Regional Brain Tissue Changes in Patients with Cystic Fibrosis

Regional Brain Tissue Changes in Patients with Cystic Fibrosis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Regional Brain Tissue Changes in Patients with Cystic Fibrosis Bhaswati Roy, Marlyn S. Woo, Susana Vacas, Patricia Eshaghian, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-769615/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background: Cystic fibrosis (CF) patients present with a variety of symptoms, including mood and cognition deficits, in addition to classical respiratory, and autonomic issues. This suggests that brain injury, which can be examined with non-invasive magnetic resonance imaging (MRI), is a manifestation of this condition. However, brain tissue integrity in sites that regulate cognitive, autonomic, respiratory, and mood functions in CF patients is unclear. Our aim was to assess regional brain changes using high-resolution T1-weighted images based gray matter (GM) density and T2-relaxometry procedures in CF over control subjects. Methods: We acquired high-resolution T1-weighted images and proton-density (PD) and T2-weighted images from 5 CF and 15 control subjects using a 3.0-Tesla MRI. High-resolution T1-weighted images were partitioned to GM-tissue type, normalized to a common space, and smoothed. Using PD- and T2-weighted images, whole-brain T2-relaxation maps were calculated, normalized, and smoothed. The smoothed GM-density and T2-relaxation maps were compared voxel-by-voxel between groups using analysis of covariance (covariates, age and sex; SPM12, p<0.001). Results: Significantly increased GM-density, indicating tissues injury, emerged in multiple brain regions, including the cerebellum, hippocampus, amygdala, basal forebrain, insula, and frontal and prefrontal cortices. Various brain areas showed significantly reduced T2-relaxation values in CF subjects, indicating predominant acute tissue changes, in the cerebellum, cerebellar tonsil, prefrontal and frontal cortices, insula, and corpus callosum. Conclusions: Cystic fibrosis subjects show predominant acute tissue changes in areas that control mood, cognition, respiratory, and autonomic functions and suggests that tissue changes may contribute to symptoms resulting from ongoing hypoxia accompanying the condition. Translational Medicine Cognition Mood Gray matter density T2-relaxometery Magnetic Resonance Imaging Figures Figure 1 Figure 2 Introduction Cystic fibrosis (CF) is a progressive genetic disorder predominately affecting lungs, liver, and the pancreas and intestine exocrine glands. Approximately 1,000 new CF cases are diagnosed each year, totaling more than 30,000 people in the United States and 70,000 worldwide. CF is caused by mutations in the CF transmembrane conductance regulator (CFTR) gene, and broadly classified into I-VI classes based on their effects on the CFTR protein [1, 2]. Symptoms include poor weight gain/growth, persistent cough, shortness of breath, and repeated lung infections. In addition, CF patients with clinically stable severe lung disease show impaired neurocognitive functions, including cognitive and mood deficits, autonomic issues, and daytime sleepiness [3], and disease exacerbation further worsens their neurobehavioral performance [4]. High rates of anxiety and depression found in CF lead to non-adherence of prescribed treatment, affecting health outcomes and health related quality of life [5]. Such psychological, including mood and cognitive functions, and autonomic deficits [6, 7] might result from tissue dysfunction in multiple brain regions; however, there are no previous studies examining brain changes in CF patients. Subtle brain tissue changes are often challenging to visualize on routine brain magnetic resonance imaging (MRI), including T1-weighted and T2-weighted imaging. High-resolution T1-weighted imaging based voxel-based morphometry (VBM), and T2-relaxometry based on proton density (PD)- and T2-weighted imaging can be used to examine subtle brain tissue changes. VBM procedures can exhibit localized gray matter (GM) density that reflects the proportion of GM relative to other tissue types within an examined region. However, T2-relaxometry measures free-water content within the tissue [8] by acquiring a series of images at different echo times, and has the potential to detect brain tissue microstructural changes, with higher specificity than conventional MRI. Immuno-histochemical evidence shows that decreased T2-relaxation values are associated with increased glial activation [9], and reduced T2-relaxation values emerged in bipolar disorder [10, 11], and spinocerebellar ataxia type 3 [12]. In addition, the main etiologies of increased T2-relaxation values in the brain are vasogenic edema, demyelination, gliosis, or neuronal loss [13–15], observed in tumor [16], chronic epilepsy [17], congenital central hypoventilation syndrome [18], traumatic brain injury [19], and multiple sclerosis [13]. Such MRI techniques are simple and rapid, utilizes data acquired from routine T1-weighted, proton-density, and T2-weighted imaging, and can be implemented on standard clinical MR systems, and the quantitative measures make them advantageous in examining brain tissue integrity. Average survival of CF patients has improved recently, and this improvement is due to the advancement in treatment, emphasis on early diagnosis, as well as effective differential disease management, though there is still no cure for the disease. In order to increase the life span and life quality of CF individuals, detection of brain changes are of utmost importance. Identifying the structural brain changes associated with cognitive and mood deficits in CF patients may provide new insights into healthcare management and long-term clinical strategies. Our study aimed to examine regional GM density changes, as well as tissue changes using T2-relaxometry procedures in CF patients over healthy controls. Based on the severity of psychological and autonomic changes exhibited in CF patients, we hypothesized that GM density and T2-relaxation values would differ from healthy population, indicating brain damage, in autonomic, mood, and cognition control areas. Materials And Methods Subjects This is a cross-sectional, comparative study of five CF patients recruited from the University of California Los Angeles (UCLA) Adult Cystic Fibrosis Center and 15 control subjects recruited through advertisements at the UCLA campus and Los Angeles area. All study procedures were followed in accordance with institutional guidelines, and the study was approved by the UCLA Institutional Review Board. Subjects were fully informed about the study procedures and provided written informed consent prior to data collection. CF patients were confirmed for CF genotype, were with mutation class I-III, and had mild to moderate CF lung disease. None of the CF patient underwent lung transplant, were not on any steroid therapy, and their oxygen saturation at rest was > 94% on room air. CF patients with history of stroke, seizure disorder, or head trauma, diagnosed psychiatric disease (clinical depression, schizophrenia, manic-depressive), airway or chest deformities that would interfere with breathing were excluded from the study. Control subjects were healthy, with no sleep disturbances, neurological or cardiovascular issues that would introduce brain damage, or drug dependency that would modify brain tissue. Assessment of Depression and Anxiety All CF and control subjects were assessed for anxiety and depression using the Beck anxiety inventory (BAI) and the Beck depression inventory (BDI-II), respectively [20, 21]. The BAI and BDI-II inventories are self-administered questionnaires, composed of 21 multiple-choice questions (each question score ranged 0–3), with total scores ranging from 0–63 based on symptom severity [20, 21]. Cognition Examination CF and control subjects underwent for cognition evaluation using the Montreal Cognitive Assessment (MoCA) [22]. The MoCA test was used for rapid evaluation of various cognitive domains, including attention and concentration, executive functions, memory, language, visuo-constructional skills, conceptual thinking, calculations, and orientation. A score < 26 was considered abnormal [22]. Magnetic Resonance Imaging All brain imaging studies were performed in a 3.0-Tesla MR scanner (Magnetom Tim-Trio and Prisma Fit, Siemens, Erlangen, Germany). We used foam pads on either side of the head to minimize head motion. Proton density (PD) and T2-weighted images were acquired using a dual-echo turbo spin-echo sequence in the axial plane [repetition time (TR) = 10,000 ms; echo-time (TE1, TE2) = 12, 123/124 ms; flip angle (FA) = 130°; matrix size = 256⋅256; field-of-view (FOV) = 230⋅230 mm; slice thickness = 3.5 mm; inter-slice gap = no]. Two high-resolution T1-weighted images were collected using a magnetization prepared rapid acquisition gradient-echo (MPRAGE) sequence (TR = 2200 ms; TE = 2.3/2.4 ms; inversion time = 900 ms; FA = 9°; matrix size = 320⋅320; FOV = 230⋅230 mm; slice thickness = 0.9 mm; number of slices = 192). Data Processing We used the statistical parametric mapping package SPM12 (Wellcome Department of Cognitive Neurology, UK; http://www.fil.ion.ucl.ac.uk/spm/ ), and MATLAB-based (The MathWorks Inc, Natick, MA) custom