Deciphering the genetics and mechanisms of predisposition to multiple myeloma.

Multiple myeloma (MM) is an incurable malignancy of plasma cells. Epidemiological studies indicate a substantial heritable component, but the underlying mechanisms remain unclear. Here, in a genome-wide association study totaling 10,906 cases and 366,221 controls, we identify 35 MM risk loci, 12 of which are novel. Through functional fine-mapping and Mendelian randomization, we uncover two causal mechanisms for inherited MM risk: longer telomeres; and elevated levels of B-cell maturation antigen (BCMA) and interleukin-5 receptor alpha (IL5RA) in plasma. The largest increase in BCMA and IL5RA levels is mediated by the risk variant rs34562254-A at TNFRSF13B. While individuals with loss-of-function variants in TNFRSF13B develop B-cell immunodeficiency, rs34562254-A exerts a gain-of-function effect, increasing MM risk through amplified B-cell responses. Our results represent an analysis of genetic MM predisposition, highlighting causal mechanisms contributing to MM development.

The genomic landscape of 2,023 colorectal cancers.

Colorectal carcinoma (CRC) is a common cause of mortality1, but a comprehensive description of its genomic landscape is lacking2-9. Here we perform whole-genome sequencing of 2,023 CRC samples from participants in the UK 100,000 Genomes Project, thereby providing a highly detailed somatic mutational landscape of this cancer. Integrated analyses identify more than 250 putative CRC driver genes, many not previously implicated in CRC or other cancers, including several recurrent changes outside the coding genome. We extend the molecular pathways involved in CRC development, define four new common subgroups of microsatellite-stable CRC based on genomic features and show that these groups have independent prognostic associations. We also characterize several rare molecular CRC subgroups, some with potential clinical relevance, including cancers with both microsatellite and chromosomal instability. We demonstrate a spectrum of mutational profiles across the colorectum, which reflect aetiological differences. These include the role of Escherichia colipks+ colibactin in rectal cancers10 and the importance of the SBS93 signature11-13, which suggests that diet or smoking is a risk factor. Immune-escape driver mutations14 are near-ubiquitous in hypermutant tumours and occur in about half of microsatellite-stable CRCs, often in the form of HLA copy number changes. Many driver mutations are actionable, including those associated with rare subgroups (for example, BRCA1 and IDH1), highlighting the role of whole-genome sequencing in optimizing patient care.

Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes.

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

Impact of ambient air pollution on colorectal cancer risk and survival: insights from a prospective cohort and epigenetic Mendelian randomization study.

BACKGROUND: This study investigates the associations between air pollution and colorectal cancer (CRC) risk and survival from an epigenomic perspective. METHODS: Using a newly developed Air Pollutants Exposure Score (APES), we utilized a prospective cohort study (UK Biobank) to investigate the associations of individual and combined air pollution exposures with CRC incidence and survival, followed by an up-to-date systematic review with meta-analysis to verify the associations. In epigenetic two-sample Mendelian randomization analyses, we examine the associations between genetically predicted DNA methylation related to air pollution and CRC risk. Further genetic colocalization and gene-environment interaction analyses provided different insights to disentangle pathogenic effects of air pollution via epigenetic modification. FINDINGS: During a median 12.97-year follow-up, 5767 incident CRC cases among 428,632 participants free of baseline CRC and 533 deaths in 2401 patients with CRC were documented in the UK Biobank. A higher APES score was associated with an increased CRC risk (HR, 1.03, 95% CI = 1.01-1.06; P = 0.016) and poorer survival (HR, 1.13, 95% CI = 1.03-1.23; P = 0.010), particularly among participants with insufficient physical activity and ever smokers (Pinteraction > 0.05). A subsequent meta-analysis of seven observational studies, including UK Biobank data, corroborated the association between PM2.5 exposure (per 10 µg/m3 increment) and elevated CRC risk (RR,1.42, 95% CI = 1.12-1.79; P = 0.004; I2 = 90.8%). Genetically predicted methylation at PM2.5-related CpG site cg13835894 near TMBIM1/PNKD and cg16235962 near CXCR5, and NO2-related cg16947394 near TMEM110 were associated with an increased CRC risk. Gene-environment interaction analysis confirmed the epigenetic modification of aforementioned CpG sites with CRC risk and survival. INTERPRETATION: Our study suggests the association between air pollution and CRC incidence and survival, underscoring the possible modifying roles of epigenomic factors. Methylation may partly mediate pathogenic effects of air pollution on CRC, with annotation to epigenetic alterations in protein-coding genes TMBIM1/PNKD, CXCR5 and TMEM110. FUNDING: Xue Li is supported by the Natural Science Fund for Distinguished Young Scholars of Zhejiang Province (LR22H260001), the National Nature Science Foundation of China (No. 82204019) and Healthy Zhejiang One Million People Cohort (K-20230085). ET is supported by a Cancer Research UK Career Development Fellowship (C31250/A22804). MGD is supported by the MRC Human Genetics Unit Centre Grant (U127527198).

