Identifying therapeutic targets for cancer among 2074 circulating proteins and risk of nine cancers

Circulating proteins can reveal key pathways to cancer and identify therapeutic targets for cancer prevention. We investigate 2,074 circulating proteins and risk of nine common cancers (bladder, breast, endometrium, head and neck, lung, ovary, pancreas, kidney, and malignant non-melanoma) using cis protein Mendelian randomisation and colocalization. We conduct additional analyses to identify adverse side-effects of altering risk proteins and map cancer risk proteins to drug targets. Here we find 40 proteins associated with common cancers, such as PLAUR and risk of breast cancer [odds ratio per standard deviation increment: 2.27, 1.88-2.74], and with high-mortality cancers, such as CTRB1 and pancreatic cancer [0.79, 0.73-0.85]. We also identify potential adverse effects of protein-altering interventions to reduce cancer risk, such as hypertension. Additionally, we report 18 proteins associated with cancer risk that map to existing drugs and 15 that are not currently under clinical investigation. In sum, we identify protein-cancer links that improve our understanding of cancer aetiology. We also demonstrate that the wider consequence of any protein-altering intervention on well-being and morbidity is required to interpret any utility of proteins as potential future targets for therapeutic prevention.

Interaction between Continuous Pack-Years Smoked and Polygenic Risk Score on Lung Cancer Risk: Prospective Results from the Framingham Heart Study

BACKGROUND

Lung cancer risk attributable to smoking is dose dependent, yet few studies examining a polygenic risk score (PRS) by smoking interaction have included comprehensive lifetime pack-years smoked.

METHODS

We analyzed data from participants of European ancestry in the Framingham Heart Study Original (n = 454) and Offspring (n = 2,470) cohorts enrolled in 1954 and 1971, respectively, and followed through 2018. We built a PRS for lung cancer using participant genotyping data and genome-wide association study summary statistics from a recent study in the OncoArray Consortium. We used Cox proportional hazards regression models to assess risk and the interaction between pack-years smoked and genetic risk for lung cancer adjusting for European ancestry, age, sex, and education.

RESULTS

We observed a significant submultiplicative interaction between pack-years and PRS on lung cancer risk (P = 0.09). Thus, the relative risk associated with each additional 10 pack-years smoked decreased with increasing genetic risk (HR = 1.56 at one SD below mean PRS, HR = 1.48 at mean PRS, and HR = 1.40 at one SD above mean PRS). Similarly, lung cancer risk per SD increase in the PRS was highest among those who had never smoked (HR = 1.55) and decreased with heavier smoking (HR = 1.32 at 30 pack-years).

CONCLUSIONS

These results suggest the presence of a submultiplicative interaction between pack-years and genetics on lung cancer risk, consistent with recent findings. Both smoking and genetics were significantly associated with lung cancer risk.

IMPACT

These results underscore the contributions of genetics and smoking on lung cancer risk and highlight the negative impact of continued smoking regardless of genetic risk.

Genomic Insights for Personalized Care: Motivating At-Risk Individuals Toward Evidence-Based Health Practices

Lung cancer and tobacco use pose significant global health challenges and require a comprehensive translational roadmap for improved prevention strategies. We propose the GREAT care paradigm ( G enomic Informed Care for Motivating High R isk Individuals E ligible for Evidence-b a sed Prevention), which employs polygenic risk scores (PRSs) to stratify disease risk and personalize interventions, such as lung cancer screening and tobacco treatment. We developed PRSs using large-scale multi-ancestry genome-wide association studies and adjusted for genetic ancestry for standardized risk stratification across diverse populations. We applied our PRSs to over 340,000 individuals of diverse ethnic background and found significant odds ratios for lung cancer and difficulty quitting smoking. These findings enable the evaluation of PRS-based interventions in ongoing trials aimed at motivating health behavior changes in high-risk patients. This pioneering approach enhances primary care with genomic insights, promising improved outcomes in cancer prevention and tobacco treatment, and is currently under assessment in clinical trials.

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls

BACKGROUND

Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated.

METHODS

The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established. The prediction models were applied to a fixed-effect meta-analysis of screening data sets with 27,120 NSCLC cases and 27,355 controls to identify the methylation markers, which were then replicated in independent data sets with 7844 lung cancer cases and 421,224 controls. Also performed was a multi-omics functional annotation for the identified CpGs by integrating genomics, epigenomics, and transcriptomics and investigation of the potential regulation pathways.

RESULTS

Of the 29,894 CpG sites passing the quality control, 39 CpGs associated with NSCLC risk (Bonferroni-corrected p ≤ 1.67 × 10-6 ) were originally identified. Of these, 16 CpGs remained significant in the validation stage (Bonferroni-corrected p ≤ 1.28 × 10-3 ), including four novel CpGs. Multi-omics functional annotation showed nine of 16 CpGs were potentially functional biomarkers for NSCLC risk. Thirty-five genes within a 1-Mb window of 12 CpGs that might be involved in regulatory pathways of NSCLC risk were identified.

CONCLUSIONS

Sixteen promising DNA methylation markers associated with NSCLC were identified. Changes of the methylation level at these CpGs might influence the development of NSCLC by regulating the expression of genes nearby.

PLAIN LANGUAGE SUMMARY

The epigenetic consequences of DNA methylation in lung cancer development are still largely unknown. This study used summary data of large-scale genome-wide association studies to investigate the associations between genetically predicted levels of methylation biomarkers and non-small cell lung cancer risk at the first time. This study looked at how well larotrectinib worked in adult patients with sarcomas caused by TRK fusion proteins. These findings will provide a unique insight into the epigenetic susceptibility mechanisms of lung cancer.

Radiomics analysis to predict pulmonary nodule malignancy using machine learning approaches

BACKGROUND

Low-dose CT screening can reduce lung cancer-related mortality. However, most screen-detected pulmonary abnormalities do not develop into cancer and it often remains challenging to identify malignant nodules, particularly among indeterminate nodules. We aimed to develop and assess prediction models based on radiological features to discriminate between benign and malignant pulmonary lesions detected on a baseline screen.

METHODS

Using four international lung cancer screening studies, we extracted 2060 radiomic features for each of 16 797 nodules (513 malignant) among 6865 participants. After filtering out low-quality radiomic features, 642 radiomic and 9 epidemiological features remained for model development. We used cross-validation and grid search to assess three machine learning (ML) models (eXtreme Gradient Boosted Trees, random forest, least absolute shrinkage and selection operator (LASSO)) for their ability to accurately predict risk of malignancy for pulmonary nodules. We report model performance based on the area under the curve (AUC) and calibration metrics in the held-out test set.

RESULTS

The LASSO model yielded the best predictive performance in cross-validation and was fit in the full training set based on optimised hyperparameters. Our radiomics model had a test-set AUC of 0.93 (95% CI 0.90 to 0.96) and outperformed the established Pan-Canadian Early Detection of Lung Cancer model (AUC 0.87, 95% CI 0.85 to 0.89) for nodule assessment. Our model performed well among both solid (AUC 0.93, 95% CI 0.89 to 0.97) and subsolid nodules (AUC 0.91, 95% CI 0.85 to 0.95).

CONCLUSIONS

We developed highly accurate ML models based on radiomic and epidemiological features from four international lung cancer screening studies that may be suitable for assessing indeterminate screen-detected pulmonary nodules for risk of malignancy.

Risk model-based management for second primary lung cancer among lung cancer survivors through a validated risk prediction model

BACKGROUND

Recent therapeutic advances and screening technologies have improved survival among patients with lung cancer, who are now at high risk of developing second primary lung cancer (SPLC). Recently, an SPLC risk-prediction model (called SPLC-RAT) was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. The predictive performance of SPLC-RAT was evaluated in a hospital-based cohort of lung cancer survivors.

METHODS

The authors analyzed data from 8448 ever-smoking patients diagnosed with initial primary lung cancer (IPLC) in 1997-2006 at Mayo Clinic, with each patient followed for SPLC through 2018. The predictive performance of SPLC-RAT and further explored the potential of improving SPLC detection through risk model-based surveillance using SPLC-RAT versus existing clinical surveillance guidelines.

RESULTS

Of 8448 IPLC patients, 483 (5.7%) developed SPLC over 26,470 person-years. The application of SPLC-RAT showed high discrimination area under the receiver operating characteristics curve: 0.81). When the cohort was stratified by a 10-year risk threshold of ≥5.6% (i.e., 80th percentile from the SPLC-RAT development cohort), the observed SPLC incidence was significantly elevated in the high-risk versus low-risk subgroup (13.1% vs. 1.1%, p < 1 × 10-6 ). The risk-based surveillance through SPLC-RAT (≥5.6% threshold) outperformed the National Comprehensive Cancer Network guidelines with higher sensitivity (86.4% vs. 79.4%) and specificity (38.9% vs. 30.4%) and required 20% fewer computed tomography follow-ups needed to detect one SPLC (162 vs. 202).

