Wang, Sophia

OBJECTIVES: Critically ill patients with COVID-19 experience high rates of delirium and coma. Whether delirium occurs through novel mechanisms in COVID-19 is not known. We analyzed the relationship among biomarkers of inflammation (C-reactive protein [CRP]), hypercoagulability (d-dimer), and lung macrophage activation (ferritin), and the primary composite outcome of delirium/coma next day. We also measured associations between biomarkers and next day delirium and coma independently, and delirium severity. DESIGN: Retrospective, observational cohort study. SETTING: ICUs at two large, urban, academic referral hospitals. PATIENTS: All consecutive adult patients admitted to the ICU from March 1, 2020, to June 7, 2020, with COVID-19 with clinical biomarkers and delirium assessments performed. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Daily concentrations of CRP, d-dimer, and ferritin were obtained. Coma (assessed by Richmond Agitation-Sedation Scale) and delirium (assessed by Confusion Assessment Method for the ICU/Confusion Assessment Method for the ICU-7) were measured bid. A cohort of 197 ICU patients with COVID-19 were included. Higher d-dimer (odds ratio [OR], 1.57; 95% CI, 1.17–2.12; p < 0.01) and ferritin quartiles (OR, 1.36; 95% CI, 1.02–1.81; p < 0.01) were associated with greater odds of the composite outcome of delirium/coma next day. d-dimer was associated with greater odds of next day delirium (OR, 1.49; 95% CI, 1.14–1.94; p < 0.01) and coma independently (OR, 1.52; 95% CI, 1.08–2.14; p = 0.017). Higher ferritin quartiles were associated with greater odds of next day delirium (OR, 1.33; 95% CI, 1.04–1.70; p = 0.026) and coma independently (OR, 1.59; 95% CI, 1.14–2.23; p < 0.01). Higher CRP quartiles were associated with coma (OR, 1.36; 95% CI, 1.03–1.79; p = 0.030) and delirium severity the next day (β = 0.30; se, 0.07; p ≤ 0.01). CONCLUSIONS: Our hypothesis-generating study found d-dimer and ferritin were associated with delirium/coma the following day, as well as delirium and coma independently. CRP was associated with next day coma and delirium severity. Larger studies to validate these results are needed.

AbstractNon‐Hodgkin lymphoma (NHL) is composed of a heterogeneous collection of subtypes with considerable differences in genetics, biology and aetiology. Studies to date on physical activity and NHL risk have not had sufficient sample size to evaluate whether associations differ by subtype. We pooled data from nine case‐control studies to examine the association between moderate‐to‐vigorous intensity physical activity (MVPA) and risk of NHL overall and by subtype (diffuse large B‐cell lymphoma, follicular lymphoma, chronic lymphocytic leukaemia/small lymphocytic lymphoma, marginal zone lymphoma and mature T‐cell lymphoma). A total of 5653 cases and 9115 controls were included in the pooled analysis. Physical activity was harmonised across nine studies and modelled as study‐specific tertiles. Multinomial logistic regression was used to estimate the association between physical activity and NHL, adjusting for confounders. The overall odds of NHL was 13% lower among participants in the most active tertile of MVPA compared to the least active tertile (adjusted odds ratio = 0.87, 95% CI = 0.80, 0.95). Similar decreases were observed across NHL subtypes. In summary, in this pooled analysis of case‐control studies, physical activity was associated with a modest risk reduction for each NHL subtype examined and with overall NHL.

AbstractBackgroundReproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear.MethodsAnalyses included up to 23 353 cases and 71 072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2–like, HER2-enriched–like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided.ResultsCompared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2–like, and HER2-enriched–like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity &lt; .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity &lt; .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like.ConclusionsThis large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction.

