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Two-step tests for gene-environment ( G × E $G\times E$ ) interactions exploit marginal single-nucleotide polymorphism (SNP) effects to improve the power of a genome-wide interaction scan. They combine a screening step based on marginal effects used to "bin" SNPs for weighted hypothesis testing in the second step to deliver greater power over single-step tests while preserving the genome-wide Type I error. However, the presence of many SNPs with detectable marginal effects on the trait of interest can reduce power by "displacing" true interactions with weaker marginal effects and by adding to the number of tests that need to be corrected for multiple testing. We introduce a new significance-based allocation into bins for Step-2 G × E $G\times E$ testing that overcomes the displacement issue and propose a computationally efficient approach to account for multiple testing within bins. Simulation results demonstrate that these simple improvements can provide substantially greater power than current methods under several scenarios. An application to a multistudy collaboration for understanding colorectal cancer reveals a G × Sex interaction located near the SMAD7 gene.
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Interacción Gen-Ambiente , Estudio de Asociación del Genoma Completo , Humanos , Modelos Genéticos , Fenotipo , Simulación por Computador , Polimorfismo de Nucleótido SimpleRESUMEN
BACKGROUND: Stomach cancer incidence presents significant racial/ethnic disparities among racial/ethnic minority groups in the United States, particularly among Asian and Hispanic immigrant populations. However, population-based evaluation of disparities by nativity has been scarce because of the lack of nativity-specific population denominators, especially for disaggregated Asian subgroups. Population-based stomach cancer incidence and tumor characteristics by detailed race/ethnicity and nativity were examined. METHODS: Annual age-adjusted incidence rates were calculated by race/ethnicity, sex, and nativity and tumor characteristics, such as stage and anatomic subsite, were evaluated using the 2011-2015 California Cancer Registry data. For Hispanic and Asian populations, nativity-specific population counts were estimated using the US Census and the American Community Survey Public Use Microdata Sample data. RESULTS: During 2011-2015 in California, 14,198 patients were diagnosed with stomach cancer. Annual age-adjusted incidence rates were higher among foreign-born individuals than their US-born counterparts. The difference was modest among Hispanics (â¼1.3-fold) but larger (â¼2- to 3-fold) among Chinese, Japanese, and Korean Americans. The highest incidence was observed for foreign-born Korean and Japanese Americans (33 and 33 per 100,000 for men; 15 and 12 per 100,000 for women, respectively). The proportion of localized stage disease was highest among foreign-born Korean Americans (44%); a similar proportion was observed among US-born Korean Americans, although numbers were limited. For other Asians and Hispanics, the localized stage proportion was generally lower among foreign-born than US-born individuals and lowest among foreign-born Japanese Americans (23%). CONCLUSIONS: Nativity-specific investigation with disaggregated racial/ethnic groups identified substantial stomach cancer disparities among foreign-born immigrant populations.
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Asiático , Neoplasias Gástricas , Masculino , Humanos , Femenino , Estados Unidos/epidemiología , Etnicidad , Neoplasias Gástricas/epidemiología , Grupos Minoritarios , Hispánicos o Latinos , California/epidemiologíaRESUMEN
BACKGROUND: Menopausal hormone therapy (MHT), a common treatment to relieve symptoms of menopause, is associated with a lower risk of colorectal cancer (CRC). To inform CRC risk prediction and MHT risk-benefit assessment, we aimed to evaluate the joint association of a polygenic risk score (PRS) for CRC and MHT on CRC risk. METHODS: We used data from 28,486 postmenopausal women (11,519 cases and 16,967 controls) of European descent. A PRS based on 141 CRC-associated genetic variants was modeled as a categorical variable in quartiles. Multiplicative interaction between PRS and MHT use was evaluated using logistic regression. Additive interaction was measured using the relative excess risk due to interaction (RERI). 30-year cumulative risks of CRC for 50-year-old women according to MHT use and PRS were calculated. RESULTS: The reduction in odds ratios by MHT use was larger in women within the highest quartile of PRS compared to that in women within the lowest quartile of PRS (p-value = 2.7 × 10-8). At the highest quartile of PRS, the 30-year CRC risk was statistically significantly lower for women taking any MHT than for women not taking any MHT, 3.7% (3.3%-4.0%) vs 6.1% (5.7%-6.5%) (difference 2.4%, P-value = 1.83 × 10-14); these differences were also statistically significant but smaller in magnitude in the lowest PRS quartile, 1.6% (1.4%-1.8%) vs 2.2% (1.9%-2.4%) (difference 0.6%, P-value = 1.01 × 10-3), indicating 4 times greater reduction in absolute risk associated with any MHT use in the highest compared to the lowest quartile of genetic CRC risk. CONCLUSIONS: MHT use has a greater impact on the reduction of CRC risk for women at higher genetic risk. These findings have implications for the development of risk prediction models for CRC and potentially for the consideration of genetic information in the risk-benefit assessment of MHT use.
