ABSTRACT High body mass index (BMI) is a causal risk factor for endometrial cancer but the tumor molecular mechanisms affected by adiposity and their therapeutic relevance remain poorly understood. Here we characterize the tumor multi-omic landscape of endometrial cancers that have developed on a background of lifelong germline genetic exposure to elevated BMI. We built a polygenic score (PGS) for BMI in women using data on independent, genome-wide significant variants associated with adult BMI in 434,794 women. We performed germline (blood) genotype quality control and imputation on data from 354 endometrial cancer cases from The Cancer Genome Atlas (TCGA). We assigned each case in this TCGA cohort their genetically predicted life-course BMI based on the BMI PGS. Multivariable generalized linear models adjusted for age, stage, microsatellite status and genetic principal components were used to test for associations between the BMI germline PGS and endometrial cancer tumor genome-wide genomic, transcriptomic, proteomic, epigenomic and immune traits in TCGA. High BMI germline PGS was associated with (i) upregulated tumor gene expression in the IL6 - JAK - STAT3 pathway (FDR=4.2×10 −7 ); (ii) increased estimated intra-tumor activated mast cell infiltration (FDR=0.008); (iii) increased single base substitution (SBS) mutational signatures 1 (FDR=0.03) and 5 (FDR=0.09) and decreased SBS13 (FDR=0.09), implicating age-related and APOBEC mutagenesis, respectively; and (iv) decreased tumor EGFR protein expression (FDR=0.07). Alterations in IL6 - JAK - STAT3 signaling gene and EGFR protein expression were, in turn, significantly associated with both overall survival and progression-free interval. Thus, we integrated germline and somatic data using a novel study design to identify associations between genetically predicted lifelong exposure to higher BMI and potentially actionable endometrial cancer tumor molecular features. These associations inform our understanding of how high BMI may influence the development and progression of this cancer, impacting endometrial tumor biology and clinical outcomes.

Table S1. Summary statistics of 7 cancer types tested with ARIC plasma proteome models, FDR<0.05, with single- and multi-variant COLOC results.

Table S3. PWAS meta-FDR<0.05 proteins with ovarian cancer associations.

Supplementary Figure S1: Workflow illustrating the methods.

Recently, the second to fourth fingers/digits ratio (2D:4D) has been reported to be associated with breast cancer (BC). We aimed to assess whether this association exists in Indian population. We derived the 2D:4D of right and left-hand from length of the index and ring finger, measured using Vernier callipers. We also calculated the right minus left 2D:4D (DR−L). For 1638 BC cases and 1723 controls, univariate unconditional logistic regression model was used to estimate odds ratio (OR) with its corresponding 95% confidence interval (CI). We observed reduced risk of BC with increase in right 2D:4D in pre- menopausal women (OR: 0.71, 95% CI: 0.52–0.96), while for post-menopausal women there was non-significant positive association. For left 2D:4D, non-significant slight increased risk of BC was observed in the highest category amongst the premenopausal women (OR: 1.12, 95% CI: 0.82–1.52). For DR−L we observed inverse association in pre-menopausal women only (OR: 0.73, 95% CI: 0.58–0.92). The association between the 2D:4D ratio and BC risk was weak and inconsistent across pre-/post-menopausal groups. Larger and more precise studies with longitudinal follow-up, and reduced random measurement error are needed to clarify whether a clinically meaningful 2D:4D ratio threshold can reliably predict BC risk.

Background: Germline alleles near genes encoding certain immune checkpoints (CTLA4, CD200) are associated with autoimmune/autoinflammatory disease and cancer, but in opposite ways. This motivates a systematic search for additional germline alleles with this pattern with the aim of identifying potential cancer immunotherapeutic targets using human genetics. Methods: Pairwise fixed effect cross-disorder meta-analyses combining genome-wide association studies (GWAS) for breast, prostate, ovarian and endometrial cancers (240,540 cases/317,000 controls) and seven autoimmune/autoinflammatory diseases (112,631 cases/895,386 controls) coupled with in silico follow-up. Results: Meta-analyses followed by linkage disequilibrium clumping identified 312 unique, independent lead variants with p < 5 × 10−8 associated with at least one of the cancer types at p < 10−3 and one of the autoimmune/autoinflammatory diseases at p < 10−3. At each lead variant, the allele that conferred autoimmune/autoinflammatory disease risk was protective for cancer. Mapping led variants to nearest genes as putative functional targets and focusing on immune-related genes implicated 32 genes. Tumor bulk RNA-Seq data highlighted that the tumor expression of 5/32 genes (IRF1, IKZF1, SPI1, SH2B3, LAT) was each strongly correlated (Spearman’s ρ > 0.5) with at least one intra-tumor T/myeloid cell infiltration marker (CD4, CD8A, CD11B, CD45) in every one of the cancer types. Tumor single-cell RNA-Seq data from all cancer types showed that the five genes were more likely to be expressed in intra-tumor immune versus malignant cells. The five lead SNPs corresponding to these genes were linked to them via the expression of quantitative trait locus mechanisms and at least one additional line of functional evidence. Proteins encoded by the genes were predicted to be druggable. Conclusions: We provide population-scale germline genetic and functional genomic evidence to support further evaluation of the proteins encoded by IRF1, IKZF1, SPI1, SH2B3 and LAT as possible targets for cancer immunotherapy.