CONCLUSION

In a large, hospital-based cohort, the authors validated the predictive performance of SPLC-RAT in identifying high-risk survivors of SPLC and showed its potential to improve SPLC detection through risk-based surveillance.

PLAIN LANGUAGE SUMMARY

Lung cancer survivors have a high risk of developing second primary lung cancer (SPLC). However, no evidence-based guidelines for SPLC surveillance are available for lung cancer survivors. Recently, an SPLC risk-prediction model was developed and validated using data from population-based epidemiological cohorts and clinical trials, but real-world validation has been lacking. Using a large, real-world cohort of lung cancer survivors, we showed the high predictive accuracy and risk-stratification ability of the SPLC risk-prediction model. Furthermore, we demonstrated the potential to enhance efficiency in detecting SPLC using risk model-based surveillance strategies compared to the existing consensus-based clinical guidelines, including the National Comprehensive Cancer Network.

Canadian COVID-19 host genetics cohort replicates known severity associations

The HostSeq initiative recruited 10,059 Canadians infected with SARS-CoV-2 between March 2020 and March 2023, obtained clinical information on their disease experience and whole genome sequenced (WGS) their DNA. We analyzed the WGS data for genetic contributors to severe COVID-19 (considering 3,499 hospitalized cases and 4,975 non-hospitalized after quality control). We investigated the evidence for replication of loci reported by the International Host Genetics Initiative (HGI); analyzed the X chromosome; conducted rare variant gene-based analysis and polygenic risk score testing. Population stratification was adjusted for using meta-analysis across ancestry groups. We replicated two loci identified by the HGI for COVID-19 severity: the LZTFL1/SLC6A20 locus on chromosome 3 and the FOXP4 locus on chromosome 6 (the latter with a variant significant at P < 5E-8). We found novel significant associations with MRAS and WDR89 in gene-based analyses, and constructed a polygenic risk score that explained 1.01% of the variance in severe COVID-19. This study provides independent evidence confirming the robustness of previously identified COVID-19 severity loci by the HGI and identifies novel genes for further investigation.

Lung Cancer in Ever- and Never-Smokers: Findings from Multi-Population GWAS Studies

BACKGROUND

Clinical, molecular, and genetic epidemiology studies displayed remarkable differences between ever- and never-smoking lung cancer.

METHODS

We conducted a stratified multi-population (European, East Asian, and African descent) association study on 44,823 ever-smokers and 20,074 never-smokers to identify novel variants that were missed in the non-stratified analysis. Functional analysis including expression quantitative trait loci (eQTL) colocalization and DNA damage assays, and annotation studies were conducted to evaluate the functional roles of the variants. We further evaluated the impact of smoking quantity on lung cancer risk for the variants associated with ever-smoking lung cancer.

RESULTS

Five novel independent loci, GABRA4, intergenic region 12q24.33, LRRC4C, LINC01088, and LCNL1 were identified with the association at two or three populations (P < 5 × 10-8). Further functional analysis provided multiple lines of evidence suggesting the variants affect lung cancer risk through excessive DNA damage (GABRA4) or cis-regulation of gene expression (LCNL1). The risk of variants from 12 independent regions, including the well-known CHRNA5, associated with ever-smoking lung cancer was evaluated for never-smokers, light-smokers (packyear ≤ 20), and moderate-to-heavy-smokers (packyear > 20). Different risk patterns were observed for the variants among the different groups by smoking behavior.

CONCLUSIONS

We identified novel variants associated with lung cancer in only ever- or never-smoking groups that were missed by prior main-effect association studies.

IMPACT

Our study highlights the genetic heterogeneity between ever- and never-smoking lung cancer and provides etiologic insights into the complicated genetic architecture of this deadly cancer.

CYP2A6 Activity and Cigarette Consumption Interact in Smoking-Related Lung Cancer Susceptibility

Cigarette smoke, containing both nicotine and carcinogens, causes lung cancer. However, not all smokers develop lung cancer, highlighting the importance of the interaction between host susceptibility and environmental exposure in tumorigenesis. Here, we aimed to delineate the interaction between metabolizing ability of tobacco carcinogens and smoking intensity in mediating genetic susceptibility to smoking-related lung tumorigenesis. Single-variant and gene-based associations of 43 tobacco carcinogen-metabolizing genes with lung cancer were analyzed using summary statistics and individual-level genetic data, followed by causal inference of Mendelian randomization, mediation analysis, and structural equation modeling. Cigarette smoke-exposed cell models were used to detect gene expression patterns in relation to specific alleles. Data from the International Lung Cancer Consortium (29,266 cases and 56,450 controls) and UK Biobank (2,155 cases and 376,329 controls) indicated that the genetic variant rs56113850 C>T located in intron 4 of CYP2A6 was significantly associated with decreased lung cancer risk among smokers (OR = 0.88, 95% confidence interval = 0.85-0.91, P = 2.18 × 10-16), which might interact (Pinteraction = 0.028) with and partially be mediated (ORindirect = 0.987) by smoking status. Smoking intensity accounted for 82.3% of the effect of CYP2A6 activity on lung cancer risk but entirely mediated the genetic effect of rs56113850. Mechanistically, the rs56113850 T allele rescued the downregulation of CYP2A6 caused by cigarette smoke exposure, potentially through preferential recruitment of transcription factor helicase-like transcription factor. Together, this study provides additional insights into the interplay between host susceptibility and carcinogen exposure in smoking-related lung tumorigenesis.

SIGNIFICANCE

The causal pathway connecting CYP2A6 genetic variability and activity, cigarette consumption, and lung cancer susceptibility in smokers highlights the need for behavior modification interventions based on host susceptibility for cancer prevention.

Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification

BACKGROUND

Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored.

METHODS

Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold.

RESULTS

Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12-3.50, P-value = 4.13 × 10-15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99-2.49, P-value = 5.70 × 10-46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72-0.74).

CONCLUSIONS

Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.

Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

BACKGROUND

Tumour-promoting inflammation is a "hallmark" of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear.

METHODS

We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combined cis-Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,294 cancer cases and up to 1,238,345 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant (P < 5.0 × 10-8) cis-acting SNPs (i.e., in or ±250 kb from the gene encoding the relevant protein) in weak linkage disequilibrium (LD, r2 < 0.10). Effect estimates were generated using inverse-variance weighted random-effects models and standard errors were inflated to account for weak LD between variants with reference to the 1000 Genomes Phase 3 CEU panel. A false discovery rate (FDR)-corrected P-value ("q-value") <0.05 was used as a threshold to define "strong evidence" to support associations and 0.05 ≤ q-value < 0.20 to define "suggestive evidence". A colocalisation posterior probability (PPH4) >70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes. Findings were replicated in the FinnGen study and then pooled using meta-analysis.

FINDINGS

We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR: 1.19, 95% CI: 1.10-1.29, q-value = 0.033, PPH4 = 84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR: 1.42, 95% CI: 1.20-1.69, q-value = 0.055, PPH4 = 73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR: 0.66, 95% CI: 0.53-0.81, q-value = 0.067, PPH4 = 81.8%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR: 0.92, 95% CI: 0.88-0.97, q-value = 0.15, PPH4 = 85.6%). These findings were replicated in pooled analyses with the FinnGen study. Though suggestive evidence was found to support an association of macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR: 2.46, 95% CI: 1.48-4.10, q-value = 0.072, PPH4 = 76.1%), this finding was not replicated when pooled with the FinnGen study. For 22 of 30 cancer outcomes examined, there was little evidence (q-value ≥0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk.

INTERPRETATION

Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 4 circulating inflammatory markers in risk of 4 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated.

FUNDING

Cancer Research UK (C68933/A28534, C18281/A29019, PPRCPJT∖100005), World Cancer Research Fund (IIG_FULL_2020_022), National Institute for Health Research (NIHR202411, BRC-1215-20011), Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4), Academy of Finland Project 326291, European Union's Horizon 2020 grant agreement no. 848158 (EarlyCause), French National Cancer Institute (INCa SHSESP20, 2020-076), Versus Arthritis (21173, 21754, 21755), National Institutes of Health (U19 CA203654), National Cancer Institute (U19CA203654).

