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BACKGROUND: Although chronic obstructive pulmonary disease (COPD) and heart failure with preserved ejection fraction often coexist with overlapping clinical features, they are usually studied separately. The SPIROMICS HF (Subpopulations and Intermediate Outcome Measures in COPD and Heart Failure Study) is testing hypotheses that new computed tomography emphysema subtypes are associated with specific cardiovascular phenotypes (eg, cor pulmonale , cor pulmonale parvus ), common airway branch variants are associated with right heart dysfunction, and symptomatic tobacco-exposed persons with preserved spirometry have signs of increased left ventricular afterload. METHODS: SPIROMICS is a multicenter observational study of COPD with extensive pulmonary phenotyping of participants with ≥20 pack-years smoking and nonsmoking controls. COPD and COPD severity were defined by standard spirometric criteria and symptomatic tobacco-exposed persons with preserved spirometry by ≥20 pack-years, normal spirometry, and COPD Assessment Test score >10. SPIROMICS HF selected all participants in SPIROMICS visit 5 at major sites. Its comprehensive speckle-tracking echocardiography, which included physiological perturbations of leg raise and low-intensity exercise, was harmonized prospectively with the Multi-Ethnic Study of Atherosclerosis Early Heart Failure and HeartSHARE (Combining Omics, Deep Phenotyping, and Electronic Health Records for Heart Failure Subtypes and Treatment Targets) studies. The cardiopulmonary magnetic resonance imaging protocol with gadolinium administration included myocardial fibrosis sequences, pulmonary angiography, time-resolved 3-dimensional cine magnetic resonance imaging (4-dimensional flow) of venous return, and metronome-paced tachypnea to induce dynamic hyperinflation. Coronary artery calcium was assessed on computed tomography scans. The Kansas City Cardiomyopathy Questionnaire was administered. RESULTS: Of the final sample of 753 participants, 57% had COPD (15% mild, 27% moderate, and 15% severe), 18% had symptomatic tobacco-exposed persons with preserved spirometry, 16% were smoking controls, and 8% were nonsmoking controls. Reproducibility of the main measures from speckle-tracking echocardiography (intraclass correlation coefficient, 0.83–0.99), exercise echocardiography (intraclass correlation coefficient, 0.71–0.99) and magnetic resonance imaging (intraclass correlation coefficient, 0.57–0.99) were good-to-excellent, including in severe COPD. CONCLUSIONS: SPIROMICS HF aims to characterize and understand cardiopulmonary interactions in COPD and COPD-related phenotypes to inform targeted treatments for combined cardiopulmonary failure.

Abstract Background Protein biomarkers are routinely measured for disease diagnosis and prognosis in clinical laboratories. Since most assays focus on protein quantity, information about proteoforms is often not acquired. Proteoforms of a protein represent the complex integration of genetic polymorphism, alternative splicing of RNA transcripts, and post-translational modifications (PTMs) on the amino-acid backbone. A detailed analysis of the post-translationally modified proteoforms (PTMPs), which are influenced by pathophysiological conditions, may lead to more precise diagnosis and prognosis. Content This article first discusses the methodologies used to accurately detect and characterize PTMPs, i.e., immunoassays, electrophoresis, chromatography, and intact and proteolysis-aided mass spectrometry techniques. Then it reviews specific examples of PTMP biomarkers that have been successfully translated from biomarker discovery to clinical use. The examples include β2–transferrin for cerebrospinal fluid leak diagnosis, phosphorylated tau proteoforms for Alzheimer disease diagnosis, and fucosylated alpha-fetoprotein for hepatocellular carcinoma prognosis. In addition, the article provides prospective views of novel analytical technologies and promising new PTMP biomarkers entering clinical practice. Summary In summary, PTMs are controlled by biochemical processes to modulate the functions of proteins by expanding their chemical diversity. PTM alterations in proteins can be indicators for pathophysiological conditions. Advances in analytical technologies are deepening our understanding of PTMPs and paving the way for their translation to clinical use. As research continues to discover the clinical meaning of PTMP biomarkers, they are poised to become valuable additions to the clinical testing menu for precision medicine.