Systematic investigation of genetically determined plasma and urinary metabolites to discover potential interventional targets for colorectal cancer.

BACKGROUND: We aimed to identify plasma and urinary metabolites related to colorectal cancer (CRC) risk and elucidate their mediator role in the associations between modifiable risk factors and CRC. METHODS: Metabolite quantitative trait loci were derived from 2 published metabolomics genome-wide association studies, and summary-level data were extracted for 651 plasma metabolites and 208 urinary metabolites. Genetic associations with CRC were obtained from a large-scale genome-wide association study meta-analysis (100 204 cases, 154 587 controls) and the FinnGen cohort (4957 cases, 304 197 controls). Mendelian randomization and colocalization analyses were performed to evaluate the causal roles of metabolites in CRC. Druggability evaluation was employed to prioritize potential therapeutic targets. Multivariable Mendelian randomization and mediation estimation were conducted to elucidate the mediating effects of metabolites on the associations between modifiable risk factors and CRC. RESULTS: The study identified 30 plasma metabolites and 4 urinary metabolites for CRC. Plasma sphingomyelin and urinary lactose, which were positively associated with CRC risk, could be modulated by drug interventions (ie, olipudase alfa, tilactase). Thirteen modifiable risk factors were associated with 9 metabolites, and 8 of these modifiable risk factors were associated with CRC risk. These 9 metabolites mediated the effect of modifiable risk factors (Actinobacteria, body mass index, waist to hip ratio, fasting insulin, smoking initiation) on CRC. CONCLUSION: This study identified key metabolite biomarkers associated with CRC and elucidated their mediator roles in the associations between modifiable risk factors and CRC. These findings provide new insights into the etiology and potential therapeutic targets for CRC and the etiological pathways of modifiable environmental factors with CRC.

Phenome-wide Mendelian randomisation analysis of 378,142 cases reveals risk factors for eight common cancers.

For many cancers there are only a few well-established risk factors. Here, we use summary data from genome-wide association studies (GWAS) in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify potentially causal relationships for over 3,000 traits. Our outcome datasets comprise 378,142 cases across breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, as well as 485,715 controls. We complement this analysis by systematically mining the literature space for supporting evidence. In addition to providing supporting evidence for well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we also find sex steroid hormones, plasma lipids, and telomere length as determinants of cancer risk. A number of the molecular factors we identify may prove to be potential biomarkers. Our analysis, which highlights aetiological similarities and differences in common cancers, should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app to visualise findings.

Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations.

Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.

Dissecting the pathogenic effects of smoking and its hallmarks in blood DNA methylation on colorectal cancer risk.

BACKGROUND: Tobacco smoking is suggested as a risk factor for colorectal cancer (CRC), but the complex relationship and the potential pathway are not fully understood. METHODS: We performed two-sample Mendelian randomisation (MR) analyses with genetic instruments for smoking behaviours and related DNA methylation in blood and summary-level GWAS data of colorectal cancer to disentangle the relationship. Colocalization analyses and prospective gene-environment interaction analyses were also conducted as replication. RESULTS: Convincing evidence was identified for the pathogenic effect of smoking initiation on CRC risk and suggestive evidence was observed for the protective effect of smoking cessation in the univariable MR analyses. Multivariable MR analysis revealed that these associations were independent of other smoking phenotypes and alcohol drinking. Genetically predicted methylation at CpG site cg17823346 [ZMIZ1] were identified to decrease CRC risk; while genetically predicted methylation at cg02149899 would increase CRC risk. Colocalization and gene-environment interaction analyses added further evidence to the relationship between epigenetic modification at cg17823346 [ZMIZ1] as well as cg02149899 and CRC risk. DISCUSSION: Our study confirms the significant association between tobacco smoking, DNA methylation and CRC risk and yields a novel insight into the pathogenic effect of tobacco smoking on CRC risk.

Exploring the Complex Relationship between Gut Microbiota and Risk of Colorectal Neoplasia Using Bidirectional Mendelian Randomization Analysis.

