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. 2022 Sep 3;11(17):5215.
doi: 10.3390/jcm11175215.

Smell as a Disease Marker in Multiple Sclerosis

Affiliations

Smell as a Disease Marker in Multiple Sclerosis

Athanasia Printza et al. J Clin Med. .

Abstract

Existing data suggest that people with multiple sclerosis (pwMS) are at an elevated risk for experiencing olfactory impairment. We investigated if smell dysfunction can be used as an MS disease marker. This is a cross-sectional, case−control study. All data were collected prospectively from 171 participants, 115 pwMS and 56 controls (age and sex stratified and matched to the patients), who reported smell, taste, and nasal breathing, and completed the Greek-validated questionnaires for nasal obstruction (NOSE), nasal-symptoms QoL (SNOT-22), and olfaction-associated QoL (QOD). The smell was assessed with the “Sniffin’ sticks” (odor threshold (OT), discrimination (OD), identification (OI) test, and total TDI). We recorded the pwMS disease characteristics (Expanded Disability Status Scale-EDSS, the disease type and duration), cognitive function, emotional status, fatigue, and impact of MS in everyday activities. A TDI < 30.75 (hyposmia) was detected in 30.8% of the patients. The patients’ OD and TDI scores were significantly lower than the controls’ (p = 0.005, and 0.015, respectively). The hyposmia correlated with disease severity and duration. The EDSS score correlated negatively with OD (r = −0.299, p = 0.001) and TDI (r = −0.242, p = 0.01). The disease duration correlated negatively with OD (r = −0.305, p = 0.001, OI (r = −0.253, p = 0.008) and TDI (r = −0.3, p = 0.001). The information processing speed (SDMT) correlated with OD, OT, and TDI (r = 0.302, p = 0.002; r = 0.242, p = 0.016; r = 0.326, p = 0.001). The olfactory function is changing in MS in accordance with disease progression.

Keywords: cognitive function; disease marker; identification; multiple sclerosis; nasal symptoms; olfaction; olfactory threshold; patient-reported-outcome measures; quality of life; smell.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
ROC curves of two probability prediction models of the olfactory outcome. Probabilities were calculated based on Binary Logistic Regression models. (A) age, gender, disease duration, Multiple Sclerosis disease type, EDSS score, smoking status, SDMT, GVLT, BVMT-R, MFIS, BDI, and MSIS were set as independent variables. (B) Age, gender, disease duration, MS type, EDSS score, and smoking status were set as independent variables. EDSS: Expanded Disability Status Scale; SDMT: Symbol Digit Modalities Test; GVLT: Greek Verbal Learning Test; BVMT-R: Brief Visuospatial Memory Test–Revised; MFIS: Modified Fatigue Impact Scale; BDI-FS: Beck Depression Inventory-Fast Screen; MSIS: Multiple Sclerosis Impact Scale.

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