A heavy-tailed model for analyzing miRNA-seq raw read counts.

This article addresses the limitations of existing statistical models in analyzing and interpreting highly skewed miRNA-seq raw read count data that can range from zero to millions. A heavy-tailed model using discrete stable distributions is proposed as a novel approach to better capture the heterogeneity and extreme values commonly observed in miRNA-seq data. Additionally, the parameters of the discrete stable distribution are proposed as an alternative target for differential expression analysis. An R package for computing and estimating the discrete stable distribution is provided. The proposed model is applied to miRNA-seq raw counts from the Norwegian Women and Cancer Study (NOWAC) and the Cancer Genome Atlas (TCGA) databases. The goodness-of-fit is compared with the popular Poisson and negative binomial distributions, and the discrete stable distributions are found to give a better fit for both datasets. In conclusion, the use of discrete stable distributions is shown to potentially lead to more accurate modeling of the underlying biological processes.

penalizedclr: an R package for penalized conditional logistic regression for integration of multiple omics layers.

BACKGROUND: The matched case-control design, up until recently mostly pertinent to epidemiological studies, is becoming customary in biomedical applications as well. For instance, in omics studies, it is quite common to compare cancer and healthy tissue from the same patient. Furthermore, researchers today routinely collect data from various and variable sources that they wish to relate to the case-control status. This highlights the need to develop and implement statistical methods that can take these tendencies into account. RESULTS: We present an R package penalizedclr, that provides an implementation of the penalized conditional logistic regression model for analyzing matched case-control studies. It allows for different penalties for different blocks of covariates, and it is therefore particularly useful in the presence of multi-source omics data. Both L1 and L2 penalties are implemented. Additionally, the package implements stability selection for variable selection in the considered regression model. CONCLUSIONS: The proposed method fills a gap in the available software for fitting high-dimensional conditional logistic regression models accounting for the matched design and block structure of predictors/features. The output consists of a set of selected variables that are significantly associated with case-control status. These variables can then be investigated in terms of functional interpretation or validation in further, more targeted studies.

Healthy lifestyle change and all-cause and cancer mortality in the European Prospective Investigation into Cancer and Nutrition cohort.

BACKGROUND: Healthy lifestyles are inversely associated with the risk of noncommunicable diseases, which are leading causes of death. However, few studies have used longitudinal data to assess the impact of changing lifestyle behaviours on all-cause and cancer mortality. METHODS: Within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, lifestyle profiles of 308,497 cancer-free adults (71% female) aged 35-70 years at recruitment across nine countries were assessed with baseline and follow-up questionnaires administered on average of 7 years apart. A healthy lifestyle index (HLI), assessed at two time points, combined information on smoking status, alcohol intake, body mass index, and physical activity, and ranged from 0 to 16 units. A change score was calculated as the difference between HLI at baseline and follow-up. Associations between HLI change and all-cause and cancer mortality were modelled with Cox regression, and the impact of changing HLI on accelerating mortality rate was estimated by rate advancement periods (RAP, in years). RESULTS: After the follow-up questionnaire, participants were followed for an average of 9.9 years, with 21,696 deaths (8407 cancer deaths) documented. Compared to participants whose HLIs remained stable (within one unit), improving HLI by more than one unit was inversely associated with all-cause and cancer mortality (hazard ratio [HR]: 0.84; 95% confidence interval [CI]: 0.81, 0.88; and HR: 0.87; 95% CI: 0.82, 0.92; respectively), while worsening HLI by more than one unit was associated with an increase in mortality (all-cause mortality HR: 1.26; 95% CI: 1.20, 1.33; cancer mortality HR: 1.19; 95% CI: 1.09, 1.29). Participants who worsened HLI by more than one advanced their risk of death by 1.62 (1.44, 1.96) years, while participants who improved HLI by the same amount delayed their risk of death by 1.19 (0.65, 2.32) years, compared to those with stable HLI. CONCLUSIONS: Making healthier lifestyle changes during adulthood was inversely associated with all-cause and cancer mortality and delayed risk of death. Conversely, making unhealthier lifestyle changes was positively associated with mortality and an accelerated risk of death.