Diagnostic accuracy of HPV16 early antigen serology for HPV-driven oropharyngeal cancer is independent of age and sex

A growing proportion of head and neck cancer (HNC), especially oropharyngeal cancer (OPC), is caused by human papillomavirus (HPV). There are several markers for HPV-driven HNC, one being HPV early antigen serology. We aimed to investigate the diagnostic accuracy of HPV serology and its performance across patient characteristics. Data from the VOYAGER consortium was used, which comprises five studies on HNC from North America and Europe. Diagnostic accuracy, that is, sensitivity, specificity, Cohen's kappa and correctly classified proportions of HPV16 E6 serology, was assessed for OPC and other HNC using p16INK4a immunohistochemistry (p16), HPV in situ hybridization (ISH) and HPV PCR as reference methods. Stratified analyses were performed for variables including age, sex, smoking and alcohol use, to test the robustness of diagnostic accuracy. A risk-factor analysis based on serology was conducted, comparing HPV-driven to non-HPV-driven OPC. Overall, HPV serology had a sensitivity of 86.8% (95% CI 85.1-88.3) and specificity of 91.2% (95% CI 88.6-93.4) for HPV-driven OPC using p16 as a reference method. In stratified analyses, diagnostic accuracy remained consistent across sex and different age groups. Sensitivity was lower for heavy smokers (77.7%), OPC without lymph node involvement (74.4%) and the ARCAGE study (66.7%), while specificity decreased for cases with <10 pack-years (72.1%). The risk-factor model included study, year of diagnosis, age, sex, BMI, alcohol use, pack-years, TNM-T and TNM-N stage. HPV serology is a robust biomarker for HPV-driven OPC, and its diagnostic accuracy is independent of age and sex. Future research is suggested on the influence of smoking on HPV antibody levels.

Ethnic differences of genetic risk and smoking in lung cancer: two prospective cohort studies

BACKGROUND

The role of genetic background underlying the disparity of relative risk of smoking and lung cancer between European populations and East Asians remains unclear.

METHODS

To assess the role of ethnic differences in genetic factors associated with smoking-related risk of lung cancer, we first constructed ethnic-specific polygenic risk scores (PRSs) to quantify individual genetic risk of lung cancer in Chinese and European populations. Then, we compared genetic risk and smoking as well as their interactions on lung cancer between two cohorts, including the China Kadoorie Biobank (CKB) and the UK Biobank (UKB). We also evaluated the absolute risk reduction over a 5-year period.

RESULTS

Differences in compositions and association effects were observed between the Chinese-specific PRSs and European-specific PRSs, especially for smoking-related loci. The PRSs were consistently associated with lung cancer risk, but stronger associations were observed in smokers of the UKB [hazard ratio (HR) 1.26 vs 1.15, P  =  0.028]. A significant interaction between genetic risk and smoking on lung cancer was observed in the UKB (RERI, 11.39 (95% CI, 7.01-17.94)], but not in the CKB. Obvious higher absolute risk was observed in nonsmokers of the CKB, and a greater absolute risk reduction was found in the UKB (10.95 vs 7.12 per 1000 person-years, P <0.001) by comparing heavy smokers with nonsmokers, especially for those at high genetic risk.

CONCLUSIONS

Ethnic differences in genetic factors and the high incidence of lung cancer in nonsmokers of East Asian ethnicity were involved in the disparity of smoking-related risk of lung cancer.

Maternal major depression during early pregnancy is associated with impaired child executive functioning at 4.5 years of age

BACKGROUND

Maternal depression is a serious condition that affects up to 1 in 7 pregnancies. Despite evidence linking maternal depression to pregnancy complications and adverse fetal outcomes, there remain large gaps in its identification and treatment. More work is needed to define the specific timing and severity of depression that most urgently requires intervention, where feasible, to protect maternal health and the developing fetus.

OBJECTIVE

This study aimed to examine whether the timing and severity of maternal depression and/or anxiety during pregnancy affect child executive functioning at age 4.5 years. Executive functioning in the preschool years is a strong predictor of both school readiness and long-term quality of life.

STUDY DESIGN

This longitudinal observational pregnancy cohort study included a sample of 323 mother-child dyads taking part in the Ontario Birth Study, an open pregnancy cohort in Toronto, Ontario, Canada. Maternal symptoms of depression and anxiety were assessed at 12 to 16 and 28 to 32 weeks of gestation and at the time of child testing at age 4.5 years using the 4-item Patient Health Questionnaire. Child executive functioning was measured during a home visit using standardized computerized administration of the Flanker test (a measure of attention) and the Dimensional Change Card Sort (a measure of cognitive flexibility). Stepwise linear regressions, controlling for possible confounding variables, were used to assess the predictive value of continuous measures of maternal depression and/or anxiety symptoms at each assessment time on the Flanker test and Dimensional Change Card Sort. Posthoc general linear models were used to assess whether maternal depression severity categories (no symptom, mild symptoms, or probable major depressive disorder) were helpful in identifying children at risk.

RESULTS

Across all children, after controlling for potential confounds, greater maternal depressive symptoms at weeks 12 to 16 weeks of gestation predicted worse performance on both the Flanker test (ΔR2=0.058; P<.001) and the Dimensional Change Card Sort (ΔR2=0.017; P=.018). Posthoc general linear modeling further demonstrated that the children of mothers meeting the screening criteria for major depression in early pregnancy scored 11.3% lower on the Flanker test and 9.8% lower on the Dimensional Change Card Sort than the children of mothers without maternal depressive symptoms in early pregnancy. Mild depressive symptoms had no significant effect on executive function scores. There was no significant effect of anxiety symptoms or maternal antidepressant use in early pregnancy or pandemic conditions or maternal symptoms in later pregnancy or at the time of child testing on either the Flanker or Dimensional Change Card Sort results.

CONCLUSION

This study demonstrated that fetal exposure to maternal major depression, but not milder forms of depression, at 12 to 16 weeks of gestation is associated with impaired executive functioning in the preschool years. Child executive functioning is crucial for school readiness and predicts long-term quality of life. This emphasizes an urgent need to improve the recognition and treatment of maternal major depression, particularly in early pregnancy, to limit its negative effects on the patient and on child cognitive development.

Cognitive and Emotional Well-Being of Preschool Children Before and During the COVID-19 Pandemic

Importance

The association between COVID-19 social disruption and young children's development is largely unknown.

Objective

To examine associations of pandemic exposure with neurocognitive and socioemotional development at 24 and 54 months of age.

Design, Setting, and Participants

This cross-sectional study evaluated associations between pandemic exposure vs nonexposure and developmental outcomes with covariate adjustment using data from the Ontario Birth Study collected between February 2018 and June 2022. Eligible participants were children aged 24 and 54 months. Data were analyzed from June to November 2022.

Exposure

COVID-19 pandemic exposure defined as assessment after March 11, 2020.

Main Outcome and Measures

Neurodevelopmental assessment using the ASQ-3 (Ages and Stages Questionnaire, Third Edition) and MCHAT-R (Modified Checklist for Autism in Toddlers, Revised) at 24 months of age, and neurocognitive and socioemotional assessment using the National Institutes of Health Toolbox at 54 months of age.

Results

A total of 718 children at age 24 months (mean [SD] age, 25.6 [1.7] months; 342 female [47.6%]; 461 White [64.2%]) and 703 at age 54 months (mean [SD] age, 55.4 [2.6] months; 331 female [47.1%]; 487 White [69.3%]) were included. At 24 months of age, 460 participants (232 female [50.4%]) were assessed during the pandemic (March 17, 2020, to May 17, 2022) and 258 (110 female [42.6%]) were assessed prepandemic (April 17, 2018, to March 10, 2020). At 54 months of age, 286 participants (129 female [45.1%]) were assessed from March 14, 2020, to June 6, 2022, and 417 (202 female [48.4%]) were assessed from February 8, 2018, to March 10, 2020. At 24 months of age, pandemic-exposed children had reduced risk of problem-solving difficulties using cutoff scores (odds ratio [OR], 0.33; 95% CI, 0.18-0.62; P = .005) and higher problem-solving (B, 3.93; 95% CI, 2.48 to 5.38; P < .001) compared with nonexposed children. In contrast, pandemic-exposed children had greater risk for personal-social difficulties using cutoff scores (OR, 1.67; 95% CI, 1.09-2.56; P = .02) and continuous scores (B, -1.70; 95% CI, -3.21 to -0.20; P = .02) compared with nonexposed children. At 54 months of age, pandemic-exposed children had higher receptive vocabulary (B, 3.16; 95% CI, 0.13 to 6.19; P = .04), visual memory (B, 5.95; 95% CI, 1.11 to 10.79; P = .02), and overall cognitive performance (B, 3.89; 95% CI, 0.73 to 7.04; P = .02) compared with nonexposed children, with no differences in socioemotional development.

