Assessing airway clearance dysfunction in Friedreich’s ataxia: A focus on peak cough flow

Abstract

Background

Friedreich’s ataxia (FRDA), a common hereditary ataxia with multisystem involvement, is caused by a biallelic GAA trinucleotide repeat expansion in the FXN gene, leading to reduced frataxin, mitochondrial dysfunction, and oxidative stress. This study evaluates cough effectiveness through voluntary peak cough flow (PCF).

Objectives

The objective was to assess airway clearance dysfunction in individuals with FRDA by examining PCF and its relationship with pulmonary and oral strength, disease severity, and genetic factors.

Methods

This cross-sectional study, part of the Biomarkers in Friedreich’s Ataxia observational study, involved 51 participants with molecularly proven FRDA undergoing respiratory testing, including spirometry, PCF, maximal respiratory pressures, sniff nasal inspiratory pressure, and lingual strength. Neurological impairment was assessed using the Modified Friedreich’s Ataxia Rating Scale (mFARS) and Functional Staging for Ataxia.

Results

Forty-seven participants completed PCF tests (31 female; mean age 22.60 years). Twenty-nine (61.7%) remained ambulant (mean mFARS 49.91). Seventeen (36.17%) had reduced PCF (<270 L/min). Lower PCF correlated with younger age, earlier disease onset, and decreased respiratory muscle strength. PCF showed strong associations with maximal inspiratory pressure (MIP), forced vital capacity (FVCpp), and maximal expiratory pressure (MEP). Multiple regression identified MIP and age of symptom onset as primary predictors.

Conclusions

The study demonstrates respiratory dysfunction in patients with FRDA, and shows that disease severity and muscle weakness affect airway clearance. PCF is a more direct and clinically meaningful indicator of cough effectiveness than FVCpp. Comprehensive respiratory evaluations, including muscle-strength testing, can identify individuals who may benefit from targeted interventions to prevent complications.

Keywords

Friedreich’s ataxia cough airway protection breathing

Background

Friedreich’s ataxia (FRDA) is the most common autosomal recessive ataxia in Caucasians, with an estimated prevalence of 1-2 per 50,000. It is characterized by progressive impairment of balance and coordination, manifesting with gait and limb ataxia, dysarthria and dysphagia, proprioceptive sensory loss and loss of tendon reflexes. Other features of FRDA include hypertrophic cardiomyopathy, diabetes, and skeletal abnormalities. In most cases, FRDA is caused by a biallelic trinucleotide GAA repeat expansion in intron 1 of the frataxin (FXN) gene, located on chromosome 9. This genetic mutation results in reduced expression of frataxin, a mitochondrial protein integral to intracellular iron homeostasis. Frataxin deficiency impairs iron-sulfur cluster biogenesis, hindering mitochondrial metabolism and promoting mitochondrial iron accumulation and oxidative stress. This leads to degeneration of the dorsal root ganglion cells and their projections, the cerebellum, and, later in the disease, the upper motor neuron pathways.^1–4 The age of symptom onset correlates with the length of GAA repeats, with longer repeats associated with earlier symptom onset and a more severe presentation.⁵

Clinical observations suggest that FRDA can impair cough, airway protection and respiratory function. Airway protection and aspiration prevention rely on coordinated reflex behaviors including coughing and swallowing. Reflexive cough occurs when food or other material penetrates at or below the level of the vocal cord, to facilitate removal of debris from the trachea. Voluntary coughing shares a similar motor pattern with reflexive coughing: an inspiratory phase consisting of inhalation toward inspiratory capacity; a compression phase consisting of simultaneous vocal fold adduction, expiratory muscle contraction, and subglottic pressure development; and an expiratory phase characterized by vocal fold relaxation with continued vigorous expiratory contraction.⁶ These coordinated actions enable the expulsion of mucus, food, or noxious particulates from the thorax to the mouth or pharynx.⁷

A retrospective study in children and adults with FRDA reported a weak cough in more than 20% of participants, accompanied by inspiratory and expiratory muscle weakness in the majority of the sample.⁸ Many respiratory parameters correlated with disease severity scores. While a younger age of onset and longer GAA repeat expansion are predictors of disease severity,⁹ this study did not identify clear associations between disease severity metrics and airway clearance or pulmonary function.