Lifestyle changes in middle age and risk of cancer: evidence from the European Prospective Investigation into Cancer and Nutrition.

In this study, we aimed to provide novel evidence on the impact of changing lifestyle habits on cancer risk. In the EPIC cohort, 295,865 middle-aged participants returned a lifestyle questionnaire at baseline and during follow-up. At both timepoints, we calculated a healthy lifestyle index (HLI) score based on cigarette smoking, alcohol consumption, body mass index and physical activity. HLI ranged from 0 (most unfavourable) to 16 (most favourable). We estimated the association between HLI change and risk of lifestyle-related cancers-including cancer of the breast, lung, colorectum, stomach, liver, cervix, oesophagus, bladder, and others-using Cox regression models. We reported hazard ratios (HR) with 95% confidence intervals (CI). Median time between the two questionnaires was 5.7 years, median age at follow-up questionnaire was 59 years. After the follow-up questionnaire, we observed 14,933 lifestyle-related cancers over a median follow-up of 7.8 years. Each unit increase in the HLI score was associated with 4% lower risk of lifestyle-related cancers (HR 0.96; 95%CI 0.95-0.97). Among participants in the top HLI third at baseline (HLI > 11), those in the bottom third at follow-up (HLI ≤ 9) had 21% higher risk of lifestyle-related cancers (HR 1.21; 95%CI 1.07-1.37) than those remaining in the top third. Among participants in the bottom HLI third at baseline, those in the top third at follow-up had 25% lower risk of lifestyle-related cancers (HR 0.75; 95%CI 0.65-0.86) than those remaining in the bottom third. These results indicate that lifestyle changes in middle age may have a significant impact on cancer risk.

Dietary amino acids and risk of stroke subtypes: a prospective analysis of 356,000 participants in seven European countries.

PURPOSE: Previously reported associations of protein-rich foods with stroke subtypes have prompted interest in the assessment of individual amino acids. We examined the associations of dietary amino acids with risks of ischaemic and haemorrhagic stroke in the EPIC study. METHODS: We analysed data from 356,142 participants from seven European countries. Dietary intakes of 19 individual amino acids were assessed using validated country-specific dietary questionnaires, calibrated using additional 24-h dietary recalls. Multivariable-adjusted Cox regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of ischaemic and haemorrhagic stroke in relation to the intake of each amino acid. The role of blood pressure as a potential mechanism was assessed in 267,642 (75%) participants. RESULTS: After a median follow-up of 12.9 years, 4295 participants had an ischaemic stroke and 1375 participants had a haemorrhagic stroke. After correction for multiple testing, a higher intake of proline (as a percent of total protein) was associated with a 12% lower risk of ischaemic stroke (HR per 1 SD higher intake 0.88; 95% CI 0.82, 0.94). The association persisted after mutual adjustment for all other amino acids, systolic and diastolic blood pressure. The inverse associations of isoleucine, leucine, valine, phenylalanine, threonine, tryptophan, glutamic acid, serine and tyrosine with ischaemic stroke were each attenuated with adjustment for proline intake. For haemorrhagic stroke, no statistically significant associations were observed in the continuous analyses after correcting for multiple testing. CONCLUSION: Higher proline intake may be associated with a lower risk of ischaemic stroke, independent of other dietary amino acids and blood pressure.

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors.

BACKGROUND: Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources. METHODS: We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations. RESULTS: In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis. CONCLUSIONS: Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

Assessment of the EarlyCDT-Lung test as an early biomarker of lung cancer in ever-smokers: A retrospective nested case-control study in two prospective cohorts.