Conclusions and Relevance

This cross-sectional study found both positive and negative associations between pandemic exposure and preschool children's cognitive and emotional well-being within a relatively socioeconomically advantaged sample.

Design and quality control of large-scale two-sample Mendelian randomization studies

Background

Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors.

Methods

We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set.

Results

We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls.

Conclusions

In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools

BACKGROUND

We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test.

METHODS

We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided.

RESULTS

The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model.

CONCLUSION

Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung.

Circulating proteome for pulmonary nodule malignancy

BACKGROUND

Although lung cancer screening with low-dose computed tomography is rolling out in many areas of the world, differentiating indeterminate pulmonary nodules remains a major challenge. We conducted one of the first systematic investigations of circulating protein markers to differentiate malignant from benign screen-detected pulmonary nodules.

METHODS

Based on 4 international low-dose computed tomography screening studies, we assayed 1078 protein markers using prediagnostic blood samples from 1253 participants based on a nested case-control design. Protein markers were measured using proximity extension assays, and data were analyzed using multivariable logistic regression, random forest, and penalized regressions. Protein burden scores (PBSs) for overall nodule malignancy and imminent tumors were estimated.

RESULTS

We identified 36 potentially informative circulating protein markers differentiating malignant from benign nodules, representing a tightly connected biological network. Ten markers were found to be particularly relevant for imminent lung cancer diagnoses within 1 year. Increases in PBSs for overall nodule malignancy and imminent tumors by 1 standard deviation were associated with odds ratios of 2.29 (95% confidence interval: 1.95 to 2.72) and 2.81 (95% confidence interval: 2.27 to 3.54) for nodule malignancy overall and within 1 year of diagnosis, respectively. Both PBSs for overall nodule malignancy and for imminent tumors were substantially higher for those with malignant nodules than for those with benign nodules, even when limited to Lung Computed Tomography Screening Reporting and Data System (LungRADS) category 4 (P < .001).

CONCLUSIONS

Circulating protein markers can help differentiate malignant from benign pulmonary nodules. Validation with an independent computed tomographic screening study will be required before clinical implementation.

Candidate pathway analysis of surfactant proteins identifies CTSH and SFTA2 that influences lung cancer risk

Pulmonary surfactant is a lipoprotein synthesized and secreted by alveolar type II cells in lung. We evaluated the associations between 200,139 single nucleotide polymorphisms (SNPs) of 40 surfactant-related genes and lung cancer risk using genotyped data from two independent lung cancer genome-wide association studies. Discovery data included 18,082 cases and 13,780 controls of European ancestry. Replication data included 1,914 cases and 3,065 controls of European descent. Using multivariate logistic regression, we found novel SNPs in surfactant-related genes CTSH [rs34577742 C > T, odds ratio (OR) = 0.90, 95% confidence interval (CI) = 0.89-0.93, P = 7.64 × 10-9] and SFTA2 (rs3095153 G > A, OR = 1.16, 95% CI = 1.10-1.21, P = 1.27 × 10-9) associated with overall lung cancer in the discovery data and validated in an independent replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.80-0.96, P = 5.76 × 10-3) and SFTA2 (rs3095153 G > A, OR = 1.14, 95% CI = 1.01-1.28, P = 3.25 × 10-2). Among ever smokers, we found SNPs in CTSH (rs34577742 C > T, OR = 0.89, 95% CI = 0.85-0.92, P = 1.94 × 10-7) and SFTA2 (rs3095152 G > A, OR = 1.20, 95% CI = 1.14-1.27, P = 4.25 × 10-11) associated with overall lung cancer in the discovery data and validated in the replication data-CTSH (rs34577742 C > T, OR = 0.88, 95% CI = 0.79-0.97, P = 1.64 × 10-2) and SFTA2 (rs3095152 G > A, OR = 1.15, 95% CI = 1.01-1.30, P = 3.81 × 10-2). Subsequent transcriptome-wide association study using expression weights from a lung expression quantitative trait loci study revealed genes most strongly associated with lung cancer are CTSH (PTWAS = 2.44 × 10-4) and SFTA2 (PTWAS = 2.32 × 10-6).

Genetic Susceptibility to Nonalcoholic Fatty Liver Disease and Risk for Pancreatic Cancer: Mendelian Randomization

BACKGROUND

There are conflicting data on whether nonalcoholic fatty liver disease (NAFLD) is associated with susceptibility to pancreatic cancer. Using Mendelian randomization (MR), we investigated the relationship between genetic predisposition to NAFLD and risk for pancreatic cancer.

METHODS

Data from genome-wide association studies (GWAS) within the Pancreatic Cancer Cohort Consortium (PanScan; cases n = 5,090, controls n = 8,733) and the Pancreatic Cancer Case Control Consortium (PanC4; cases n = 4,163, controls n = 3,792) were analyzed. We used data on 68 genetic variants with four different MR methods [inverse variance weighting (IVW), MR-Egger, simple median, and penalized weighted median] separately to predict genetic heritability of NAFLD. We then assessed the relationship between each of the four MR methods and pancreatic cancer risk, using logistic regression to calculate ORs and 95% confidence intervals (CI), adjusting for PC risk factors, including obesity and diabetes.

RESULTS

No association was found between genetically predicted NAFLD and pancreatic cancer risk in the PanScan or PanC4 samples [e.g., PanScan, IVW OR, 1.04; 95% confidence interval (CI), 0.88-1.22; MR-Egger OR, 0.89; 95% CI, 0.65-1.21; PanC4, IVW OR, 1.07; 95% CI, 0.90-1.27; MR-Egger OR, 0.93; 95% CI, 0.67-1.28]. None of the four MR methods indicated an association between genetically predicted NAFLD and pancreatic cancer risk in either sample.

CONCLUSIONS

Genetic predisposition to NAFLD is not associated with pancreatic cancer risk.

IMPACT

Given the close relationship between NAFLD and metabolic conditions, it is plausible that any association between NAFLD and pancreatic cancer might reflect host metabolic perturbations (e.g., obesity, diabetes, or metabolic syndrome) and does not necessarily reflect a causal relationship between NAFLD and pancreatic cancer.

Large-scale whole exome sequencing studies identify two genes,CTSL and APOE, associated with lung cancer

Common genetic variants associated with lung cancer have been well studied in the past decade. However, only 12.3% heritability has been explained by these variants. In this study, we investigate the contribution of rare variants (RVs) (minor allele frequency <0.01) to lung cancer through two large whole exome sequencing case-control studies. We first performed gene-based association tests using a novel Bayes Factor statistic in the International Lung Cancer Consortium, the discovery study (European, 1042 cases vs. 881 controls). The top genes identified are further assessed in the UK Biobank (European, 630 cases vs. 172 864 controls), the replication study. After controlling for the false discovery rate, we found two genes, CTSL and APOE, significantly associated with lung cancer in both studies. Single variant tests in UK Biobank identified 4 RVs (3 missense variants) in CTSL and 2 RVs (1 missense variant) in APOE stongly associated with lung cancer (OR between 2.0 and 139.0). The role of these genetic variants in the regulation of CTSL or APOE expression remains unclear. If such a role is established, this could have important therapeutic implications for lung cancer patients.

Association between duration of smoking abstinence before non-small-cell lung cancer diagnosis and survival: a retrospective, pooled analysis of cohort studies

BACKGROUND

The association between duration of smoking abstinence before non-small-cell lung cancer (NSCLC) diagnosis and subsequent survival can influence public health messaging delivered in lung-cancer screening. We aimed to assess whether the duration of smoking abstinence before diagnosis of NSCLC is associated with improved survival.

METHODS

In this retrospective, pooled analysis of cohort studies, we used 26 cohorts participating in Clinical Outcomes Studies of the International Lung Cancer Consortium (COS-ILCCO) at 23 hospitals. 16 (62%) were from North America, six (23%) were from Europe, three (12%) were from Asia, and one (4%) was from South America. Patients enrolled were diagnosed between June 1, 1983, and Dec 31, 2019. Eligible patients had smoking data before NSCLC diagnosis, epidemiological data at diagnosis (obtained largely from patient questionnaires), and clinical information (retrieved from medical records). Kaplan-Meier curves and multivariable Cox models (ie, adjusted hazard ratios [aHRs]) were generated with individual, harmonised patient data from the consortium database. We estimated overall survival for all causes, measured in years from diagnosis date until the date of the last follow-up or death due to any cause and NSCLC-specific survival.

