O’Connor, George T.

Abstract RATIONALE: Susceptibility to severe COVID-19 and long COVID may be influenced by pre-existing lung structure. ECG-gated, non-contrast cardiac CT scans, originally acquired for assessing coronary artery calcium, are available in multiple longitudinal cohort studies and have been previously validated against lung CT scans for densitometry; however, protocol variation across cohorts may hinder direct comparison. To address this, we developed a quality control (QC) rubric to grade cardiac CT scans for standardized quantitative lung measures across cohorts. METHODS: C4R assessed SARS-CoV-2 infection and outcomes in 14 NHLBI cohorts, of which 10 (six community-based and four longitudinal case-control studies) included CT scans (12,459 participants with lung and 13,752 with cardiac CTs). Logic rules were applied to categorize scans (Table): Grade “A-B” scans had 2-3.5mm slice thickness, at least 20 axial slices, no lung cropping in axial view and lung and airway volumes greater than the cohort-specific 1st percentile. “C-D” scans had one lung obscured by cropping around the heart, so quantitative measures were restricted to the lung in complete view. “F-H” scans were deemed unusable, suffering from low slice count (<20), severe image cropping, low lung or airway volumes (< 1st%ile). Visual inspection was performed on a sample from each category to ensure accuracy. Percent of lung voxels in low attenuation areas < -950 HU (LAA950), high attenuation areas (-600 to -250 HU, HAA) and 15th percentile HU value (perc15) were measured. Within-participant variability was quantified using the intraclass correlation coefficient (ICC). RESULTS: We performed QC on cardiac CT scans from an initial sample of 6,275 participants from three C4R cohorts (ARIC, CARDIA, MASALA), imaged with GE or Siemens scanners. Of these, 5,125 (81.7%) were graded “A-B”, 496 (7.9%) were “C-D” and 654 (10.4%) were “F-H”. The percentage of “F-H” scans varied widely across cohorts [<1% to 26%] due to image cropping. Among the 5,621 cardiac CT scans graded A-D, the mean±SD for LAA950, HAA and perc15 respectively were 1.1±2.1%, 7.2±4.7% and -887±33 HU. Repeated imaging was available for 107 participants (time interval 5.1±0.7y). For paired scans in grades A-B (n=101/107), the within-participant correlation for LAA950, HAA and perc15 were 0.91, 0.38 and 0.74 respectively. CONCLUSION: Initial application of QC to cardiac CT scans identified scans with high reproducibility, with the aim to provide valid quantitative lung metrics on over 20,000 highly characterized participants in C4R.

Abstract Background:Chronic obstructive pulmonary disease (COPD) is a major global health burden, with genome-wide association studies explaining only a fraction of its heritability. Recent advancements, including large-scale, multi-ancestry whole-genome sequencing and a focus on severe, early-onset cases, offer promising avenues to identify additional COPD-related variants. Furthermore, recent studies show that adjusting for polygenic risk scores (PRS) enhances statistical power to detect rare variants, advancing efforts to understand COPD's genetic basis. Methods:We performed a whole genome sequencing association study of severe, early-onset COPD (FEV1 < 50%, age ≤ 55), FEV1 and FEV1/FVC in eight population-based studies (ARIC, CARDIA, CFS, CHS, FHS, HCHS/SOL, JHS, MESA) and seven COPD-enriched studies (COPDGene, ECLIPSE, Boston Early-Onset COPD Study, LTRC, TCGS (Poland), ICGN, SPIROMICS). We performed single-variant analyses using regenie software, applying a genome-wide significance threshold of P < 5.0 x 10-8. For rare variant set (MAF <1%) analysis, we annotated variants with loss of function or deleterious missense using WGS Annotator and prediction tools LOFTEE, SIFT, and PolyPhen2, then analyzed these variants with SKATO-ACAT method in regenie, adjusting for covariates including sex, sequencing center, and principal components of ancestry. We additionally evaluated adjusting the analyses for PRSs for lung function traits. Results: We analyzed 53,028 participants including 34,751 European, 12,508 African, 1,088 Latino American, and 674 East Asian ancestry. Across cohorts, we analyzed 5,063 severe (FEV1 < 50%) COPD cases, among whom 1,103 were early-onset (age ≤ 55). Excluding variants within 1 Mbp of known variants, single-variant analysis identified 68 novel associations (MAC ≥ 30), with 8 common associations (MAF ≥ 1%) in 6 genomic regions. Our most significant novel association for severe early-onset COPD was rs74297390 (intergenic to POM121L12, MAF = 9.6%, Beta = 0.41, P = 3.5 x 10-8). For FEV1 and FEV1/FVC ratio, variants near DKK2 and AKR1E2 were significantly associated and were replicated in an independent dataset (Shrine et al., 2019). DKK2 is an antagonist in the Wnt pathway. In a preliminary variant set analysis, CHRM3-AS1 was associated with severe early-onset COPD, GPAT with FEV1, and COL8A1I and HMCN1 with FEV1/FVC. With PRS adjustment, ST6GALNAC5 was associated with FEV1/FVC. Conclusions: In a whole genome sequencing study of lung function and severe early-onset COPD, we identified new loci for COPD-related phenotypes, including two novel loci that replicated in an independent dataset. Ongoing work involves variant set-based analyses with additional covariate adjustments, as well as PRS adjustments for binary traits.