BACKGROUND: Human gut microbiome has complex relationships with the host, contributing to metabolism, immunity, and carcinogenesis. METHODS: Summary-level data for gut microbiota and metabolites were obtained from MiBioGen, FINRISK and human metabolome consortia. Summary-level data for colorectal cancer were derived from a genome-wide association study meta-analysis. In forward Mendelian randomization (MR), we employed genetic instrumental variables (IV) for 24 gut microbiota taxa and six bacterial metabolites to examine their causal relationship with colorectal cancer. We also used a lenient threshold for nine apriori gut microbiota taxa as secondary analyses. In reverse MR, we explored association between genetic liability to colorectal neoplasia and abundance of microbiota studied above using 95, 19, and 7 IVs for colorectal cancer, adenoma, and polyps, respectively. RESULTS: Forward MR did not find evidence indicating causal relationship between any of the gut microbiota taxa or six bacterial metabolites tested and colorectal cancer risk. However, reverse MR supported genetic liability to colorectal adenomas was causally related with increased abundance of two taxa: Gammaproteobacteria (ß = 0.027, which represents a 0.027 increase in log-transformed relative abundance values of Gammaproteobacteria for per one-unit increase in log OR of adenoma risk; P = 7.06×10-8), Enterobacteriaceae (ß = 0.023, P = 1.29×10-5). CONCLUSIONS: We find genetic liability to colorectal neoplasia may be associated with abundance of certain microbiota taxa. It is more likely that subset of colorectal cancer genetic liability variants changes gut biology by influencing both gut microbiota and colorectal cancer risk. IMPACT: This study highlights the need of future complementary studies to explore causal mechanisms linking both host genetic variation with gut microbiome and colorectal cancer susceptibility.

Risk factors for eight common cancers revealed from a phenome-wide Mendelian randomisation analysis of 378,142 cases and 485,715 controls.

For many cancers there are few well-established risk factors. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify causal relationships. We performed a MR-PheWAS of breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, comprising 378,142 cases and 485,715 controls. To derive a more comprehensive insight into disease aetiology we systematically mined the literature space for supporting evidence. We evaluated causal relationships for over 3,000 potential risk factors. In addition to identifying well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we provide evidence for specific factors, including dietary intake, sex steroid hormones, plasma lipids and telomere length as determinants of cancer risk. We also implicate molecular factors including plasma levels of IL-18, LAG-3, IGF-1, CT-1, and PRDX1 as risk factors. Our analyses highlight the importance of risk factors that are common to many cancer types but also reveal aetiological differences. A number of the molecular factors we identify have the potential to be biomarkers. Our findings should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app (https://mrcancer.shinyapps.io/mrcan/) to visualise findings.

Risk factors for eight common cancers revealed from a phenome-wide Mendelian randomisation analysis of 378,142 cases and 485,715 controls.

For many cancers there are few well-established risk factors. Summary data from genome-wide association studies (GWAS) can be used in a Mendelian randomisation (MR) phenome-wide association study (PheWAS) to identify causal relationships. We performed a MR-PheWAS of breast, prostate, colorectal, lung, endometrial, oesophageal, renal, and ovarian cancers, comprising 378,142 cases and 485,715 controls. To derive a more comprehensive insight into disease aetiology we systematically mined the literature space for supporting evidence. We evaluated causal relationships for over 3,000 potential risk factors. In addition to identifying well-established risk factors (smoking, alcohol, obesity, lack of physical activity), we provide evidence for specific factors, including dietary intake, sex steroid hormones, plasma lipids and telomere length as determinants of cancer risk. We also implicate molecular factors including plasma levels of IL-18, LAG-3, IGF-1, CT-1, and PRDX1 as risk factors. Our analyses highlight the importance of risk factors that are common to many cancer types but also reveal aetiological differences. A number of the molecular factors we identify have the potential to be biomarkers. Our findings should aid public health prevention strategies to reduce cancer burden. We provide a R/Shiny app (https://mrcancer.shinyapps.io/mrcan/) to visualise findings.

Combining Asian-European Genome-Wide Association Studies of Colorectal Cancer Improves Risk Prediction Across Race and Ethnicity.

Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expanded PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS were 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1,681-3,651 cases and 8,696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They were significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values<0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.

Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries.

Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.

Integrating genome-wide polygenic risk scores and non-genetic risk to predict colorectal cancer diagnosis using UK Biobank data: population based cohort study.

