Umans, Jason G.

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.

Background: Thrombo-inflammation is a hallmark of acute Covid-19, with higher thrombo-inflammatory markers during infection associated with adverse outcomes. We hypothesized that higher pre-pandemic biomarkers, reflecting a higher thrombo-inflammatory setpoint, might identify people at greater risk of severe manifestations of Covid-19. Hypothesis: Pre-pandemic inflammation markers are associated with risk of hospitalized or fatal (hereafter, “severe”) Covid-19 in a multi-ethnic US sample. Methods: From 2020-2023, C4R harmonized pre-pandemic measures and ascertained Covid-19 across 14 longstanding cohort studies. In 12 cohorts, we assessed biomarker data and covariates from the study visit closest to the pandemic for 6 analytes shown in the Table. HRs of severe Covid-19 by pre-pandemic biomarkers were estimated using cause-specific Cox regression, treating non-severe Covid-19 as a competing risk, and adjusting for pre-pandemic sociodemographic and clinical characteristics. Results: Biomarkers were measured a mean of 20 years before the pandemic with different sample sizes for each (Table footnote). Mean age at the start of the pandemic was in the 60s or 70s depending on the biomarker. The most represented race or ethnic groups were White and Black. The largest sample was for C-reactive protein, and there were 1,001 severe Covid-19 cases among 38,784 participants. In the adjusted models, considered individually, higher CRP, leukocyte count, factor VIII and fibrinogen, but not other markers, were associated with greater risk of severe Covid-19 (Table).Associations were robust across subgroups and time since biomarker measurement (example for C-reactive protein in Figure). Conclusions: In this prospective multi-study analysis of a multi-ethnic population, higher basal levels of thrombo-inflammation markers were associated with greater risk of severe Covid-19. Since we considered non-severe Covid-19 as a competing risk, associations may reflect factors related to progression to more serious Covid-19 illness.

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.

ImportancePersistent symptoms and disability following SARS-CoV-2 infection, known as post–COVID-19 condition or “long COVID,” are frequently reported and pose a substantial personal and societal burden.ObjectiveTo determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.Design, Setting, and ParticipantsFor this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health–funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.ExposurePreinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.Main Outcomes and MeasuresProbability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.ResultsOf 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.Conclusions and RelevanceIn this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

AbstractIntroductionData on cigarette smoking prevalence among Alaska Native and American Indian (ANAI) people are limited to cross-sectional studies or specific subpopulations. Using data from the Alaska Education and Research toward Health (EARTH) Study 10-year follow-up, this study assessed patterns of smoking from baseline and factors associated with current use.Aims and MethodsEARTH Study urban south central ANAI participants (N = 376; 73% women) provided questionnaire data on smoking at baseline and 10-year follow-up. Multivariable-adjusted logistic regression assessed whether gender, cultural factors (Tribal identity, language spoken in the home), depressive symptoms (PHQ-9), baseline smoking status, and baseline cigarettes per day (CPD) were associated with current smoking at follow-up.ResultsCurrent smoking was 27% and 23% at baseline and follow-up, respectively. Of baseline smokers, 60% reported smoking at follow-up (77% men, 52% women). From multivariable-adjusted analyses, the odds of current smoking at follow-up were lower among women than men, those who never or formerly smoked versus currently smoked at baseline, and smoking <10 CPD compared with ≥10 CPD at baseline. PHQ-9 score or cultural variables were not associated with smoking at follow-up. Smoking fewer baseline CPD was associated with former smoking status (ie, quitting) at follow-up among women, but not men.ConclusionsOur project is among the first to longitudinally explore smoking within an ANAI cohort. While we observed persistent smoking during a 10-year period, there were important differences by gender and CPD in quitting. These differences may be important to enhance the reach and efficacy of cessation interventions for ANAI people.ImplicationsThis study contributes novel longitudinal information on cigarette smoking prevalence during a 10-year period among Alaska Native and American Indian (ANAI) people. Prior data on smoking prevalence among ANAI people are limited to cross-sectional studies or specific subpopulations. Our project is among the first to longitudinally explore smoking prevalence within an ANAI cohort. We observed persistent smoking during a 10-year period. The study also contributes information on differences by gender and cigarettes smoked per day in quitting. These findings have implications for enhancing the reach and efficacy of cessation interventions for ANAI people.

Background and Purpose— American Indians have high rates of stroke. Improved risk stratification could enhance prevention, but the ability of biochemical and echocardiographic markers of preclinical disease to improve stroke prediction is not well-defined. Methods— We evaluated such markers as predictors of ischemic stroke in a community-based cohort of American Indians without prevalent cardiovascular or renal disease. Laboratory markers included C-reactive protein, fibrinogen, urine albumin-to-creatinine ratio, and glycohemoglobin (HbA1c), whereas echocardiographic parameters comprised left atrial diameter, left ventricular mass, mitral annular calcification, and the ratio of early to late mitral diastolic velocities. Predictive performance was judged by indices of discrimination, reclassification, and calibration. Results— After adjustment for standard risk factors, only HbA1c, albuminuria, and left atrial diameter were significantly associated with first ischemic stroke. Addition of HbA1c, although not urine albumin-to-creatinine ratio, to a basic clinical model significantly improved the C-statistic (0.714 versus 0.695; P =0.044), whereas left atrial diameter modestly enhanced integrated discrimination improvement (0.90%; P =0.004), but not the C-statistic (0.701; P =0.528). When combined with HbA1c, left atrial diameter further increased integrated discrimination improvement (1.81%; P <0.001) but not the C-statistic (0.716). No marker achieved significant net reclassification improvement. Conclusions— In this cohort at high cardiometabolic risk, HbA1c emerged as the foremost predictor of ischemic stroke when added to traditional risk factors, affording substantially improved discrimination, with a more modest contribution for left atrial diameter. These findings bolster the role of HbA1c in cardiovascular risk assessment among persons with glycometabolic disorders and provide impetus for further study of the incremental value of echocardiography in high-risk populations.