The EarlyCDT-Lung test is a blood-based autoantibody assay intended to identify high-risk individuals for low-dose computed tomography lung cancer screening. However, there is a paucity of evidence on the performance of the EarlyCDT-Lung test in ever-smokers. We conducted a nested case-control study within two prospective cohorts to evaluate the risk-discriminatory performance of the EarlyCDT-Lung test using prediagnostic blood samples from 154 future lung cancer cases and 154 matched controls. Cases were selected from those who had ever smoked and had a prediagnostic blood sample <3 years prior to diagnosis. Conditional logistic regression was used to estimate the association between EarlyCDT-Lung test results and lung cancer risk. Sensitivity and specificity of the EarlyCDT-Lung test were calculated in all subjects and subgroups based on age, smoking history, lung cancer stage, sample collection time before diagnosis and year of sample collection. The overall lung cancer odds ratios were 0.89 (95% CI: 0.34-2.30) for a moderate risk EarlyCDT-Lung test result and 1.09 (95% CI: 0.48-2.47) for a high-risk test result compared to no significant test result. The overall sensitivity was 8.4% (95% CI: 4.6-14) and overall specificity was 92% (95% CI: 87-96) when considering a high-risk result as positive. Stratified analysis indicated higher sensitivity (17%, 95% CI: 7.2-32.1) in subjects with blood drawn up to 1 year prior to diagnosis. In conclusion, our study does not support a role of the EarlyCDT-Lung test in identifying the high-risk subjects in ever-smokers for lung cancer screening in the EPIC and NSHDS cohorts.

Circulating amino acid levels and colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition and UK Biobank cohorts.

BACKGROUND: Amino acid metabolism is dysregulated in colorectal cancer patients; however, it is not clear whether pre-diagnostic levels of amino acids are associated with subsequent risk of colorectal cancer. We investigated circulating levels of amino acids in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) and UK Biobank cohorts. METHODS: Concentrations of 13-21 amino acids were determined in baseline fasting plasma or serum samples in 654 incident colorectal cancer cases and 654 matched controls in EPIC. Amino acids associated with colorectal cancer risk following adjustment for the false discovery rate (FDR) were then tested for associations in the UK Biobank, for which measurements of 9 amino acids were available in 111,323 participants, of which 1221 were incident colorectal cancer cases. RESULTS: Histidine levels were inversely associated with colorectal cancer risk in EPIC (odds ratio [OR] 0.80 per standard deviation [SD], 95% confidence interval [CI] 0.69-0.92, FDR P-value=0.03) and in UK Biobank (HR 0.93 per SD, 95% CI 0.87-0.99, P-value=0.03). Glutamine levels were borderline inversely associated with colorectal cancer risk in EPIC (OR 0.85 per SD, 95% CI 0.75-0.97, FDR P-value=0.08) and similarly in UK Biobank (HR 0.95, 95% CI 0.89-1.01, P=0.09) In both cohorts, associations changed only minimally when cases diagnosed within 2 or 5 years of follow-up were excluded. CONCLUSIONS: Higher circulating levels of histidine were associated with a lower risk of colorectal cancer in two large prospective cohorts. Further research to ascertain the role of histidine metabolism and potentially that of glutamine in colorectal cancer development is warranted.

Calcium Intake and Lung Cancer Risk: A Pooled Analysis of 12 Prospective Cohort Studies.

BACKGROUND: Previous studies on calcium intake and lung cancer risk reported inconsistent associations, possibly due to the differences in intake amounts and contributing sources of calcium and smoking prevalence. OBJECTIVES: We investigated the associations of lung cancer risk with intake of calcium from foods and/or supplements and major calcium-rich foods in 12 studies. METHODS: Data from 12 prospective cohort studies conducted in the United States, Europe, and Asia were pooled and harmonized. We applied the DRI to categorize calcium intake based on the recommendations and quintile distribution to categorize calcium-rich food intake. We ran multivariable Cox regression by each cohort and pooled risk estimates to compute overall HR (95% CI). RESULTS: Among 1,624,244 adult men and women, 21,513 incident lung cancer cases were ascertained during a mean follow-up of 9.9 y. Overall, the dietary calcium intake was not significantly associated with lung cancer risk; the HRs (95% CI) were 1.08 (0.98-1.18) for higher (>1.5 RDA) and 1.01 (0.95-1.07) for lower intake (<0.5 RDA) comparing with recommended intake (EAR to RDA). Milk and soy food intake were positively or inversely associated with lung cancer risk [HR (95% CI) = 1.07 (1.02-1.12) and 0.92 (0.84-1.00)], respectively. The positive association with milk intake was significant only in European and North American studies (P-interaction for region = 0.04). No significant association was observed for calcium supplements. CONCLUSIONS: In this largest prospective investigation, overall, calcium intake was not associated with risk of lung cancer, but milk intake was associated with a higher risk. Our findings underscore the importance of considering food sources of calcium in studies of calcium intake.

