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Background: Patients with respiratory manifestations of acute COVID-19 infection have enlarged luminal areas of central conducting airways demonstrated on computed tomography imaging and abnormal pulmonary function. In some cases, COVID-19 symptoms may persist for more than 4 weeks, referred to as long COVID, and the effect on airway luminal area remains unknown. Herein, we report airway luminal cross-sections areas among a long COVID group, compared to individuals with an acute COVID-19. We aim to investigate if large conducting airways sizes are different between acute COVID-19 and long COVID patients. Methods: A cohort of 181 people with long COVID were screened, of which 20 people (9 men, 11 women; 55.9 ± 14.1 years) were included in analyses. Twenty age, height, and sex matched patients with an acute (< 4 weeks of persistent symptoms from diagnosis) COVID-19 infection (55.7 ± 15.2 years) served as a comparison group. We used a three-dimensional reconstruction of computed tomography imaging to measure luminal areas of the trachea, right and left main bronchi, bronchus intermediate, right and left upper lobe, and left lower lobe bronchi at proximal, middle, and distal cross-sectional points in both groups. Airway luminal area was taken as the average of the three points. We compared average lumen area of long COVID patients with acute COVID-19 individuals, using an independent samples t-test. Results: We found no significant difference comparing measurements of the following airway luminal cross-sectional areas: trachea (277.7 ± 100.4 vs. 268.0 ± 70.5 mm2 p=0.73), right main bronchus (191.0 ± 66.1 vs. 190.1 ± 49.0 mm2, p=0.96), bronchus intermediate (112.3 ± 33.4 vs. 109.3 ± 27.9 mm2, p=0.76), right upper lobe bronchus (74.4 ± 21.0 vs. 73.7 ± 25.5 mm2, p=0.92), left main bronchus (129.1 ± 50.1 vs. 136.9 ± 38.0 mm2, p=0.58), left lower lobe bronchus (57.8 ± 18.2 vs. 59.0 ± 13.4 mm2, p=0.82), and left upper lobe bronchus (80.1 ± 19.5 vs. 77.9 ± 22.9 mm2, p=0.75) in the long COVID and acute COVID-19 groups respectively. Conclusion: In patients with long COVID, compared to those with an acute COVID-19 infection, we did not see differences in central airway luminal areas. Further analysis of a larger cohort is needed to determine whether enlarged airway luminal areas, associated with acute COVID-19, persist in long COVID. This research will expand knowledge on functional consequences for patients with long COVID. Funding: F32HL154320 to JWS; 5R35HL139854 to MJJ. This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 369 nominally genome-wide significant loci ( P < 5 × 10 −8 ) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 360 loci for which replication data were available, 241 loci influencing surface area and 66 influencing thickness remained significant after replication, with 237 loci passing multiple testing correction ( P < 8.3 × 10 −10 ; 187 influencing surface area and 50 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation ( r G = −0.32, SE = 0.05, P = 6.5 × 10 −12 ), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 46 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function. Identifying genetic influences on human cortical structure. ( A ) Measurement of cortical surface area and thickness from MRI. ( B ) Genomic locations of common genetic variants that influence global and regional cortical structure. ( C ) Our results support the radial unit hypothesis that the expansion of cortical surface area is driven by proliferating neural progenitor cells. ( D ) Cortical surface area shows genetic correlation with psychiatric and cognitive traits. Error bars indicate SE. IMAGE CREDITS: (A) K. COURTNEY; (C) M. R. GLASS