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Neoplasias Colorrectales , Predisposición Genética a la Enfermedad , Humanos , Femenino , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/epidemiología , Persona de Mediana Edad , Estudios de Casos y Controles , Factores de Riesgo , Anciano , Terapia de Reemplazo de Hormonas/efectos adversos , Medición de Riesgo , Menopausia , Posmenopausia , Terapia de Reemplazo de Estrógeno/efectos adversosRESUMEN
BACKGROUND: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. METHODS: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). RESULTS: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value3-d.f.: 5.46 × 10-11) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value2-d.f.: 7.84 × 10-09). DISCUSSION: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.
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Neoplasias Colorrectales , Diabetes Mellitus , Humanos , Interacción Gen-Ambiente , Predisposición Genética a la Enfermedad , Factores de Riesgo , Diabetes Mellitus/genética , Neoplasias Colorrectales/genética , Polimorfismo de Nucleótido Simple , Estudio de Asociación del Genoma Completo/métodos , Proteínas de Microfilamentos/genéticaRESUMEN
BACKGROUND: Attitudes and behaviors towards mask wearing may influence the ability to reduce transmission of COVID-19 and other diseases. METHODS: University students, staff, and faculty (N = 9653) responded to an email invitation to complete electronic surveys (November 2021 and April 2022). Surveys included 19 items measuring attitudes and behaviors towards mask wearing from the Understanding America Study. Linear mixed models including variables for sex, age group, division, race and ethnicity, political affiliation, and history of COVID-19, were used to estimate the mean difference of the mean score for attitudes and behavior between Time 1 (November 2021) and Time 2 (April 2022). RESULTS: Participants were mostly female (62.1%), students (70.6%), White (39.5%) and Asian (34.7%). More than half identified their political affiliation as Democrat (65.5%). Characteristic variable-by-time interactions for difference in mean mask attitude scores difference were significant at Time 1 (T1) and Time 2 (T2) between Black and White participants (B = 0.18 (0.05), 95% CI: 0.07, 0.28, p = 0.001), Asian and White participants (B = 0.07 (0.02), 95% CI: 0.03-0.12, p = 0.001), participants with self-reported history of COVID-19 and no history of COVID-19 (B= -0.13 (0.02), 95% CI: -0.07, -0.18, p < 0.0001), females and males (B = 0.07 (0.02), 95% CI: 0.03, 0.11, p = 0.001), Republicans and Democrats (B= -0.18 (0.04), 95%CI: -0.26, -0.10, p < 0.0001) and Independents and Democrats (B= -0.10 (0.03), 95%CI: -0.15, -0.05, p < 0.0001). Mean difference in mean scores for mask behaviors at Time and Time 2 were significant between participants with COVID-19 and participants who did not have COVID-19 (B= -0.12 (0.04), 95% CI: -0.19, -0.04, p = 0.004), students compared to faculty and staff (B=-0.22 (0.05), -0.32, -0.12, p < 0.0001), between Republicans and Democrats (B-= -0.16 (0.07), 95% CI: -0.28, -0.03, p = 0.020, and between Independents and Democrats (B=-0.08 (0.04), 95% CI: -0.16, -0.002, p = 0.04). CONCLUSION: Race and ethnicity, political affiliation, and division may affect attitudes and behaviors in mask wearing. Further investigation into how characteristics influence public health measures such as mask wearing is needed to contain the spread of the COVID-19 virus, other infectious diseases, and future pandemics.