Importance SARS-CoV-2 infection has been linked to neurotoxic effects and cognitive deficits. Objective To determine whether decreases in cognitive function were accelerated after SARS-CoV-2 infection compared with individuals not infected. Design, Setting, and Participants Multicenter, prospective cohort study from 2016 to 2022 among 3525 participants alive on March 1, 2020, and enrolled in The Atherosclerosis Risk in Communities (ARIC) study and the Collaborative Cohort of Cohorts for COVID-19 Research study who completed a prepandemic cognitive assessment and a pandemic-era assessment of SARS-CoV-2 infection. Final analyses performed in November 2024. Exposure SARS-CoV-2 infection determined via self-report of a positive SARS-CoV-2 test or health care professional diagnosis of COVID-19, a positive SARS-CoV-2 antinucleocapsid antibody response, or presence of an administrative code for COVID-19 on medical records. Main outcomes and measures A neuropsychological battery assessed multiple cognitive domains, and a cocalibrated confirmatory factor analysis generated factor scores for global cognitive function. The primary outcome was the rate of excess change in cognitive function. Results The 3525 eligible participants had a mean (SD) age of 80.8 (4.7) years, 2085 (59.1%) were female, 752 (21.4%) were Black, and 2773 (78.6%) were White. SARS-CoV-2 infection was detected among 307 participants (8.7%), 103 of whom (33.6%) were hospitalized. Among uninfected participants, the mean annualized change in cognitive function was −0.09 (95% CI, −0.13 to −0.04). Compared with this rate, change was faster (β = −0.06; 95% CI, −0.09 to −0.02) among participants hospitalized for infection, but not different from participants who were infected but not hospitalized (β = 0.00; 95% CI, −0.02 to 0.03). The association among participants hospitalized for infection was evident in the cognitive domains of memory and executive function, but not language. Conclusions and relevance This cohort study of older participants found accelerated decreases in cognition among individuals hospitalized for SARS-CoV-2 infection, but not nonhospitalized infection, in comparison with individuals not yet infected.

Abstract Rationale: SARS-CoV-2 infection may be associated with new or worsening respiratory symptoms that, if persistent, may contribute to “Long COVID.” Research is needed on the prevalence and risk determinants of Long COVID and related respiratory symptoms in adults with and without pre-existing obstructive lung disease or smoking history. Methods: C4R is a prospective, observational study that collected information on SARS-CoV-2 infection using standardized methods across 14 NIH-funded cohorts. The third wave of C4R questionnaires, administered June 2023 to January 2025, assessed self-reported Long COVID via the question, “Do you think that you are experiencing, or have ever experienced, what has been called “long COVID,” or symptoms related to COVID at least a month after your infection?” Questionnaires also assessed the presence (vs absence) of 22 symptoms that have been linked to Long COVID, including cough, shortness of breath, and post-exertional malaise. Pre-pandemic obstructive lung disease (COPD or asthma) and smoking status (ever/never) were harmonized from self-reported data collected at the most recent pre-pandemic cohort exam. Poisson regression was used to assess prevalence ratios (PRs) adjusting for age, sex, BMI, education, and pre-pandemic hypertension, diabetes, cardiovascular disease, and depressive symptoms. PRs for respiratory symptoms were tested according to self-reported Long COVID and history of non-hospitalized or hospitalized infection; effect modification by pre-pandemic lung disease and smoking was assessed by multiplicative interaction terms and in fully stratified models. Results: Among 23,434 questionnaire respondents, 1,484 (6.3%) self-reported Long COVID, including 246/1,262 (19.5%) with pre-pandemic lung disease and 664/4,018 (16.5%) with smoking history. The adjusted PR for Long COVID was 1.17 (95%CI:0.99-1.39;P=0.06) comparing participants with/without lung disease and 1.17 (95%CI:1.04-1.32;P=0.01) comparing participants with/without smoking history. Respiratory symptoms were more prevalent in those with self-reported Long COVID, as well as in those with a history of hospitalized or non-hospitalized infection (Table). Associations were generally stronger in participants without pre-pandemic lung disease (p-interaction<0.05 for all comparisons). Respiratory symptoms were also more prevalent with a history of repeated, and pre-Omicron infections, and were less prevalent among participants vaccinated prior to their first infection; findings were similar even after excluding participants with self-reported Long COVID. Conclusions: Long COVID is common, particularly in adults with pre-existing COPD or asthma or smoking history. Long COVID and history of SARS-CoV-2 infection, including non-hospitalized infections, was associated with greater respiratory symptom burden. Whether SARS-CoV-2 infection or Long COVID are associated with development or progression of obstructive lung diseases warrants future studies.