software to process MRI data. Also, we used the MRIcroN software to visualize images. Visual examination: High-resolution T1-weighted, PD-weighted, and T2-weighted images of CF and control subjects were examined for any visible brain changes, including cystic lesions, infarcts, tumors, or other types of brain lesions. All images were also assessed for motion-related or any other imaging artifacts before GM density and T2-relaxation calculations. Calculation of GM density: Both high-resolution T1-weighted image series were realigned to remove any potential variations between scans, and averaged to improve signal-to-noise ratio. The averaged images were segmented into GM, white matter, and cerebrospinal fluid tissue types, using the Diffeomorphic Anatomical Registration through Exponentiated Lie algebra algorithm (DARTEL) toolbox [23], and created flow fields and template images. The flow fields and final template images were normalized to Montreal Neurological Institute (MNI) space (unmodulated, re-sliced to 1×1×1 mm 3 ) and smoothed with a Gaussian filter (8 mm kernel). Calculation of T2-relaxation: Using PD and T2-weighted images, whole-brain pixel-by-pixel T2-relaxation values were calculated [18, 24]. We calculated the average noise level outside the brain tissue from PD- and T2-weighted images, and was used as a noise threshold to exclude non-brain areas. The same noise threshold was used for the PD and T2-weighted images in all subjects. The following equation was used to calculate T2-relaxation values [18, 24, 25] where TE 1 and TE 2 are the echo-times for PD and T2-weighted images, and SI 1 , SI 2 denote PD and T2-weighted images signal intensities, respectively. Whole-brain T2-relaxation maps were generated from each voxel value. T2-relaxation maps were normalized to the standard MNI space and smoothed using a Gaussian filter (8 mm). Statistical Analyses We used the statistical package for social sciences (SPSS® v26) for data analyses. The independent samples t-tests were used to examine the demographic and clinical characteristics with continuous variables, and the Chi-square tests to assess categorical variables between CF and control subjects. The MoCA, BDI-II, and BAI scores were examined with analysis of covariance (ANCOVA; covariates; age and sex). A p value < 0.05 was considered statistically- significant. We performed whole-brain voxel-based analyses procedures to examine regional brain changes between CF and control subjects. For assessment of regional brain GM density and tissue changes, the normalized and smoothed whole-brain GM density and T2-relaxation maps were compared voxel-by-voxel between groups using ANCOVA, with age and sex as covariates [SPM12; p < 0.001; uncorrected; minimum extended cluster size, 10 voxels]. The extended cluster size 10 was chosen to avoid brain sites with less than 10 voxels appearing as a cluster. Brain clusters with significant GM density and T2-relaxation value differences between CF and control subjects were overlaid onto the normalized mean anatomical images for structural identification. Regional brain GM density and T2-relaxation values were calculated from region of interest (ROI) analyses and examined for significant magnitude differences between CF and control subjects. Results Subject Characteristics Demographic and clinical variables of CF and control subjects are summarized in Table 1 . No significant difference in age (p = 0.08), sex (p = 0.79), or body mass index (p = 0.33) appeared between the groups. Table 1 Demographics and other variables of CF and control subjects. Variables CF (n = 5) Mean ± SD Controls (n = 15) Mean ± SD P-values Age (years) 29.7 ± 3.7 33.9 ± 4.5 0.08 Sex [male] (%) 3 (60%) 10 (67%) 0.79 BMI (kg/m 2 , mean ± SD) 22.0 ± 0.8 23.8 ± 3.9 0.33 BAI 7.8 ± 4.4 1.7 ± 4.2 0.02 BDI-II 5.0 ± 3.0 1.3 ± 2.8 0.03 Total MoCA scores MoCA: Visuospatial MoCA: Naming MoCA: Attention MoCA: Language MoCA: Abstraction MoCA: Delayed Recall MoCA: Orientation 26.5 ± 1.5 4.1 ± 0.6 3.0 ± 0.0 5.9 ± 0.8 2.4 ± 0.5 1.6 ± 0.5 4.1 ± 1.0 5.7 ± 0.4 28.2 ± 1.4 4.8 ± 0.5 3.0 ± 0.0 5.5 ± 0.8 2.8 ± 0.4 2.0 ± 0.4 4.2 ± 1.0 5.9 ± 0.3 0.04 0.02 - 0.34 0.17 0.13 0.85 0.30 SD = standard deviation; BMI = body mass index; BDI-II = Beck depression inventory II; BAI= Beck anxiety inventory; MoCA= Montreal cognitive assessment. Mood and Cognitive Scores The BDI-II and BAI scores were significantly higher in CF over control subjects (Table 1 ). The total MoCA scores were significantly lower in CF as compared to control subjects (p = 0.04), and the visuospatial was the most affected sub-scale (p = 0.02). Regional GM density changes After controlling for age and sex, several brain areas showed increased GM density in CF subjects compared to healthy controls (Table 2 ). Very few sites emerged with significantly low GM density in CF compared to control subjects. Brain regions with increased GM density in CF subjects emerged in the right cerebellum, hippocampus, amygdala, parahippocampal gyrus, ventral medial prefrontal cortices, superior temporal cortices, bilateral basal forebrain, insula, parietal cortices, left mid and superior frontal, and prefrontal cortices, compared to controls (Fig. 1). Brain regions showing decreased GM density in CF patients emerged in the right inferior temporal cortices and bilateral occipital cortices. Table 2 Regional brain gray matter density (mean ± SD, mm 3 /voxel) of CF patients and control corrected for age and sex. Brain areas CF (n = 5) Mean ± SD Controls (n = 15) Mean ± SD P-values Left Prefrontal Cortex 0.44 ± 0.03 0.38 ± 0.03 0.001 Right Prefrontal Cortex 0.47 ± 0.03 0.41 ± 0.03 0.001 Right Ventral Med Prefrontal Cortex 0.57 ± 0.03 0.52 ± 0.03 0.002 Left Basal Forebrain 0.49 ± 0.02 0.44 ± 0.02 < 0.001 Right Basal Forebrain 0.45 ± 0.03 0.39 ± 0.03 0.001 Right Amygdala 0.38 ± 0.02 0.34 ± 0.02 0.001 Right Hippocampus 0.71 ± 0.01 0.68 ± 0.01 0.002 Right Parahippocampus 0.59 ± 0.02 0.55 ± 0.01 < 0.001 Right Cerebellar Cortex 0.75 ± 0.02 0.70 ± 0.02 0.001 Left Insula 0.63 ± 0.03 0.56 ± 0.03 0.001 Right Insula 0.61 ± 0.03 0.55 ± 0.03 0.001 Left Mid Frontal Cortex 0.60 ± 0.02 0.55 ± 0.01 < 0.001 Left Sup Frontal Cortex 0.62 ± 0.02 0.57 ± 0.02 0.001 Left Sup Parietal Cortex 0.69 ± 0.04 0.61 ± 0.04 0.002 Right Sup Parietal Cortex 0.59 ± 0.04 0.51 ± 0.03 0.001 Right Sup Temporal Cortex 0.67 ± 0.02 0.63 ± 0.02 0.001 CF = Cystic Fibrosis; SD = Standard deviation; Med = Medial; Mid = Middle; Sup = Superior. Brain regions with T2-relaxation value differences Several brain areas in CF participants showed significantly lower T2-relaxation values, indicating acute tissue injury, compared to control subjects (Table 3 ). Few brain sites showed significantly higher T2-relaxation values in CF compared to controls. Regions with significantly reduced T2-relaxation values in CF participants appeared in the bilateral cerebellum, cerebellar tonsil, prefrontal and superior temporal cortices, parietal cortices, left frontal cortices, and right insula (Fig. 2). Other sites, including white matter areas, were also detected with reduced T2-relaxation values in CF over controls in regions that link important gray matter regions associated with cognition, anxiety, and depression, including frontal white matter, corpus callosum, and medulla (Fig. 2). Brain regions showing prolonged T2-relaxation values in CF emerged in the bilateral hippocampus and left para-hippocampal gyrus. Table 3 Regional brain T2-relaxation values (mean ± SD, ms) of CF patients and control corrected for age and sex. Brain areas CF (n = 5) Mean ± SD Controls (n = 15) Mean ± SD P-values Left Prefrontal Cortex 139.5 ± 7.3 162.5 ± 6.9 < 0.001 Right Prefrontal Cortex 162.6 ± 17.3 199.2 ± 16.5 0.001 Left Cerebellum 123.6 ± 9.6 149.3 ± 9.1 < 0.001 Right Cerebellum 123.3 ± 5.4 136.0 ± 5.2 < 0.001 Left Cerebellar Tonsil 126.9 ± 10.8 160.8 ± 10.3 < 0.001 Right Cerebellar Tonsil 127.5 ± 11.4 159.1 ± 10.9 < 0.001 Right Insula 157.6 ± 12.2 182.7 ± 11.6 0.001 Brainstem 138.1 ± 14.5 168.2 ± 13.8 0.001 Left Frontal Cortex 133.8 ± 7.3 155.4 ± 7.0 < 0.001 Left Parietal Cortex 152.4 ± 13.9 182.6 ± 13.3 0.001 Right Parietal Cortex 128.0 ± 10.2 148.9 ± 9.7 0.001 Left Sup Temporal Cortex 142.6 ± 10.8 166.0 ± 10.3 0.001 Right Sup Temporal Cortex 132.1 ± 7.1 153.6 ± 6.8 < 0.001 Corpus Callosum 121.3 ± 15.8 154.5 ± 15.0 0.001 Left Frontal White Matter 119.7 ± 5.3 134.2 ± 5.0 < 0.001 CF = Cystic Fibrosis; ms = millisecond; SD = Standard deviation; Sup = Superior. Discussion People with chronic diseases, such as CF, are at increased risk of depression and autonomic deficits. In addition, many aspects of the disease itself can lead to high levels of anxiety. We report significantly high scores of BAI and BDI-II in CF patients over healthy controls, consistent with previous studies [26, 27]. Also, we found that CF patients had a lower overall MoCA scores and this change was most significant in the visuospatial/executive sub domains. Several brain sites, including cerebellum, hippocampus, amygdala, insula, prefrontal, and temporal sites showed tissue changes based on GM density or T2-relaxometry procedures, areas that are involved in cognition, mood, and autonomic functions. Neuronal damage meditated through hypoxia and/or hypercapnia is considered to be one of the key mechanisms in pulmonary diseases [28, 29]. Both hypoxia and hypercapnia are often present in CF patients along with mutated CFTR gene and are potential underlying causes for the observed neural findings. CF patients showed cognitive dysfunction, including the executive function, and mood deficits. Executive function is associated with skills requiring higher mental activities, such as setting goals, abstract logical thinking, planning, taking into account the long-term consequences, initiating intentional actions, creating different possible alternative reactions, or modifying own activity in response to changing conditions. Abnormal executive function has been found in other diseases with respiratory compromise, such as chronic obstructive pulmonary disease, asthma, obstructive sleep apnea [30–32], and abnormal function in CF patients may contribute to such diminished actions. Depression and anxiety, as observed in our study, affects disease management, including clinic attendance and adherence to prescribed treatments, leading to increased hospitalization and healthcare costs, worse pulmonary function, and decreased health-related quality of life [27, 33–35]. These findings reiterate the need for annual screening for depression and anxiety in patient with CF. Although cognitive and mood symptoms are considered to be due to aspects surrounding the diagnosis of the disease, our findings show that CF patients have a brain structural basis for these symptoms. CF patients showed increased GM density and reduced T2-relaxation values in several brain areas, though GM density measures indicated more changes over T2-relaxometry. Such particular brain tissue changes were evident in the cerebellum, hippocampus, amygdala, superior temporal cortices, basal forebrain, insula, parietal cortices, and frontal and prefrontal cortices. The increased GM density or reduced T2-relaxation values in our patient population might be due to increased neuronal and axonal swelling (although the disease is chronic, the condition is associated with ongoing hypoxia), increased size neurons, increased glial cell size or number, higher vascular density to support sustained increased metabolic demand, more connective tissue, dendritic outgrowth, or synaptogenesis [36, 37]. Higher neuronal numbers may result from an abnormal developmental process, including accentuated neuronal birth rate or the survival of excess neurons [36]. In addition, the elevated GM density may be related to pre-apoptotic osmotic changes or hypertrophy, marking areas of early neuronal deficits. Previous depression studies indicated increased glucose metabolism [38, 39] resulting from the inhibition of reciprocal connections between the prefrontal cortex and the amygdala in limbic-thalamic-cortical circuit or limbic-cortical-striatal-pallidal-thalamic circuit enlarging amygdala [37, 40], and such processing may be operating in other structures as observed here. The hippocampus, prefrontal cortices, and amygdala regions are highly interconnected and constitute the neuroanatomical network for mood regulation [40, 41], and these areas showed increased GM density or altered T2-relaxation values in our study. Activation of the amygdala has been demonstrated to increase dopamine in the nucleus accumbens and other motor control centers, resulting in increased fear behaviors and anxiety and might be plausible explanation for higher anxiety in CF patients. The amygdala and hippocampus have projections from the prefrontal cortices and other limbic-related forebrain structures that are involved in several cognitive domains, and increased GM volume or altered T2-relaxation values in these sites, as found in our study, may suggest abnormal cognition. The superior temporal gyrus has connections to limbic and prefrontal regions [42], and right superior temporal structures in particular have been associated with responses to emotional prosody [43]. The superior temporal lobe along with insula and cingulate regions form a part of the salience network that is involved in the coordination of the behavioral responses. The anterior insula displays altered functional connectivity within the salience network and with other brain network in depression condition. Another brain region that showed increased GM density and tissue changes was cerebellum, where climbing fiber codes error signal reflecting the motor performance failure and works to depress the synaptic transmission between parallel fibers and Purkinje cell that can lead to depression and autonomic deficits [44, 45]. Furthermore, the cerebellum contributes to cognitive processing in several cognitive domains, including executive and visuospatial functioning and extensively interconnected with the cerebral hemisphere, both in feed-forward and feed-backward directions, and provides a structural basis for cognitive deficits in CF patients. Patients with CF experience a wide spectrum of chronic pain, including headache, chest pain, back pain, abdominal pain, and limb pain [46]. Brain regions that showed increased GM density or altered T2-relaxation values, including the insula and hippocampus, are subjected to pain modulation and stress-induced changes [47, 48]. Stress can lead to microglial proliferation in areas around the third ventricle, including hippocampus, and activate microglia that can cause neuronal damage with the release of proinflammatory and cytotoxic factors and plausibly increase GM density or alter T2-relaxation values as observed in our study. Several brain areas showed reduced T2-relaxation values in CF patients which could result from increased astrocyte and microglial activation due to chronic pain. Earlier human postmortem studies reported reduced T2-relaxation values due to pronounced reactive microgliosis and astrogliosis [9], and showed the association between chronic pain and prolonged astrocyte activation at the level of the primary afferent synapse [49, 50]. Multiple diseases have demonstrated altered GM and white matter volume and tissue integrity [10–12, 51, 52]. However, this is the first study that shows significant brain structural (GM density and brain tissue integrity) changes in CF patients, which could account for the symptomatology reported in the condition. Several basic and clinical studies, particularly those using neuroimaging techniques, report that specific brain regions play essential roles in cognitive, autonomic, depression, and anxiety regulation [51, 52]. The altered brain regions we encountered in CF patients have a considerably important role in their cognitive and mood wellbeing. With a high incidence of psychological symptoms in adult CF patients, this study highlights the importance for improved early identification and management strategies for adult CF patients. One of the limitations of this study is the small sample size that may affect the statistical analyses with findings not corrected for multiple comparisons, and may limit the magnitude of the significant alterations, as well as with type 1 error that we observed in various brain regions of CF patients. Also, T2-relaxometry procedures had poor resolution in slice thickness direction, resulting to less sites with damage over GM density measures. Thus, procedures with higher resolution would be required with bigger sample size to examine extend of tissue damage. We used MoCA, BDI-II, and BAI screening instruments to identify cognitive impairment and symptoms of depression and anxiety, combined with comprehensive clinical tests should be used for future studies. Conclusions Patient with CF showed significant brain structural changes, as evidenced by altered GM density or T2 relaxation values, indicative of tissue injury, in brain regions that control cognitive, autonomic, and mood functions. These sites included the cerebellum, hippocampus, amygdala, superior temporal cortices, basal forebrain, insula, parietal cortices, frontal and prefrontal cortices, and corpus callosum. In addition, CF patients exhibited significant anxiety and depression symptoms and impaired cognitive abilities, and brain regions regulating such functions showed altered brain structural integrity. Integration of mental health screening and early identification and targeted treatment of CF patients can improve the mortality and morbidity seen in the condition. Declarations Ethics approval and consent to participate We included statements on ethics approval and consent from participants and provided the name of the ethics committee that approved the study. Consent for publication Not applicable Availability of data and material The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests . Funding This work was supported by National Institutes of Health grants (K23GM132795 to SV; R21 AG070269 to BR, SV, and RK). Authors' contributions BR collected, analyzed and interpreted the patient data, performed statistical analyses, and wrote the manuscript; MSW and RK designed the study, collected the patient data and was a major contributor in writing the manuscript; SV and PE, interpreted the patient data and was a major contributor in writing the manuscript; APR collected the patient data and contributed in writing the manuscript. All authors read and approved the final manuscript. Acknowledgments The authors would like to thank Mr. Luke Ehlert for help in data collection. 