Impairment in respiratory function can also be accompanied by speech impediments in patients with FRDA,^10–16 many of which can degrade cough force.¹⁰ Abnormalities in speech breathing kinematics have been documented, along with reduced lip and tongue strength, endurance, and rate of repetitive movements.¹⁰ Given that dysphagia is a prevalent feature in patients with FRDA, impaired cough and weakened respiratory function may exacerbate aspiration risk and contribute to poorer outcomes by compromising cough effectiveness and secondary airway protection.¹⁷ However, respiratory weakness is not universally reported in patients with FRDA, and spirometry tests were largely normal in early studies of adolescents and young adults (average age: 16 years).^18–20

Several studies have evaluated predictors of disease progression in FRDA, focusing primarily on genetic factors, age of onset, and composite clinical scales such as the modified Friedreich Ataxia Rating Scale (mFARS).^21–25 While mFARS subscores capture meaningful functional aspects of disease progression, such as the gradual loss of ambulation driven by specific motor impairments, respiratory function has been comparatively less well characterized in FRDA. In particular, the relationship between respiratory dysfunction, respiratory muscle strength, and other measures of disease severity or functional outcomes remains poorly defined. Disease-specific respiratory metrics may therefore provide clinically relevant, quantifiable indicators of disease burden and airway protection abilities.

Pneumonia is the reported cause of death in approximately 10% of patients with FRDA, illustrating that respiratory dysfunction itself is a significant contributor to FRDA disease severity, although literature regarding respiratory morbidity in patients with FRDA is scarce.^26,27 Therefore, a more comprehensive picture of pulmonary function could help healthcare providers identify airway clearance dysfunction earlier in individuals with FRDA. Moreover, further research regarding pulmonary function testing is needed to determine which parameters are the most informative for illustrating and tracking respiratory progression in this disease.

Objectives

This study aimed to (1) evaluate the prevalence of airway clearance dysfunction in a cohort of patients with FRDA, as measured by voluntary peak cough flow (PCF) and (2) explore correlations between PCF and other measures of pulmonary and oral strength and function, disease severity, and genetic factors. We hypothesized that both respiratory strength and overall disease severity would influence voluntary PCF.

Methods

Design

This was a cross-sectional study. Baseline pulmonary function was analyzed as part of a larger observational study called Biomarkers in Friedreich’s Ataxia (NCT 02497534). Participants visited the research lab for a single session of respiratory testing, including spirometry and peak cough flow, maximal respiratory pressures, sniff nasal inspiratory pressure, and lingual strength measurements.

Participants

Ambulant and non-ambulant individuals were eligible for the Biomarkers in Friedreich’s Ataxia study if they had a genetically confirmed diagnosis of FRDA and were between the ages of 8 and 70-years old at the time of testing. Exclusion criteria included pregnancy, unstable heart disease, heart transplant, or any other concurrent medical condition that, in the opinion of the principal investigator, would make participation unsafe. All study procedures were approved by the University of Florida Institutional Review Board (IRB), and written informed consent was obtained from all participants. Participation in the study was voluntary.

Pulmonary function testing

Participants completed pulmonary testing in the upright position. Prior to testing, individuals rested at least 30 minutes. Testing order included: spirometry, voluntary cough, maximal inspiratory pressure, maximal expiratory pressure, sniff nasal inspiratory pressure, lingual force, and labial force. Each respiratory test was performed for a minimum of three trials or until less than 10% variability was achieved between three repetitions, with at least a 2-minute break between efforts. If declining test results suggested fatigue or participants requested time to rest, additional break time was provided as needed. The highest value was chosen for analysis. All testing maneuvers were done in accordance with American Thoracic Society testing guidelines.²⁸

Peak voluntary cough

Peak cough flow (PCF) was measured using a clinical spirometer (COSMED Pony Fx, Rome, Italy). Participants wore a nose clip to occlude the nasal airway and used an antiviral and antibacterial respiratory filter mouthpiece connected to the spirometer. For participants unable to independently place and hold the mouthpiece, the operator assisted with mouthpiece management, holding the mouthpiece and maintaining lip seal with manual pressure at the lips as needed. Participants were instructed to take a full inspiration and then cough as forcefully as possible, producing a single cough rather than a sequential one.^29,30

Spirometry

Measures taken from the upright spirometry included forced vital capacity (FVC) and forced expiratory volume in one second (FEV₁) tests.²⁹ Equipment included a bacterial filtered mouthpiece, nose clip, and clinical spirometer (COSMED, Pony FX, Rome, Italy). For subjects unable to independently place and hold the mouthpiece, the operator provided assistance. Participants were instructed to inhale to total lung capacity and then exhale as forcefully and completely as possible.³⁰ Percent predicted values were calculated from the Global Lung Index (GLI) reference set.³¹ Results were expressed as percent predicted from the GLI (FVCpp, FEV1pp).