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COVID-19 , Conocimientos, Actitudes y Práctica en Salud , Máscaras , Pandemias , Femenino , Humanos , Masculino , Asiático , COVID-19/epidemiología , COVID-19/prevención & control , Pandemias/prevención & control , SARS-CoV-2 , Autoinforme , Blanco , Control de Enfermedades Transmisibles/métodos , Negro o AfroamericanoRESUMEN
BACKGROUND: Mistrust in science and scientists may adversely influence the rate of COVID-19 vaccination and undermine public health initiatives to reduce virus transmission. METHODS: Students, staff and faculty responded to an email invitation to complete an electronic survey. Surveys included 21-items from the Trust in Science and Scientists Inventory questionnaire. Responses were coded so higher scores indicated a higher trust in science and scientists, A linear regression model including sex, age group, division, race and ethnicity, political affiliation, and history of COVID-19, was used to determine variables significantly associated with trust in science and scientists scores at the p < 0.05 level. RESULTS: Participants were mostly female (62.1%), Asian (34.7%) and White (39.5%) and students (70.6%). More than half identified their political affiliation as Democrat (65%). In the final regression model, all races and ethnicities had significantly lower mean trust in science and scientists scores than White participants [Black ([Formula: see text]= -0.42, 95% CI: -0.55, -0.43, p < 0.001); Asian ([Formula: see text]= -0.20, 95% CI: -0.24, -0.17, p < 0.001); Latinx ([Formula: see text]= -0.22, 95% CI: -0.27, -0.18, p < 0.001); Other ([Formula: see text]= -0.19, 95% CI: -0.26, -0.11, p < 0.001)]. Compared to those identifying as Democrat, all other political affiliations had significantly lower mean scores. [Republican ([Formula: see text] =-0.49, 95% CI: -0.55, -0.43, p < 0.0001); Independent ([Formula: see text] =-0.29, 95% CI: -0.33, -0.25, p < 0.0001); something else ([Formula: see text] =-0.19, 95% CI: -0.25, -0.12, p < 0.0001)]. Having had COVID-19 ([Formula: see text]= -0.10, 95% CI: -0.15, -0.06, p < 0.001) had significantly lower scores compared to those who did not have COVID-19. CONCLUSION: Despite the setting of a major research University, trust in science is highly variable. This study identifies characteristics that could be used to target and curate educational campaigns and university policies to address the COVID19 and future pandemics.
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COVID-19 , Ciencia , Confianza , Femenino , Humanos , Masculino , COVID-19/epidemiología , Vacunas contra la COVID-19 , Docentes , Los Angeles , Pandemias , Estudiantes , UniversidadesRESUMEN
The heart transplantation policy change (PC) has improved outcomes in high-acuity (Old 1A, New 1-3) patients, but the effect on low-priority (Old 1B/2, New 4-6) patients is unknown. We sought to determine if low-priority patient outcomes were compromised by benefits to high-priority patients by evaluating for interaction between PC and priority status (PS). We included adult first-time heart transplant candidates and recipients from the UNOS registry during a 19-month period before and after the PC. We compared clinical characteristics and performed competing risks and survival analyses stratified by PC and PS. There was a dependence of PC and PS on waitlist death/deterioration with an interaction sub-distribution hazard ratio (adjusted sdHR) of 0.59 (0.45-0.78), p-value < .001. There was a trend toward a benefit of PC on waitlist death/deterioration (adjusted sdHR: 0.86 [0.73-1.01]; p = .07) and an increase in heart transplantation (adjusted sdHR: 1.08 [1.02-1.14], p = .007) for low-priority patients. There was no difference in 1-year post-transplant survival (log-rank p = .22) when stratifying by PC and PS. PC did not negatively affect waitlisted or transplanted low-priority patients. High-priority, post-PC patients had a targeted reduction in waitlist death/deterioration and did not come at the expense of worse post-transplant survival.
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Trasplante de Corazón , Obtención de Tejidos y Órganos , Adulto , Humanos , Tasa de Supervivencia , Estudios Retrospectivos , Listas de Espera , PolíticasRESUMEN
Defined by their genetic profile, individuals may exhibit differential clinical outcomes due to an environmental exposure. Identifying subgroups based on specific exposure-modifying genes can lead to targeted interventions and focused studies. Genome-wide interaction scans (GWIS) can be performed to identify such genes, but these scans typically suffer from low power due to the large multiple testing burden. We provide a novel framework for powerful two-step hypothesis tests for GWIS with a time-to-event endpoint under the Cox proportional hazards model. In the Cox regression setting, we develop an approach that prioritizes genes for Step-2 G×E testing based on a carefully constructed Step-1 screening procedure. Simulation results demonstrate this two-step approach can lead to substantially higher power for identifying gene-environment ( G×E ) interactions compared to the standard GWIS while preserving the family wise error rate over a range of scenarios. In a taxane-anthracycline chemotherapy study for breast cancer patients, the two-step approach identifies several gene expression by treatment interactions that would not be detected using the standard GWIS.