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Decreased survival in cystic fibrosis patients with a positive screen for depression. J Cyst Fibros. 2021;20:120-6. Yohannes AM, Willgoss TG, Fatoye FA, Dip MD, Webb K. Relationship between anxiety, depression, and quality of life in adult patients with cystic fibrosis. Respir Care. 2012;57:550-6. Row BW. Intermittent hypoxia and cognitive function: implications from chronic animal models. Adv Exp Med Biol. 2007;618:51-67. Zheng GQ, Wang Y, Wang XT. Chronic hypoxia-hypercapnia influences cognitive function: a possible new model of cognitive dysfunction in chronic obstructive pulmonary disease. Med Hypotheses. 2008;71:111-3. Dodd JW. Lung disease as a determinant of cognitive decline and dementia. Alzheimers Res Ther. 2015;7:32. Crews WD, Jefferson AL, Bolduc T, Elliott JB, Ferro NM, Broshek DK, et al. Neuropsychological dysfunction in patients suffering from end-stage chronic obstructive pulmonary disease. Arch Clin Neuropsychol. 2001;16:643-52. Dodd JW, Getov SV, Jones PW. Cognitive function in COPD. The European respiratory journal. 2010;35:913-22. Smith BA, Modi AC, Quittner AL, Wood BL. Depressive symptoms in children with cystic fibrosis and parents and its effects on adherence to airway clearance. Pediatric pulmonology. 2010;45:756-63. Snell C, Fernandes S, Bujoreanu IS, Garcia G. Depression, illness severity, and healthcare utilization in cystic fibrosis. Pediatric pulmonology. 2014;49:1177-81. Riekert KA, Bartlett SJ, Boyle MP, Krishnan JA, Rand CS. The association between depression, lung function, and health-related quality of life among adults with cystic fibrosis. Chest. 2007;132:231-7. Young KA, Holcomb LA, Yazdani U, Hicks PB, German DC. Elevated neuron number in the limbic thalamus in major depression. Am J Psychiatry. 2004;161:1270-7. Frodl T, Meisenzahl E, Zetzsche T, Bottlender R, Born C, Groll C, et al. Enlargement of the amygdala in patients with a first episode of major depression. Biol Psychiatry. 2002;51:708-14. Drevets WC, Videen TO, Price JL, Preskorn SH, Carmichael ST, Raichle ME. A functional anatomical study of unipolar depression. J Neurosci. 1992;12:3628-41. Ho AP, Gillin JC, Buchsbaum MS, Wu JC, Abel L, Bunney WE, Jr. Brain glucose metabolism during non-rapid eye movement sleep in major depression. A positron emission tomography study. Arch Gen Psychiatry. 1996;53:645-52. Soares JC, Mann JJ. The anatomy of mood disorders--review of structural neuroimaging studies. Biol Psychiatry. 1997;41:86-106. Drevets WC. Functional anatomical abnormalities in limbic and prefrontal cortical structures in major depression. Prog Brain Res. 2000;126:413-31. Pandya DN. Anatomy of the auditory cortex. Revue neurologique. 1995;151:486-94. Mitchell RL, Elliott R, Barry M, Cruttenden A, Woodruff PW. Neural response to emotional prosody in schizophrenia and in bipolar affective disorder. The British journal of psychiatry. 2004;184:223-30. Hirano T. Long-term depression and other synaptic plasticity in the cerebellum. Proc Jpn Acad Ser B Phys Biol Sci. 2013;89:183-95. Miura M, Reis DJ. Cerebellum: a pressor response elicited from the fastigial nucleus and its efferent pathway in brainstem. Brain research. 1969;13:595-9. Ravilly S, Robinson W, Suresh S, Wohl ME, Berde CB. Chronic pain in cystic fibrosis. Pediatrics. 1996;98:741-7. Joels M, Krugers H, Karst H. Stress-induced changes in hippocampal function. Prog Brain Res. 2008;167:3-15. McEwen BS. Effects of adverse experiences for brain structure and function. Biol Psychiatry. 2000;48:721-31. Okada-Ogawa A, Suzuki I, Sessle BJ, Chiang CY, Salter MW, Dostrovsky JO, et al. Astroglia in medullary dorsal horn (trigeminal spinal subnucleus caudalis) are involved in trigeminal neuropathic pain mechanisms. J Neurosci. 2009;29:11161-71. Shi Y, Gelman BB, Lisinicchia JG, Tang SJ. Chronic-pain-associated astrocytic reaction in the spinal cord dorsal horn of human immunodeficiency virus-infected patients. J Neurosci. 2012;32:10833-40. Roy B, Ehlert L, Mullur R, Freeby MJ, Woo MA, Kumar R, et al. Regional Brain Gray Matter Changes in Patients with Type 2 Diabetes Mellitus. Scientific reports. 2020;10:9925. Pike NA, Roy B, Gupta R, Singh S, Woo MA, Halnon NJ, et al. Brain abnormalities in cognition, anxiety, and depression regulatory regions in adolescents with single ventricle heart disease. Journal of neuroscience research. 2018;96:1104-18. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-769615","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":44131843,"identity":"f12c0435-05cc-4b90-9cba-705f5eaf6560","order_by":0,"name":"Bhaswati Roy","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Bhaswati","middleName":"","lastName":"Roy","suffix":""},{"id":44131844,"identity":"044ffe20-380b-4d3c-946f-4b365e95d850","order_by":1,"name":"Marlyn S. Woo","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marlyn","middleName":"S.","lastName":"Woo","suffix":""},{"id":44131845,"identity":"cd24efc3-a193-4656-b351-32017d8e7b24","order_by":2,"name":"Susana Vacas","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Susana","middleName":"","lastName":"Vacas","suffix":""},{"id":44131846,"identity":"40fa36c8-e22a-46e5-b6f1-2886350f206b","order_by":3,"name":"Patricia Eshaghian","email":"","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Patricia","middleName":"","lastName":"Eshaghian","suffix":""},{"id":44131847,"identity":"85bcbe33-0b3c-4641-a77a-3747ab5262cb","order_by":4,"name":"Adupa P. Rao","email":"","orcid":"","institution":"University of Southern California Keck School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Adupa","middleName":"P.","lastName":"Rao","suffix":""},{"id":44131848,"identity":"3a06defb-5b41-47ca-84d6-1c3060da7fb4","order_by":5,"name":"Rajesh Kumar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7ElEQVRIiWNgGAWjYDACHjBpA8QJEAE+hCheLWkQLQeAFBuRWg6ToMW854zphp97zkfzs+cefPyB4bA8G/sBxgdv23BrkTnbY3az59nt3Jk975INDjAcNmzjSWA2nItHiwQ/j9kNngO3czfcyDGTAGpJYGNIYJPmJaDl5p8D53L338gx/wHWwv+A/TdeLbw9Zrd5DhzI3SCRY8YA1iKRwMaMVwvPsbLbMgeSc2eceWMsccYg3bBN4mGz5Jxz+LQkb7v55oBdbn97juGHigpreX7+5IMf3pTh1oIGDEAEYwPR6kfBKBgFo2AUYAcAJh9RfuI88G4AAAAASUVORK5CYII=","orcid":"","institution":"University of California Los Angeles","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Rajesh","middleName":"","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2021-07-31 06:55:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-769615/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-769615/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":12258039,"identity":"2653cc37-0561-4efd-9d0b-375567ca11c0","added_by":"auto","created_at":"2021-08-09 18:01:07","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":874681,"visible":true,"origin":"","legend":"Regional GM density changes","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-769615/v1/1e5a6c436eb589aa8bc826b7.jpg"},{"id":12258040,"identity":"fe665411-d2e1-48f5-a285-4c0d7821c2db","added_by":"auto","created_at":"2021-08-09 18:01:07","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":845327,"visible":true,"origin":"","legend":"Brain regions with T2-relaxation value differences","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-769615/v1/1e180afa0a7142e07e57e2d7.jpg"},{"id":13708439,"identity":"793cf1db-9692-4905-9e18-25ce3668369d","added_by":"auto","created_at":"2021-09-17 14:07:46","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":739386,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-769615/v1/b29cae31-37ee-4600-b317-a0972e99d765.pdf"}],"financialInterests":"","formattedTitle":"Regional Brain Tissue Changes in Patients with Cystic Fibrosis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCystic fibrosis (CF) is a progressive genetic disorder predominately affecting lungs, liver, and the pancreas and intestine exocrine glands. Approximately 1,000 new CF cases are diagnosed each year, totaling more than 30,000 people in the United States and 70,000 worldwide. CF is caused by mutations in the CF transmembrane conductance regulator (CFTR) gene, and broadly classified into I-VI classes based on their effects on the CFTR protein [1, 2]. Symptoms include poor weight gain/growth, persistent cough, shortness of breath, and repeated lung infections. In addition, CF patients with clinically stable severe lung disease show impaired neurocognitive functions, including cognitive and mood deficits, autonomic issues, and daytime sleepiness [3], and disease exacerbation further worsens their neurobehavioral performance [4]. High rates of anxiety and depression found in CF lead to non-adherence of prescribed treatment, affecting health outcomes and health related quality of life [5]. Such psychological, including mood and cognitive functions, and autonomic deficits [6, 7] might result from tissue dysfunction in multiple brain regions; however, there are no previous studies examining brain changes in CF patients.