Maximal respiratory pressures

Maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP) provide noninvasive estimates of inspiratory and expiratory muscle strength, respectively.²⁹ Tests were performed using a nose clip and bacterial filtered flanged mouthpiece connected to a handheld pressure manometer (MicroRPM, Vyaire Medical, Inc., Mettawa, IL). For subjects unable to independently place and hold the mouthpiece, the operator provided assistance. During MIP testing, individuals were asked to exhale to residual volume and then inhale as forcefully as possible against a closed valve. To measure MEP, subjects inspired to total lung capacity and then exhaled as forcefully as possible against a closed valve.³² Respiratory efforts were maintained for 3-5 seconds.

Sniff nasal inspiratory pressure (SNIP)

To measure sniff nasal inspiratory pressure (SNIP), a pressure sensor was connected to a handheld manometer (MicroRPM, Vyaire Medical, Inc., Mettawa, IL) and then inserted into the subject’s nostril to completely occlude the opening. The other nostril remained open during the test. Subjects were instructed to sniff as forcefully and quickly as possible with their mouth closed. The manometer displayed the most negative pressure, and the highest value of 5 SNIP efforts was recorded.

Oral motor strength

Lingual and labial strength were measured using an air-filled bulb attached to a manometer (IOPI; IOPI Medical, LLC, Redmond, Washington). For lingual strength, the bulb was placed on the anterior midline body of the tongue, and subjects were asked to press the bulb to the hard palate as forcefully as possible.³³ For labial strength, the bulb was positioned between the subject’s upper lip and gum, just lateral to midline, and subjects were instructed to purse their lips. Each measurement was performed a minimum of five trials or until less than 10% variability was achieved across three repetitions, and the highest value was used for analysis.

Modified Friedreich’s Ataxia Rating Scale (mFARS) and functional staging for ataxia scale

The mFARS provides a standardized and quantifiable measure of neurological function in FRDA patients, and consists of 4 subsections: bulbar, upper limb coordination, lower limb coordination, and upright stability. Scores range from 0 to 93, with lower scores indicating better neurological function.³⁴ The Functional Staging for Ataxia score indicates the impact of FRDA on daily functioning,³⁵ ranging from 0 (no disability) to 6 (confined to a wheelchair or bed with complete dependency for all activities of daily living, indicating total disability). The mFARS and the Functional Staging for Ataxia scores were obtained by a trained evaluator on the day of pulmonary function testing.

Genetic testing

GAA1 and GAA2 triplet repeat expansions were obtained through review of patient medical records.

Age of symptom onset

Age of symptoms onset was defined as the age at which the first disease-related clinical symptoms were reported or documented in the medical record, as determined retrospectively from patient history and/or clinician documentation. This variable reflects the timing of initial disease manifestation and is independent of the subject’s age at the time of respiratory assessment.

Data analysis

Data analysis was conducted using Graph Pad Prism 9.5 (GraphPad Software, San Diego, California USA). To describe characteristics of the sample, means and standard deviations of continuous variables were calculated. The distribution of the dataset was assessed with Shapiro-Wilk tests. Relationships between disease severity and pulmonary function parameters were tested using a Pearson correlation matrix. The mFARS bulbar score was analyzed with Mann-Whitney U and Spearman’s correlation tests. The effect of scoliosis on PCF was assessed with ANOVA. To investigate the contributions of strength, pulmonary function, and disease-related variables to cough generation, a series of univariate linear regressions was conducted. Then, multiple linear regression analysis was used to identify which respiratory- and disease-related variables identified from the correlations best contributed to the peak cough flow. A complex model containing FVCpp, MIP, MEP, mFARS, GAA1, and age of symptom onset was compared to simpler models containing one respiratory and one disease variable. The extra-sum-of-squares approach was used to identify the simplest model that could account for the largest variance in the dataset.

Results

Participant demographics

All values are presented as mean (±SD) unless otherwise indicated. Of the 51 participants enrolled in the study, 47 (16 male and 31 female) successfully completed PCF tests. The age range of these participants spanned from 11 to 69 years, with a mean age of 22.60 years (±10.88). The mean mFARS sore for this group was 49.61 (±18.55). Notably, 29 out of the 47 participants were classified as functionally ambulant, defined as the ability to walk at least five meters without any assistance or device. A detailed summary of the clinical characteristics and demographics data of the study sample can be found in Table 1.

Table 1.

Participant demographic and clinical characteristics.

Characteristics	Value
N (male, female)	47 (17 male, 31 female)
Ethnicity/Race	2 Hispanic/White; 45 Non-Hispanic/White

Characteristics	Mean	Standard deviation	Range
Age (years)	22.60	10.88	10 - 66
Age at Symptom Onset (years)	11.43	6.90	2 - 30
Age at Diagnosis (years)	14.62	8.41	3 - 47
GAA1*	738	229	174 - 1160
GAA2*	867	214	116 - 1300
Functional Staging for Ataxia	4	1.53	1 - 6
mFARS (max=93)	49.61	18.55	12.99 - 91
mFARS Bulbar (max=5)	1.21	0.95	0 - 5

*Two participants contain point mutations and were excluded from GAA analysis in Table 1.