Fluorine Mass Balance, including Total Fluorine, Extractable Organic Fluorine, Oxidizable Precursors, and Target Per- and Polyfluoroalkyl Substances, in Pooled Human Serum from the Tromsø Population in 1986, 2007, and 2015.

Of the thousands of per- and polyfluoroalkyl substances (PFAS) known to exist, only a small fraction (≤1%) are commonly monitored in humans. This discrepancy has led to concerns that human exposure may be underestimated. Here, we address this problem by applying a comprehensive fluorine mass balance (FMB) approach, including total fluorine (TF), extractable organic fluorine (EOF), total oxidizable precursors (TOP), and selected target PFAS, to human serum samples collected over a period of 28 years (1986, 2007, and 2015) in Tromsø, Norway. While concentrations of TF did not change between sampling years, EOF was significantly higher in 1986 compared to 2007 and 2015. The ∑12PFAS concentrations were highest in 2007 compared to 1986 and 2015, and unidentified EOF (UEOF) decreased from 1986 (46%) to 2007 (10%) and then increased in 2015 (37%). While TF and EOF were not influenced by sex, women had higher UEOF compared to men, opposite to target PFAS. This is the first FMB in human serum to include TOP, and it suggests that precursors with >4 perfluorinated carbon atoms make a minor contribution to EOF (0-4%). Additional tools are therefore needed to identify substances contributing to the UEOF in human serum.

Overall lifestyle changes in adulthood are associated with cancer incidence in the Norwegian Women and Cancer Study (NOWAC) - a prospective cohort study.

BACKGROUND: Cancer is a leading cause of premature death worldwide and incidence is expected to rise in the coming decades. Many cohort studies, measuring lifestyle factors at one time-point, have observed that overall healthy lifestyles were inversely related to cancer incidence. However, there is little knowledge on the impact of lifestyle modification within adulthood. METHODS: Using the Norwegian Women and Cancer study, two repeated self-reported assessments of lifestyle behaviours were used to calculate healthy lifestyle index scores at each time-point (N = 66 233). The associations between change in healthy lifestyle index score and lifestyle-related cancer incidence, including alcohol-, tobacco-, obesity-, and reproductive-related, and site-specific breast and colorectal cancer incidence were estimated using Cox proportional hazard regression models. To assess nonlinearity in the dose-response relationships, restricted cubic spline models were used. RESULTS: Independent of baseline lifestyle, positive lifestyle changes were inversely related to the incidence of overall lifestyle-related cancers, as well as alcohol-related, tobacco-related, obesity-related, and reproductive-related cancers, but not breast and colorectal site-specific cancers. An association between lifestyle worsening and cancer incidence compared to stable lifestyle was observed. CONCLUSIONS: This study provides evidence that overall lifestyle changes among cancer-free women between the ages of 41 and 76 impact the incidence of many cancer types. Regardless of baseline lifestyle, there was a negative dose-response relationship between magnitude of positive lifestyle change and the incidence of overall lifestyle-related cancers. We observed that underlying this trend was an especially clear association between lifestyle worsening and increased risk compared to stable lifestyle. For adult women, maintaining a stable healthy lifestyle and lifestyle improvement are important for preventing the occurrence of many cancer types.

A Prospective Diet-Wide Association Study for Risk of Colorectal Cancer in EPIC.