FINDINGS

Of 42 087 patients with NSCLC in the COS-ILCCO database, 21 893 (52·0%) of whom were male and 20 194 (48·0%) of whom were female, we excluded 4474 (10·6%) with missing data. Compared with current smokers (15 036 [40·0%] of 37 613), patients with 1-3 years of smoking abstinence before NSCLC diagnosis (2890 [7·7%]) had an overall survival aHR of 0·92 (95% CI 0·87-0·97), patients with 3-5 years of smoking abstinence (1114 [3·0%]) had an overall survival aHR of 0·90 (0·83-0·97), and patients with more than 5 years of smoking abstinence (10 841 [28·8%]) had an overall survival aHR of 0·90 (0·87-0·93). Improved NSCLC-specific survival was observed in 4301 (44%) of 9727 patients who had quit cigarette smoking and was significant at abstinence durations of more than 5 years (aHR 0·87, 95% CI 0·81-0·93). Results were consistent across age, sex, histology, and disease-stage distributions.

INTERPRETATION

In this large, pooled analysis of cohort studies across Asia, Europe, North America, and South America, overall survival was improved in patients with NSCLC whose duration of smoking abstinence before diagnosis was as short as 1 year. These findings suggest that quitting smoking can improve overall survival, even if NSCLC is diagnosed at a later lung-cancer screening visit. These findings also support the implementation of public health smoking cessation strategies at any time.

FUNDING

The Alan B Brown Chair, The Posluns Family Fund, The Lusi Wong Fund, and the Princess Margaret Cancer Foundation.

Maternal and childhood medical history and the risk of childhood brain tumours: a case-control study in Ontario, Canada

BACKGROUND

Studies to date have yielded inconclusive results as to whether maternal medical history during pregnancy, and a child's early-life medical history contribute to the development of childhood brain tumours (CBTs). This study examined associations between maternal and childhood medical history and the risk of CBTs.

METHODS

The Childhood Brain Tumour Epidemiology Study of Ontario (CBREO) examined children 0-15 years of age with newly diagnosed CBTs from 1997 to 2003. Multivariable logistic regression analysis determined associations for prenatal medications and childhood medical history, adjusted for child's demographics, and maternal education. Analyses were stratified by histology. A latency period analysis was conducted using 12- and 24-month lead times.

RESULTS

Maternal intake of immunosuppressants during the prenatal period was significantly associated with glial tumours (OR 2.73, 95% CI 1.17-6.39). Childhood intake of anti-epileptics was significantly associated with CBTs overall, after accounting for 12-month (OR 8.51, 95% CI 3.35-21.63) and 24-month (OR 6.04, 95% CI 2.06-17.70) lead time before diagnosis. No associations for other medications were found.

CONCLUSIONS

This study underscores the need to examine potential carcinogenic effects of the medication classes highlighted and of the indication of medication use. Despite possible reverse causality, increased CBT surveillance for children with epilepsy might be warranted.

Mosaic Chromosomal Alterations Are Associated With Increased Lung Cancer Risk: Insight From the INTEGRAL-ILCCO Cohort Analysis

INTRODUCTION

Mosaic chromosomal alterations (mCAs) detected in white blood cells represent a type of clonal hematopoiesis (CH) that is understudied compared with CH-related somatic mutations. A few recent studies indicated their potential link with nonhematological cancers, especially lung cancer.

METHODS

In this study, we investigated the association between mCAs and lung cancer using the high-density genotyping data from the OncoArray study of INTEGRAL-ILCCO, the largest single genetic study of lung cancer with 18,221 lung cancer cases and 14,825 cancer-free controls.

RESULTS

We identified a comprehensive list of autosomal mCAs, ChrX mCAs, and mosaic ChrY (mChrY) losses from these samples. Autosomal mCAs were detected in 4.3% of subjects, in addition to ChrX mCAs in 3.6% of females and mChrY losses in 9.6% of males. Multivariable logistic regression analysis indicated that the presence of autosomal mCAs in white blood cells was associated with an increased lung cancer risk after adjusting for key confounding factors, including age, sex, smoking status, and race. This association was mainly driven by a specific type of mCAs: copy-neutral loss of heterozygosity on autosomal chromosomes. The association between autosome copy-neutral loss of heterozygosity and increased risk of lung cancer was further confirmed in two major histologic subtypes, lung adenocarcinoma and squamous cell carcinoma. In addition, we observed a significant increase of ChrX mCAs and mChrY losses in smokers compared with nonsmokers and racial differences in certain types of mCA events.

CONCLUSIONS

Our study established a link between mCAs in white blood cells and increased risk of lung cancer.

Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions

BACKGROUND

The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci.

METHODS

We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci.

RESULTS

We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci.

CONCLUSIONS

Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

The blood proteome of imminent lung cancer diagnosis

Identification of risk biomarkers may enhance early detection of smoking-related lung cancer. We measured between 392 and 1,162 proteins in blood samples drawn at most three years before diagnosis in 731 smoking-matched case-control sets nested within six prospective cohorts from the US, Europe, Singapore, and Australia. We identify 36 proteins with independently reproducible associations with risk of imminent lung cancer diagnosis (all p < 4 × 10-5). These include a few markers (e.g. CA-125/MUC-16 and CEACAM5/CEA) that have previously been reported in studies using pre-diagnostic blood samples for lung cancer. The 36 proteins include several growth factors (e.g. HGF, IGFBP-1, IGFP-2), tumor necrosis factor-receptors (e.g. TNFRSF6B, TNFRSF13B), and chemokines and cytokines (e.g. CXL17, GDF-15, SCF). The odds ratio per standard deviation range from 1.31 for IGFBP-1 (95% CI: 1.17-1.47) to 2.43 for CEACAM5 (95% CI: 2.04-2.89). We map the 36 proteins to the hallmarks of cancer and find that activation of invasion and metastasis, proliferative signaling, tumor-promoting inflammation, and angiogenesis are most frequently implicated.

Genome-wide association study of lung adenocarcinoma in East Asia and comparison with a European population

Lung adenocarcinoma is the most common type of lung cancer. Known risk variants explain only a small fraction of lung adenocarcinoma heritability. Here, we conducted a two-stage genome-wide association study of lung adenocarcinoma of East Asian ancestry (21,658 cases and 150,676 controls; 54.5% never-smokers) and identified 12 novel susceptibility variants, bringing the total number to 28 at 25 independent loci. Transcriptome-wide association analyses together with colocalization studies using a Taiwanese lung expression quantitative trait loci dataset (n = 115) identified novel candidate genes, including FADS1 at 11q12 and ELF5 at 11p13. In a multi-ancestry meta-analysis of East Asian and European studies, four loci were identified at 2p11, 4q32, 16q23, and 18q12. At the same time, most of our findings in East Asian populations showed no evidence of association in European populations. In our studies drawn from East Asian populations, a polygenic risk score based on the 25 loci had a stronger association in never-smokers vs. individuals with a history of smoking (Pinteraction = 0.0058). These findings provide new insights into the etiology of lung adenocarcinoma in individuals from East Asian populations, which could be important in developing translational applications.

A risk prediction model for head and neck cancers incorporating lifestyle factors, HPV serology and genetic markers

Head and neck cancer is often diagnosed late and prognosis for most head and neck cancer patients remains poor. To aid early detection, we developed a risk prediction model based on demographic and lifestyle risk factors, human papillomavirus (HPV) serological markers and genetic markers. A total of 10 126 head and neck cancer cases and 5254 controls from five North American and European studies were included. HPV serostatus was determined by antibodies for HPV16 early oncoproteins (E6, E7) and regulatory early proteins (E1, E2, E4). The data were split into a training set (70%) for model development and a hold-out testing set (30%) for model performance evaluation, including discriminative ability and calibration. The risk models including demographic, lifestyle risk factors and polygenic risk score showed a reasonable predictive accuracy for head and neck cancer overall. A risk model that also included HPV serology showed substantially improved predictive accuracy for oropharyngeal cancer (AUC = 0.94, 95% CI = 0.92-0.95 in men and AUC = 0.92, 95% CI = 0.88-0.95 in women). The 5-year absolute risk estimates showed distinct trajectories by risk factor profiles. Based on the UK Biobank cohort, the risks of developing oropharyngeal cancer among 60 years old and HPV16 seropositive in the next 5 years ranged from 5.8% to 14.9% with an average of 8.1% for men, 1.3% to 4.4% with an average of 2.2% for women. Absolute risk was generally higher among individuals with heavy smoking, heavy drinking, HPV seropositivity and those with higher polygenic risk score. These risk models may be helpful for identifying people at high risk of developing head and neck cancer.