GAA: Guanine-Adenine-Adenine; mFARS: modified Friedreich’s Ataxia Rating Scale.

Characteristics of participants with reduced cough force

PCF was obtained in 47 participants, with a mean value of 338 (±129) L/min. Seventeen participants had a PCF <270 L/min, which according to published thresholds for neuromuscular diseases, placed them at an increased risk for ineffective airway clearance during respiratory infection.³⁶ Figure 1 illustrates respiratory-related variables, and Figure 2 depicts disease parameters in those with PCF ≥270 L/min and <270 L/min.

Figure 1.

Respiratory parameters in participants with PCF <270L/min and those with PCF <270 L/min. (a) FVCpp, (b) FEV1pp, (c) MIP, (d) MEP, (e) Lingual force, (f) Labial force (* p<0.05; ** p<0.005, *** p<0.0005).

Figure 2.

Disease severity parameters in those with cough force ≥ 270L/min and those with PCF <270 L/min. (a) GAA1 repeats, (b) GAA2 repeats, (c) mFARS score, (d) mFARS bulbar subscore, (e) age of onset.

Individuals with PCF ≥270 L/min had FVCpp of 87 (±18) % predicted, MIP of 74.3 (±28.4) cm H₂O, MEP of 69.9 (±32.1) cm H₂O, and peak labial force of 26.3 (±7.2) kPa, with the values for those with PCF <270 L/min being significantly lower: 66 (±16) % predicted, (p<0.0005); 46.8 (±23.8) cm H₂O, (p<0.005), 49.5 (±22.4) cm H₂O, (p<0.005); and 20.8 (±6.0) kPa, (p<0.05), respectively. While SNIP and peak lingual force trended lower in those with weak cough, the differences were not significant.

Individuals with an at-risk PCF had earlier age of FRDA symptom onset (6.7 (±2.4) versus 14.1 (±7.2) years, p<0.0005) and were younger than those with PCF>270L/min (16.1 (±4.7) versus 26.3 (±11.7) years, p<0.0005, Mann-Whitney U test). Scoliosis was diagnosed in 23 participants, not present in 6, and not reported in 18. PCF did not differ between participants with scoliosis (311 (±131) L/min), without scoliosis (394 (±70) L/min), or with unreported status (370 (±139) L/min; ANOVA, F (2,44) = 1.578, p=0.2178).

Relationships between respiratory-related and disease severity measures

As illustrated in the correlation matrix outlined in Table 2, most pulmonary function and respiratory strength measures were strongly and positively correlated. Among disease severity metrics, the number of GAA1 repeats correlated strongly with both age of symptom onset (r= -0.451, p<0.005) and disease duration (r= -0.427, p<0.005). The mFARS score significantly correlated with age of onset (r= -0.449, p<0.005) and the bulbar subscore (r=0.747, Spearman’s correlation, p<0.0001). However, the bulbar subscore did not correspond with other non-respiratory disease severity variables.

Table 2.

Correlations between respiratory-related and disease severity variables in participants with FRDA. Italicized values represent Spearman’s correlation analysis.

