Oelsner, Elizabeth C.

Objectives: Administrative criteria are often used to define COVID-19 outcomes despite challenges in differentiating hospitalization “for” vs “with” COVID-19 and unknown reliability for identifying COVID-related cardiopulmonary complications. We implemented a protocol to adjudicate COVID-related events across 14 studies participating in C4R. Methods: C4R cohorts ascertained COVID-related hospitalizations and deaths via questionnaires or ongoing surveillance. Medical records were reviewed by C4R physicians using a standardized protocol to assign COVID-related diagnoses as definite or probable. C4R diagnoses were compared against ICD codes assigned to the events. This report includes data from events centrally adjudicated by C4R as of September 2022. Results: Among 144 events ascertained across 7 cohorts as potentially COVID-related, SARS-CoV-2 infection was confirmed in 107/117 (91%) non-fatal hospitalizations and 26/27 (96%) deaths. Of confirmed infections, COVID-19 illness was diagnosed as the cause of 101/107 (94%) hospitalizations and 24/26 (92%) deaths ( Table ). Of non-fatal hospitalizations with infection, 72% were diagnosed with severe or critical COVID-19, 78% with COVID-associated pneumonia, and 29% with renal failure; other complications were less common. C4R review did not validate diagnoses indicated by ICD codes for 1 COVID-19 infection, 5 pneumonias, 1 stroke, and 7 renal failure cases. C4R review did identify diagnoses that were not ICD-coded for 13 infections, 31 pneumonias, 6 myocardial infarctions, 5 venous thromboses, and 21 renal failure cases. Conclusions: Protocolized medical records review by C4R confirmed COVID-19 as the cause of hospitalization or death in 87% of events ascertained as potentially COVID-related and 94% of those in which SARS-CoV-2 infection was confirmed. Both false-positive and false-negative misclassification by ICD criteria was observed. Protocolized review may be useful to identify and validate COVID-related events for epidemiologic research.

Background: Adults with cardiovascular co-morbidities and risk factors are at greater risk of severe COVID-19. These same risk factors may also be associated with an attenuated antibody response to COVID-19 vaccines, although studies in diverse, U.S. population-based cohorts have been limited. Methods: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) conducted a serosurvey for SARS-CoV-2 antibodies via dried blood spot (DBS) in 14 U.S. cohorts. IgG antibodies to SARS-CoV-2 spike subunit 1 (S1) and nucleocapsid (N) were measured from DBS using a semi-quantitative microsphere immunoassay and reported as median fluorescence intensity (MFI). Multivariable adjusted linear models regressed log-transformed anti-S1 MFI on age, sex, race/ethnicity, education attainment, self-reported diabetes, hypertension, cardiovascular disease (CVD), chronic kidney disease, smoking history, body mass index (BMI), asthma, obstructive lung diseases, DBS batch, anti-N MFI, vaccine type, time between vaccine and DBS, and vaccine dose at time of DBS collection. Results are presented as the percent difference in anti-S1 MFI compared with a reference group. Results: There were 6614 vaccinated participants prior to booster regimens and DBS collection (April 2021-July 2022) with 50%, 48%, and 2% of the cohort who received BNT162b2, mRNA-1273, or other vaccines, respectively. The mean (SD) time between vaccination and DBS was 3.8 (1.8) months. Over 10% of the cohort had self-reported a history of diabetes, 55% had hypertension, and 74% had a BMI>25 kg/m 2 . Anti-S1 MFI decreased as the time between vaccine dose and DBS collection increased. Diabetes was associated with a 16.1% lower anti-S1 MFI (95%CI:-22.4,-9.5) whereas neither hypertension (-3.8%;95%CI:-9.3,2.1), nor cardiovascular disease history (-5.3%;95%CI:-16.3,7.4) were associated with anti-S1 MFI. Former and current smoking history were each associated with a lower anti-S1 MFI: (-6.6%;95%CI:-12.1,-0.8) and (-16.1%;95%CI:-24.7,-6.6), respectively. Participants with a BMI 25-29.9 kg/m 2 had a 7.6% higher anti-S1 MFI (95%CI:0.3,15.4) whereas those with a BMI of 30-35 kg/m 2 and >35 kg/m 2 had 6.2% (95%CI:-2.4,15.5) higher and 8.9% lower (95%CI:-17.6,0.7) MFI levels, respectively. Older age and male sex were each associated with a lower anti-S1 MFI and mRNA-1273 vaccine, Asian subgroup, higher anti-N titer, and prior COVID-19 infection were each associated with higher anti-S1 MFI. Chronic kidney disease, education attainment, and lung disease were not associated with anti-S1 MFI. Conclusions: Several traditional cardiovascular disease risk factors were associated with diminished humoral responses to the initial COVID-19 vaccine regimens in a diverse U.S. population-based cohort and may have implications on strategies to improve vaccine responses.

