Our recently published study of >2.4 million adults in Northern California indicated that current versus never-tobacco smoking was associated with lower risk of SARS-CoV-2 infection and less severe coronavirus disease 2019 (COVID-19). We extended this research by evaluating whether these associations were moderated by socio-demographic factors and medical comorbidities. This retrospective cohort study of 1,885,826 adults with current or never-smoking status in Kaiser Permanente Northern California from 3/5/2020 (baseline) to 12/31/2020 (pre-vaccine) included electronic health record-based socio-demographics (sex, age, race/ethnicity, neighborhood deprivation index (NDI)) and medical comorbidities (obesity, cardiovascular conditions, diabetes, renal disease, respiratory conditions). We estimated the adjusted risk of SARS-CoV-2 infection and hospitalization (≤30 days of infection) associated with smoking status using Cox proportional hazard regression models. We estimated associations within subgroups of socio-demographics and comorbidities, and tested for effect modification using interaction terms. During the study, 35,627 patients had SARS-CoV-2 infection. Current versus never-smoking status was associated with lower adjusted rates of SARS-CoV-2 infection (aHR ranging from 0.51 to 0.89) and hospitalization (aHR ranging from 0.32 to 0.70) within nearly every socio-demographic and comorbidity subgroup. Statistically significant interactions showed that the magnitude of protection for SARS-CoV-2 infection varied by sex, age, race/ethnicity, NDI, cardiovascular conditions and diabetes, and for SARS-CoV-2 hospitalization by age and renal disease. Taken together, results indicated that while some socio-demographics and comorbidities moderated the associations, the lower risk of SARS-CoV-2 infection and hospitalization associated with current versus never-smoking status persisted among patients regardless of socio-demographics or comorbidities.

It is unknown whether use of e-cigarettes increases susceptibility to COVID-19. In a large clinical sample of young adults, we evaluated whether current or ever e-cigarette use was associated with polymerase chain reaction (PCR)-confirmed COVID-19. To address the confounding of combustible smoking, the sample was restricted to never smokers. This retrospective cohort study analyzed data from the electronic health records of 74,853 young adults (aged 18-35 years), without a history of cigarette smoking, who were screened for e-cigarette use (current, former, never) in the Kaiser Permanente Northern California (KPNC) healthcare system from 3/5/2020 (baseline) to 11/30/2020 (pre-vaccine). COVID-19 risk was estimated in time-to-event analyses using multivariable Cox proportional hazard regression models, adjusted for socio-demographics and medical comorbidities. E-cigarette status in the cohort was: 1.6% current, 1.2% former, and 97.2% never. During follow-up, 1965 (2.6%) patients acquired COVID-19. We did not find evidence that current (vs never) e-cigarette use was associated with risk of COVID-19 (aHR = 1.12 95%CI:0.77-1.62). However, we did find suggestive evidence that former (versus never) e-cigarette use may be associated with greater risk of COVID-19 (aHR = 1.39 95%CI:0.98-1.96). While e-cigarette use is associated with health risks for young adults, results from this study suggest that current use of e-cigarettes may not increase susceptibility for COVID-19 among young adults who have never smoked cigarettes.

Introduction

The relationship between tobacco smoking status and SARS-CoV-2 infection and coronavirus disease 2019 (COVID-19) severity is highly debated. We conducted a retrospective cohort study of >2.4 million adults in a large healthcare system to evaluate whether smoking is associated with SARS-CoV-2 infection and disease severity.

Aims and methods

This retrospective cohort study of 2,427,293 adults in KPNC from March 5, 2020 (baseline) to December 31, 2020 (pre-vaccine) included smoking status (current, former, never), socio-demographics, and comorbidities from the electronic health record. SARS-CoV-2 infection (identified by a positive PCR test) and COVID-19 severity (hospitalization, ICU admission or death ≤ 30 days of COVID-19 diagnosis) were estimated in time-to-event analyses using Cox proportional hazard regression models adjusting for covariates. Secondary analyses examined COVID-19 severity among patients with COVID-19 using logistic regression.

Results

During the study, 44,270 patients had SARS-CoV-2 infection. Current smoking was associated with lower adjusted rates of SARS-CoV-2 infection (aHR = 0.64 95% CI: 0.61-0.67), COVID-19-related hospitalization (aHR = 0.48 95% CI: 0.40-0.58), ICU admission (aHR = 0.62 95% CI: 0.42-0.87), and death (aHR = 0.52 95% CI: 0.27-0.89) than never-smoking. Former smoking was associated with a lower adjusted rate of SARS-CoV-2 infection (aHR = 0.96 95% CI: 0.94-0.99) and higher adjusted rates of hospitalization (aHR = 1.10 95% CI: 1.03-1.08) and death (aHR = 1.32 95% CI: 1.11-1.56) than never-smoking. Logistic regression analyses among patients with COVID-19 found lower odds of hospitalization for current versus never-smoking and higher odds of hospitalization and death for former versus never-smoking.