	PCF (L/min)	FVCpp (% pred)	FEV1pp (% pred)	MIP	MEP	SNIP	Lingual force	Labial force	mFARS	Bulbar mFARS	GAA1	GAA2
PCF (L/min)		0.568 n=46	0.467^{^} n=46	0.594^# n=46	0.546^# n=46	0.299^* n=46	0.221 n=47	0.391^& n=46	-0.284 n=47	-0.128 n=47	-0.341^* n=47	-0.169 n=47
FVCpp (% pred)	0.568^# n=46		0.671^# n=46	0.620^# n=45	0.582^# n=45	0.539^$ n=45	0.371^* n=46	0.213 n=45	-0.500^$ n=46	-0.389 ^& n=46	-0.288 n=46	-0.113 n=46
FEV₁pp (% pred)	0.467^{^} n=46	0.671^# n=46		0.517^$ n=45	0.588^# n=45	0.557^# n=45	0.439^{^} n=46	0.303 n=45	-0.520^$ n=46	-0.532 ^$ n=46	-0.124 n=46	-0.109 n=46
MIP	0.594^# n=46	0.620^# n=45	0.517^$ n=45		0.764^# n=46	0.593^# n=46	0.607^# n=46	0.471^$ n=46	-0.365^* n=46	-0.304 ^* n=46	-0.140 n=46	0.004 n=46
MEP	0.546^# n=46	0.582^# n=45	0.588^# n=45	0.764^# n=46		0.525^$ n=46	0.443^{^} n=46	0.242 n=46	-0.570^# n=46	-0.496 ^$ n=46	-0.142 n=46	-0.087 n=46
SNIP	0.299^* n=46	0.539^$ n=45	0.557^# n=45	0.593^# n=46	0.525^$ n=46		0.494^$ n=46	0.399^& n=46	-0.469^$ n=46	-0.487 ^$ n=46	-0.080 n=46	-0.051 n=46
Lingual force	0.221 n=47	0.371^* n=46	0.439^{^} n=46	0.607^# n=46	0.443^{^} n=46	0.494^$ n=46		0.542^# n=46	-0.273 n=47	-0.348 ^* n=47	0.165 n=47	0.069 n=47
Labial force	0.391^& n=46	0.213 n=45	0.303^* n=45	0.471^$ n=46	0.242 n=46	0.399^& n=46	0.542^# n=46		-0.157 n=46	-0.148 n=46	-0.026 n=46	-0.056 n=46
mFARS	-0.284 n=47	-0.500^$ n=46	-0.520^$ n=46	-0.365^* n=46	-0.570^# n=46	-0.469^{^} n=46	-0.273 n=47	-0.157 n=46		0.747 ^# n=47	0.065 n=47	0.182 n=47
Bulbar mFARS	-0.128 n=47	-0.389 ^& n=46	-0.532 ^$ n=46	-0.304 ^* n=46	-0.496 ^$ n=46	-0.487 ^$ n=46	-0.348 ^* n=47	-0.148 n=46	0.747 ^# n=47		-0.113 n=47	0.189 n=47
GAA1	-0.341^* n=47	-0.288 n=46	-0.124 n=46	-0.140 n=46	-0.142 n=46	-0.080 n=46	0.165 n=47	-0.026 n=46	0.065 n=47	-0.113 n=47		0.290^* n=47
GAA2	-0.169 n=47	-0.113 n=46	-0.109 n=46	0.004 n=46	-0.087 n=46	-0.051 n=46	0.069 n=47	-0.056 n=46	0.182 n=47	0.189 n=47	0.290^* n=47

*p<0.05.

^& p<0.01.

^{^} p<0.005.

^$ p<0.001.

^# p<0.0001.

FVCpp: Forced vital capacity (percent predicted); FEV_1pp: Forced expiratory volume in 1 second (percent predicted); MIP: Maximal inspiratory pressure; MEP: Maximal expiratory pressure; SNIP: sniff nasal inspiratory pressure; mFARS: modified Friedreich’s Ataxia Rating Scale, GAA: Guanine-Adenine-Adenine.

Several respiratory parameters correlated closely with disease severity variables. mFARS score had a significant negative correlation with expiratory metrics, including MEP (r= -0.570, p<0.0001), FEV_1pp (r= -0.520, p<0.001), and pp (r= -0.500, p<0.001); with smaller yet significant inverse correlations observed for SNIP (r= -0.469, p<0.001) and MIP (r= -0.365, p<0.05). The mFARS bulbar subscore also correlated significantly with most respiratory metrics. Significant positive relationships were found between age of onset and measures of forceful expiratory efforts, including FVCpp (r= 0.618, p<0.0001), MEP (r= 0.596, p<0.0001), and FEV_1pp (r= 0.497, p<0.001); while significant yet modest correlations occurred between age of onset and MIP (r= 0.464, p<0.005) and SNIP (r= 0.438, p<0.005). In contrast, GAA1 and GAA2 copy numbers were not significantly associated with any respiratory-related measures.

Relationships between PCF and respiratory and disease parameters

PCF was strongly and positively correlated with all respiratory measures except lingual force (Table 2). The most robust associations were observed with MIP (r=0.594, n=46, p<0.0001), FVCpp (r=0.568, n=46, p<0.0001), and MEP (r=0.546, n=46, p<0.0001), with additional significant correlations for FEV1pp (r=0.467, n=46, p<0.005), labial strength (r=0.391, n=46, p<0.01), and SNIP (r=0.299, r=46, p<0.05). Of the disease severity parameters collected, PCF correlated strongly with the age of symptom onset (r=0.662, n=47, p<0.00001). Modest correlation was also found with the number of GAA1 repeats (r= -0.341, n=47, p<0.05).

Multiple linear regression

Three different respiratory strength metrics (MIP, MEP, labial force) were selected for inclusion into the multiple linear regression analysis to represent inspiratory, expiratory, and oral-motor components of cough production while reducing potential confounding effects of multi-collinearity. In addition, the two disease severity metrics that significantly correlated with PCF (age of onset and GAA1) and mFARS were included. As depicted in Table 3, four models were statistically significant in determining peak cough flow. Compared to Model D, containing all six independent variables, the combination of MIP and age of onset (Model C) was the simplest alternative, two-variable model that explained the largest proportion of the variance (R²=0.5293, F[2,43]=24.18, p<0.0001).