HostSeq: a Canadian whole genome sequencing and clinical data resource

HostSeq was launched in April 2020 as a national initiative to integrate whole genome sequencing data from 10,000 Canadians infected with SARS-CoV-2 with clinical information related to their disease experience. The mandate of HostSeq is to support the Canadian and international research communities in their efforts to understand the risk factors for disease and associated health outcomes and support the development of interventions such as vaccines and therapeutics. HostSeq is a collaboration among 13 independent epidemiological studies of SARS-CoV-2 across five provinces in Canada. Aggregated data collected by HostSeq are made available to the public through two data portals: a phenotype portal showing summaries of major variables and their distributions, and a variant search portal enabling queries in a genomic region. Individual-level data is available to the global research community for health research through a Data Access Agreement and Data Access Compliance Office approval. Here we provide an overview of the collective project design along with summary level information for HostSeq. We highlight several statistical considerations for researchers using the HostSeq platform regarding data aggregation, sampling mechanism, covariate adjustment, and X chromosome analysis. In addition to serving as a rich data source, the diversity of study designs, sample sizes, and research objectives among the participating studies provides unique opportunities for the research community.

The association between genetically elevated polyunsaturated fatty acids and risk of cancer

BACKGROUND

The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain.

METHODS

Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures.

FINDINGS

Genetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07-1.11]), esophageal squamous cell carcinoma (1.16 [1.06-1.26]), lung cancer (1.06 [1.03-1.08]) and basal cell carcinoma (1.05 [1.02-1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99-1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99-1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95-1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98-1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding.

INTERPRETATION

The PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease.

FUNDING

Cancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

Common genetic variations in telomere length genes and lung cancer: a Mendelian randomisation study and its novel application in lung tumour transcriptome

Background

Genome-wide association studies (GWASs) have identified genetic susceptibility variants for both leukocyte telomere length (LTL) and lung cancer susceptibility. Our study aims to explore the shared genetic basis between these traits and investigate their impact on somatic environment of lung tumours.

Methods

We performed genetic correlation, Mendelian randomisation (MR), and colocalisation analyses using the largest available GWASs summary statistics of LTL (N=464,716) and lung cancer (N=29,239 cases and 56,450 controls). Principal components analysis based on RNA-sequencing data was used to summarise gene expression profile in lung adenocarcinoma cases from TCGA (N=343).

Results

Although there was no genome-wide genetic correlation between LTL and lung cancer risk, longer LTL conferred an increased risk of lung cancer regardless of smoking status in the MR analyses, particularly for lung adenocarcinoma. Of the 144 LTL genetic instruments, 12 colocalised with lung adenocarcinoma risk and revealed novel susceptibility loci, including MPHOSPH6, PRPF6, and POLI. The polygenic risk score for LTL was associated with a specific gene expression profile (PC2) in lung adenocarcinoma tumours. The aspect of PC2 associated with longer LTL was also associated with being female, never smokers, and earlier tumour stages. PC2 was strongly associated with cell proliferation score and genomic features related to genome stability, including copy number changes and telomerase activity.

Conclusions

This study identified an association between longer genetically predicted LTL and lung cancer and sheds light on the potential molecular mechanisms related to LTL in lung adenocarcinomas.

Funding

Institut National du Cancer (GeniLuc2017-1-TABAC-03-CIRC-1-TABAC17-022), INTEGRAL/NIH (5U19CA203654-03), CRUK (C18281/A29019), and Agence Nationale pour la Recherche (ANR-10-INBS-09).

A polygenic two-hit hypothesis for prostate cancer

Prostate cancer is one of the most heritable cancers. Hundreds of germline polymorphisms have been linked to prostate cancer diagnosis and prognosis. Polygenic risk scores can predict genetic risk of a prostate cancer diagnosis. Although these scores inform the probability of developing a tumor, it remains unknown how germline risk influences the tumor molecular evolution. We cultivated a cohort of 1250 localized European-descent patients with germline and somatic DNA profiling. Men of European descent with higher genetic risk were diagnosed earlier and had less genomic instability and fewer driver genes mutated. Higher genetic risk was associated with better outcome. These data imply a polygenic "two-hit" model where germline risk reduces the number of somatic alterations required for tumorigenesis. These findings support further clinical studies of polygenic risk scores as inexpensive and minimally invasive adjuncts to standard risk stratification. Further studies are required to interrogate generalizability to more ancestrally and clinically diverse populations.

Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers

BACKGROUND

Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties.

OBJECTIVE

We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors.

METHODS

We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses.

RESULTS

We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31).

CONCLUSIONS

We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Cigarette smoking cessation, duration of smoking abstinence, and head and neck squamous cell carcinoma prognosis

BACKGROUND

Tobacco use is a major risk factor for developing head and neck squamous cell carcinoma (HNSCC). However, the prognostic associations with smoking cessation are limited. The authors assessed whether smoking cessation and increased duration of abstinence were associated with improved overall (OS) and HNSCC-specific survival.

METHODS

Clinicodemographic and smoking data from patients with HNSCC at Princess Margaret Cancer Center (2006-2019) were prospectively collected. Multivariable Cox and Fine and Gray competing-risk models were used to assess the impact of smoking cessation and duration of abstinence on overall mortality and HNSCC-specific/noncancer mortality, respectively.

RESULTS

Among 2482 patients who had HNSCC, former smokers (adjusted hazard ratio [aHR], 0.71; 95% CI, 0.58-0.87; p = .001; N = 841) had a reduced risk of overall mortality compared with current smokers (N = 931). Compared with current smokers, former smokers who quit >10 years before diagnosis (long-term abstinence; n = 615) had the most improved OS (aHR, 0.72; 95% CI, 0.56-0.93; p = .001). The 5-year actuarial rates of HNSCC-specific and noncancer deaths were 16.8% and 9.4%, respectively. Former smokers (aHR, 0.71; 95% CI, 0.54-0.95; p = .019) had reduced HNSCC-specific mortality compared with current smokers, but there was no difference in noncancer mortality. Abstinence for >10 years was associated with decreased HNSCC-specific death compared with current smoking (aHR, 0.64; 95% CI, 0.46-0.91; p = .012). Smoking cessation with a longer duration of quitting was significantly associated with reduced overall and HNSCC-specific mortality in patients who received primary radiation.

CONCLUSIONS

Smoking cessation before the time of diagnosis reduced overall mortality and cancer-specific mortality among patients with HNSCC, but no difference was observed in noncancer mortality. Long-term abstinence (>10 pack-years) had a significant OS and HNSCC-specific survival benefit.

Using Recurrent Neural Networks to Extract High-Quality Information From Lung Cancer Screening Computerized Tomography Reports for Inter-Radiologist Audit and Feedback Quality Improvement

PURPOSE

Lung cancer screening programs generate a high volume of low-dose computed tomography (LDCT) reports that contain valuable information, typically in a free-text format. High-performance named-entity recognition (NER) models can extract relevant information from these reports automatically for inter-radiologist quality control.

METHODS

Using LDCT report data from a longitudinal lung cancer screening program (8,305 reports; 3,124 participants; 2006-2019), we trained a rule-based model and two bidirectional long short-term memory (Bi-LSTM) NER neural network models to detect clinically relevant information from LDCT reports. Model performance was tested using F1 scores and compared with a published open-source radiology NER model (Stanza) in an independent evaluation set of 150 reports. The top performing model was applied to a data set of 6,948 reports for an inter-radiologist quality control assessment.

RESULTS

The best performing model, a Bi-LSTM NER recurrent neural network model, had an overall F1 score of 0.950, which outperformed Stanza (F1 score = 0.872) and a rule-based NER model (F1 score = 0.809). Recall (sensitivity) for the best Bi-LSTM model ranged from 0.916 to 0.991 for different entity types; precision (positive predictive value) ranged from 0.892 to 0.997. Test performance remained stable across time periods. There was an average of a 2.86-fold difference in the number of identified entities between the most and the least detailed radiologists.

CONCLUSION

We built an open-source Bi-LSTM NER model that outperformed other open-source or rule-based radiology NER models. This model can efficiently extract clinically relevant information from lung cancer screening computerized tomography reports with high accuracy, enabling efficient audit and feedback to improve quality of patient care.

Respiratory and Cardiometabolic Comorbidities and Stages I to III NSCLC Survival: A Pooled Analysis From the International Lung Cancer Consortium

INTRODUCTION

We explored the association of respiratory and cardiometabolic comorbidities with NSCLC overall survival (OS) and lung cancer-specific survival (LCSS), by stage, in a large, multicontinent NSCLC pooled data set.