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Interacción Gen-Ambiente , Estudio de Asociación del Genoma Completo , Simulación por Computador , Estudio de Asociación del Genoma Completo/métodos , Humanos , Modelos Genéticos , Polimorfismo de Nucleótido SimpleRESUMEN
BACKGROUND: Intra-aortic balloon pumps (IABP) are used to bridge select end-stage heart disease patients to heart transplant (HT). IABP use and exception requests both increased dramatically after the UNOS policy change (PC). The purpose of this study was to evaluate the effect of PC and exception status requests on waitlist and post-transplant outcomes in patients bridged to HT with IABP support. METHODS: We analyzed adult, first-time, single-organ HT recipients from the UNOS Registry either on IABP at the time of registration for HT or at the time of HT. We compared waitlist and post-HT outcomes between patients from the PRE (October 18, 2016 to May 30, 2018) and POST (October 18, 2018 to May 30, 2020) eras using Kaplan-Meier curves and time-to-event analyses. RESULTS: A total of 1267 patients underwent HT from IABP (261 pre-policy/1006 post-policy). On multivariate analysis, PC was associated with an increase in HT (sub-distribution hazard ratio (sdHR): 2.15, p < .001) and decrease in death/deterioration (sdHR: 0.55, p = .011) on the waitlist with no effect on 1-year post-HT survival (p = .8). The exception status of patients undergoing HT was predominantly seen in the POST era (29%, 293/1006); only four patients in the PRE era. Exception requests in the POST era did not alter patient outcomes. CONCLUSIONS: In patients bridged to heart transplant with an IABP, policy change is associated with decreased rates of death/deterioration and increased rates of heart transplantation on the waitlist without affecting 1-year post-transplant survival. While exception status use has markedly increased post-PC, it is not associated with patient outcomes.
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Insuficiencia Cardíaca , Trasplante de Corazón , Corazón Auxiliar , Adulto , Insuficiencia Cardíaca/cirugía , Corazón Auxiliar/efectos adversos , Humanos , Contrapulsador Intraaórtico/efectos adversos , Políticas , Estudios Retrospectivos , Listas de EsperaRESUMEN
Sparse high-dimensional massive sample size (sHDMSS) time-to-event data present multiple challenges to quantitative researchers as most current sparse survival regression methods and software will grind to a halt and become practically inoperable. This paper develops a scalable â0 -based sparse Cox regression tool for right-censored time-to-event data that easily takes advantage of existing high performance implementation of â2 -penalized regression method for sHDMSS time-to-event data. Specifically, we extend the â0 -based broken adaptive ridge (BAR) methodology to the Cox model, which involves repeatedly performing reweighted â2 -penalized regression. We rigorously show that the resulting estimator for the Cox model is selection consistent, oracle for parameter estimation, and has a grouping property for highly correlated covariates. Furthermore, we implement our BAR method in an R package for sHDMSS time-to-event data by leveraging existing efficient algorithms for massive â2 -penalized Cox regression. We evaluate the BAR Cox regression method by extensive simulations and illustrate its application on an sHDMSS time-to-event data from the National Trauma Data Bank with hundreds of thousands of observations and tens of thousands sparsely represented covariates.
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Algoritmos , Simulación por Computador , Humanos , Modelos de Riesgos Proporcionales , Análisis de Regresión , Tamaño de la MuestraRESUMEN
Background: Associated with high-dimensional omics data there are often "meta-features" such as biological pathways and functional annotations, summary statistics from similar studies that can be informative for predicting an outcome of interest. We introduce a regularized hierarchical framework for integrating meta-features, with the goal of improving prediction and feature selection performance with time-to-event outcomes. Methods: A hierarchical framework is deployed to incorporate meta-features. Regularization is applied to the omic features as well as the meta-features so that high-dimensional data can be handled at both levels. The proposed hierarchical Cox model can be efficiently fitted by a combination of iterative reweighted least squares and cyclic coordinate descent. Results: In a simulation study we show that when the external meta-features are informative, the regularized hierarchical model can substantially improve prediction performance over standard regularized Cox regression. We illustrate the proposed model with applications to breast cancer and melanoma survival based on gene expression profiles, which show the improvement in prediction performance by applying meta-features, as well as the discovery of important omic feature sets with sparse regularization at meta-feature level. Conclusions: The proposed hierarchical regularized regression model enables integration of external meta-feature information directly into the modeling process for time-to-event outcomes, improves prediction performance when the external meta-feature data is informative. Importantly, when the external meta-features are uninformative, the prediction performance based on the regularized hierarchical model is on par with standard regularized Cox regression, indicating robustness of the framework. In addition to developing predictive signatures, the model can also be deployed in discovery applications where the main goal is to identify important features associated with the outcome rather than developing a predictive model.