Table 3.

Regression coefficients of respiratory strength and disease severity parameters on peak cough flow in patients with FRDA. Models A-C represent significant two-factor models selected from the model incorporating all variables (Model D).

	Model A ****	Model B ****	Model C ****	Model D ****
Constant	322.1 **** (54.01)	92.17 (50.95)	134.6 *** (33.62)	113.4 (99.38)
MIP	2.324 **** (0.472)		1.605 ** (0.507)	1.084 (0.786)
MEP				0.6023 (0.860)
Labial force		4.931 * (1.952)		3.294 (2.133)
mFARS				0.8107 (0.886)
GAA1	-0.1842 ** (0.054)			-0.1035 (0.065)
Age of onset		11.13 **** (2.063)	8.872 *** (2.207)	6.332 * (3.095)
R-squared	0.4908	0.4947	0.5293	0.5853
Adjusted R2	0.4671	0.4712	0.5074	0.5215
No. observations				46

*p<0.05.

**p<0.005.

***p<0.001.

****p<0.0001.

MIP: Maximal inspiratory pressure; MEP: Maximal expiratory pressure; SNIP: sniff nasal inspiratory pressure; mFARS: modified Friedreich’s Ataxia Rating Scale; GAA1: Guanine-Adenine-Adenine 1 repeats.

Discussion

FRDA is a multisystem disease that carries important morbidity and mortality due to respiratory complications. This study is the first to characterize the complex relationship among respiratory function, age, parameters of disease severity, and genetic factors. We investigated the effectiveness of cough by measuring PCF in individuals with FRDA, finding that 36.17% of subjects had a PCF <270 L/min, a threshold associated with an increased risk of complications during a respiratory infection.³⁷ In this cohort, both respiratory function and disease severity contributed to the impaired PCF. Individuals with an at-risk PCF also exhibited lower inspiratory, expiratory, and labial force generation compared to those with PCF > 270 L/min, and one-third had a FVCpp <50% of predicted values, a common clinical criterion for establishing noninvasive ventilation for patients with neuromuscular conditions,³⁸ although literature from other conditions suggests that initiation of noninvasive ventilation at higher thresholds would be beneficial.³⁹ These individuals were also younger and had an earlier onset of FRDA symptoms. Among the parameters examined, MIP and age of symptom onset were the strongest predictors of PCF. In contrast, limited to no relationships were seen between PCF and mFARS, bulbar mFARS subscores, or GAA1 repeat number.

Although FVC is often the standard test to evaluate respiratory involvement in FRDA and other neuromuscular disorders, airway clearance includes crucial protective reflex behaviors essential for respiratory health. PCF is a functional pulmonary function test often reported as a predictor of successful extubation and adequate airway clearance in other conditions,⁴⁰ Terzi, 2018 #⁴². In neuromuscular or neurodegenerative conditions, cough force can be impaired by respiratory muscle weakness or an inability to rapidly coordinate the inspiratory, laryngeal, and expiratory muscles that contribute to cough. While respiratory muscle involvement is frequent among neuromuscular disorders,^41–43 defects in timing and phase switching during cough have also been found to contribute to poor cough force and an increased risk of aspiration in other neurological conditions.^44–46 Approximately one-third of individuals with FRDA are reported to aspirate,¹⁷ and voluntary PCF has been demonstrated in other neuromuscular conditions to be a simple and clinically useful predictive tool for identifying individuals at risk for aspiration.⁴⁷

Since FRDA affects sensory neurons and the cerebellum, a lack of coordination between components of the respiratory system can affect the ability to execute respiratory efforts, specifically during speech.^17,48,49 In a study by Murdoch et al., half of the subjects with cerebellar disease exhibited reduced vital capacity.⁴⁸ Several tests of pulmonary function, including FVC and PCF, depend on coordination between inspiratory, expiratory, and oropharyngeal motor function, making them directly influenced by respiratory muscle strength and coordination. However, associations between respiratory and oral strength measures and pulmonary function have not been previously investigated in detail.

