527, p =0.029). Compared with HCs, MS(DMTs−) showed higher Shannon diversity ( p =0.038), increased Proteobacteria ( p =0.004), reduced Moraxellaceae ( p =0.037) and Enterobacteriaceae ( p =0.033), and enriched branched-chain amino acid biosynthesis ( p =0.026). In MS(DMTs+), Campylobacter, Anaerococcus, Peptoniphilus, Prevotella , and Finegoldia were positively correlated with circulating NK cells (all p 1 month) of drugs that impair olfaction, an EDSS score exceeding 6.5, and an MMSE score below 24. Ethical approval for this study was granted by the Clinical Ethics Committee of the Affiliated Hospital of Guizhou Medical University (approval Nos. 2021 Lun 495 and 2023 Lun 897). The study was performed in accordance with the principles outlined in the Declaration of Helsinki. All participants provided written informed consent prior to inclusion. The dataset used in this study partly overlaps with a previously published cohort ( 18 ). However, the present analysis focused specifically on the effects of DMT exposure, which were not a primary focus of the previous publication. 2.2 Olfactory assessment methods Olfactory performance was measured using the University of Pennsylvania Smell Identification Test (UPSIT), a validated method for quantitative assessment ( 19 , 20 ). The validated simplified Chinese 40-item version with microencapsulated odorant strips was used ( 20 ). The UPSIT score was defined as the number of correctly identified odorants (0–40), and age- and sex-adjusted normative criteria were applied to classify the severity of olfactory dysfunction. All tests were administered by two trained investigators ( 20 ). Two trained researchers carried out the testing for all subjects and performed the statistical analyses. 2.3 Biospecimen collection Nasal samples were collected using sterile swabs (LONGSEE, Guangzhou, China), which were inserted approximately 2–3 cm into the middle nasal passage and gently rotated for 5–10 s. After collection, each swab was transferred into 1 mL of sterile saline preservative and stored at −80°C for subsequent analysis. 2.4 Sequence analysis Genomic DNA was extracted from human nasal swabs using the QIAamp DNA Mini Kit (QIAGEN). The V4 region of the 16S rRNA gene was amplified with primers 515F and 806R using Premix Taq (TaKaRa) under the following conditions: 94°C for 5 min; 30 cycles of 94°C 30 s, 52°C 30 s, 72°C 30 s; and 72°C for 10 min. Amplicons were purified and sequenced on the Illumina platform (PE250). Raw reads were quality-trimmed using fastp (v0.14.1; sliding window: -W 4, -M 20) and primer-trimmed using cutadapt. Paired-end reads were merged with usearch v10 (-fastq_mergepairs; min overlap 16 bp, max mismatch 5 bp). OTUs were clustered at 97% identity using UPARSE, and chimeras, singletons, and sequences assigned to mitochondria or unclassified at the kingdom level were filtered out. Taxonomic classification was performed with SINTAX against the SILVA 138 database at a confidence threshold of 0.8; unclassified taxa at the genus level were labeled at the family level with an “unclassified” suffix. Functional profiles were predicted using PICRUSt2, with annotations mapped to the KEGG Orthology (KO) and COG databases. 2.5 Percentages and absolute counts of lymphocyte subsets Peripheral venous blood (2 mL) was collected from MS patients into heparinized tubes. For flow cytometry, 100 μL of whole blood was incubated for 30 min in the dark with fluorochrome-conjugated monoclonal antibodies against CD3, CD4, CD8, CD19, and CD16/CD56, including CD3-FITC, CD16/CD56-PE, CD19-APC, CD4-PerCP-Cy5.5, and CD8-BV421 (BD Biosciences, USA). Phosphate-buffered saline was obtained from Solarbio (Beijing, China), and all flow cytometry tubes and instruments were from BD Biosciences (USA). 2.6 Statistical analysis Statistical analyses were performed using SPSS 24.0, GraphPad Prism 8.0.2, and R 3.5.1. Continuous variables were compared using unpaired two-tailed t-tests, and categorical variables were analyzed with the chi-square test or Fisher’s exact test, as appropriate. Pearson and Spearman correlation analyses were applied to assess relationships between clinical variables, lymphocyte subsets, and UPSIT scores. A two-sided p value < 0.05 was considered statistically significant. For nasal microbiota analysis, α-diversity was evaluated using richness, Chao1, Shannon, and Simpson indices, and Beta diversity was assessed using Bray–Curtis dissimilarity and visualized by PCoA. Differences in community composition among groups were tested by PERMANOVA based on Bray–Curtis distance matrices using the Adonis R 2 . Taxonomic composition was summarized at the phylum and family levels, with taxa of relative abundance < 0.5% and unclassified taxa grouped as “Others”. Differential taxa were identified using LEfSe, and correlations between nasal microbiota and lymphocytes were visualized using heatmaps. 