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Original Research

Alteration of the irisin–brain-derived neurotrophic factor axis contributes to disturbance of mood in COPD patients

, , , , , , , , & show all
Pages 2023-2033 | Published online: 07 Jul 2017

Figures & data

Table 1 Main characteristics of the whole COPD cohort (n=74)

Table 2 Main characteristics of two groups of the COPD cohort dichotomized according to mood disturbances indicated by the Impacts score

Figure 1 Correlation of mood disturbance (characterized by the Impacts score of SGRQ) and reciprocal of serum irisin concentration in the whole data set (n=74).

Notes: The x-axis shows the reciprocal of serum irisin level (in ng/mL), whereas the y-axis denotes the Impacts score of SGRQ. The blue line shows the fitted line to the data points (represented by the green dots), whereas the grey zone indicates the 95% CI.
Abbreviations: CI, confidence interval; SGRQ, St George’s Respiratory Questionnaire.
Figure 1 Correlation of mood disturbance (characterized by the Impacts score of SGRQ) and reciprocal of serum irisin concentration in the whole data set (n=74).

Table 3 Significant predictors of reciprocal of serum irisin level and Impacts score of SGRQ determined with simple linear regression for the whole COPD cohort (n=74)

Table 4 Multiple linear regression model for the SGRQ’s Impacts score of the whole COPD cohort and its strata with respect to the median BDNF level

Table 5 ANOVA tables describing the final model for the whole cohort (Panel A), lower BDNF stratum (Panel B), and higher BDNF stratum (Panel C)

Figure 2 The model describing the correlation between the Impacts score of SGRQ and reciprocal of serum irisin concentration in the whole data set (n=74).

Notes: The x-axis shows the reciprocal of serum irisin concentration (in ng/mL), whereas the y-axis denotes the Impacts score of SGRQ. The blue and red dots indicate the raw and fitted values obtained by multiple linear regression, respectively. The green and orange lines indicate the curves fitted to the raw data and to data provided by multiple linear regression. Fitting was done by locally weighted scatterplot smoothing (lowess).
Abbreviation: SGRQ, St George’s Respiratory Questionnaire.
Figure 2 The model describing the correlation between the Impacts score of SGRQ and reciprocal of serum irisin concentration in the whole data set (n=74).