Genetic correlation and causal associations between psychiatric disorders and lung cancer risk.

BACKGROUND: Patients with certain psychiatric disorders have increased lung cancer incidence. However, establishing a causal relationship through traditional epidemiological methods poses challenges. METHODS: Available summary statistics of genome-wide association studies of cigarette smoking, lung cancer, and eight psychiatric disorders, including attention deficit/hyperactivity disorder (ADHD), autism, depression, major depressive disorder, bipolar disorder, insomnia, neuroticism, and schizophrenia (range N: 46,350-1,331,010) were leveraged to estimate genetic correlations using Linkage Disequilibrium Score Regression and assess causal effect of each psychiatric disorder on lung cancer using two-sample Mendelian randomization (MR) models, comprising inverse-variance weighted (IVW), weighted median, MR-Egger, pleiotropy residual sum and outlier testing (MR-PRESSO), and a constrained maximum likelihood approach (cML-MR). RESULTS: Significant positive correlations were observed between each psychiatric disorder and both smoking and lung cancer (all FDR < 0.05), except for the correlation between autism and lung cancer. Both univariable and the cML-MA MR analyses demonstrated that liability to schizophrenia, depression, ADHD, or insomnia was associated with an increased risk of overall lung cancer. Genetic liability to insomnia was linked specifically to squamous cell carcinoma (SCC), while genetic liability to ADHD was associated with an elevated risk of both SCC and small cell lung cancer (all P < 0.05). The later was further supported by multivariable MR analyses, which accounted for smoking. LIMITATIONS: Participants were constrained to European ancestry populations. Causal estimates from binary psychiatric disorders may be biased. CONCLUSION: Our findings suggest appropriate management of several psychiatric disorders, particularly ADHD, may potentially reduce the risk of developing lung cancer.

Drug-target Mendelian randomization revealed a significant association of genetically proxied metformin effects with increased prostate cancer risk.

The association between metformin use and risk of prostate cancer remains controversial, while data from randomized trials is lacking. We aim to evaluate the association of genetically proxied metformin effects with prostate cancer risk using a drug-target Mendelian randomization (MR) approach. Summary statistics for prostate cancer were obtained from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome Consortium (79,148 cases and 61,106 controls). Cis-expression quantitative trait loci (cis-eQTL) variants in the gene targets of metformin were identified in the GTEx project and eQTLGen consortium. We also obtained male-specific genome-wide association study data for type 2 diabetes, body mass index (BMI), total testosterone, bioavailable testosterone, estradiol, and sex hormone binding globulin for mediation analysis. Inverse-variance weighted (IVW) regression, weighted median, MR-Egger regression, and MR-PRESSO were performed in the main MR analysis. Multivariable MR was used to identify potential mediators and genetic colocalization analysis was performed to assess any shared genetic basis between two traits of interest. We found that genetically proxied metformin effects (1-SD HbA1c reduction, equivalent to 6.75 mmol/mol) were associated with higher risk of prostate cancer (odds ratioIVW [ORIVW]: 1.55, 95% confidence interval, CI: 1.23-1.96, p = 3.0 × 10-3). Two metformin targets, mitochondrial complex I (ORIVW: 1.48, 95% CI: 1.07-2.03, p = 0.016) and gamma-secretase complex (ORIVW: 2.58, 95%CI :1.47-4.55, p = 0.001), showed robust associations with prostate cancer risk, and their effects were partly mediated through BMI (16.4%) and total testosterone levels (34.3%), respectively. These results were further supported by colocalization analysis that expressions of NDUFA13 and BMI, APH1A, and total testosterone may be influenced by shared genetic factors, respectively. In summary, our study indicated that genetically proxied metformin effects may be associated with an increased risk of prostate cancer. Repurposing metformin for prostate cancer prevention in general populations is not supported by our findings.

Genetic correlation and causal associations between circulating C-reactive protein levels and lung cancer risk.

PURPOSE: We aimed to characterize genetic correlations and causal associations between circulating C-reactive protein (CRP) levels and the risk of lung cancer (LC). METHODS: Leveraging summary statistics from genome-wide association studies of circulating CRP levels among 575,531 individuals of European ancestry, and LC risk among 29,266 cases and 56,450 controls, we investigated genetic associations of circulating CRP levels with the risk of overall lung cancer and its histological subtypes, by using linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analyses. RESULTS: Significant positive genetic correlations between circulating CRP levels and the risk of LC and its histological subtypes were identified from LDSC regression, with correlation coefficients ranging from 0.12 to 0.26, and all false discovery adjusted p < 0.05. Univariable MR demonstrated a nominal association between CRP levels and an increased risk of lung squamous cell carcinoma (SCC) (inverse variance-weighted OR = 1.15, 95% CI 1.01-1.30). However, this association disappeared when multivariable MR included cigarettes per day and/or body mass index. By using our recently developed constrained maximum likelihood-based MR method, we identified significant associations of CRP levels with the risk of overall LC (OR 1.06, 95% CI 1.03-1.09), SCC (OR 1.06, 95% CI 1.02-1.09), and small cell lung cancer (SCLC, OR 1.09, 95% CI 1.03-1.15). Moreover, most univariable and multivariable MR analyses also revealed consistent CRP-SCLC associations. CONCLUSION: There may be a genetic and causal association between circulating CRP levels and the risk of SCLC, which is in line with previous population-based observational studies.