\u003c/p\u003e \u003cp\u003eSubtle brain tissue changes are often challenging to visualize on routine brain magnetic resonance imaging (MRI), including T1-weighted and T2-weighted imaging. High-resolution T1-weighted imaging based voxel-based morphometry (VBM), and T2-relaxometry based on proton density (PD)- and T2-weighted imaging can be used to examine subtle brain tissue changes. VBM procedures can exhibit localized gray matter (GM) density that reflects the proportion of GM relative to other tissue types within an examined region. However, T2-relaxometry measures free-water content within the tissue [8] by acquiring a series of images at different echo times, and has the potential to detect brain tissue microstructural changes, with higher specificity than conventional MRI. Immuno-histochemical evidence shows that decreased T2-relaxation values are associated with increased glial activation [9], and reduced T2-relaxation values emerged in bipolar disorder [10, 11], and spinocerebellar ataxia type 3 [12]. In addition, the main etiologies of increased T2-relaxation values in the brain are vasogenic edema, demyelination, gliosis, or neuronal loss [13\u0026ndash;15], observed in tumor [16], chronic epilepsy [17], congenital central hypoventilation syndrome [18], traumatic brain injury [19], and multiple sclerosis [13]. Such MRI techniques are simple and rapid, utilizes data acquired from routine T1-weighted, proton-density, and T2-weighted imaging, and can be implemented on standard clinical MR systems, and the quantitative measures make them advantageous in examining brain tissue integrity.\u003c/p\u003e \u003cp\u003eAverage survival of CF patients has improved recently, and this improvement is due to the advancement in treatment, emphasis on early diagnosis, as well as effective differential disease management, though there is still no cure for the disease. In order to increase the life span and life quality of CF individuals, detection of brain changes are of utmost importance. Identifying the structural brain changes associated with cognitive and mood deficits in CF patients may provide new insights into healthcare management and long-term clinical strategies.\u003c/p\u003e \u003cp\u003e Our study aimed to examine regional GM density changes, as well as tissue changes using T2-relaxometry procedures in CF patients over healthy controls. Based on the severity of psychological and autonomic changes exhibited in CF patients, we hypothesized that GM density and T2-relaxation values would differ from healthy population, indicating brain damage, in autonomic, mood, and cognition control areas.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eSubjects\u003c/h2\u003e\n \u003cp\u003eThis is a cross-sectional, comparative study of five CF patients recruited from the University of California Los Angeles (UCLA) Adult Cystic Fibrosis Center and 15 control subjects recruited through advertisements at the UCLA campus and Los Angeles area. All study procedures were followed in accordance with institutional guidelines, and the study was approved by the UCLA Institutional Review Board. Subjects were fully informed about the study procedures and provided written informed consent prior to data collection. CF patients were confirmed for CF genotype, were with mutation class I-III, and had mild to moderate CF lung disease. None of the CF patient underwent lung transplant, were not on any steroid therapy, and their oxygen saturation at rest was \u0026gt;\u0026thinsp;94% on room air. CF patients with history of stroke, seizure disorder, or head trauma, diagnosed psychiatric disease (clinical depression, schizophrenia, manic-depressive), airway or chest deformities that would interfere with breathing were excluded from the study. Control subjects were healthy, with no sleep disturbances, neurological or cardiovascular issues that would introduce brain damage, or drug dependency that would modify brain tissue.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eAssessment of Depression and Anxiety\u003c/h2\u003e\n \u003cp\u003eAll CF and control subjects were assessed for anxiety and depression using the Beck anxiety inventory (BAI) and the Beck depression inventory (BDI-II), respectively [20, 21]. The BAI and BDI-II inventories are self-administered questionnaires, composed of 21 multiple-choice questions (each question score ranged 0\u0026ndash;3), with total scores ranging from 0\u0026ndash;63 based on symptom severity [20, 21].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eCognition Examination\u003c/h2\u003e\n \u003cp\u003eCF and control subjects underwent for cognition evaluation using the Montreal Cognitive Assessment (MoCA) [22]. The MoCA test was used for rapid evaluation of various cognitive domains, including attention and concentration, executive functions, memory, language, visuo-constructional skills, conceptual thinking, calculations, and orientation. A score\u0026thinsp;\u0026lt;\u0026thinsp;26 was considered abnormal [22].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eMagnetic Resonance Imaging\u003c/h2\u003e\n \u003cp\u003eAll brain imaging studies were performed in a 3.0-Tesla MR scanner (Magnetom Tim-Trio and Prisma Fit, Siemens, Erlangen, Germany). We used foam pads on either side of the head to minimize head motion. Proton density (PD) and T2-weighted images were acquired using a dual-echo turbo spin-echo sequence in the axial plane [repetition time (TR)\u0026thinsp;=\u0026thinsp;10,000 ms; echo-time (TE1, TE2)\u0026thinsp;=\u0026thinsp;12, 123/124 ms; flip angle (FA)\u0026thinsp;=\u0026thinsp;130\u0026deg;; matrix size\u0026thinsp;=\u0026thinsp;256\u0026sdot;256; field-of-view (FOV)\u0026thinsp;=\u0026thinsp;230\u0026sdot;230 mm; slice thickness\u0026thinsp;=\u0026thinsp;3.5 mm; inter-slice gap\u0026thinsp;=\u0026thinsp;no]. Two high-resolution T1-weighted images were collected using a magnetization prepared rapid acquisition gradient-echo (MPRAGE) sequence (TR\u0026thinsp;=\u0026thinsp;2200 ms; TE\u0026thinsp;=\u0026thinsp;2.3/2.4 ms; inversion time\u0026thinsp;=\u0026thinsp;900 ms; FA\u0026thinsp;=\u0026thinsp;9\u0026deg;; matrix size\u0026thinsp;=\u0026thinsp;320\u0026sdot;320; FOV\u0026thinsp;=\u0026thinsp;230\u0026sdot;230 mm; slice thickness\u0026thinsp;=\u0026thinsp;0.9 mm; number of slices\u0026thinsp;=\u0026thinsp;192).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eData Processing\u003c/h2\u003e\n \u003cp\u003eWe used the statistical parametric mapping package SPM12 (Wellcome Department of Cognitive Neurology, UK; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.fil.ion.ucl.ac.uk/spm/\u003c/span\u003e\u003c/span\u003e), and MATLAB-based (The MathWorks Inc, Natick, MA) custom software to process MRI data. Also, we used the MRIcroN software to visualize images.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eVisual examination:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eHigh-resolution T1-weighted, PD-weighted, and T2-weighted images of CF and control subjects were examined for any visible brain changes, including cystic lesions, infarcts, tumors, or other types of brain lesions. All images were also assessed for motion-related or any other imaging artifacts before GM density and T2-relaxation calculations.\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCalculation of GM density:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eBoth high-resolution T1-weighted image series were realigned to remove any potential variations between scans, and averaged to improve signal-to-noise ratio. The averaged images were segmented into GM, white matter, and cerebrospinal fluid tissue types, using the Diffeomorphic Anatomical Registration through Exponentiated Lie algebra algorithm (DARTEL) toolbox [23], and created flow fields and template images. The flow fields and final template images were normalized to Montreal Neurological Institute (MNI) space (unmodulated, re-sliced to 1\u0026times;1\u0026times;1 mm\u003csup\u003e3\u003c/sup\u003e) and smoothed with a Gaussian filter (8 mm kernel).\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCalculation of T2-relaxation:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eUsing PD and T2-weighted images, whole-brain pixel-by-pixel T2-relaxation values were calculated [18, 24]. We calculated the average noise level outside the brain tissue from PD- and T2-weighted images, and was used as a noise threshold to exclude non-brain areas. The same noise threshold was used for the PD and T2-weighted images in all subjects. The following equation was used to calculate T2-relaxation values [18, 24, 25]\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58893_b39df98f09c4a4bb/58893_custom_files/img1628518027.png\"\u003e\u003c/p\u003e\n \u003cp\u003ewhere TE\u003csub\u003e1\u003c/sub\u003e and TE\u003csub\u003e2\u003c/sub\u003e are the echo-times for PD and T2-weighted images, and SI\u003csub\u003e1\u003c/sub\u003e, SI\u003csub\u003e2\u003c/sub\u003e denote PD and T2-weighted images signal intensities, respectively. Whole-brain T2-relaxation maps were generated from each voxel value. T2-relaxation maps were normalized to the standard MNI space and smoothed using a Gaussian filter (8 mm).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eStatistical Analyses\u003c/h2\u003e\n \u003cp\u003eWe used the statistical package for social sciences (SPSS\u0026reg; v26) for data analyses. The independent samples t-tests were used to examine the demographic and clinical characteristics with continuous variables, and the Chi-square tests to assess categorical variables between CF and control subjects. The MoCA, BDI-II, and BAI scores were examined with analysis of covariance (ANCOVA; covariates; age and sex). A p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically- significant.