A poor nutritional status is associated with worse pulmonary function and survival in people with cystic fibrosis (pwCF). CF transmembrane conductance regulator modulators can improve pulmonary function and body weight, but more data is needed to evaluate its effects on body composition. In this retrospective study, a pre-trained deep-learning network was used to perform a fully automated body composition analysis on chest CTs from 66 adult pwCF before and after receiving elexacaftor/tezacaftor/ivacaftor (ETI) therapy. Muscle and adipose tissues were quantified and divided by bone volume to obtain body size-adjusted ratios. After receiving ETI therapy, marked increases were observed in all adipose tissue ratios among pwCF, including the total adipose tissue ratio (+ 46.21%, p < 0.001). In contrast, only small, but statistically significant increases of the muscle ratio were measured in the overall study population (+ 1.63%, p = 0.008). Study participants who were initially categorized as underweight experienced more pronounced effects on total adipose tissue ratio (p = 0.002), while gains in muscle ratio were equally distributed across BMI categories (p = 0.832). Our findings suggest that ETI therapy primarily affects adipose tissues, not muscle tissue, in adults with CF. These effects are primarily observed among pwCF who were initially underweight. Our findings may have implications for the future nutritional management of pwCF.

Introduction: Cystic fibrosis (CF), especially CF lung disease, is characterized by chronic infection, immune dysfunction including impairment of regulatory T cells (Tregs) and an exaggerated inflammatory response. CF transmembrane conductance regulator (CFTR) modulators have shown to improve clinical outcomes in people with CF (PwCF) with a wide range of CFTR mutations. However, it remains unclear whether CFTR modulator therapy also affects CF-associated inflammation. We aimed to examine the effect of elexacaftor/tezacaftor/ivacaftor therapy on lymphocyte subsets and systemic cytokines in PwCF.Methods: Peripheral blood mononuclear cells and plasma were collected before and at three and six months after the initiation of elexacaftor/tezacaftor/ivacaftor therapy; lymphocyte subsets and systemic cytokines were determined using flow cytometry.Results: Elexacaftor/tezacaftor/ivacaftor treatment was initiated in 77 PwCF and improved percent predicted FEV1 by 12.5 points (p<0.001) at 3 months. During elexacaftor/tezacaftor/ivacaftor therapy, percentages of Tregs were enhanced (+18.7%, p<0.001), with an increased proportion of Tregs expressing CD39 as a marker of stability (+14.4%, p<0.001). Treg enhancement was more pronounced in PwCF clearing Pseudomonas aeruginosa infection. Only minor, non-significant shifts were observed among Th1-, Th2- and Th17-expressing effector T helper cells. These results were stable at 3- and 6-month follow-up. Cytokine measurements showed a significant decrease in interleukin-6 levels during treatment with elexacaftor/tezacaftor/ivacaftor (–50.2%, p<0.001).Conclusion: Treatment with elexacaftor/tezacaftor/ivacaftor was associated with an increased percentage of Tregs, especially in PwCF clearing Pseudomonas aeruginosa infection. Targeting Treg homeostasis is a therapeutic option for PwCF with persistent Treg impairment.

Cystic fibrosis (CF) is associated with dysregulated immune responses, exaggerated inflammation and chronic infection. CF transmembrane conductance regulator (CFTR) modulator therapies directly target the underlying protein defects and resulted in significant clinical benefits for people with CF (pwCF). This study analysed the effects of triple CFTR modulator therapy elexacaftor/tezacaftor/ivacaftor (ETI) on CF-associated inflammation, especially systemic chemokines. A bead-based immunoassay was used to quantify proinflammatory chemokines (IL-8, IP-10, Eotaxin, TARC, RANTES, MIP-1α, MIP-1β, MIP-3α, MIG, ENA-78, GROα, I-TAC) in plasma samples from pwCF collected before, at three, and at six months after starting ETI therapy. Fifty-one pwCF (47 % female; mean age 32 ± 10.4 years) were included. At baseline, 67 % were already receiving CFTR modulator therapy with tezacaftor/ivacaftor or lumacaftor/ivacaftor. After initiation of ETI therapy there was a significant improvement in percent predicted forced expiratory volume in 1 s (+12.7 points, p < 0.001) and a significant decrease in sweat chloride levels (-53.6 %, p < 0.001). After 6 months' treatment with ETI therapy there were significant decreases in plasma levels of MIP-3α (-68.2 %, p = 0.018), GROα (-17.7 %, p = 0.013), ENA-78 (-16.3 %, p = 0.034) and I-TAC (-3.4 %, p = 0.032). IL-8 exhibited a reduction that did not reach statistical significance (-17.8 %, p = 0.057); levels of other assessed cytokines did not change significantly from baseline. ETI appears to affect a distinct group of chemokines that are predominately associated with neutrophilic inflammation, demonstrating the anti-inflammatory properties of ETI therapy.

Background: Cystic fibrosis bone disease (CFBD) is a common comorbidity in adult people with cystic fibrosis (pwCF), resulting in an increased risk of bone fractures. This study evaluated the capacity of artificial intelligence (AI)-assisted low-dose chest CT (LDCT) opportunistic screening for detecting low bone mineral density (BMD) in adult pwCF. Methods: In this retrospective single-center study, 65 adult pwCF (mean age 30.1 ± 7.5 years) underwent dual-energy X-ray absorptiometry (DXA) of the lumbar vertebrae L1 to L4 to determine BMD and corresponding z-scores and completed LDCTs of the chest within three months as part of routine clinical care. A fully automated CT-based AI algorithm measured the attenuation values (Hounsfield units [HU]) of the thoracic vertebrae Th9–Th12 and first lumbar vertebra L1. The ability of the algorithm to diagnose CFBD was assessed using receiver operating characteristic (ROC) curves. Results: HU values of Th9 to L1 and DXA-derived BMD and the corresponding z-scores of L1 to L4 showed a strong correlation (all p < 0.05). The area under the curve (AUC) for diagnosing low BMD was highest for L1 (0.796; p = 0.001) and Th11 (0.835; p < 0.001), resulting in a specificity of 84.9% at a sensitivity level of 75%. The HU threshold values for distinguishing normal from low BMD were <197 (L1) and <212 (Th11), respectively. Conclusions: Routine LDCT of the chest with the fully automated AI-guided determination of thoracic and lumbar vertebral attenuation values is a valuable tool for predicting low BMD in adult pwCF, with the best results for Th11 and L1. However, further studies are required to define clear threshold values.