3 Results 3.1 Baseline characteristics The baseline features of this cohort are outlined here and have been described in detail in our earlier report ( 18 ). The study included 30 individuals with MS and 30 healthy controls (HCs) matched for age and sex. No significant differences were found between MS and HC groups in sex distribution, age, BMI, or MMSE score ( 18 ). MS patients were stratified into untreated (MS(DMTs−), n = 13) and treated [MS(DMTs+), n = 17] groups. A significant difference in sex distribution was observed between subgroups ( p = 0.01); however, other baseline demographic and clinical variables were comparable ( Table 1 ). A subset of participants, comprising 14 healthy controls, 10 MS(DMTs+), and 3 MS(DMTs−) patients, underwent nasal microbiota analysis. The remaining participants were not included because of incomplete sample collection/insufficient sample volume/failure to meet predefined sample quality-control criteria/participant noncompliance ( Figure 1A ). In this study, the V3–V4 region of the 16S rRNA gene was sequenced in 27 nasal samples, generating a total of 3,349,902 raw paired-end reads. After quality filtering, sequence merging, and chimera removal, 3,136,801 high-quality clean tags were retained for downstream analyses. The mean number of clean tags per sample was 115,646 in the HC group, 116,518 in the MS (DMT+) group, and 117,526 in the MS (DMT−) group. The comparable sequencing depths across the three groups indicate that the sequencing data were sufficient for microbial composition and diversity analyses ( Supplementary Table 1 ). Table 1 Characteristics MS (DMTs-) n=13 MS (DMTs+) n=17 Statistical values p -V value Gender b (Females/Males) 7/6 16/1 6.679 † 0.01 * Age b 31.00 (28.00-35.50) 34.00 (29.00-43.50) -1.175 & 0.240 BMI b 22.27 (19.30-24.28) 20.96 (19.78-22.74) -0.314 & 0.754 Age at onset b 28.00 (20.50-30.50) 30.00 (23.00-37.00) -0.943 & 0.346 Disease duration a 5.74 ± 1.3 4.96 ± 1.03 0.503 # 0.619 Number of relapses a 2.92 ± 1.61 2.65 ± 1.62 0.465 # 0.646 EDSS Score b 2.00 (1.25-3.25) 2.00 (1.75-2.75) -0.149 & 0.881 Type of DMTs Teriflunomide 11 Siponimod 4 Dimethyl fumarate 1 Rituximab Injection 1 UPSIT Score a 26.31 ± 0.59 29.06 ± 0.82 -2.574 # 0.016 * Characteristics of MS patients with DMTs and without DMT . a Data are presented as mean ± standard error of the mean (SEM) or b median (interquartile range, Q1–Q3), as appropriate. * p < 0.05 indicates statistical significance. # Comparisons between groups were performed using the independent-samples t-test for normally distributed variables. & The Mann–Whitney U test ( Z value) was used for non-normally distributed variables. † The chi-square ( χ² ) test was applied for categorical variables. MS, multiple sclerosis; BMI, body mass index; EDSS, Expanded Disability Status Scale; DMTs, Disease Modifying Therapies; UPSIT, University of Pennsylvania Smell Identification Test. Figure 1 Study flowchart and UPSIT(University of Pennsylvania Smell Identification Test) analysis. (A) Study flowchart (B) Comparison of UPSIT scores between healthy controls (HC)(n=30) and patients with multiple sclerosis (MS)(n=30). (C) Comparison of UPSIT scores between HC(n=30) and MS (DMTs+)(n=17). (D) Comparison of UPSIT scores between HC and MS (DMTs−)(n=13). (E) Comparison of UPSIT scores between patients with MS (DMTs−)(n=13) and MS (DMTs+)(n=17). UPSIT scores are shown as bar charts and presented as mean ± standard deviation (SD). Statistical comparisons between groups were conducted using Student’s t-test. * p < 0.05, *** p < 0.001,ns= not significant. UPSIT, University of Pennsylvania Smell Identification Test; MS, multiple sclerosis; HC, healthy control; DMTs, disease-modifying therapies. 