\u003c/p\u003e\n \u003cp\u003eWe performed whole-brain voxel-based analyses procedures to examine regional brain changes between CF and control subjects. For assessment of regional brain GM density and tissue changes, the normalized and smoothed whole-brain GM density and T2-relaxation maps were compared voxel-by-voxel between groups using ANCOVA, with age and sex as covariates [SPM12; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; uncorrected; minimum extended cluster size, 10 voxels]. The extended cluster size 10 was chosen to avoid brain sites with less than 10 voxels appearing as a cluster. Brain clusters with significant GM density and T2-relaxation value differences between CF and control subjects were overlaid onto the normalized mean anatomical images for structural identification.\u003c/p\u003e\n \u003cp\u003eRegional brain GM density and T2-relaxation values were calculated from region of interest (ROI) analyses and examined for significant magnitude differences between CF and control subjects.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eSubject Characteristics\u003c/h2\u003e\n \u003cp\u003eDemographic and clinical variables of CF and control subjects are summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. No significant difference in age (p\u0026thinsp;=\u0026thinsp;0.08), sex (p\u0026thinsp;=\u0026thinsp;0.79), or body mass index (p\u0026thinsp;=\u0026thinsp;0.33) appeared between the groups.\u003c/p\u003e\n \u003ctable border=\"1\" width=\"0\"\u003e\n \u003ccaption\u003e\n \u003cp\u003eTable 1\u003c/p\u003e\n \u003cp\u003eDemographics and other variables of CF and control subjects.\u003c/p\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"252\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"138\"\u003e\n \u003cp\u003e\u003cstrong\u003eCF (n = 5)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"144\"\u003e\n \u003cp\u003e\u003cstrong\u003eControls (n = 15)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-values\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"252\"\u003e\n \u003cp\u003eAge (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"138\"\u003e\n \u003cp\u003e29.7 \u0026plusmn; 3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"144\"\u003e\n \u003cp\u003e33.9 \u0026plusmn; 4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"252\"\u003e\n \u003cp\u003eSex [male] (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"138\"\u003e\n \u003cp\u003e3 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"144\"\u003e\n \u003cp\u003e10 (67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"252\"\u003e\n \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e, mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"138\"\u003e\n \u003cp\u003e22.0 \u0026plusmn; 0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"144\"\u003e\n \u003cp\u003e23.8 \u0026plusmn; 3.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"252\"\u003e\n \u003cp\u003eBAI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"138\"\u003e\n \u003cp\u003e7.8 \u0026plusmn; 4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"144\"\u003e\n \u003cp\u003e1.7 \u0026plusmn; 4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"252\"\u003e\n \u003cp\u003eBDI-II\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"138\"\u003e\n \u003cp\u003e5.0 \u0026plusmn; 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"144\"\u003e\n \u003cp\u003e1.3 \u0026plusmn; 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"252\"\u003e\n \u003cp\u003eTotal MoCA scores\u003c/p\u003e\n \u003cp\u003eMoCA: Visuospatial\u003c/p\u003e\n \u003cp\u003eMoCA: Naming\u003c/p\u003e\n \u003cp\u003eMoCA: Attention\u003c/p\u003e\n \u003cp\u003eMoCA: Language\u003c/p\u003e\n \u003cp\u003eMoCA: Abstraction\u003c/p\u003e\n \u003cp\u003eMoCA: Delayed Recall\u003c/p\u003e\n \u003cp\u003eMoCA: Orientation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"138\"\u003e\n \u003cp\u003e26.5 \u0026plusmn; 1.5\u003c/p\u003e\n \u003cp\u003e4.1 \u0026plusmn; 0.6\u003c/p\u003e\n \u003cp\u003e3.0 \u0026plusmn; 0.0\u003c/p\u003e\n \u003cp\u003e5.9 \u0026plusmn; 0.8\u003c/p\u003e\n \u003cp\u003e2.4 \u0026plusmn; 0.5\u003c/p\u003e\n \u003cp\u003e1.6 \u0026plusmn; 0.5\u003c/p\u003e\n \u003cp\u003e4.1 \u0026plusmn; 1.0\u003c/p\u003e\n \u003cp\u003e5.7 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"144\"\u003e\n \u003cp\u003e28.2 \u0026plusmn; 1.4\u003c/p\u003e\n \u003cp\u003e4.8 \u0026plusmn; 0.5\u003c/p\u003e\n \u003cp\u003e3.0 \u0026plusmn; 0.0\u003c/p\u003e\n \u003cp\u003e5.5 \u0026plusmn; 0.8\u003c/p\u003e\n \u003cp\u003e2.8 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e2.0 \u0026plusmn; 0.4\u003c/p\u003e\n \u003cp\u003e4.2 \u0026plusmn; 1.0\u003c/p\u003e\n \u003cp\u003e5.9 \u0026plusmn; 0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"102\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eSD = standard deviation; BMI = body mass index; BDI-II = Beck depression inventory II; BAI= Beck anxiety inventory; MoCA= Montreal cognitive assessment.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eMood and Cognitive Scores\u003c/h2\u003e\n \u003cp\u003eThe BDI-II and BAI scores were significantly higher in CF over control subjects (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The total MoCA scores were significantly lower in CF as compared to control subjects (p\u0026thinsp;=\u0026thinsp;0.04), and the visuospatial was the most affected sub-scale (p\u0026thinsp;=\u0026thinsp;0.02).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003eRegional GM density changes\u003c/h2\u003e\n \u003cp\u003eAfter controlling for age and sex, several brain areas showed increased GM density in CF subjects compared to healthy controls (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). Very few sites emerged with significantly low GM density in CF compared to control subjects. Brain regions with increased GM density in CF subjects emerged in the right cerebellum, hippocampus, amygdala, parahippocampal gyrus, ventral medial prefrontal cortices, superior temporal cortices, bilateral basal forebrain, insula, parietal cortices, left mid and superior frontal, and prefrontal cortices, compared to controls (Fig.\u0026nbsp;1). Brain regions showing decreased GM density in CF patients emerged in the right inferior temporal cortices and bilateral occipital cortices.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRegional brain gray matter density (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, mm\u003csup\u003e3\u003c/sup\u003e/voxel) of CF patients and control corrected for age and sex.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBrain areas\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCF (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControls (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-values\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Prefrontal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Prefrontal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Ventral Med Prefrontal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.52\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Basal Forebrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.44\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Basal Forebrain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.39\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Amygdala\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Hippocampus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.71\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.68\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Parahippocampus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Cerebellar Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.70\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Insula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.56\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Insula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Mid Frontal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.60\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.55\u0026thinsp;\u0026plusmn;\u0026thinsp;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Sup Frontal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.62\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Sup Parietal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Sup Parietal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Sup Temporal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.67\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eCF = Cystic Fibrosis; SD = Standard deviation; Med = Medial; Mid = Middle; Sup = Superior.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec13\"\u003e\n \u003ch2\u003eBrain regions with T2-relaxation value differences\u003c/h2\u003e\n \u003cp\u003eSeveral brain areas in CF participants showed significantly lower T2-relaxation values, indicating acute tissue injury, compared to control subjects (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Few brain sites showed significantly higher T2-relaxation values in CF compared to controls. Regions with significantly reduced T2-relaxation values in CF participants appeared in the bilateral cerebellum, cerebellar tonsil, prefrontal and superior temporal cortices, parietal cortices, left frontal cortices, and right insula (Fig.