OBJECTIVE: To evaluate the benefit of combining polygenic risk scores with the QCancer-10 (colorectal cancer) prediction model for non-genetic risk to identify people at highest risk of colorectal cancer. DESIGN: Population based cohort study. SETTING: Data from the UK Biobank study, collected between March 2006 and July 2010. PARTICIPANTS: 434 587 individuals with complete data for genetics and QCancer-10 predictions were included in the QCancer-10 plus polygenic risk score modelling and validation cohorts. MAIN OUTCOME MEASURES: Prediction of colorectal cancer diagnosis by genetic, non-genetic, and combined risk models. Using data from UK Biobank, six different polygenic risk scores for colorectal cancer were developed using LDpred2 polygenic risk score software, clumping, and thresholding approaches, and a model based on genome-wide significant polymorphisms. The top performing genome-wide polygenic risk score and the score containing genome-wide significant polymorphisms were combined with QCancer-10 and performance was compared with QCancer-10 alone. Case-control (logistic regression) and time-to-event (Cox proportional hazards) analyses were used to evaluate risk model performance in men and women. RESULTS: Polygenic risk scores derived using the LDpred2 program performed best, with an odds ratio per standard deviation of 1.584 (95% confidence interval 1.536 to 1.633), and top age and sex adjusted C statistic of 0.733 (95% confidence interval 0.710 to 0.753) in logistic regression models in the validation cohort. Integrated QCancer-10 plus polygenic risk score models out-performed QCancer-10 alone. In men, the integrated LDpred2 model produced a C statistic of 0.730 (0.720 to 0.741) and explained variation of 28.2% (26.3 to 30.1), compared with 0.693 (0.682 to 0.704) and 21.0% (18.9 to 23.1) for QCancer-10 alone. In women, the C statistic for the integrated LDpred2 model was 0.687 (0.673 to 0.702) and explained variation was 21.0% (18.7 to 23.7), compared with 0.645 (0.631 to 0.659) and 12.4% (10.3 to 14.6) for QCancer-10 alone. In the top 20% of individuals at highest absolute risk, the sensitivity and specificity of the integrated LDpred2 models for predicting colorectal cancer diagnosis was 47.8% and 80.3% respectively in men, and 42.7% and 80.1% respectively in women, with increases in absolute risk in the top 5% of risk in men of 3.47-fold and in women of 2.77-fold compared with the median. Illustrative decision curve analysis indicated a small incremental improvement in net benefit with QCancer-10 plus polygenic risk score models compared with QCancer-10 alone. CONCLUSIONS: Integrating polygenic risk scores with QCancer-10 modestly improves risk prediction over use of QCancer-10 alone. Given that QCancer-10 data can be obtained relatively easily from health records, use of polygenic risk score in risk stratified population screening for colorectal cancer currently has no clear justification. The added benefit, cost effectiveness, and acceptability of polygenic risk scores should be carefully evaluated in a real life screening setting before implementation in the general population.

Exploiting gene dependency to inform drug development for multiple myeloma.

Despite recent advances in therapy, multiple myeloma essentially remains an incurable malignancy. Targeting tumour-specific essential genes, which constitute a druggable dependency, potentially offers a strategy for developing new therapeutic agents to treat MM and overcome drug resistance. To explore this possibility, we analysed DepMap project data identifying 23 MM essential genes and examined the relationship between their expression and patient outcome in three independent series totalling 1503 cases. The expression of TCF3 and FLVCR1 were both significantly associated with progression-free survival. IKBKB is already a drug target in other diseases, offering the prospect of repurposing to treat MM, while PIM2 is currently being investigated as a treatment for the disease. Our analysis supports the rationale of using large-scale genetic perturbation screens to guide the development of new therapeutic agents for MM.

Alcohol consumption, DNA methylation and colorectal cancer risk: Results from pooled cohort studies and Mendelian randomization analysis.

Alcohol consumption is thought to be one of the modifiable risk factors for colorectal cancer (CRC). However, the causality and mechanisms by which alcohol exerts its carcinogenic effect are unclear. We evaluated the association between alcohol consumption and CRC risk by analyzing data from 32 cohort studies and conducted two-sample Mendelian randomization (MR) analysis to examine for casual relationship. To explore the effect of alcohol related DNA methylation on CRC risk, we performed an epigenetic MR analysis with data from an epigenome-wide association study (EWAS). We additionally performed gene-alcohol interaction analysis nested in the UK Biobank to assess effect modification between alcohol consumption and susceptibility genes. We discovered distinct effects of alcohol on CRC incidence and mortality from the meta-analyses, and genetic predisposition to alcohol drinking was causally associated with an increased CRC risk (OR = 1.79, 95% CI: 1.23-2.61) using two-sample MR approaches. In epigenetic MR analysis, two alcohol-related CpG sites (cg05593667 and cg10045354 mapped to COLCA1/COLCA2 gene) were identified causally associated with an increased CRC risk (P < 8.20 × 10-4 ). Gene-alcohol interaction analysis revealed that carriage of the risk allele of the eQTL (rs3087967) and mQTL (rs11213823) polymorphism of COLCA1/COLCA2 would interact with alcohol consumption to increase CRC risk (PInteraction  = .027 and PInteraction  = .016). Our study provides comprehensive evidence to elucidate the role of alcohol in CRC and highlights that the pathogenic effect of alcohol on CRC could be partly attributed to DNA methylation by regulating the expression of COLCA1/COLCA2 gene.