Abstract RATIONALE: Chronic kidney disease (CKD) is common in the general population and is associated with inflammation and compromised immune function. Since these mechanisms are hypothesized to promote severe COVID-19, we tested associations of pre-pandemic CKD with incident COVID-19 hospitalization or death in a large, multi-ethnic, US general population-based meta-cohort of adults. METHODS: Data were harmonized and pooled from 9 NIH-funded longitudinal cohorts participating in the Collaborative Cohort of Cohorts for COVID-19 Research (C4R). CKD was classified by KDIGO 2024 CKD guideline (Low Risk, Moderately Increased Risk, High Risk, Very High Risk) using pre-pandemic urinary albumin-to-creatinine ratio (uACR) and estimated glomerular filtration rate using creatinine (eGFRcr). Incident COVID-19 hospitalization or death was ascertained over 2020−2023 via self-report and active surveillance, with medical record adjudication in a subset. In our primary analysis, we assessed associations between CKD stages and incident COVID-19 hospitalization or death. A secondary analysis examined joint association of CKD stages and the number of comorbidities (obesity, hypertension, diabetes, and cardiovascular disease) with the severe COVID-19. Multivariable hazard ratios (HRs) were estimated by cause-specific Cox regression, adjusting for socio-demographics and smoking. RESULTS: Among 26,039 multi-ethnic adult participants (mean age 66.1±14.8, 60.6 % female, 28.6% Whites, 3.2% Asians, 20.6% Blacks, 41.3% Hispanics, 6.3% American Indians) with a median follow-up of 550 days since the onset of the pandemic (baseline: March 1, 2020), there were 734 incident COVID-19 hospitalizations or deaths. The mean time since CKD markers were measured before the baseline was 6.5 years. The cumulative incidence of severe COVID-19 was 2.3, 3.5, 6.5, and 7.3% across CKD risk stages, and similar patterns were observed within variant types (Figure 1). Compared to participants with Low Risk of CKD, there was a graded increased hazards of severe COVID-19 across CKD stages, with HRs (95% CIs) of 1.27 (1.03−1.55) for Moderately Increased Risk, 2.33 (1.77−3.06) for High Risk, and 2.72 (1.89−3.92) for Very High Risk. In a joint analysis, both increased CKD risk and a higher number of comorbidities were associated with a higher risk of severe COVID-19, showing the highest HR of 12.29 (5.75−26.27) in Very High Risk individuals with four comorbidities compared to Low Risk individuals with none. CONCLUSIONS: Higher CKD stages were associated with a greater risk of COVID-19 hospitalization or death and the risk is substantially heightened with additional comorbidities. These results suggest that adults with CKD and related comorbidities may merit enhanced COVID-19 risk mitigation.

Abstract Chronic obstructive pulmonary disease (COPD) and pulmonary emphysema were the third-leading cause of death globally in 2019. Besides alpha-1 antitrypsin deficiency, emphysema lacks disease-modifying medications due to its heterogeneity and there remains a need to further investigate emphysema subtypes to advance its diagnosis and treatment. Recent unsupervised machine learning of the texture and anatomical location of emphysema on computed tomography (CT) images of the lung defined six quantitative CT emphysema subtypes uniquely associated with specific gene variants, environmental exposures, symptoms, physiology and clinical events. We aim to identify associations of plasma proteins with each CT emphysema subtype cross-sectionally in a multi-ethnic general population sample. MESA is a prospective cohort study that recruited 6,814 participants from six communities who self-identified as White, Black, Hispanic, or Asian race/ethnicity, ages 45-84 years old and free of clinical cardiovascular disease in 2000-02. The MESA Lung Study performed CT scans among 3,137 participants in 2010-12, which were labeled with previously described (PMID: 37268414) CT emphysema subtypes. Proteomics was assessed using SomaScan version 4.1 assay (7,596 plasma proteins). Linear regression models were adjusted for age, height, weight, sex, race, educational attainment, smoking status, pack years, urine cotinine level, body-mass index (BMI), estimated glomerular filtration rate (eGFR), CT scanner manufacturer and other CT emphysema subtypes. Results were adjusted to reflect a False Discovery Rate (FDR) p-value of less than 5% using the Benjamini-Hochberg method. Among 2,343 participants with both CT and proteomic data (mean age 69.5 years, 52.3% women, 23.7% with COPD), we identified statistically significant associations of proteins with the vanishing lung subtype (42 proteins; top hit Natural cytotoxicity triggering receptor 3 ligand 1, q = 2.9[asterisk]10-9), restrictive combined pulmonary fibrosis/emphysema (CPFE) subtype (11 proteins; top hit Integrin alpha-2/b1, q=1.0[asterisk]10-5), the combined bronchitis-apical emphysema subtype (9 proteins; top hit Desmoglein-2, q=8.8[asterisk]10-13), and the diffuse emphysema subtype (4 proteins; top hit Pulmonary surfactant-associated protein D, q=5.7[asterisk]10-3). No significant proteins were associated with the obstructive CPFE or senile subtypes after FDR correction. Most proteins were uniquely associated with one CT emphysema subtype, while a few proteins were associated with more than one subtype. This study identified specific proteins for different CT emphysema subtypes, many of which have been related less specifically to emphysema, including pulmonary surfactant production, anti-inflammatory pathways, and mitochondrial deregulation, amongst others. Validation of these proteomic associations can provide insight into further pathway assessment, clinical biomarker discovery, and targeted prevention of emphysema in the general population.