Abstract Rationale Increased risk of coronavirus disease (COVID-19) hospitalization and death has been reported among patients with clinical lung disease. Objectives To test the association of objective measures of prepandemic lung function and structure with COVID-19 outcomes in U.S. adults. Methods Prepandemic obstruction (FEV1/FVC < 0.70) and restriction (FEV1/FVC ⩾ 0.7, FVC < 80%) were defined based on the most recent spirometry exam conducted in 11 prospective U.S. general population–based cohorts. Severe obstruction was classified by FEV1 < 50%. Percentage emphysema, percentage high-attenuation areas, and interstitial lung abnormalities were defined on computed tomography in a subset. Incident COVID-19 was ascertained via questionnaires, serosurvey, and medical records from 2020 to 2023 and classified as severe (hospitalized or fatal) or nonsevere. Cause-specific hazard models were adjusted for sociodemographics, anthropometry, smoking, comorbidities, and COVID-19 vaccination status. Measurements and Main Results Among 29,323 participants (mean age, 67 yr), there were 748 severe incident COVID-19 cases over median follow-up of 17.3 months from March 1, 2020. Greater hazards of severe COVID-19 were associated with severe obstruction (vs. normal; adjusted hazard ratio [aHR], 2.11; 95% confidence interval [CI], 1.02–1.27), restriction (vs. normal; aHR, 1.40; 95% CI, 1.12–1.76), and percentage emphysema (highest vs. lowest quartile; aHR, 1.64; 95% CI, 1.03–2.61), but not greater high-attenuation areas or interstitial lung abnormalities. COVID-19 vaccination provided greater absolute risk reduction in these groups. Results were similar in participants without smoking, obesity, or clinical cardiopulmonary disease. Conclusions Prepandemic severe spirometric obstruction, spirometric restriction, and greater percentage emphysema lung on computed tomography were associated with risk of severe COVID-19. These findings support enhanced COVID-19 risk mitigation for individuals with impaired lung health and warrant further mechanistic studies on interactions of lung function, structure, and vulnerability to acute respiratory illnesses.

ImportanceChronic obstructive pulmonary disease (COPD) is often undiagnosed. Although genetic risk plays a significant role in COPD susceptibility, its utility in guiding spirometry testing and identifying undiagnosed cases is unclear.ObjectiveTo determine whether a COPD polygenic risk score (PRS) enhances the identification of undiagnosed COPD beyond a case-finding questionnaire (eg, the Lung Function Questionnaire) using conventional risk factors and respiratory symptoms.Design, Setting, and ParticipantsThis cross-sectional analysis of participants 35 years or older who reported no history of physician-diagnosed COPD was conducted using data from 2 observational studies: the community-based Framingham Heart Study (FHS) and the COPD-enriched Genetic Epidemiology of COPD (COPDGene) study.ExposuresModified Lung Function Questionnaire (mLFQ) scores and COPD PRS.Main Outcomes and MeasuresThe primary outcome was spirometry-defined moderate to severe COPD (forced expiratory volume in the first second of expiration/forced vital capacity [FEV1/FVC] <0.7 and FEV1 [percent predicted] <80%). The performance of logistic models was assessed using the PRS, mLFQ score, and PRS plus mLFQ score for predicting spirometry-defined COPD.ResultsAmong 3385 FHS participants (median age, 52.0 years; 45.9% male) and 4095 COPDGene participants (median age, 56.8 years; 55.5% male) who reported no history of COPD, 160 (4.7%) FHS and 775 (18.9%) COPDGene participants had spirometry-defined COPD. Adding the PRS to the mLFQ score significantly improved the area under the curve from 0.78 to 0.84 (P < .001) in FHS, 0.69 to 0.72 (P = .04) in COPDGene non-Hispanic African American, and 0.75 to 0.78 (P < .001) in COPDGene non-Hispanic White participants. At a risk threshold for spirometry referral of 10%, the addition of the PRS to the mLFQ score correctly reclassified 13.8% (95% CI, 6.6%-21.0%) of COPD cases in FHS, but not in COPDGene.Conclusions and RelevanceA COPD PRS enhances the identification of undiagnosed COPD beyond a conventional case-finding approach in the general population. Further research is needed to assess its impact on COPD diagnosis and outcomes.