Abstract Background: A previous International Lymphoma Epidemiology (InterLymph) Consortium evaluation of joint associations between five immune gene variants and autoimmune conditions reported interactions between B-cell response-mediated autoimmune conditions and the rs1800629 genotype on risk of B-cell non–Hodgkin lymphoma (NHL) subtypes. Here, we extend that evaluation using NHL subtype-specific polygenic risk scores (PRS) constructed from loci identified in genome-wide association studies of three common B-cell NHL subtypes. Methods: In a pooled analysis of NHL cases and controls of Caucasian descent from 14 participating InterLymph studies, we evaluated joint associations between B-cell–mediated autoimmune conditions and tertile (T) of PRS for risk of diffuse large B-cell lymphoma (DLBCL; n = 1,914), follicular lymphoma (n = 1,733), and marginal zone lymphoma (MZL; n = 407), using unconditional logistic regression. Results: We demonstrated a positive association of DLBCL PRS with DLBCL risk [T2 vs. T1: OR = 1.24; 95% confidence interval (CI), 1.08–1.43; T3 vs. T1: OR = 1.81; 95% CI, 1.59–2.07; P-trend (Ptrend) &lt; 0.0001]. DLBCL risk also increased with increasing PRS tertile among those with an autoimmune condition, being highest for those with a B-cell–mediated autoimmune condition and a T3 PRS [OR = 6.46 vs. no autoimmune condition and a T1 PRS, Ptrend &lt; 0.0001, P-interaction (Pinteraction) = 0.49]. Follicular lymphoma and MZL risk demonstrated no evidence of joint associations or significant Pinteraction. Conclusions: Our results suggest that PRS constructed from currently known subtype-specific loci may not necessarily capture biological pathways shared with autoimmune conditions. Impact: Targeted genetic (PRS) screening among population subsets with autoimmune conditions may offer opportunities for identifying those at highest risk for (and early detection from) DLBCL.

Genome-wide association studies (GWAS) have identified more than 200 susceptibility loci for breast cancer, but these variants explain less than a fifth of the disease risk. Although gene–environment interactions have been proposed to account for some of the remaining heritability, few studies have empirically assessed this. We obtained genotype and risk factor data from 46,060 cases and 47,929 controls of European ancestry from population-based studies within the Breast Cancer Association Consortium (BCAC). We built gene expression prediction models for 4,864 genes with a significant (P &lt; 0.01) heritable component using the transcriptome and genotype data from the Genotype-Tissue Expression (GTEx) project. We leveraged predicted gene expression information to investigate the interactions between gene-centric genetic variation and 14 established risk factors in association with breast cancer risk, using a mixed-effects score test. After adjusting for number of tests using Bonferroni correction, no interaction remained statistically significant. The strongest interaction observed was between the predicted expression of the C13orf45 gene and age at first full-term pregnancy (PGXE = 4.44 × 10−6). In this transcriptome-informed genome-wide gene–environment interaction study of breast cancer, we found no strong support for the role of gene expression in modifying the associations between established risk factors and breast cancer risk. Our study suggests a limited role of gene–environment interactions in breast cancer risk.

AbstractEvidence for the human health effects of pesticides is needed to inform risk assessment. We studied the relationship between occupational insecticide use and risk of non‐Hodgkin lymphoma (NHL) by pooling data from nine case‐control studies participating in the InterLymph Consortium, including 7909 cases and 8644 controls from North America, the European Union and Australia. Insecticide use was coded using self‐report or expert assessment, for insecticide groups (eg, organophosphates, pyrethroids) and active ingredients (eg, malathion, permethrin). Associations with insecticides were estimated using logistic regression to produce odds ratios (ORs) and 95% confidence intervals (CI) for all NHL and NHL subtypes, with adjustment for study site, demographic factors and use of other pesticides. Occupational insecticide use, overall, was not associated with risk of NHL. Use of organophosphate insecticides was associated with increased risk of all NHL and the subtype follicular lymphoma, and an association was found with diazinon, in particular (ever use: OR = 2.05, 95%CI: 1.24‐3.37). The carbamate insecticide, carbaryl, was associated with risk of all NHL, and the strongest associations were found with T‐cell NHL for ever‐use (OR = 2.44, 95%CI: 1.13‐5.28) and longer duration (>8 years vs never: OR = 2.90, 95%CI: 1.02‐8.25). There was no association of NHL with other broad groups of insecticides, including organochlorines and pyrethroids, and some inverse associations were estimated in relation to historical DDT use. Our findings contribute to the totality of evidence available to help inform risk decisions by public health and regulatory agencies of importance given continued, widespread use of organophosphate and carbamate insecticides.