METHODS

On the basis of patients pooled from 11 International Lung Cancer Consortium studies with available respiratory and cardiometabolic comorbidity data, adjusted hazard ratios (aHRs) were estimated using Cox models for OS. LCSS was evaluated using competing risk Grey and Fine models and cumulative incidence functions. Logistic regression (adjusted OR [aOR]) was applied to assess factors associated with surgical resection.

RESULTS

OS analyses used patients with NSCLC with respiratory health or cardiometabolic health data (N = 16,354); a subset (n = 11,614) contributed to LCSS analyses. In stages I to IIIA NSCLC, patients with respiratory comorbidities had worse LCCS (stage IA aHR = 1.51, confidence interval [CI]: 1.17-1.95; stages IB-IIIA aHR = 1.20, CI: 1.06-1.036). In contrast, patients with stages I to IIIA NSCLC with cardiometabolic comorbidities had a higher risk of death from competing (non-NSCLC) causes (stage IA aHR = 1.34, CI: 1.12-1.69). The presence of respiratory comorbidities was inversely associated with having surgical resection (stage IA aOR = 0.54, CI: 0.35-0.83; stages IB-IIIA aOR = 0.57, CI: 0.46-0.70).

CONCLUSIONS

The presence of either cardiometabolic or respiratory comorbidities is associated with worse OS in stages I to III NSCLC. Patients with respiratory comorbidities were less likely to undergo surgery and had worse LCSS, whereas patients with cardiometabolic comorbidities had a higher risk of death from competing causes. As more treatment options for stages I to III NSCLC are introduced into the practice, accounting for cardiometabolic and respiratory comorbidities becomes essential in trial interpretation and clinical management.

Maternal acetaminophen use and cognitive development at 4 years: the Ontario Birth Study

BACKGROUND

Studies have suggested a link between prenatal maternal acetaminophen use and adverse developmental outcomes in children. However, there exists a knowledge gap regarding overall cognitive development and use of acetaminophen, especially concerning the timing of use in pregnancy. This study aimed to characterize the relationship between maternal acetaminophen use and cognitive development at 4 years.

METHODS

This analysis included data collected throughout pregnancy and delivery from women in the Ontario Birth Study prospective cohort from 2013 to 2019 and from the NIH Toolbox Early Childhood Cognition battery administered to 4-year-old children between 2018 and 2021 (n = 436). The exposure was maternal acetaminophen use and the primary outcome was a cognition composite score. The relationship between exposure and outcome was determined using Poisson regression with a robust error variance.

RESULTS

We did not observe any association between maternal acetaminophen intake any time before or during pregnancy and low cognition composite score of offspring. The IRR of suboptimal overall cognition was 1.38 (0.78-2.45), 1.22 (0.67-2.22), 0.80 (0.44-1.47), and 1.56 (0.74-3.29) for maternal use of acetaminophen before, in early, late, or overall pregnancy, respectively.

CONCLUSION

Current data do not provide evidence to support a relationship of maternal acetaminophen use during pregnancy with adverse cognitive effects at 4 years.

IMPACT

Acetaminophen use during pregnancy may influence the risk of child neurocognitive disorders, but there is conflicting evidence of its relationship to sub-clinical measures of cognitive development such as executive function. The study design allowed us to examine the role of timing of acetaminophen use in its relationship with cognitive development, based on a validated and standardized tablet-administered instrument for children, instead of a teacher or parent report. We did not observe a clear relationship between maternal acetaminophen use at different timepoints during pregnancy and child cognitive development.

Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program

The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smoking and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project measured 1078 proteins among participants with a heavy smoking history within four LDCT screening studies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.

Association of germline TYK2 variation with lung cancer and non-Hodgkin lymphoma risk

Deucravacitinib, a novel, selective inhibitor of TYK2 is currently under review at the FDA and EMA for treatment of moderate-to-severe plaque psoriasis. It is unclear whether recent safety concerns (ie, elevated rates of lung cancer and lymphoma) related to similar medications (ie, other JAK inhibitors) are shared with this novel TYK2 inhibitor. We used a partial loss-of-function variant in TYK2 (rs34536443), previously shown to protect against psoriasis and other autoimmune diseases, to evaluate the potential effect of therapeutic TYK2 inhibition on risk of lung cancer and non-Hodgkin lymphoma. Summary genetic association data on lung cancer risk were obtained from a GWAS meta-analysis of 29 266 cases and 56 450 controls in the Integrative Analysis of Lung Cancer Risk and Aetiology (INTEGRAL) consortium. Summary genetic association data on non-Hodgkin lymphoma risk were obtained from a GWAS meta-analysis of 8489 cases and 374 506 controls in the UK Biobank and InterLymph consortium. In the primary analysis, each copy of the minor allele of rs34536443, representing partial TYK2 inhibition, was associated with an increased risk of lung cancer (OR 1.15, 95% CI 1.09-1.23, P = 2.29 × 10-6 ) and non-Hodgkin lymphoma (OR 1.18, 95% CI 1.05-1.33, P = 5.25 × 10-3 ). Our analyses using an established partial loss-of-function mutation to mimic TYK2 inhibition provide genetic evidence that therapeutic TYK2 inhibition may increase risk of lung cancer and non-Hodgkin lymphoma. These findings, consistent with recent reports from postmarketing trials of similar JAK inhibitors, could have important implications for future safety assessment of deucravacitinib and other TYK2 inhibitors in development.

Maternal prenatal psychological distress and vitamin intake with children's neurocognitive development

BACKGROUND

Maternal prenatal psychological distress (PPD) is increasingly linked to sub-optimal child neurodevelopment. Daily intake of prenatal vitamin during pre-conception and early pregnancy may ameliorate the effects of PPD on cognition in the offspring.

METHODS

PPD was assessed in early (12-16 weeks) and late (28-32 weeks) gestation in the Ontario Birth Study. Prenatal vitamin supplement intake information was collected in early gestation. Child cognition at 4 years was assessed using the NIH Toolbox. Poisson regression was used to investigate associations between PPD and/or prenatal vitamin intake and child cognition.

RESULTS

Four hundred and eighteen mother-child dyads were assessed. Moderate-severe PPD experienced during early gestation was associated with reduced cognition (adjusted incidence rate ratio (IRR_adj) = 3.71, 95% confidence interval (CI): 1.57-8.77, P = 0.003). Daily intake of prenatal vitamins was not associated with cognition (IRR_adj = 1.34, 95% CI: 0.73-2.46, P = 0.34). Upon stratification, the experience of mild-severe PPD with daily intake of prenatal vitamins was associated with higher incident rates of suboptimal cognition compared to children of women with daily prenatal vitamin intake without any episode of PPD (IRR_adj = 2.88, 95% CI: 1.1-7.4).

CONCLUSIONS

Moderate-severe PPD in early pregnancy is associated with poor cognition in children and daily intake of prenatal vitamin did not ameliorate this association.

IMPACT

Our findings expand on existing literature by highlighting that exposure to prenatal psychological distress (PPD), in moderate-to-severe form, in the early stages of pregnancy, can have detrimental effects on the offspring's cognitive development at 4 years. Overall, prenatal vitamin intake did not ameliorate the effects of PPD. Early screening and treatment of prenatal maternal mental illness is crucial.

Autophagopathies: from autophagy gene polymorphisms to precision medicine for human diseases

At a time when complex diseases affect globally 280 million people and claim 14 million lives every year, there is an urgent need to rapidly increase our knowledge into their underlying etiologies. Though critical in identifying the people at risk, the causal environmental factors (microbiome and/or pollutants) and the affected pathophysiological mechanisms are not well understood. Herein, we consider the variations of autophagy-related (ATG) genes at the heart of mechanisms of increased susceptibility to environmental stress. A comprehensive autophagy genomic resource is presented with 263 single nucleotide polymorphisms (SNPs) for 69 autophagy-related genes associated with 117 autoimmune, inflammatory, infectious, cardiovascular, neurological, respiratory, and endocrine diseases. We thus propose the term 'autophagopathies' to group together a class of complex human diseases the etiology of which lies in a genetic defect of the autophagy machinery, whether directly related or not to an abnormal flux in autophagy, LC3-associated phagocytosis, or any associated trafficking. The future of precision medicine for common diseases will lie in our ability to exploit these ATG SNP x environment relationships to develop new polygenetic risk scores, new management guidelines, and optimal therapies for afflicted patients.Abbreviations: ATG, autophagy-related; ALS-FTD, amyotrophic lateral sclerosis-frontotemporal dementia; ccRCC, clear cell renal cell carcinoma; CD, Crohn disease; COPD, chronic obstructive pulmonary disease; eQTL, expression quantitative trait loci; HCC, hepatocellular carcinoma; HNSCC, head and neck squamous cell carcinoma; GTEx, genotype-tissue expression; GWAS, genome-wide association studies; LAP, LC3-associated phagocytosis; LC3-II, phosphatidylethanolamine conjugated form of LC3; LD, linkage disequilibrium; LUAD, lung adenocarcinoma; MAF, minor allele frequency; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; NSCLC, non-small cell lung cancer; OS, overall survival; PtdIns3K CIII, class III phosphatidylinositol 3 kinase; PtdIns3P, phosphatidylinositol-3-phosphate; SLE, systemic lupus erythematosus; SNPs, single-nucleotide polymorphisms; mQTL, methylation quantitative trait loci; ULK, unc-51 like autophagy activating kinase; UTRs, untranslated regions; WHO, World Health Organization.