\u0026nbsp;2). Other sites, including white matter areas, were also detected with reduced T2-relaxation values in CF over controls in regions that link important gray matter regions associated with cognition, anxiety, and depression, including frontal white matter, corpus callosum, and medulla (Fig.\u0026nbsp;2). Brain regions showing prolonged T2-relaxation values in CF emerged in the bilateral hippocampus and left para-hippocampal gyrus.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eRegional brain T2-relaxation values (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, ms) of CF patients and control corrected for age and sex.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBrain areas\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCF (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eControls (n\u0026thinsp;=\u0026thinsp;15)\u003c/p\u003e\n \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-values\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Prefrontal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e139.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e162.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Prefrontal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e162.6\u0026thinsp;\u0026plusmn;\u0026thinsp;17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e199.2\u0026thinsp;\u0026plusmn;\u0026thinsp;16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Cerebellum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e123.6\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e149.3\u0026thinsp;\u0026plusmn;\u0026thinsp;9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Cerebellum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e123.3\u0026thinsp;\u0026plusmn;\u0026thinsp;5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e136.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Cerebellar Tonsil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e126.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e160.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Cerebellar Tonsil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e127.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e159.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Insula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e157.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e182.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrainstem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e138.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e168.2\u0026thinsp;\u0026plusmn;\u0026thinsp;13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Frontal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e133.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e155.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Parietal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e152.4\u0026thinsp;\u0026plusmn;\u0026thinsp;13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e182.6\u0026thinsp;\u0026plusmn;\u0026thinsp;13.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Parietal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e128.0\u0026thinsp;\u0026plusmn;\u0026thinsp;10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e148.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Sup Temporal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e142.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e166.0\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight Sup Temporal Cortex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e132.1\u0026thinsp;\u0026plusmn;\u0026thinsp;7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e153.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCorpus Callosum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e121.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e154.5\u0026thinsp;\u0026plusmn;\u0026thinsp;15.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLeft Frontal White Matter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119.7\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e134.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003eCF = Cystic Fibrosis; ms = millisecond; SD = Standard deviation; Sup = Superior.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003ePeople with chronic diseases, such as CF, are at increased risk of depression and autonomic deficits. In addition, many aspects of the disease itself can lead to high levels of anxiety. We report significantly high scores of BAI and BDI-II in CF patients over healthy controls, consistent with previous studies [26, 27]. Also, we found that CF patients had a lower overall MoCA scores and this change was most significant in the visuospatial/executive sub domains. Several brain sites, including cerebellum, hippocampus, amygdala, insula, prefrontal, and temporal sites showed tissue changes based on GM density or T2-relaxometry procedures, areas that are involved in cognition, mood, and autonomic functions. Neuronal damage meditated through hypoxia and/or hypercapnia is considered to be one of the key mechanisms in pulmonary diseases [28, 29]. Both hypoxia and hypercapnia are often present in CF patients along with mutated CFTR gene and are potential underlying causes for the observed neural findings.\u003c/p\u003e \u003cp\u003eCF patients showed cognitive dysfunction, including the executive function, and mood deficits. Executive function is associated with skills requiring higher mental activities, such as setting goals, abstract logical thinking, planning, taking into account the long-term consequences, initiating intentional actions, creating different possible alternative reactions, or modifying own activity in response to changing conditions. Abnormal executive function has been found in other diseases with respiratory compromise, such as chronic obstructive pulmonary disease, asthma, obstructive sleep apnea [30\u0026ndash;32], and abnormal function in CF patients may contribute to such diminished actions. Depression and anxiety, as observed in our study, affects disease management, including clinic attendance and adherence to prescribed treatments, leading to increased hospitalization and healthcare costs, worse pulmonary function, and decreased health-related quality of life [27, 33\u0026ndash;35]. These findings reiterate the need for annual screening for depression and anxiety in patient with CF.\u003c/p\u003e \u003cp\u003eAlthough cognitive and mood symptoms are considered to be due to aspects surrounding the diagnosis of the disease, our findings show that CF patients have a brain structural basis for these symptoms. CF patients showed increased GM density and reduced T2-relaxation values in several brain areas, though GM density measures indicated more changes over T2-relaxometry. Such particular brain tissue changes were evident in the cerebellum, hippocampus, amygdala, superior temporal cortices, basal forebrain, insula, parietal cortices, and frontal and prefrontal cortices. The increased GM density or reduced T2-relaxation values in our patient population might be due to increased neuronal and axonal swelling (although the disease is chronic, the condition is associated with ongoing hypoxia), increased size neurons, increased glial cell size or number, higher vascular density to support sustained increased metabolic demand, more connective tissue, dendritic outgrowth, or synaptogenesis [36, 37]. Higher neuronal numbers may result from an abnormal developmental process, including accentuated neuronal birth rate or the survival of excess neurons [36]. In addition, the elevated GM density may be related to pre-apoptotic osmotic changes or hypertrophy, marking areas of early neuronal deficits. Previous depression studies indicated increased glucose metabolism [38, 39] resulting from the inhibition of reciprocal connections between the prefrontal cortex and the amygdala in limbic-thalamic-cortical circuit or limbic-cortical-striatal-pallidal-thalamic circuit enlarging amygdala [37, 40], and such processing may be operating in other structures as observed here.\u003c/p\u003e \u003cp\u003eThe hippocampus, prefrontal cortices, and amygdala regions are highly interconnected and constitute the neuroanatomical network for mood regulation [40, 41], and these areas showed increased GM density or altered T2-relaxation values in our study. Activation of the amygdala has been demonstrated to increase dopamine in the nucleus accumbens and other motor control centers, resulting in increased fear behaviors and anxiety and might be plausible explanation for higher anxiety in CF patients. The amygdala and hippocampus have projections from the prefrontal cortices and other limbic-related forebrain structures that are involved in several cognitive domains, and increased GM volume or altered T2-relaxation values in these sites, as found in our study, may suggest abnormal cognition. The superior temporal gyrus has connections to limbic and prefrontal regions [42], and right superior temporal structures in particular have been associated with responses to emotional prosody [43]. The superior temporal lobe along with insula and cingulate regions form a part of the salience network that is involved in the coordination of the behavioral responses. The anterior insula displays altered functional connectivity within the salience network and with other brain network in depression condition. Another brain region that showed increased GM density and tissue changes was cerebellum, where climbing fiber codes error signal reflecting the motor performance failure and works to depress the synaptic transmission between parallel fibers and Purkinje cell that can lead to depression and autonomic deficits [44, 45]. Furthermore, the cerebellum contributes to cognitive processing in several cognitive domains, including executive and visuospatial functioning and extensively interconnected with the cerebral hemisphere, both in feed-forward and feed-backward directions, and provides a structural basis for cognitive deficits in CF patients.