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BACKGROUND: High red meat and/or processed meat consumption are established colorectal cancer risk factors. We conducted a genome-wide gene-environment (GxE) interaction analysis to identify genetic variants that may modify these associations. METHODS: A pooled sample of 29,842 colorectal cancer cases and 39,635 controls of European ancestry from 27 studies were included. Quantiles for red meat and processed meat intake were constructed from harmonized questionnaire data. Genotyping arrays were imputed to the Haplotype Reference Consortium. Two-step EDGE and joint tests of GxE interaction were utilized in our genome-wide scan. RESULTS: Meta-analyses confirmed positive associations between increased consumption of red meat and processed meat with colorectal cancer risk [per quartile red meat OR = 1.30; 95% confidence interval (CI) = 1.21-1.41; processed meat OR = 1.40; 95% CI = 1.20-1.63]. Two significant genome-wide GxE interactions for red meat consumption were found. Joint GxE tests revealed the rs4871179 SNP in chromosome 8 (downstream of HAS2); greater than median of consumption ORs = 1.38 (95% CI = 1.29-1.46), 1.20 (95% CI = 1.12-1.27), and 1.07 (95% CI = 0.95-1.19) for CC, CG, and GG, respectively. The two-step EDGE method identified the rs35352860 SNP in chromosome 18 (SMAD7 intron); greater than median of consumption ORs = 1.18 (95% CI = 1.11-1.24), 1.35 (95% CI = 1.26-1.44), and 1.46 (95% CI = 1.26-1.69) for CC, CT, and TT, respectively. CONCLUSIONS: We propose two novel biomarkers that support the role of meat consumption with an increased risk of colorectal cancer. IMPACT: The reported GxE interactions may explain the increased risk of colorectal cancer in certain population subgroups.
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Neoplasias Colorrectales , Carne Roja , Humanos , Interacción Gen-Ambiente , Carne Roja/efectos adversos , Carne/efectos adversos , Factores de Riesgo , Neoplasias Colorrectales/genéticaRESUMEN
BACKGROUND: Consumption of fibre, fruits and vegetables have been linked with lower colorectal cancer (CRC) risk. A genome-wide gene-environment (G × E) analysis was performed to test whether genetic variants modify these associations. METHODS: A pooled sample of 45 studies including up to 69,734 participants (cases: 29,896; controls: 39,838) of European ancestry were included. To identify G × E interactions, we used the traditional 1--degree-of-freedom (DF) G × E test and to improve power a 2-step procedure and a 3DF joint test that investigates the association between a genetic variant and dietary exposure, CRC risk and G × E interaction simultaneously. FINDINGS: The 3-DF joint test revealed two significant loci with p-value <5 × 10-8. Rs4730274 close to the SLC26A3 gene showed an association with fibre (p-value: 2.4 × 10-3) and G × fibre interaction with CRC (OR per quartile of fibre increase = 0.87, 0.80, and 0.75 for CC, TC, and TT genotype, respectively; G × E p-value: 1.8 × 10-7). Rs1620977 in the NEGR1 gene showed an association with fruit intake (p-value: 1.0 × 10-8) and G × fruit interaction with CRC (OR per quartile of fruit increase = 0.75, 0.65, and 0.56 for AA, AG, and GG genotype, respectively; G × E -p-value: 0.029). INTERPRETATION: We identified 2 loci associated with fibre and fruit intake that also modify the association of these dietary factors with CRC risk. Potential mechanisms include chronic inflammatory intestinal disorders, and gut function. However, further studies are needed for mechanistic validation and replication of findings. FUNDING: National Institutes of Health, National Cancer Institute. Full funding details for the individual consortia are provided in acknowledgments.