BACKGROUND & AIMS: Evidence regarding the association of dietary exposures with colorectal cancer (CRC) risk is not consistent with a few exceptions. Therefore, we conducted a diet-wide association study (DWAS) in the European Prospective Investigation into Cancer and Nutrition (EPIC) to evaluate the associations between several dietary exposures with CRC risk. METHODS: The association of 92 food and nutrient intakes with CRC risk was assessed in 386,792 participants, 5069 of whom developed incident CRC. Correction for multiple comparisons was performed using the false discovery rate, and emerging associations were examined in the Netherlands Cohort Study (NLCS). Multiplicative gene-nutrient interactions were also tested in EPIC based on known CRC-associated loci. RESULTS: In EPIC, alcohol, liquor/spirits, wine, beer/cider, soft drinks, and pork were positively associated with CRC, whereas milk, cheese, calcium, phosphorus, magnesium, potassium, riboflavin, vitamin B6, beta carotene, fruit, fiber, nonwhite bread, banana, and total protein intakes were inversely associated. Of these 20 associations, 13 were replicated in the NLCS, for which a meta-analysis was performed, namely alcohol (summary hazard ratio [HR] per 1-SD increment in intake: 1.07; 95% confidence interval [CI], 1.04-1.09), liquor/spirits (HR per 1-SD increment in intake, 1.04; 95% CI, 1.02-1.06), wine (HR per 1-SD increment in intake, 1.04; 95% CI, 1.02-1.07), beer/cider (HR per 1-SD increment in intake, 1.06; 95% CI, 1.04-1.08), milk (HR per 1-SD increment in intake, 0.95; 95% CI, 0.93-0.98), cheese (HR per 1-SD increment in intake, 0.96; 95% CI, 0.94-0.99), calcium (HR per 1-SD increment in intake, 0.93; 95% CI, 0.90-0.95), phosphorus (HR per 1-SD increment in intake, 0.92; 95% CI, 0.90-0.95), magnesium (HR per 1-SD increment in intake, 0.95; 95% CI, 0.92-0.98), potassium (HR per 1-SD increment in intake, 0.96; 95% CI, 0.94-0.99), riboflavin (HR per 1-SD increment in intake, 0.94; 95% CI, 0.92-0.97), beta carotene (HR per 1-SD increment in intake, 0.96; 95% CI, 0.93-0.98), and total protein (HR per 1-SD increment in intake, 0.94; 95% CI, 0.92-0.97). None of the gene-nutrient interactions were significant after adjustment for multiple comparisons. CONCLUSIONS: Our findings confirm a positive association for alcohol and an inverse association for dairy products and calcium with CRC risk, and also suggest a lower risk at higher dietary intakes of phosphorus, magnesium, potassium, riboflavin, beta carotene, and total protein.

Circulating inflammatory cytokines and risk of five cancers: a Mendelian randomization analysis.

BACKGROUND: Epidemiological and experimental evidence has linked chronic inflammation to cancer aetiology. It is unclear whether associations for specific inflammatory biomarkers are causal or due to bias. In order to examine whether altered genetically predicted concentration of circulating cytokines are associated with cancer development, we performed a two-sample Mendelian randomisation (MR) analysis. METHODS: Up to 31,112 individuals of European descent were included in genome-wide association study (GWAS) meta-analyses of 47 circulating cytokines. Single nucleotide polymorphisms (SNPs) robustly associated with the cytokines, located in or close to their coding gene (cis), were used as instrumental variables. Inverse-variance weighted MR was used as the primary analysis, and the MR assumptions were evaluated in sensitivity and colocalization analyses and a false discovery rate (FDR) correction for multiple comparisons was applied. Corresponding germline GWAS summary data for five cancer outcomes (breast, endometrial, lung, ovarian, and prostate), and their subtypes were selected from the largest cancer-specific GWASs available (cases ranging from 12,906 for endometrial to 133,384 for breast cancer). RESULTS: There was evidence of inverse associations of macrophage migration inhibitory factor with breast cancer (OR per SD = 0.88, 95% CI 0.83 to 0.94), interleukin-1 receptor antagonist with endometrial cancer (0.86, 0.80 to 0.93), interleukin-18 with lung cancer (0.87, 0.81 to 0.93), and beta-chemokine-RANTES with ovarian cancer (0.70, 0.57 to 0.85) and positive associations of monokine induced by gamma interferon with endometrial cancer (3.73, 1.86 to 7.47) and cutaneous T-cell attracting chemokine with lung cancer (1.51, 1.22 to 1.87). These associations were similar in sensitivity analyses and supported in colocalization analyses. CONCLUSIONS: Our study adds to current knowledge on the role of specific inflammatory biomarker pathways in cancer aetiology. Further validation is needed to assess the potential of these cytokines as pharmacological or lifestyle targets for cancer prevention.

Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition.

BACKGROUND: Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations. METHODS: We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty. RESULTS: Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk. CONCLUSIONS: These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.

Epigenetic mechanisms of lung carcinogenesis involve differentially methylated CpG sites beyond those associated with smoking.

Smoking-related epigenetic changes have been linked to lung cancer, but the contribution of epigenetic alterations unrelated to smoking remains unclear. We sought for a sparse set of CpG sites predicting lung cancer and explored the role of smoking in these associations. We analysed CpGs in relation to lung cancer in participants from two nested case-control studies, using (LASSO)-penalised regression. We accounted for the effects of smoking using known smoking-related CpGs, and through conditional-independence network. We identified 29 CpGs (8 smoking-related, 21 smoking-unrelated) associated with lung cancer. Models additionally adjusted for Comprehensive Smoking Index-(CSI) selected 1 smoking-related and 49 smoking-unrelated CpGs. Selected CpGs yielded excellent discriminatory performances, outperforming information provided by CSI only. Of the 8 selected smoking-related CpGs, two captured lung cancer-relevant effects of smoking that were missed by CSI. Further, the 50 CpGs identified in the CSI-adjusted model complementarily explained lung cancer risk. These markers may provide further insight into lung cancer carcinogenesis and help improving early identification of high-risk patients.

Inflammatory potential of diet and pancreatic cancer risk in the EPIC study.

PURPOSE: There is existing evidence on the potential role of chronic inflammation in the pathogenesis of pancreatic cancer (PC) and on how risk may be modulated by dietary factors. Pro-inflammatory diets are suggested to be associated with increased risk of PC but, so far, evidence remains not conclusive. We examined the association between the dietary inflammatory potential and PC risk within the European Prospective Investigation into Cancer and Nutrition (EPIC) study, which includes 450,112 participants. METHODS: After a 14-year follow-up, a total of 1239 incident PC cases were included in this study. The inflammatory potential of the diet was estimated using an Inflammatory Score of the Diet (ISD). Hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between the ISD and PC were estimated using multivariable Cox regression models, adjusted for known risk factors for PC. RESULTS: Participants with higher ISDs had a higher risk of developing PCs. In the fully adjusted multivariate model, the risk of PC increased by 11% (HR 1.11, 95% CI 1.02-1.22) for 1 point each standard deviation increase in the ISD score. Neither obesity nor any other known risk factor for PC showed statistically significant interactions. CONCLUSION: To the best of our knowledge, this is the first prospective study reporting a positive relationship between the inflammatory potential of diet and PC. Since early diagnosis and treatment of pancreatic cancer might be challenging, prevention remains the major hope for reducing the burden of this disease.

Longitudinal changes in concentrations of persistent organic pollutants (1986-2016) and their associations with type 2 diabetes mellitus.

BACKGROUND: Positive associations have been reported between persistent organic pollutants (POPs) and type 2 diabetes mellitus (T2DM); however, causality has not been established. Over the last decades, environmental exposure to legacy POPs has decreased, complicating epidemiological studies. In addition, physiological risk factors for T2DM may also influence POP concentrations, contributing to a complex network of factors that could impact associations with T2DM. Longitudinal studies on this topic are lacking, and few have assessed prospective and cross-sectional associations between repeated POP measurements and T2DM in the same individuals, which may shed light on causality. OBJECTIVES: To compare longitudinal trends in concentrations of polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs) in T2DM cases and controls, and to examine prospective and cross-sectional associations between PCBs, OCPs and T2DM at different time-points before and after T2DM diagnosis in cases. METHODS: We conducted a longitudinal, nested case-control study (1986-2016) of 116 T2DM cases and 139 controls from the Tromsø Study. All participants had three blood samples collected before T2DM diagnosis in cases, and up to two samples thereafter. We used linear mixed-effect models to assess temporal changes of POPs within and between T2DM cases and controls, and logistic regression models to investigate the associations between different POPs and T2DM at different time-points. RESULTS: PCBs, trans-nonachlor, cis-nonachlor, oxychlordane, cis-heptachlor epoxide, p,p'-DDE, and p,p'-DDT declined more slowly in cases than controls, whereas ß-HCH and HCB declined similarly in both groups. Most POPs showed positive associations between both pre- and post-diagnostic concentrations and T2DM, though effect estimates were imprecise. These associations were most consistent for cis-heptachlor epoxide. DISCUSSION: The observed positive associations between certain POPs and T2DM may be because of higher POP concentrations within prospective T2DM cases, due to slower temporal declines as compared to controls.