Abstract Rationale In addition to rare genetic variants and the MUC5B locus, common genetic variants contribute to idiopathic pulmonary fibrosis (IPF) risk. The predictive power of common variants outside the MUC5B locus for IPF and interstitial lung abnormalities (ILAs) is unknown. Objectives We tested the predictive value of IPF polygenic risk scores (PRSs) with and without the MUC5B region on IPF, ILA, and ILA progression. Methods We developed PRSs that included (PRS-M5B) and excluded (PRS-NO-M5B) the MUC5B region (500-kb window around rs35705950-T) using an IPF genome-wide association study. We assessed PRS associations with area under the receiver operating characteristic curve (AUC) metrics for IPF, ILA, and ILA progression. Measurements and Main Results We included 14,650 participants (1,970 IPF; 1,068 ILA) from six multi-ancestry population-based and case–control cohorts. In cases excluded from genome-wide association study, the PRS-M5B (odds ratio [OR] per SD of the score, 3.1; P = 7.1 × 10−95) and PRS-NO-M5B (OR per SD, 2.8; P = 2.5 × 10−87) were associated with IPF. Participants in the top PRS-NO-M5B quintile had ∼sevenfold odds for IPF compared with those in the first quintile. A clinical model predicted IPF (AUC, 0.61); rs35705950-T and PRS-NO-M5B demonstrated higher AUCs (0.73 and 0.7, respectively), and adding both genetic predictors to a clinical model yielded the highest performance (AUC, 0.81). The PRS-NO-M5B was associated with ILA (OR, 1.25) and ILA progression (OR, 1.16) in European ancestry participants. Conclusions A common genetic variant risk score complements the MUC5B variant to identify individuals at high risk of interstitial lung abnormalities and pulmonary fibrosis.

Background: Previous studies suggest poor pulmonary function is associated with increased burden of cerebral white matter hyperintensities and brain atrophy among elderly individuals, but the results are inconsistent. Objective: To study the cross-sectional associations of pulmonary function with structural brain variables. Methods: Data from six large community-based samples (N = 11,091) were analyzed. Spirometric measurements were standardized with respect to age, sex, height, and ethnicity using reference equations of the Global Lung Function Initiative. Associations of forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and their ratio FEV1/FVC with brain volume, gray matter volume, hippocampal volume, and volume of white matter hyperintensities were investigated using multivariable linear regressions for each study separately and then combined using random-effect meta-analyses. Results: FEV1 and FVC were positively associated with brain volume, gray matter volume, and hippocampal volume, and negatively associated with white matter hyperintensities volume after multiple testing correction, with little heterogeneity present between the studies. For instance, an increase of FVC by one unit was associated with 3.5 ml higher brain volume (95% CI: [2.2, 4.9]). In contrast, results for FEV1/FVC were more heterogeneous across studies, with significant positive associations with brain volume, gray matter volume, and hippocampal volume, but not white matter hyperintensities volume. Associations of brain variables with both FEV1 and FVC were consistently stronger than with FEV1/FVC, specifically with brain volume and white matter hyperintensities volume. Conclusion: In cross-sectional analyses, worse pulmonary function is associated with smaller brain volumes and higher white matter hyperintensities burden.