Alcohol consumption has been linked to cancer risk. Evidence is strongest for seven cancer types: breast, colorectum, oesophagus, liver, mouth, pharynx, and larynx. However, evidence supporting a causal effect from Mendelian randomization is inconsistent. We perform a comprehensive Mendelian randomization analysis to assess whether genetically-predicted alcohol consumption associates with risk of 20 cancers. Such associations would provide supportive evidence for a causal effect of alcohol consumption on cancer risk. We used 95 genetic variants associated with alcohol consumption at genome-wide significance. Primary analyses were conducted in European ancestry participants from UK Biobank (367,643 individuals), FinnGen (500,348 individuals), All of US (169,312 individuals), and Million Veteran Program (451,206 individuals). We also estimated associations in cancer-specific consortia. No association was observed between genetically-predicted alcohol consumption and overall cancer (odds ratio (OR) per 1 standard deviation increase in alcohol consumption 0.96, p = 0.45). Among the seven highlighted cancer types, we saw a multiply-corrected significant positive estimate for combined head/neck cancer (OR 1.51, p = 0.001), and nominally significant positive estimates for colorectal (OR 1.21, p = 0.035) and oesophageal (OR 1.42 p = 0.033) cancer. For liver cancer, there was a null estimate overall (OR 1.40, p = 0.10), but a nominally significant positive estimate in Million Veteran Program and when using the ADH1B-rs1229984 variant. For breast cancer, there was a null estimate in biobank data (OR 1.09, p = 0.25) and consortium data (OR 0.98, p = 0.84). Conversely, we observed multiply-corrected significant negative estimates for kidney cancer (OR 0.64, p = 0.0003) and endometrial cancer (OR 0.56, p = 0.0006), and nominally significant negative estimates for non-Hodgkin’s lymphoma (OR 0.75, p = 0.010), myeloma (OR 0.61, p = 0.014), and some subtypes of ovarian cancer. There was a nominally significant positive association with cancer mortality (OR 1.44, p = 0.003), although this attenuated on adjustment for smoking heaviness. Limitations include potential invalidity of the genetic variants as instruments, limited power, multiple testing, variable cancer detection rates, and unrepresentativeness of the datasets. We observed moderate-to-weak evidence supporting causal effects of alcohol consumption on risk of head/neck, oesophageal, and colorectal cancer, inconsistent evidence for liver cancer, and no evidence for breast cancer. Overall, human genetic data do not provide evidence that alcohol consumption is a cause of all cancers and suggest there may even be inverse associations with certain cancer types.

Somatic DNMT3A-R882 codon mutations drive the most common form of clonal haematopoiesis (CH) and are associated with increased acute myeloid leukaemia (AML) risk1,2. Preventing expansion of DNMT3A-R882-mutant haematopoietic stem/progenitor cells (HSPCs) may therefore avert progression to AML. To identify DNMT3A-R882-mutant-specific vulnerabilities, we conducted a genome-wide CRISPR screen on primary mouse Dnmt3aR882H/+ HSPCs. Among the 640 vulnerability genes identified, many were involved in mitochondrial metabolism, and metabolic flux analysis confirmed enhanced oxidative phosphorylation use in Dnmt3aR882H/+ versus Dnmt3a+/+ (WT) HSPCs. We selected citrate/malate transporter Slc25a1 and complex I component Ndufb11, for which pharmacological inhibitors are available, for downstream studies. In vivo administration of SLC25A1 inhibitor CTPI2 and complex I inhibitors IACS-010759 and metformin suppressed post-transplantation clonal expansion of Dnmt3aR882H/+, but not WT, long-term haematopoietic stem cells. The effect of metformin was recapitulated using a primary human DNMT3A-R882 CH sample. Notably, analysis of 412,234 UK Biobank participants showed that individuals taking metformin had a markedly lower prevalence of DNMT3A-R882-mutant CH, after controlling for potential confounders including glycated haemoglobin, diabetes and body mass index. Collectively, our data propose modulation of mitochondrial metabolism as a therapeutic strategy for prevention of DNMT3A-R882-mutant AML.

Table S4. PWAS meta-FDR<0.05 proteins with endometrial cancer associations.

Table S5. PhenomeXcan TWAS results for 8 genes that had cancer associations.

