Humans without a sense of smell breathe differently

Abstract

Olfaction may play a restricted role in human behavior, yet paradoxically, its absence in anosmia is associated with diverse deleterious outcomes, culminating in reduced life expectancy. The mammalian nose serves two purposes: olfaction and breathing. Because respiratory patterns are impacted by odors, we hypothesized that nasal respiratory airflow may be altered in anosmia. We apply a wearable device that precisely logs nasal airflow for 24-hour-long sessions in participants with isolated congenital anosmia and controls. We observe significantly altered patterns of respiratory nasal airflow in anosmia in wake and in sleep. These differences allow classification of anosmia at 83% accuracy using the respiratory trace alone. Patterns of respiratory airflow have pronounced impact on health, emotion and cognition. We therefore suggest that a portion of the deleterious outcomes associated with anosmia may be attributed to altered patterns of respiratory nasal airflow rather than a direct result of lost odor perception per se.

Fig. 1. Distinguishing between respiratory rate and respiratory peaks.

A, B An illustration of the wearable device, attached to A the nape of the neck and B connected by nasal cannula to measure nasal airflow in each nostril separately. C Four consecutive breaths from an anosmic participant. Peaks identified by the software circled in red. Here total breath count is 4 and number of inhalation peaks is also 4. D Four consecutive breaths from a normosmic participant. Peaks identified by the software circled in red. Here total breath count is also 4 yet the number of inhalation peaks is 9. Samples from all participants, 21 anosmics and 31 normosmics, are depicted in Supplementary Fig. 1. E Breaths per minute (BPM) during sleep and wake in normosmia (green) and anosmia (orange), plotted along the unit-slope line (dotted line x = y), with raincloud plots and probability density. An rmANOVA uncovered a significant effect for Arousal (F_1,50 = 54.8, p < 0.001, η² = 0.16; Normosmics sleep vs. wake: t₃₀ = 5.48, d’ = 0.99, p < 0.001. Anosmics sleep vs. wake: t₂₀ = 4.98, d’ = 1.1, p < 0.001), but no effect for Sense of Smell (F_1,50 = 2.5, p = 0.12), nor interaction (F_1,50 = 0.49, p = 0.49). F Inhalation peaks per minute (IPPM) during sleep and wake in normosmia (green) and anosmia (orange), plotted along the unit-slope line (dotted line x = y), with raincloud plots and probability density. An rmANOVA uncovered a significant effect for Arousal (F_1,50 = 118, p < 0.001, η² = 0.37), a significant effect for Sense of Smell (F_1,50 = 6.3, p = 0.016, η² = 0.05), and a significant interaction (F_1,50 = 4.7, p = 0.03, η² = 0.015). Post hoc analysis revealed significantly increased frequency of nasal inhalation peaks in normosmics during wake (t₅₀ = 3, p = 0.004, d’ = 0.84) but not during sleep (Normosmics vs. anosmics: t₅₀ = 1.2, p = 0.23). For panels C and D, the area for each separated inhale colored with different arbitrary color, and the nasal airflow is given in arbitrary units. For panels E and F, each circle is the mean of a participant, bars are the group mean, lines are the standard error of the mean and group size is anosmia n = 21, normosmia n = 31. The boxplots in these panels represent data distribution, with the box extending from the first to the third quartile and a solid line indicating the median. The whiskers extend to the furthest data points that are within 1.5 times the interquartile range.

Fig. 2. Classifying anosmia without using odorants.

A A comparison of anosmics vs. normosmics along 27 nasal respiratory parameters, rank-ordered by the extent of difference across groups (using two-sided t-test), with a horizontal line for (uncorrected) p = 0.05, where yellow dots represent parameters in wake and dark grey dots represent parameters in sleep. Following Benjamini-Hochberg correction for multiple comparisons (corrected p < 0.0074), we found four parameters below the corrected threshold. B Percent of breaths with inhale pause during sleep and wake in normosmia (green) and anosmia (orange). A two-sided t-test between the groups in wake revealed a significant difference (t₅₀ = 3, p = 0.004, d’ = 0.85). C Coefficient of Variation (CoV) of inhale volume during sleep and wake in normosmia (green) and anosmia (orange). A two-sided t-test between the groups in sleep revealed a significant difference (t₅₀ = 2.98, p = 0.004, d’ = 0.84). D Mean exhale peak value during sleep and wake in normosmia (green) and anosmia (orange). A two-sided t-test between the groups in wake revealed a significant difference (t₅₀ = −2.82, p = 0.007, d’ = −0.8). E The receiver operating characteristic curve from the KNN classifier applied to the airflow data. F The distribution of 10,000 classifications on shuffled data, with the actual classification accuracy marked by the dotted red line. For all panels, group size is anosmia n = 21, normosmia n = 31. For panels B–D, the measurements are plotted along the unit-slope line (dotted line x = y), with raincloud plots and probability density, where each circle is the mean of a participant, bars are the group mean, and lines are standard error of the mean. The boxplots in these panels represent data distribution, with the box extending from the first to the third quartile and a solid line indicating the median. The whiskers extend to the furthest data points that are within 1.5 times the interquartile range.