AbstractBackgroundEpidemiological studies have demonstrated a positive association between chronic lymphocytic leukaemia (CLL) and non-melanoma skin cancer (NMSC). We hypothesized that shared genetic risk factors between CLL and NMSC could contribute to the association observed between these diseases.MethodsWe examined the association between (i) established NMSC susceptibility loci and CLL risk in a meta-analysis including 3100 CLL cases and 7667 controls and (ii) established CLL loci and NMSC risk in a study of 4242 basal cell carcinoma (BCC) cases, 825 squamous cell carcinoma (SCC) cases and 12802 controls. Polygenic risk scores (PRS) for CLL, BCC and SCC were constructed using established loci. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs).ResultsHigher CLL-PRS was associated with increased BCC risk (OR4th-quartile-vs-1st-quartile = 1.13, 95% CI: 1.02–1.24, Ptrend = 0.009), even after removing the shared 6p25.3 locus. No association was observed with BCC-PRS and CLL risk (Ptrend = 0.68). These findings support a contributory role for CLL in BCC risk, but not for BCC in CLL risk. Increased CLL risk was observed with higher SCC-PRS (OR4th-quartile-vs-1st-quartile = 1.22, 95% CI: 1.08–1.38, Ptrend = 1.36 × 10–5), which was driven by shared genetic susceptibility at the 6p25.3 locus.ConclusionThese findings highlight the role of pleiotropy regarding the pathogenesis of CLL and NMSC and shows that a single pleiotropic locus, 6p25.3, drives the observed association between genetic susceptibility to SCC and increased CLL risk. The study also provides evidence that genetic susceptibility for CLL increases BCC risk.

Abstract Background: It is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype. Methods: We analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer–specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype. Results: There was no evidence of heterogeneous associations between risk factors and mortality by subtype (Padj &gt; 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5–25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06–1.34)]; current versus never smoking [1.37 (1.27–1.47)], high versus low physical activity [0.43 (0.21–0.86)], age ≥30 years versus &lt;20 years at first pregnancy [0.79 (0.72–0.86)]; &gt;0–&lt;5 years versus ≥10 years since last full-term birth [1.31 (1.11–1.55)]; ever versus never use of oral contraceptives [0.91 (0.87–0.96)]; ever versus never use of menopausal hormone therapy, including current estrogen–progestin therapy [0.61 (0.54–0.69)]. Similar associations with breast cancer mortality were weaker; for example, 1.11 (1.02–1.21) for current versus never smoking. Conclusions: We confirm associations between modifiable lifestyle factors and 10-year all-cause mortality. There was no strong evidence that associations differed by ER status or intrinsic-like subtype. Impact: Given the large dataset and lack of evidence that associations between modifiable risk factors and 10-year mortality differed by subtype, these associations could be cautiously used in prognostication models to inform patient-centered care.