Rationale: The impact of the COVID-19 pandemic on tobacco use patterns remains incompletely understood. We aimed to examine changes in cigarette smoking patterns over the first 2 years of the COVID-19 pandemic (2020-22) in a large, multiethnic, US community-based sample. Methods: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) ascertained the impact of the COVID-19 pandemic on participants from 14 longitudinal NIH-funded cohorts via 2 waves of standardized questionnaires conducted 2020-22. The C4R questionnaire collected data on cigarette use patterns for the current and immediate pre-pandemic periods (January-March 2020). These data were used to define pandemic-era smoking initiation, smoking cessation, and changes in smoking intensity. Multivariable logistic regression models were adjusted for centrally harmonized pre-pandemic data on sociodemographic characteristics, remote smoking history, and co-morbidities and pandemic-era psychological health, insomnia, and SARS-CoV-2 infection history ascertained through C4R questionnaires. Multiple imputation by chained equations was used to account for missing covariate data. Results: Of 17179 participants completing C4R questions on pandemic-era smoking behaviors, 1899 (11%) participants reported current smoking in the immediate pre-pandemic period (mean age 70 years, 59% women, 31% African American, 2% Hispanic, 1% Asian, 22% American Indian/Alaskan Native [AIAN]). Of these 181 (10%) self-reported quitting during the pandemic. Among 1718 (90%) who continued smoking, smoking intensity increased in 17% and decreased in 26%. Among 15093 participants who were not smoking prior to March 2020, 135 (0.9%) initiated smoking during the pandemic period, including 120 (89%) with a remote history of smoking and 15 (11%) with no history of smoking. Pandemic-era smoking cessation was associated with older age(80+ years vs <65 years [adjusted odds ratio; 95%CI] 2.1; 1.1-4.0), obesity(vs normal weight 1.6; 1.02-2.6) and history of SARS-CoV-2 infection (2.1; 1.3-3.1). Pandemic-era smoking initiation was associated with concurrent use of cannabis (3.1; 1.9-5.2), e-cigarette (29.6; 14.8-59.2), and/or alcohol (1.8; 1.1-2.9). Compared to non-Hispanic white participants, AIAN participants had lower odds of quitting (0.1; 0.03-0.6) and African American participants had higher odds of increased smoking intensity (2.0; 1.3-3.1). Depressive symptoms were associated with smoking initiation (2.4; 1.3-4.3) and increased smoking intensity (2.6; 1.5-4.5). Conclusion: Greater odds of smoking initiation and/or increased smoking intensity were observed in minoritized groups and participants reporting depressive symptoms. Majority of those who initiated smoking during pandemic-era were relapsers. Smoking cessation programs remain important to improving public health and reducing health disparities.

Abstract Background Across complex traits, common variants explain only a modest amount of variance, with SNP-heritability consistently below heritability estimates from close relatives. Here, we examined the contribution of rare variant to tobacco use risk in up to 26,000 individuals of European ancestry in the Trans-Omics for Precision Medicine (TOPMed) program with whole genome sequence (WGS;~30X coverage).Method We grouped about 35 million genetic variants by their minor allele frequencies (MAF) and linkage disequilibrium (LD) and estimated SNP-heritability for age of smoking initiation (N = 14,747), cigarettes smoked per day (N = 15,425), smoking cessation (N = 17,871) and initiation (N = 26,340) using linear mixed model. Rare variant population structure is detected and adjusted for by permutation procedure. We estimated an upper bound for narrow-sense heritability for tobacco use using available pedigrees consisting of close relatives in TOPMed.Results Rare variants with MAF 0.1–0.01%, mostly from non-protein altering region, accounted for 26% of variation in age of initiation and 15% for cessation. Follow-up analysis indicated that about one-third of these rare variants contribtion is potentially confounded with rare variants structure even after adjusting for principal components. After further conservative adjustment of population structure, we estimated SNP-based heritability to be 0.21 (SE = 0.08) for age of initiation, 0.15 (0.06) for cigarettes per day, 0.21 (0.09) for cessation, and 0.24 (0.07) for initiation, 1.8–4.5 times higher than previous SNP-based estimates. Our pedigree-based upper-bound for SNP-based heritability ranged from 0.18–0.35.Conclusion The substantial contribution of rare variants for several smoking phenotypes sheds light on the missing heritability and genetic etiology of tobacco use. It also informs fine-mapping strategies since the majority of the rare variant contribution was located in non-coding regulatory regions.