3.2 Olfactory function Olfactory function was assessed using UPSIT. The mean UPSIT scores in individuals with MS were significantly reduced compared to those in HCs [27.87 ± 3.10 vs. 29.93 ± 3.84, p = 0.027, 95% CI: (−3.887 to −0.247)] ( 18 ). There was no significant difference between MS (DMTs+) and HCs ( p = 0.437; Figure 1B ), whereas MS(DMTs−) showed significantly lower UPSIT scores than HCs [29.93 ± 3.84 vs. 26.31 ± 0.59, p < 0.001,95% CI: (−5.484 to −1.767), Figure 1C ]. Among patients with MS, those in the MS (DMTs−) group had significantly lower UPSIT scores compared with the MS (DMTs+) group [26.31 ± 0.59 vs. 29.06 ± 0.82, p = 0.016, 95% CI: (0.5614 to 4.941) Table 1 ; Figure 1C ]. 3.3 Lymphocyte subsets Lymphocyte subset counts and proportions were compared between MS(DMTs−) and MS(DMTs+). Absolute counts of total T cells [ p = 0.001, 95% CI: (307.009 to 1169.162)], CD8 + T cells [ p = 0.002, 95% CI: (96.554 to 395.743)], CD4 + T cells [ p = 0.001, 95% CI: (214.720 to 807.496)], and B cells ( p < 0.001) were significantly lower in MS(DMTs+) than MS(DMTs−) ( Table 2 ; Figures 2A–C, E ). Absolute NK-cell counts were also lower in MS(DMTs+) [ p = 0.049, 95% CI: (-244.7 to -0.2109) ( Table 2 ; Figure 2F )]. There was no difference in the CD4/CD8 ratio among the groups ( p = 0.739; Table 2 ; Figure 2D ). In contrast, the combined proportion of T+B+NK% was significantly lower in MS(DMTs+) than in MS(DMTs-) ( p = 0.018; Table 2 ). NK-cell proportions tended to be higher in MS(DMTs+), though not significantly ( p = 0.098; Figures 2G, H ). MS (DMTs+) patients exhibited lower proportions of total T cells, CD8 + T cells, CD4 + T cells, and B cells, but these differences were not significant ( Figures 2G, H ). Table 2 Characteristics MS (DMTs-) n=13 MS (DMTs+) n=17 Statistical values p -V value T Cells a 1661.62 ± 173.85 923.53 ± 127.48 3.507 0.001 ** CD8 + T Cells a 596.39 ± 52.43 350.23 ± 49.68 3.371 0.002 ** CD4 + T Cells a 976.46 ± 138.57 465.35 ± 69.74 4.940 0.001 ** NK Cells a 332.39 ± 53.35 209.94 ± 21.90 2.123 † 0.049 * B Cells b 241.00 (187.00-380.00) 138.00 (45.00- 188.00) -3.327 † <0.001 *** CD4/8 a 1.72 ± 0.23 1.60 ± 0.26 0.336 0.739 T+B+NK % b 99.84(99.75-99.93) 99.73 (99.50-99.81) -2.349 † 0.018 * T Cells % a 72.89 ± 1.88 68.55 ± 3.25 1.064 0.296 CD8 + TCells % a 28.15 ± 2.99 26.99 ± 2.25 0.314 0.756 CD4 + T Cells % a 41.31 ± 2.57 34.49 ± 3.24 1.573 0.127 NK Cells % a 14.34 ± 1.88 20.16 ± 2.73 -1.712 0.091 B Cells % a 12.64 ± 1.29 10.12 ± 1.34 1.318 0.198 Lymphocyte subgroup test results of MS patients. a Data are presented as mean ± standard error of the mean (SEM) or b median (interquartile range, Q1–Q3), as appropriate. * p < 0.05, ** p < 0.01, *** p < 0.001 indicate statistical significance. † The Mann–Whitney U test ( Z value) was used for non-normally distributed variables. All other continuous variables were analyzed using the independent-samples t -test. MS, multiple sclerosis; DMTs, disease-modifying therapies. Figure 2 Lymphocyte subset analysis. (A–F) Violin plots showing differences in peripheral lymphocyte subsets between MS(DMTs−)(n=13) and MS(DMTs+)(n=17) patients, including total T cells (A) , CD4+ T cells (B) , CD8+ T cells (C) , CD4+/CD8+ ratio (D) , B cells (E) , and NK cells (F) ; individual values are shown, data are presented as mean ± SD, and linear regression lines with 95% CI (dotted) are indicated. (G, H) Pie charts showing the relative proportions of major lymphocyte subsets in the MS(DMTs−) group (G) and the MS(DMTs+) group (H) , including CD8+ T cells, CD4+ T cells, NK cells, and B cells. (I–K) Correlation analyses between UPSIT scores and NK cell counts in all patients with MS (I) , in the MS(DMTs−) group (J) , and in the MS(DMTs+) group (K) . Statistical significance is indicated as follows: * p < 0.05, ** p < 0.01, *** p < 0.001. ns, not significant. UPSIT, University of Pennsylvania Smell Identification Test; DMT, disease-modifying therapy; NK, natural killer. 3.4 UPSIT and lymphocyte subsets Correlation analysis was used to examine the relationship between olfactory performance and lymphocyte subsets in MS. In the overall MS group, UPSIT scores were not significantly correlated with NK-cell absolute counts ( r = -0.164, p = 0.386; Figure 2I ) or in the MS(DMTs−) subgroup ( r = -0.051, p = 0.868; Figure 2J ). By comparison, the MS (DMTs+) subgroup showed a significant inverse correlation ( r = −0.527, p = 0.029; Figure 2K ). There were no significant correlations between UPSIT s
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