Circulating Isovalerylcarnitine and Lung Cancer Risk: Evidence from Mendelian Randomization and Prediagnostic Blood Measurements

BACKGROUND

Tobacco exposure causes 8 of 10 lung cancers, and identifying additional risk factors is challenging due to confounding introduced by smoking in traditional observational studies.

MATERIALS AND METHODS

We used Mendelian randomization (MR) to screen 207 metabolites for their role in lung cancer predisposition using independent genome-wide association studies (GWAS) of blood metabolite levels (n = 7,824) and lung cancer risk (n = 29,266 cases/56,450 controls). A nested case-control study (656 cases and 1,296 matched controls) was subsequently performed using prediagnostic blood samples to validate MR association with lung cancer incidence data from population-based cohorts (EPIC and NSHDS).

RESULTS

An MR-based scan of 207 circulating metabolites for lung cancer risk identified that blood isovalerylcarnitine (IVC) was associated with a decreased odds of lung cancer after accounting for multiple testing (log10-OR = 0.43; 95% CI, 0.29-0.63). Molar measurement of IVC in prediagnostic blood found similar results (log10-OR = 0.39; 95% CI, 0.21-0.72). Results were consistent across lung cancer subtypes.

CONCLUSIONS

Independent lines of evidence support an inverse association of elevated circulating IVC with lung cancer risk through a novel methodologic approach that integrates genetic and traditional epidemiology to efficiently identify novel cancer biomarkers.

IMPACT

Our results find compelling evidence in favor of a protective role for a circulating metabolite, IVC, in lung cancer etiology. From the treatment of a Mendelian disease, isovaleric acidemia, we know that circulating IVC is modifiable through a restricted protein diet or glycine and L-carnatine supplementation. IVC may represent a modifiable and inversely associated biomarker for lung cancer.

Lung Cancer Absolute Risk Models for Mortality in an Asian Population using the China Kadoorie Biobank

BACKGROUND

Lung cancer is the leading cause of cancer mortality globally. Early detection through risk-based screening can markedly improve prognosis. However, most risk models were developed in North American cohorts of smokers, whereas less is known about risk profiles for never-smokers, which represent a growing proportion of lung cancers, particularly in Asian populations.

METHODS

Based on the China Kadoorie Biobank, a population-based prospective cohort of 512 639 adults with up to 12 years of follow-up, we built Asian Lung Cancer Absolute Risk Models (ALARM) for lung cancer mortality using flexible parametric survival models, separately for never and ever-smokers, accounting for competing risks of mortality. Model performance was evaluated in a 25% hold-out test set using the time-dependent area under the curve and by comparing model-predicted and observed risks for calibration.

RESULTS

Predictors assessed in the never-smoker lung cancer mortality model were demographics, body mass index, lung function, history of emphysema or bronchitis, personal or family history of cancer, passive smoking, and indoor air pollution. The ever-smoker model additionally assessed smoking history. The 5-year areas under the curve in the test set were 0.77 (95% confidence interval = 0.73 to 0.80) and 0.81 (95% confidence interval = 0.79 to 0.84) for ALARM-never-smokers and ALARM-ever smokers, respectively. The maximum 5-year risk for never and ever-smokers was 2.6% and 12.7%, respectively.

CONCLUSIONS

This study is among the first to develop risk models specifically for Asian populations separately for never and ever-smokers. Our models accurately identify Asians at high risk of lung cancer death and may identify those with risks exceeding common eligibility thresholds who may benefit from screening.

Body Size at Different Ages and Risk of 6 Cancers: A Mendelian Randomization and Prospective Cohort Study

It is unclear if body weight in early life affects cancer risk independently of adult body weight. To investigate this question for 6 obesity-related cancers, we performed univariable and multivariable analyses using 1) Mendelian randomization (MR) analysis and 2) longitudinal analyses in prospective cohorts. Both the MR and longitudinal analyses indicated that larger early life body size was associated with higher risk of endometrial (odds ratioMR = 1.61, 95% confidence interval = 1.23 to 2.11) and kidney (odds ratioMR = 1.40, 95% confidence interval = 1.09 to 1.80) cancer. These associations were attenuated after accounting for adult body size in both the MR and cohort analyses. Early life body mass index (BMI) was not consistently associated with the other investigated cancers. The lack of clear independent risk associations suggests that early life BMI influences endometrial and kidney cancer risk mainly through pathways that are common with adult BMI.

Genome-wide interaction analysis identified low-frequency variants with sex disparity in lung cancer risk

Differences by sex in lung cancer incidence and mortality have been reported which cannot be fully explained by sex differences in smoking behavior, implying existence of genetic and molecular basis for sex disparity in lung cancer development. However, the information about sex dimorphism in lung cancer risk is quite limited despite the great success in lung cancer association studies. By adopting a stringent two-stage analysis strategy, we performed a genome-wide gene-sex interaction analysis using genotypes from a lung cancer cohort including ~ 47 000 individuals with European ancestry. Three low-frequency variants (minor allele frequency < 0.05), rs17662871 [odds ratio (OR) = 0.71, P = 4.29×10-8); rs79942605 (OR = 2.17, P = 2.81×10-8) and rs208908 (OR = 0.70, P = 4.54×10-8) were identified with different risk effect of lung cancer between men and women. Further expression quantitative trait loci and functional annotation analysis suggested rs208908 affects lung cancer risk through differential regulation of Coxsackie virus and adenovirus receptor gene expression in lung tissues between men and women. Our study is one of the first studies to provide novel insights about the genetic and molecular basis for sex disparity in lung cancer development.

Genetic Analysis of Lung Cancer and the Germline Impact on Somatic Mutation Burden

BACKGROUND

Germline genetic variation contributes to lung cancer (LC) susceptibility. Previous genome-wide association studies (GWAS) have implicated susceptibility loci involved in smoking behaviors and DNA repair genes, but further work is required to identify susceptibility variants.

METHODS

To identify LC susceptibility loci, a family history-based genome-wide association by proxy (GWAx) of LC (48 843 European proxy LC patients, 195 387 controls) was combined with a previous LC GWAS (29 266 patients, 56 450 controls) by meta-analysis. Colocalization was used to explore candidate genes and overlap with existing traits at discovered susceptibility loci. Polygenic risk scores (PRS) were tested within an independent validation cohort (1 666 LC patients vs 6 664 controls) using variants selected from the LC susceptibility loci and a novel selection approach using published GWAS summary statistics. Finally, the effects of the LC PRS on somatic mutational burden were explored in patients whose tumor resections have been profiled by exome (n = 685) and genome sequencing (n = 61). Statistical tests were 2-sided.

RESULTS

The GWAx-GWAS meta-analysis identified 8 novel LC loci. Colocalization implicated DNA repair genes (CHEK1), metabolic genes (CYP1A1), and smoking propensity genes (CHRNA4 and CHRNB2). PRS analysis demonstrated that these variants, as well as subgenome-wide significant variants related to expression quantitative trait loci and/or smoking propensity, assisted in LC genetic risk prediction (odds ratio = 1.37, 95% confidence interval = 1.29 to 1.45; P < .001). Patients with higher genetic PRS loads of smoking-related variants tended to have higher mutation burdens in their lung tumors.

CONCLUSIONS

This study has expanded the number of LC susceptibility loci and provided insights into the molecular mechanisms by which these susceptibility variants contribute to LC development.

Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians

INTRODUCTION

Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).

METHODS

Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.

RESULTS

With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10-13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10-13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10-13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10-4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.

CONCLUSIONS

Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.