Conclusions

In the largest US study to date on smoking and COVID-19, current and former smoking showed lower risk of SARS-CoV-2 infection than never-smoking, while a history of smoking was associated with higher risk of severe COVID-19.

Implications

In this cohort study of 2.4 million adults, adjusting for socio-demographics and medical comorbidities, current tobacco smoking was associated with a lower risk of both SARS-CoV-2 infection and severe COVID-19 illness compared to never-smoking. A history of smoking was associated with a slightly lower risk of SARS-CoV-2 infection and a modestly higher risk of severe COVID-19 illness compared to never-smoking. The lower observed COVID-19 risk for current versus never-smoking deserves further investigation. Results support prioritizing individuals with smoking-related comorbidities for vaccine outreach and treatments as they become available.

Purpose

We compared across age-related macular degeneration (AMD) subtypes the effect of AMD risk variants, their predictive power, and heritability.

Methods

The prevalence of AMD was estimated among active non-Hispanic white Kaiser Permanente Northern California members who were at least 65 years of age as of June 2013. The genetic analysis included 5,170 overall AMD cases ascertained from electronic health records (EHR), including 1,239 choroidal neovascularization (CNV) cases and 1,060 nonexudative AMD cases without CNV, and 23,130 controls of non-Hispanic white ancestry from the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. Imputation was based on the 1000 Genomes Project reference panel.

Results

The narrow-sense heritability due to common autosomal single nucleotide polymorphisms (SNPs) was 0.37 for overall AMD, 0.19 for AMD unspecified, 0.20 for nonexudative AMD, and 0.60 for CNV. For the 19 previously reported AMD risk loci, the area under the receiver operating characteristic (ROC) curve was 0.675 for overall AMD, 0.640 for AMD unspecified, 0.678 for nonexudative AMD, and 0.766 for CNV. The individual effects on the risk of AMD for 18 of the 19 SNPs were in a consistent direction with those previously reported, including a protective effect of the APOE ε4 allele. Conversely, the risk of AMD was significantly increased in carriers of the ε2 allele.

Conclusions

These findings provide an independent confirmation of many of the previously identified AMD risk loci, and support a potentially greater role of genetic factors in the development of CNV. The replication of established associations validates the use of EHR in genetic studies of ophthalmologic traits.

Background

Up to one of every six individuals diagnosed with one cancer will be diagnosed with a second primary cancer in their lifetime. Genetic factors contributing to the development of multiple primary cancers, beyond known cancer syndromes, have been underexplored.

Methods

To characterize genetic susceptibility to multiple cancers, we conducted a pan-cancer, whole-exome sequencing study of individuals drawn from two large multi-ancestry populations (6429 cases, 165,853 controls). We created two groupings of individuals diagnosed with multiple primary cancers: (1) an overall combined set with at least two cancers across any of 36 organ sites and (2) cancer-specific sets defined by an index cancer at one of 16 organ sites with at least 50 cases from each study population. We then investigated whether variants identified from exome sequencing were associated with these sets of multiple cancer cases in comparison to individuals with one and, separately, no cancers.

Results

We identified 22 variant-phenotype associations, 10 of which have not been previously discovered and were significantly overrepresented among individuals with multiple cancers, compared to those with a single cancer.

Conclusions

Overall, we describe variants and genes that may play a fundamental role in the development of multiple primary cancers and improve our understanding of shared mechanisms underlying carcinogenesis.

Background

Much of the heritable risk of renal cell carcinoma (RCC) associated with common genetic variation is unexplained. New analytic approaches have been developed to increase the discovery of risk variants in genome-wide association studies (GWAS), including multi-locus testing through pathway analysis.

Methods

We conducted a pathway analysis using GWAS summary data from six previous scans (10,784 cases and 20,406 controls) and evaluated 3,678 pathways and gene sets drawn from the Molecular Signatures Database. To replicate findings, we analyzed GWAS summary data from the UK Biobank (903 cases and 451,361 controls) and the Genetic Epidemiology Research on Adult Health and Aging cohort (317 cases and 50,511 controls).