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Neoplasias Colorrectales , Fibras de la Dieta , Frutas , Interacción Gen-Ambiente , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple , Verduras , Humanos , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/etiología , Fibras de la Dieta/administración & dosificación , Genotipo , Dieta , Masculino , Femenino , Factores de RiesgoRESUMEN
Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.
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Antiinflamatorios no Esteroideos , Neoplasias Colorrectales , Estudio de Asociación del Genoma Completo , Polimorfismo de Nucleótido Simple , Humanos , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/tratamiento farmacológico , Antiinflamatorios no Esteroideos/farmacología , Aspirina/farmacología , Subtipo EP4 de Receptores de Prostaglandina E/genética , Subtipo EP4 de Receptores de Prostaglandina E/metabolismo , Masculino , Predisposición Genética a la Enfermedad , Femenino , Estudios de Casos y Controles , Persona de Mediana Edad , Sitios Genéticos , AncianoRESUMEN
Two-step testing is the state-of-the art approach for performing genome-wide interaction scans (GWIS). It is computationally efficient and yields higher power than standard single-step-based GWIS for virtually all biologically plausible scenarios. However, while two-step tests control the genome-wide type I error rate at the desired level, the lack of associated valid p-values can make it difficult for users to compare with single step-results. We show how multiple-testing adjusted p-values can be defined for two-step test based on standard multiple-testing theory, and how they can be in turn scaled to make valid comparisons with single-step tests possible.
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Data from Asian Americans (AsA) are commonly aggregated in research studies and reporting, obscuring the significant differences across AsA subgroups. We investigated the differential experience of AsA subgroups in COVID-19 testing, vaccination, engagement in risky and protective behaviors and mental health status against this infectious disease. We surveyed a representative sample of the Los Angeles County population (N = 5500) in April 2021 as part of the Los Angeles Pandemic Surveillance Cohort Study and focused on participants who self-identified as AsA (N = 756). There were significant differences across the AsA subgroups, with Koreans, Asian Indians, and Other Asians living in areas with higher COVID-19 mortality rates, and Asian Indians demonstrating the lowest proportion of COVID-19 vaccination. Vietnamese and Koreans had a higher proportion of becoming unemployed during the pandemic. Although the AsA sample on average demonstrated better outcomes than other racial and ethnic groups, the apparent advantages were heterogenous and due to specific subgroups of AsAs rather than AsAs as a whole. The observed differences in COVID-19 measures across AsA subgroups underscore the need to disaggregate AsA data to identify and reduce existing disparities.
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Prevention of COVID-19 with vaccine requires multiple doses and updated boosters to maintain protection; however currently there are no tests that can measure immunity and guide clinical decisions about timing of booster doses. This study examined the association between the risk of COVID-19 breakthrough infections and receptor binding domain (RBD) antibody levels and receipt of booster of COVID-19 vaccines. A community sample of Los Angeles County adults were surveyed between 2021 and 2022 to determine if they had a self-reported breakthrough infection. Predictors included RBD antibody levels, measured by binding antibody responses to the ancestral strain at baseline and self-reported booster shot during the study period. Of the 859 participants, 182 (21%) reported a breakthrough infection. Irrespective of the level of antibodies, the risk of breakthrough infection was similar, ranging from 19 to 23% (P = 0.78). The risk of breakthrough infections was lower among participants who had a booster shot (P = 0.004). The protective effect of a booster shot did not vary by antibody levels prior to receiving the booster. This study found no association between RBD antibody levels and risk of breakthrough infections, while the receipt of booster was associated with lower risk of breakthrough infections, which was independent of pre-booster antibody levels. Therefore, antibody levels might not be a useful guide for clinical decisions about timing of booster doses.