Background: Despite the availability of effective vaccines and a recent decrease in annual deaths, coronavirus disease-2019 (COVID-19) remains a leading cause of death. Serological studies of anti-nucleocapsid (N) antibody response to infection provide insights into host immunobiology of adaptive immune response, which holds promise for identifying high-risk individuals for adverse acute and chronic COVID-19 outcomes. Hypothesis: Among participants previously infected with SARS-CoV-2, traditional vascular disease risk factors are associated with higher anti-N antibodies while vaccination is associated with lower anti-N antibodies. Methods: Among previously infected participants, anti-N antibodies were measured from dried blood spots collected between February 2021-February 2023 among 1,419 Collaborative Cohort of Cohorts for COVID-19 Research (C4R) participants with prior SARS-CoV-2 infection. We measured anti-N IgG antibodies reported as median fluorescence intensity (MFI) units; reactivity (i.e., seropositivity) was defined based on MFI above a validated threshold. Vascular disease risk factors were assessed via pre-pandemic in-person examination, questionnaires, and medical record review. Multivariable generalized linear models regressed anti-N reactivity (modified Poisson) or LN transformed MFI (linear). Results: Among 1,419 participants with prior infection, mean age (standard deviation) was 65.8(12.1) years, 61% were women, and 42.8% were self-reported from a race/ethnicity minority group. Participant reactivity to nucleocapsid peaked at 69% by 4 months post-infection and waned to only 44% ≥12 months after infection. After multivariable adjustment, higher anti-N antibody response was associated with older age, Hispanic (vs. White) or American Indian (vs. White) race/ethnicity, lower income and education, former smoking, and higher anti-spike antibody levels. Asian race (vs. White) and vaccination ( even after infection ) were associated with lower nucleocapsid reactivity; common cardiometabolic co-morbidities were not associated with anti-N reactivity or levels (Figures 1 and 2). Conclusions: Among participants previously infected with SARS-CoV-2, select sociodemographic and behavioral risk factors were associated with higher anti-N antibody levels while vaccination was associated with lower anti-N antibody levels. The observation that vaccination, even after infection, is related to lower anti-N antibody levels merits further investigation.

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.

Abstract Despite the availability of effective vaccines and a recent decrease in annual deaths, COVID-19 remains a leading cause of death. Serological studies provide insights into host immunobiology of adaptive immune response to infection, which holds promise for identifying high-risk individuals for adverse COVID-19 outcomes. We investigated correlates of anti-nucleocapsid antibody responses following SARS-CoV-2 infection in a US population-based meta-cohort of adults participating in longstanding National Institutes of Health–funded cohort studies. Anti-nucleocapsid antibodies were measured from dried blood spots collected between February 2021 and February 2023. Among 1419 Collaborative Cohort of Cohorts for COVID-19 Research participants with prior SARS-CoV-2 infection, the mean age (standard deviation) was 65.8 (12.1), 61% were women, and 42.8% self-reported membership in a race/ethnicity minority group. The proportion of participants reactive to nucleocapsid peaked at 69% by 4 months after infection and waned to only 44% ≥12 months after infection. Higher anti-nucleocapsid antibody response was associated with older age, Hispanic or American Indian Alaskan Native (vs White) race/ethnicity, lower income, lower education, former smoking, and higher anti-spike antibody levels. Asian race (vs White) and vaccination (even after infection) were associated with lower nucleocapsid reactivity. Neither vaccine manufacturer nor common cardiometabolic comorbidities were not associated with anti-nucleocapsid response. These findings inform the underlying immunobiology of adaptive immune response to infection, as well as the potential utility of anti-nucleocapsid antibody response for clinical practice and COVID-19 serosurveillance.