Seroprevalence of antibodies against SARS-CoV-2 in the adult population during the pre-vaccination period, Norway, winter 2020/21.

BackgroundSince March 2020, 440 million people worldwide have been diagnosed with COVID-19, but the true number of infections with SARS-CoV-2 is higher. SARS-CoV-2 antibody seroprevalence can add crucial epidemiological information about population infection dynamics.AimTo provide a large population-based SARS-CoV-2 seroprevalence survey from Norway; we estimated SARS-CoV-2 seroprevalence before introduction of vaccines and described its distribution across demographic groups.MethodsIn this population-based cross-sectional study, a total of 110,000 people aged 16 years or older were randomly selected during November-December 2020 and invited to complete a questionnaire and provide a dried blood spot (DBS) sample.ResultsThe response rate was 30% (31,458/104,637); compliance rate for return of DBS samples was 88% (27,700/31,458). National weighted and adjusted seroprevalence was 0.9% (95% CI (confidence interval): 0.7-1.0). Seroprevalence was highest among those aged 16-19 years (1.9%; 95% CI: 0.9-2.9), those born outside the Nordic countries 1.4% (95% CI: 1.0-1.9), and in the counties of Oslo 1.7% (95% CI: 1.2-2.2) and Vestland 1.4% (95% CI: 0.9-1.8). The ratio of SARS-CoV-2 seroprevalence (0.9%) to cumulative incidence of virologically detected cases by mid-December 2020 (0.8%) was slightly above one. SARS-CoV-2 seroprevalence was low before introduction of vaccines in Norway and was comparable to virologically detected cases, indicating that most cases in the first 10 months of the pandemic were detected.ConclusionFindings suggest that preventive measures including contact tracing have been effective, people complied with physical distancing recommendations, and local efforts to contain outbreaks have been essential.

Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer.

BACKGROUND: Cancer genomic studies often include data collected from several omics platforms. Each omics data source contributes to the understanding of the underlying biological process via source specific ("individual") patterns of variability. At the same time, statistical associations and potential interactions among the different data sources can reveal signals from common biological processes that might not be identified by single source analyses. These common patterns of variability are referred to as "shared" or "joint". In this work, we show how the use of joint and individual components can lead to better predictive models, and to a deeper understanding of the biological process at hand. We identify joint and individual contributions of DNA methylation, miRNA and mRNA expression collected from blood samples in a lung cancer case-control study nested within the Norwegian Women and Cancer (NOWAC) cohort study, and we use such components to build prediction models for case-control and metastatic status. To assess the quality of predictions, we compare models based on simultaneous, integrative analysis of multi-source omics data to a standard non-integrative analysis of each single omics dataset, and to penalized regression models. Additionally, we apply the proposed approach to a breast cancer dataset from The Cancer Genome Atlas. RESULTS: Our results show how an integrative analysis that preserves both components of variation is more appropriate than standard multi-omics analyses that are not based on such a distinction. Both joint and individual components are shown to contribute to a better quality of model predictions, and facilitate the interpretation of the underlying biological processes in lung cancer development. CONCLUSIONS: In the presence of multiple omics data sources, we recommend the use of data integration techniques that preserve the joint and individual components across the omics sources. We show how the inclusion of such components increases the quality of model predictions of clinical outcomes.

The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium.

BACKGROUND: Excess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI). METHODS AND FINDINGS: We assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case-control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10-8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10-5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some-but not all-metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., -0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10-5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10-3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds. CONCLUSIONS: This study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI-the principal modifiable risk factor of kidney cancer.