The severity and progression of FDRA can be systematically evaluated using mFARS scores, and mFARS can offer insights into the efficacy of investigational treatments.⁵⁰ While mFARS scores reflect overall disease progression, the mFARS bulbar subscore relates more specifically to speech and cough production and had limited relationship with lingual and labial force generation. The ordinal scoring of the mFARS bulbar subscore also did not provide specific insights on the coordination between inspiratory, airway, and expiratory muscle groups, as assessed by pulmonary function testing. Indeed, a post-hoc analysis revealed no appreciable differences in PCF based on either the bulbar subscore or the FARS cough item score, highlighting the need for a more objective assessment of cough efficacy. On the other hand, tests of bulbar weakness provide further objective information beyond clinical disease severity scales. Peak labial force was associated with low PCF, but lingual strength and SNIP were not. These results suggest that differing bulbar weakness patterns could contribute to various bulbar-related motor dysfunction. For example, threshold lingual strength values have been reported in ALS that distinguish typical swallowing from unsafe or inefficient swallowing.⁵¹ While the contributions of labial strength to cough effectiveness are poorly understood, we suggest that oral co-contractions contribute to airflow direction, propulsion of respiratory droplets, and expulsion of debris.

In other neuromuscular diseases, it appears that a breakdown in respiratory motor coordination may precede a decline in peak flow.⁵² This observation is particularly relevant in FRDA, where impaired respiratory motor coordination not only compromises cough efficiency but also directly impacts the swallowing processes. Both swallowing and cough reflexes require coordination of antagonist muscle groups with exquisite precision. Such impairments in FRDA or similar neuromuscular conditions can lead to ineffective or absent cough reflex along with swallowing difficulties, elevating the risk of serious comorbidities like dysphagia and aspiration.⁵³ Dysphagia occurs when there is a disruption in one or more of the phases of swallowing: oral preparatory, oral, pharyngeal, and esophageal phase. The complex pharyngeal phase plays the largest role in airway protection during the swallowing process, requiring timely coordination of a multitude of anatomical structures. During a safe bolus passage through the pharyngeal phase, the tongue propels the bolus into the pharynx, the soft palate closes off the nasopharynx, and the base of the tongue retracts. Subsequently, the vocal folds adduct to seal the glottis, the epiglottis covers the laryngeal vestibule, and the upper esophageal sphincter opens to allow the bolus to pass to the esophagus.⁵⁴ A disturbance in this rapid, complex, multisystem phase can result in a sequalae of airway interferences, including penetration (entry of food into the larynx) or aspiration (passage of materials below the vocal folds). It is likely that some of these processes are impaired in patients with FRDA and warrants further investigation.

Role of inspiratory strength in generating effective PCF

Our findings underscore the essential contribution of inspiration to effective cough generation. The inspired volume at the onset of coughing, or operating volume, is critical for generating an effective expulsive effort.⁵⁵ A robust inspiration increases the elastic forces of the lungs and thoracic cage, provides sufficient volume to extend the cough effort, and engages the diaphragm and accessory respiratory muscles.⁶ The diaphragm remains active during the expulsive phase of cough to preserve stiffness of the lateral costal margins and optimize the length-tension relationship of the expiratory muscles. Our finding that inspiratory muscle strength is a primary contributor to effective cough aligns with reports in other neuromuscular and neurodegenerative conditions, including Pompe disease, amyotrophic lateral sclerosis (ALS), and Duchenne muscular dystrophy.^29,52,56 From a clinical perspective, these results suggests that inspiratory strength should be routinely monitored in individuals with FRDA, along with tests of expiratory strength and cough force. Since each test reflects different aspects of respiratory muscle performance, their regular use can help distinguish inspiratory, glottic, and expiratory weakness.

Respiratory strengthening exercises reported to improve cough and swallowing metrics in patients with Pompe Disease, Parkinson’s Disease and ALS,^57–59 could offer functional benefit in FRDA. In contrast, the evidence for respiratory strengthening is mixed in other neuromuscular conditions, including spinal muscular atrophy⁶⁰ and Duchenne muscular dystrophy.⁶¹ The training intensity, mode of resistance, and exercise compliance can widely influence training outcomes, and direct comparisons between training studies can be challenging due to design variations.⁶² Further investigation is needed.

Limitations/critique of the method

Several limitations of this study should be acknowledged. Cross-sectional data from a single site are represented, and large samples can be challenging to acquire in a rare condition. Participation in a natural history study (as opposed to data from clinical visits) could perhaps lead to a selection bias, where more severely impacted patients seek novel treatments for their condition, or where mildly affected patients are more likely able to travel for research purposes. There are also fewer normative pediatric respiratory data.

Patients were instructed to take a deep breath prior to their voluntary cough effort, consistent with some prior studies.^52,63 However, in other reports of voluntary cough in neuromuscular disease, participants were instructed to cough as forcefully as possible without designating a large inspiration.^64,65 With differing cough instructions, the contributions of other respiratory-related muscles could predominate.

Additionally, a desktop spirometer was used to capture voluntary cough efforts. A research pneumotachograph would offer higher sampling resolution, enabling a more precise characterization of cough volume, timing, and pressure dynamics of the entire cough effort. Moreover, the use of a mouthpiece instead of a mask may allow air to escape from the corners of the mouth, potentially affected recorded measurements.