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COVID-19 , SARS-CoV-2 , Adulto , Humanos , COVID-19/epidemiología , Infección Irruptiva , Vacunas contra la COVID-19 , Estudios de Cohortes , Pandemias , Anticuerpos , Anticuerpos AntiviralesRESUMEN
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binding antibody (Ab) levels following vaccination or natural infection could be used as a surrogate for immune protection if results of serological assays were standardized to yield quantitative results using an international standard. Using a bead-based serological assay (Luminex xMAP), anti-receptor binding domain (anti-RBD) Ab levels were determined for 1,450 participants enrolled in the Los Angeles Pandemic Surveillance Cohort (LAPSC) study. For 123 participants, SARS-CoV-2 binding antibody unit (BAU) levels were also quantified using WHO standards and then compared to the semiquantitative results. Samples were chosen to represent the range of results and time from vaccination. Antibody levels and decay rates were then compared using unadjusted and adjusted linear regression models. The linear range of the assay used in this study was determined to be 300 to 5,000 mean fluorescence intensity units (MFI). Among the fully vaccinated groups (vaccinated only and vaccinated with past infection), 84.8% had anti-RBD MFI values above the linear range of >5,000 MFI, and 33.8% had values of >15,000 MFI. Among vaccinated participants with past infection (hybrid immunity), 97% had anti-RBD values of >5,000 MFI and 70% (120/171) had anti-RBD values of >15,000 MFI. In the subgroup quantified using the WHO control, BAU levels were significantly higher than the semiquantitative MFI results. In vaccinated participants, Ab decay levels were similar between infected and noninfected groups (P = 0.337). These results demonstrate that accurate quantitation is possible if standardized with an international standard. BAU can then be compared over time or between subjects and would be useful in clinical decision making. IMPORTANCE Accurate quantification of SARS-CoV-2-specific antibodies can be achieved using a universal standard with sample dilution within the linear range. With hybrid immunity being now common, it is critical to use protocols adapted to high Ab levels to standardize serological results. We validated this approach with the Los Angeles Pandemic Surveillance Cohort by comparing the antibody decay rates in vaccinated participants and vaccinated infected participants.
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COVID-19 , Vacunas , Humanos , SARS-CoV-2 , COVID-19/prevención & control , Anticuerpos Antivirales , Vacunación , Organización Mundial de la SaludRESUMEN
Objectives: Despite the widespread availability of COVID-19 vaccines in the United States, vaccine hesitancy remains high among certain groups. This study examined the correlates of being unvaccinated among a sample of students attending a single university (N = 2900) during the spring and summer of 2021, when the campus had been closed for over a year and students were preparing to return to in-person learning. Methods: Students responded to an email invitation and completed electronic surveys. Results: In multivariable logistic regression analyses, students were more likely to be unvaccinated if they were African American, identified with any political affiliation other than Democrat, were undergraduates or international students, had not traveled outside the Los Angeles during the pandemic, and/or had previously been ill with COVID-19. Conclusion: Findings indicate that culturally resonant educational interventions, and possibly vaccine requirements, are needed to promote vaccination among university students.
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BACKGROUND: The 2018 United Network for Organ Sharing (UNOS) heart transplant policy change (PC) sought to improve waitlist risk stratification to decrease waitlist mortality and promote geographically broader sharing for high-acuity patients awaiting heart transplantation. Our analysis sought to determine the effect of the UNOS PC on outcomes in patients waiting for, or who have received, a heart-kidney transplantation. METHODS: We analyzed adult (≥18 years old), first-time, heart-only and heart-kidney transplant candidates and recipients from the UNOS Registry. Patients were divided into pre-PC (PRE: October 18, 2016-May 30, 2018) and post-PC (POST: October 18, 2018-May 30, 2020) groups for comparison. Competing risks analysis (subdistribution and cause-specific hazards analyses) was performed to assess for differences in waitlist death/deterioration or heart transplantation. One-year post-transplant survival was assessed with Kaplan-Meier and Cox analyses. We included an interaction term (policy era × heart ± kidney) in our analyses to evaluate the effect of PC on outcomes in heart-kidney patients. RESULTS: One-year post-transplant survival was similar (p = 0.83) for PRE heart-kidney and heart-only recipients, but worse (p < 0.001) for POST heart-kidney vs heart-only recipients. There was a policy-era interaction between heart-kidney and heart-only recipients (HR 1.92[1.04,3.55], p = 0.038) indicating a detrimental effect of policy on 1-year survival in POST vs PRE heart-kidney recipients. No added beneficial effect of PC on waitlist outcomes in heart-kidney vs heart-only candidates was observed. CONCLUSIONS: There was no added policy-era benefit on waitlist outcomes for heart-kidney candidates when compared to heart-only candidates. POST heart-kidney recipients experienced worse 1-year survival compared to PRE heart-kidney recipients with no policy effect on heart-only recipients.