Results

We identified 14 pathways/gene sets associated with RCC in both the discovery (P < 1.36 × 10^-5, the Bonferroni correction threshold) and replication (P < 0.05) sets, 10 of which include components of the PI3K/AKT pathway. In tests across 2,035 genes in these pathways, associations (Bonferroni corrected P < 2.46 × 10^-5 in discovery and replication sets combined) were observed for CASP9, TIPIN, and CDKN2C. The strongest SNP signal was for rs12124078 (P _Discovery = 2.6 × 10^-5; P _Replication = 1.5 × 10^-4; P _Combined = 6.9 × 10^-8), a CASP9 expression quantitative trait locus.

Conclusions

Our pathway analysis implicates genetic variation within the PI3K/AKT pathway as a source of RCC heritability and identifies several promising novel susceptibility genes, including CASP9, which warrant further investigation.

Impact

Our findings illustrate the value of pathway analysis as a complementary approach to analyzing GWAS data.

Deciphering the shared genetic basis of distinct cancers has the potential to elucidate carcinogenic mechanisms and inform broadly applicable risk assessment efforts. Here, we undertake genome-wide association studies (GWAS) and comprehensive evaluations of heritability and pleiotropy across 18 cancer types in two large, population-based cohorts: the UK Biobank (408,786 European ancestry individuals; 48,961 cancer cases) and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging cohorts (66,526 European ancestry individuals; 16,001 cancer cases). The GWAS detect 21 genome-wide significant associations independent of previously reported results. Investigations of pleiotropy identify 12 cancer pairs exhibiting either positive or negative genetic correlations; 25 pleiotropic loci; and 100 independent pleiotropic variants, many of which are regulatory elements and/or influence cross-tissue gene expression. Our findings demonstrate widespread pleiotropy and offer further insight into the complex genetic architecture of cross-cancer susceptibility.

Even distinct cancer types share biological hallmarks. Here, we investigate polygenic risk score (PRS)-specific pleiotropy across 16 cancers in European ancestry individuals from the Genetic Epidemiology Research on Adult Health and Aging cohort (16,012 cases, 50,552 controls) and UK Biobank (48,969 cases, 359,802 controls). Within cohorts, each PRS is evaluated in multivariable logistic regression models against all other cancer types. Results are then meta-analyzed across cohorts. Ten positive and one inverse cross-cancer associations are found after multiple testing correction. Two pairs show bidirectional associations; the melanoma PRS is positively associated with oral cavity/pharyngeal cancer and vice versa, whereas the lung cancer PRS is positively associated with oral cavity/pharyngeal cancer, and the oral cavity/pharyngeal cancer PRS is inversely associated with lung cancer. Overall, we validate known, and uncover previously unreported, patterns of pleiotropy that have the potential to inform investigations of risk prediction, shared etiology, and precision cancer prevention strategies.

Mammographic density (MD) phenotypes are strongly associated with breast cancer risk and highly heritable. In this GWAS meta-analysis of 24,192 women, we identify 31 MD loci at P < 5 × 10^-8, tripling the number known to 46. Seventeen identified MD loci also are associated with breast cancer risk in an independent meta-analysis (P < 0.05). Mendelian randomization analyses show that genetic estimates of dense area (DA), nondense area (NDA), and percent density (PD) are all significantly associated with breast cancer risk (P < 0.05). Pathway analyses reveal distinct biological processes involving DA, NDA and PD loci. These findings provide additional insights into the genetic basis of MD phenotypes and their associations with breast cancer risk.

The Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort includes DNA specimens extracted from saliva samples of 110,266 individuals. Because of its relationship to aging, telomere length measurement was considered an important biomarker to develop on these subjects. To assay relative telomere length (TL) on this large cohort over a short time period, we created a novel high throughput robotic system for TL analysis and informatics. Samples were run in triplicate, along with control samples, in a randomized design. As part of quality control, we determined the within-sample variability and employed thresholds for the elimination of outlying measurements. Of 106,902 samples assayed, 105,539 (98.7%) passed all quality control (QC) measures. As expected, TL in general showed a decline with age and a sex difference. While telomeres showed a negative correlation with age up to 75 years, in those older than 75 years, age positively correlated with longer telomeres, indicative of an association of longer telomeres with more years of survival in those older than 75. Furthermore, while females in general had longer telomeres than males, this difference was significant only for those older than age 50. An additional novel finding was that the variance of TL between individuals increased with age. This study establishes reliable assay and analysis methodologies for measurement of TL in large, population-based human studies. The GERA cohort represents the largest currently available such resource, linked to comprehensive electronic health and genotype data for analysis.