Abstract Background. The strongest established prognostic factors for follicular lymphoma are age and clinical factors. Biologic studies suggest a major role for the host immunologic environment in follicular lymphomagenesis, which is in part determined by host genetic background. Cytokines are key regulators of immune function and regulation, are highly polymorphic, and have been implicated in lymphoma etiology and prognosis. We evaluated the hypothesis that inherited variability in cytokine and related immune genes impact overall survival in follicular lymphoma. Methods. We genotyped 73 single nucleotide polymorphisms (SNPs) from 44 candidate cytokine and immune genes in 278 follicular lymphoma patients who participated in a population-based case-control study conducted from 1998–2000 in the Detroit, Iowa, Los Angeles and Seattle SEER (Surveillance, Epidemiology and End Results) cancer registries. Baseline clinical data and survival through early 2005 were obtained from cancer registry files. Cox proportional hazards analysis was used to estimate hazard ratios (HR) and corresponding 95% confidence intervals for the association between individual SNPs and overall survival, adjusting for age, demographic and clinical factors. We also used parallel modeling strategies to identify the best summary multi-SNP risk score to predict survival, and applied these results in a time-dependent receiver-operator characteristics (ROC) analysis. Results. The median age at diagnosis was 57 years (range, 25–74), and 59 (21%) of the patients died during follow-up, with a median follow-up of 59 months (range, 27 – 78 months) for surviving patients. In multivariate modeling, SNPs in IL8 (rs4073; HRTT=2.14, 1.26–3.63), IL2 (rs2069762; HRGT/TT=1.80, 1.06–3.05), IL12B (rs3212227; HRAA/CC=1.83, 1.06–3.06), and IL1RN (rs454078; HRAA=1.93, 1.11–3.34) were the strongest and most robust predictors of survival. A summary score of the number of deleterious genotypes from these four genes was strongly associated with survival (p=1.4 × 10−5) after accounting for demographic and clinical variables (HR=2.06 per deleterious genotype, 1.52–2.79). A combination of the four SNPs and the demographic and clinical risk scores was strongly associated with survival (p=1.8 × 10−11); the 5-year Kaplan Meier survival estimates were 96% (93%–100%), 72% (62%–83%) and 58% (48%–72%) for low, intermediate, and high risk groups respectively. In a time-dependent ROC analysis the three risk groups had an area under the curve (AUC) of 0.83 at 72 months of follow-up (95% CI 0.72–0.93). Conclusion: Host genetic variability in immune genes, particularly IL8, IL2, IL12B, and IL1RN, individually and particularly in combination, was associated with overall survival in follicular lymphoma after accounting for demographic and clinical factors. Host immunogenetics is a promising class of prognostic factors in follicular lymphoma that warrants further evaluation.

Abstract Background: Several studies suggest that smoking and obesity may increase the risk of developing NHL, but the impact of these factors on survival is relatively unexplored. One recent population-based Italian study found that smoking may negatively impact overall survival. Methods: We evaluated the association of body mass index (BMI) and cigarette smoking on overall survival in 1,286 patients who participated in a population-based case-control study conducted through the Surveillance, Epidemiology, and End Results (SEER) cancer registries in Detroit, Iowa, Seattle and Los Angeles. BMI (on 1189 participants) and a smoking history (on 471 participants) were obtained through in-person interviews. Histology, stage, presence of B symptoms, first course of therapy, date of last follow-up, and vital status were derived from linkage to registry databases at each study site in the spring of 2005. Hazard Ratios (HRs) and 95% confidence intervals were estimated using Cox proportional hazards models, while adjusting for demographic and clinical factors. Results: The median age at diagnosis was 58 years (range: 16 – 74), and the most common histologies were DLBCL (33%), follicular (25%), SLL/CLL (12%), marginal zone (9%), mantle cell (4%) and Peripheral T-cell (3%). The median BMI was 26.6 (range: 16.2 – 47.3), and 26% of patients were classified as obese (i.e. BMI &gt;30). Of patients with a smoking history, 47% had never smoked, 19% were active smokers at diagnosis, and 34% were former smokers. No significant differences were observed between those with and without tobacco use data in terms of primary lymphoma characteristics. Overall survival (OS) was defined as time from diagnosis to death due to any cause. Median follow-up on all living patients was 58 months (range: 4 – 78), and 333 patients had died. When BMI was assessed as a continuous measure, it was borderline significantly associated with OS (p=0.050). An indicator of whether or not BMI &gt; 30 was also significantly associated with OS (HR=1.30; 95% CI: 1.01 – 1.68; p=0.042). Ever vs. never smokers also exhibited a survival disadvantage (HR=1.66; 95% CI: 1.12 – 2.44; p=0.011). When broken down further, former smokers who had smoked for &gt;10 years (HR=1.61; 95% CI: 1.02 – 2.52; p=0.039) and current smokers (HR=1.79; 95% CI: 1.07 – 3.02; p=0.028) were at a survival disadvantage over those who had never smoked. When both smoking and BMI status were included in the model, only the indicator of being a current smoker remained statistically significant (p=0.031), with a trend toward decreased survival for former smokers who had smoked &gt;10 years (p=0.061) and those with BMI &gt;30 (p=0.058). Conclusions: NHL patients who smoke or are obese had a poorer overall survival. These observations warrant further investigation, including whether interventions for smoking cessation or weight loss can impact NHL survival.