\u003c/p\u003e \u003cp\u003ePatients with CF experience a wide spectrum of chronic pain, including headache, chest pain, back pain, abdominal pain, and limb pain [46]. Brain regions that showed increased GM density or altered T2-relaxation values, including the insula and hippocampus, are subjected to pain modulation and stress-induced changes [47, 48]. Stress can lead to microglial proliferation in areas around the third ventricle, including hippocampus, and activate microglia that can cause neuronal damage with the release of proinflammatory and cytotoxic factors and plausibly increase GM density or alter T2-relaxation values as observed in our study. Several brain areas showed reduced T2-relaxation values in CF patients which could result from increased astrocyte and microglial activation due to chronic pain. Earlier human postmortem studies reported reduced T2-relaxation values due to pronounced reactive microgliosis and astrogliosis [9], and showed the association between chronic pain and prolonged astrocyte activation at the level of the primary afferent synapse [49, 50].\u003c/p\u003e \u003cp\u003eMultiple diseases have demonstrated altered GM and white matter volume and tissue integrity [10\u0026ndash;12, 51, 52]. However, this is the first study that shows significant brain structural (GM density and brain tissue integrity) changes in CF patients, which could account for the symptomatology reported in the condition. Several basic and clinical studies, particularly those using neuroimaging techniques, report that specific brain regions play essential roles in cognitive, autonomic, depression, and anxiety regulation [51, 52]. The altered brain regions we encountered in CF patients have a considerably important role in their cognitive and mood wellbeing. With a high incidence of psychological symptoms in adult CF patients, this study highlights the importance for improved early identification and management strategies for adult CF patients.\u003c/p\u003e \u003cp\u003eOne of the limitations of this study is the small sample size that may affect the statistical analyses with findings not corrected for multiple comparisons, and may limit the magnitude of the significant alterations, as well as with type 1 error that we observed in various brain regions of CF patients. Also, T2-relaxometry procedures had poor resolution in slice thickness direction, resulting to less sites with damage over GM density measures. Thus, procedures with higher resolution would be required with bigger sample size to examine extend of tissue damage. We used MoCA, BDI-II, and BAI screening instruments to identify cognitive impairment and symptoms of depression and anxiety, combined with comprehensive clinical tests should be used for future studies.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003ePatient with CF showed significant brain structural changes, as evidenced by altered GM density or T2 relaxation values, indicative of tissue injury, in brain regions that control cognitive, autonomic, and mood functions. These sites included the cerebellum, hippocampus, amygdala, superior temporal cortices, basal forebrain, insula, parietal cortices, frontal and prefrontal cortices, and corpus callosum. In addition, CF patients exhibited significant anxiety and depression symptoms and impaired cognitive abilities, and brain regions regulating such functions showed altered brain structural integrity. Integration of mental health screening and early identification and targeted treatment of CF patients can improve the mortality and morbidity seen in the condition.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe included statements on ethics approval and consent from participants and provided the name of the ethics committee that approved the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by National Institutes of Health grants (K23GM132795 to SV; R21 AG070269 to BR, SV, and RK).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBR collected, analyzed and interpreted the patient data, performed statistical analyses, and wrote the manuscript; MSW and RK designed the study, collected the patient data and was a major contributor in writing the manuscript; SV and PE, interpreted the patient data and was a major contributor in writing the manuscript; APR collected the patient data and contributed in writing the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank Mr. Luke Ehlert for help in data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGriesenbach U, Alton EW. Recent advances in understanding and managing cystic fibrosis transmembrane conductance regulator dysfunction. F1000prime reports. 2015;7:64.\u003c/li\u003e\n \u003cli\u003eDeeks ED. Lumacaftor/Ivacaftor: A Review in Cystic Fibrosis. Drugs. 2016.\u003c/li\u003e\n \u003cli\u003eDancey DR, Tullis ED, Heslegrave R, Thornley K, Hanly PJ. Sleep quality and daytime function in adults with cystic fibrosis and severe lung disease. The European respiratory journal. 2002;19:504-10.\u003c/li\u003e\n \u003cli\u003eDobbin CJ, Bartlett D, Melehan K, Grunstein RR, Bye PT. 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Journal of neuroscience research. 2018;96:1104-18.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cognition, Mood, Gray matter density, T2-relaxometery, Magnetic Resonance Imaging","lastPublishedDoi":"10.21203/rs.3.rs-769615/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-769615/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Cystic fibrosis (CF) patients present with a variety of symptoms, including mood and cognition deficits, in addition to classical respiratory, and autonomic issues. This suggests that brain injury, which can be examined with non-invasive magnetic resonance imaging (MRI), is a manifestation of this condition. However, brain tissue integrity in sites that regulate cognitive, autonomic, respiratory, and mood functions in CF patients is unclear. Our aim was to assess regional brain changes using high-resolution T1-weighted images based gray matter (GM) density and T2-relaxometry procedures in CF over control subjects. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We acquired high-resolution T1-weighted images and proton-density (PD) and T2-weighted images from 5 CF and 15 control subjects using a 3.0-Tesla MRI. High-resolution T1-weighted images were partitioned to GM-tissue type, normalized to a common space, and smoothed. Using PD- and T2-weighted images, whole-brain T2-relaxation maps were calculated, normalized, and smoothed. The smoothed GM-density and T2-relaxation maps were compared voxel-by-voxel between groups using analysis of covariance (covariates, age and sex; SPM12, p\u0026lt;0.001). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Significantly increased GM-density, indicating tissues injury, emerged in multiple brain regions, including the cerebellum, hippocampus, amygdala, basal forebrain, insula, and frontal and prefrontal cortices. Various brain areas showed significantly reduced T2-relaxation values in CF subjects, indicating predominant acute tissue changes, in the cerebellum, cerebellar tonsil, prefrontal and frontal cortices, insula, and corpus callosum. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Cystic fibrosis subjects show predominant acute tissue changes in areas that control mood, cognition, respiratory, and autonomic functions and suggests that tissue changes may contribute to symptoms resulting from ongoing hypoxia accompanying the condition.\u003c/p\u003e","manuscriptTitle":"Regional Brain Tissue Changes in Patients with Cystic Fibrosis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-08-09 18:01:04","doi":"10.21203/rs.3.rs-769615/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2021-08-09T11:22:17+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-08-05T06:44:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-08-03T11:48:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Translational Medicine","date":"2021-07-30T15:59:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6be0bc81-bcf1-4aed-a992-d005a9fbbd76","owner":[],"postedDate":"August 9th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":6322564,"name":"Translational Medicine"}],"tags":[],"updatedAt":"2021-09-26T06:36:58+00:00","versionOfRecord":[],"versionCreatedAt":"2021-08-09 18:01:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-769615","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-769615","identity":"rs-769615","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}