Gut microbiome in association with chemotherapy-induced toxicities among patients with breast cancer.

BACKGROUND: Little research has focused on the relationship between gut microbiome and chemotherapy-induced toxicity. METHODS: This prospective study involves 301 patients with breast cancer who had prechemotherapy stool samples collected. Gut microbiome was sequenced by shotgun metagenomics; associations with chemotherapy-induced toxicities during first-line treatment by gut microbial diversity, composition, and metabolic pathways with severe (i.e., grade ≥3) hematological and gastrointestinal toxicities were evaluated via multivariable logistic regression. RESULTS: High prechemotherapy α-diversity was associated with a significantly reduced risk of both severe hematological toxicity (odds ratio [OR] = 0.94; 95% CI, 0.89-0.99; p = .048) and neutropenia (OR = 0.94; 95% CI, 0.89-0.99; p = .016). A high abundance of phylum Synergistota, class Synergistia, and order Synergistales were significantly associated with a reduced risk of severe neutropenia; conversely, enrichment of phylum Firmicutes C, class Negativicutes, phylum Firmicutes I, and class Bacilli A, order Paenibacillales were significantly associated with an increased risk of severe neutropenia (p range: 0.012-2.32 × 10-3 ; false discovery rate <0.1). Significant positive associations were also observed between severe nausea/vomiting and high Chao1 indexes, ß-diversity (p < .05), 20 species belonging to the family Lachnospiraceae, Oscillospiraceae, and Ruminococcaceae (p value range: 6.14 × 10-3 to 1.33 × 10-5 ; false discovery rate <0.1), and three metabolic pathways involved in reductive tricarboxylic acid cycle I and cycle II, and an incomplete reductive tricarboxylic acid cycle (p < .01). Conversely, a high abundance of species Odoribacter laneus and the pathway related to the L-proline biosynthesis II were inversely associated with severe nausea/vomiting. CONCLUSIONS: Our study suggests that gut microbiota may be a potential preventive target to reduce chemotherapy-induced toxicity.

Lifestyle factors, genetic susceptibility to obesity and their interactions on coronary artery disease risk: A cohort study in the UK Biobank.

OBJECTIVE: We aimed to evaluate potential modifying effects of genetic susceptibility to obesity on the association of lifestyle factors with coronary artery disease (CAD) risk. METHODS: A total of 328,606 participants (54% women) were included using data from the UK Biobank. We evaluated the risk of developing CAD associated with obesity-related polygenic scores (PGSs) and healthy lifestyle scores (HLSs). HLSs were constructed using six lifestyle factors. Obesity PGSs were created using genetic variants identified by genome-wide association studies, including 941 variants for body mass index (BMI) and 457 for waist-to-hip ratio (WHR). Both HLSs and PGSs were categorized into three groups. RESULTS: During a 9-year median follow-up, 14,541 participants developed CAD. An unhealthy lifestyle was significantly associated with an increased CAD risk (hazard ratio [HR] = 2.24, 95% confidence interval [CI] = 2.09-2.40). High BMI and WHR PGSs were each significantly associated with an increased CAD risk (HRBMI = 1.23, 1.17-1.29; HRWHR = 1.15, 1.09-1.21). Lifestyle factors explained 41% (95% CI = 38%-45%) of CAD, while genetic variants for BMI explained only 10% (7%-14%). Risks of CAD were increased with poorer HLS independent of obesity-related PGSs. Individuals with the most unhealthy lifestyle and highest BMI PGS had the highest risk of CAD risk (HR = 2.59, 95% CI = 2.26-2.97), compared with participants with the healthiest lifestyle and lowest BMI PGS. CONCLUSIONS: While the observational nature of the study precludes the establishment of causality, our study provides supports for a causal association between obesity and CAD risk and the importance of lifestyle modification in the prevention of CAD.

Gut Microbiome of Patients With Breast Cancer in Vietnam.