The mechanisms through which mutations in splicing factor genes drive clonal hematopoiesis (CH) and myeloid malignancies, and their close association with advanced age, remain poorly understood. Here we show that telomere maintenance plays an important role in this phenomenon. First, by studying 454,098 UK Biobank participants, we find that, unlike most CH subtypes, splicing-factor-mutant CH is more common in those with shorter genetically predicted telomeres, as is CH with mutations in PPM1D and the TERT gene promoter. We go on to show that telomere attrition becomes an instrument for clonal selection in advanced age, with splicing factor mutations 'rescuing' HSCs from critical telomere shortening. Our findings expose the lifelong influence of telomere maintenance on hematopoiesis and identify a potential shared mechanism through which different splicing factor mutations drive leukemogenesis. Understanding the mechanistic basis of these observations can open new therapeutic avenues against splicing-factor-mutant CH and hematological or other cancers.

Table S2. Replication of cancer PWAS results in independent cohort with meta-analysis FDR<0.05.

Nineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We meta-analyzed >22 million variants for 398,238 women from the Ovarian Cancer Association Consortium (OCAC), UK Biobank (UKBB) and Consortium of Investigators of Modifiers of BRCA1/BRCA2 (CIMBA) to identify novel HGSOC susceptibility loci. Eight novel variants were associated with HGSOC risk. An interesting discovery biologically was TP53 3’-UTR SNP rs78378222-T’s association with HGSOC (per-T-allele relative risk (RR) = 1.44, 95% CI:1.28–1.62, P = 1.76 × 10−9). Polygenic scores (PGS) were developed using OCAC and CIMBA data and trained on FinnGen data. The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95% CI:1.37–1.54) per standard deviation when validated in the UKBB. This study represents the largest HGSOC GWAS to date – demonstrating that improvements in imputation reference panels and increased sample sizes help to identify HGSOC associated variants that previously went undetected, ultimately improving PGS which can improve personalized HGSOC risk prediction.

Background Genome-wide association studies (GWASs) of oral cancers (OC) to date have focused predominantly on European Ancestry (EA) populations. India faces an excess burden of OC, but the most common is the buccal mucosa cancer (BMC), which is relatively rare in EA populations. Methods We conducted a GWAS comprising 2160 BMC cases and 2325 controls from different geographical locations in India. We additionally conducted a GWAS of 397 BMC cases and 439 controls from Taiwan and performed multi-ancestry GWAS meta-analysis of OC on 5255 cases and 8748 controls across EA, Indian and Taiwanese populations. Findings Single SNP analysis of the Indian GWAS discovered a risk locus at 6q27 conferring susceptibility specifically to BMC and identified multiple independent association signals within known OC loci 5p15.33 and 6p21.32 (HLA region). Further, gene-level analysis of multi-ancestry GWAS identified the tumour suppressor gene NOTCH1 as an OC locus. Using data from the Indian BMC GWAS, we further identified statistically significant evidence of multiplicative interactions (P-value = 0.031 likelihood-ratio test (LRT)) between polygenic risk of BMC and tobacco chewing habit, indicating stronger relative-risk associated with genetic predisposition for non-users compared to chewers. Interpretation Our study provides insights into the aetiologies of BMC in India, highlighting both its similarities and differences with other types of oral cavity cancers, as well as the interactions between polygenic risk and tobacco chewing. Funding Department of Health Research, New Delhi—Grant No. ICMR/EU/13/2012/NCD-III. Intramural Research Program, US National Cancer Institute, National Institutes of Health.

Background 'Benign ethnic neutropenia' (BEN) is a heritable condition characterized by lower neutrophil counts, predominantly observed in individuals of African ancestry, and the genetic basis of BEN remains a subject of extensive research. In this study, we aimed to dissect the genetic architecture underlying neutrophil count variation through a linear-mixed model genome-wide association study (GWAS) in a population of African ancestry ( N = 5976). Malaria caused by P. falciparum imposes a tremendous public health burden on people living in sub-Saharan Africa. Individuals living in malaria endemic regions often have a reduced circulating neutrophil count due to BEN, raising the possibility that reduced neutrophil counts modulate severity of malaria in susceptible populations. As a follow-up, we tested this hypothesis by conducting a Mendelian randomization (MR) analysis of neutrophil counts on severe malaria (MalariaGEN, N = 17,056). Results We carried out a GWAS of neutrophil count in individuals associated to an African continental ancestry group within UK Biobank, identifying 73 loci ( r 2 = 0.1) and 10 index SNPs (GCTA-COJO loci) associated with neutrophil count, including previously unknown rare loci regulating neutrophil count in a non-European population. BOLT-LMM was reliable when conducted in a non-European population, and additional covariates added to the model did not largely alter the results of the top loci or index SNPs. The two-sample bi-directional MR analysis between neutrophil count and severe malaria showed the greatest evidence for an effect between neutrophil count and severe anaemia, although the confidence intervals crossed the null. Conclusion Our GWAS of neutrophil count revealed unique loci present in individuals of African ancestry. We note that a small sample-size reduced our power to identify variants with low allele frequencies and/or low effect sizes in our GWAS. Our work highlights the need for conducting large-scale biobank studies in Africa and for further exploring the link between neutrophils and severe malaria.