Individuals aged 14 years and older with PCF <270 L/min face an increased risk for ineffective airway clearance during a respiratory infection, and cough augmentation is often recommended below this threshold.⁶⁶ Nevertheless, the clinical relevance of PCF threshold is not well understood, especially in children. This sample included 9 children <14 years of age, with the youngest participant being 10.5 years old. Of these, six had PCF <270 L/min. While the threshold values for an ineffective PCF have not been validated in children with neuromuscular conditions under 14 years of age, the largest study of PCF in healthy children found that the 5^th percentile for 10-year-olds averaged 270 L/m in girls and 250 L/min in boys.³⁰ Thus, PCF values below 250-270 L/min in participants aged 10-14 years may be considered clinically significant. Differing PCF cutoffs have been proposed as relevant to children with neuromuscular disease, especially when considering the number of chest infections, necessity of antibiotics, or hospitalization.⁶⁷ Besides PCF thresholds, the distribution and lower limit of normal (LLN) of MIP and MEP vary in pediatric patients when compared to adults.⁶⁸ While only ten participants in this study were < 18 years of age, of those with a PCF < 270 L/min (N=6), all of them had a MEP below the LLN for age and sex, and only one participant had a MIP above the expected LLN (MIP 53 cmH₂O, LLN: 51.9 cmH_2.O).⁶⁹ In addition, when participants <14 years were excluded for analysis, age of onset remained significantly lower in the lower (<270 L/min) PCF group.

Conclusions

This study on FRDA offers critical insights into the disease’s impact on airway clearance and respiratory function. Key conclusions include:

1) Prevalence of airway clearance dysfunction: A notable portion of the FRDA participants, 36.17%, exhibited significantly reduced PCF. While the literature regarding respiratory morbidity and mortality is quite limited in patients with FRDA, data from other conditions strongly demonstrates that a reduced PCF correlates with significant respiratory complications, including extubation failure, aspiration and mortality etc.^70–73 This finding emphasizes the importance of routine airway clearance assessment in patients with FRDA.

2) Correlation between PCF and respiratory measures: The study revealed strong positive correlations between PCF and various respiratory metrics such as MIP, FVCpp, and MEP. The observed impairments of volume, flow, and pressure underscore the presence of respiratory muscle dysfunction in many patients diagnosed with FRDA.

3) Influence of disease severity and age of onset: Lower PCF was associated with earlier symptom onset and younger age of FRDA patients, underscoring the impact of disease progression on respiratory function. MIP and age of symptom onset were identified as the strongest predictors of PCF.

Overall, this study provides further understanding of the respiratory challenges experienced by individuals with FRDA, which include impaired cough, low FVC, impaired inspiratory, expiratory, and bulbar strength. The data highlight the importance of including respiratory function assessments into clinical evaluations. Clinical respiratory evaluations could identify respiratory impairment and aid in the timely implementation of clinical interventions such as cough augmentation techniques or noninvasive ventilation in patients with FRDA. Further longitudinal data are needed to help identify progression and impacts of respiratory neuromuscular dysfunction in FRDA.

Footnotes

Acknowledgments

We want to acknowledge and thank our patients and their families for their participation and consent. Additionally, we want to thank Claudia Mercado-Rodriguez for reviewing and editing the manuscript.

ORCID iDs

Cristina Liberati

Carmen Leon-Astudillo

Ethical considerations

This study received ethical approval from the University of Florida IRB (#201500369) in September 2015.

Consent to participate

Written informed consent was obtained from all participants. Participation in the study was voluntary.

Author contributions

Barbara K Smith was involved in conceptualization, study design, data analysis, and manuscript writing.

Mackenzi A Coker was involved in study design, data collection, data curation, review and editing of the manuscript, and project administration.

Cristina Liberati was involved in clinical assessment and review and editing of the manuscript.

Blake P Meyer was involved in data collection, data curation, and review and editing of the manuscript.

Samantha Norman was involved in data collection and data curation.

Jessica Ehrbar was involved in data collection and data analysis.

Carmen Leon-Astudillo was involved in clinical assessment and review and editing of the manuscript.

Sub Subramony was involved in conceptualization, clinical assessment, data collection, and review and editing of the manuscript.

Manuela Corti was involved in conceptualization, study design, study supervision, compliance with institutional requirements and administrative coordination, data collection, manuscript writing, and funding acquisition.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Sub Subramony discloses receipt of financial support from the Friedreich’s Ataxia Research Alliance (FARA). Manuela Corti discloses receipt of financial support from the Friedreich’s Ataxia Research Alliance (FARA) and Children Miracle Network.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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