PURPOSE: Gut microbiota play an important role in human health, including cancer. Cancer and its treatment, in turn, may alter the gut microbiome. To understand this complex relationship, we profiled the gut microbiome of 356 Vietnamese patients with breast cancer. MATERIALS AND METHODS: Stool samples were collected before chemotherapy, with 162 pre- and 194 postsurgery. The gut microbiome was measured by shotgun metagenomic sequencing. Associations of gut microbial diversity, taxa abundance, and gut microbiome health index (GMHI) with sociodemographic, clinical factors, and tumor characteristics were evaluated. RESULTS: Postsurgery samples were associated with significantly lower α- and ß-diversities (P < .001) and showed significant differences in the abundance of 15% of 2,864 investigated taxa (false discovery rate [FDR] <0.1) compared with presurgery samples. An unhealthy gut microbiome was prevalent among patients with breast cancer, with a mean GMHI of -0.79 and -2.81 in pre- and postsurgery stool samples, respectively. In an analysis of 162 presurgery stool samples, diagnosis delay was significantly associated with lower α-diversity, variation in ß-diversity, an increased abundance of species Enorma massiliensis, and a decreased abundance of Faecalicoccus pleomorphus. High intake of fiber was significantly associated with lower α-diversity and a higher abundance of species belonging to Bifidobacterium, Prevotella, and Bacteroides gena (FDR < 0.1). We did not find that cancer stage and subtype, menopausal status, comorbidity, antibiotic use during 3 months before stool collection, or physical activity was significantly associated with α- and ß-diversities or GMHI although a few significant differences were observed in taxa abundance. CONCLUSION: Our study revealed that diagnosis delay, high fiber intake, and breast cancer surgery, which is always followed by antibiotic prophylaxis in Vietnam, led to a less diverse and unhealthy gut microbiome among patients with breast cancer.

Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia.

BACKGROUND: Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. METHODS: We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). RESULTS: In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). CONCLUSION: The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.

A large-scale microRNA transcriptome-wide association study identifies two susceptibility microRNAs, miR-1307-5p and miR-192-3p, for colorectal cancer risk.

Transcriptome-wide association studies (TWAS) have identified many putative susceptibility genes for colorectal cancer (CRC) risk. However, susceptibility miRNAs, critical dysregulators of gene expression, remain unexplored. We genotyped DNA samples from 313 CRC East Asian patients and performed small RNA sequencing in their normal colon tissues distant from tumors to build genetic models for predicting miRNA expression. We applied these models and data from genome-wide association studies (GWAS) including 23 942 cases and 217 267 controls of East Asian ancestry to investigate associations of predicted miRNA expression with CRC risk. Perturbation experiments separately by promoting and inhibiting miRNAs expressions and further in vitro assays in both SW480 and HCT116 cells were conducted. At a Bonferroni-corrected threshold of P < 4.5 × 10-4, we identified two putative susceptibility miRNAs, miR-1307-5p and miR-192-3p, located in regions more than 500 kb away from any GWAS-identified risk variants in CRC. We observed that a high predicted expression of miR-1307-5p was associated with increased CRC risk, while a low predicted expression of miR-192-3p was associated with increased CRC risk. Our experimental results further provide strong evidence of their susceptible roles by showing that miR-1307-5p and miR-192-3p play a regulatory role, respectively, in promoting and inhibiting CRC cell proliferation, migration, and invasion, which was consistently observed in both SW480 and HCT116 cells. Our study provides additional insights into the biological mechanisms underlying CRC development.

Novel insights into genetic susceptibility for colorectal cancer from transcriptome-wide association and functional investigation.

BACKGROUND: Transcriptome-wide association studies have been successful in identifying candidate susceptibility genes for colorectal cancer (CRC). To strengthen susceptibility gene discovery, we conducted a large transcriptome-wide association study and an alternative splicing transcriptome-wide association study in CRC using improved genetic prediction models and performed in-depth functional investigations. METHODS: We analyzed RNA-sequencing data from normal colon tissues and genotype data from 423 European descendants to build genetic prediction models of gene expression and alternative splicing and evaluated model performance using independent RNA-sequencing data from normal colon tissues of the Genotype-Tissue Expression Project. We applied the verified models to genome-wide association studies (GWAS) summary statistics among 58 131 CRC cases and 67 347 controls of European ancestry to evaluate associations of genetically predicted gene expression and alternative splicing with CRC risk. We performed in vitro functional assays for 3 selected genes in multiple CRC cell lines. RESULTS: We identified 57 putative CRC susceptibility genes, which included the 48 genes from transcriptome-wide association studies and 15 genes from splicing transcriptome-wide association studies, at a Bonferroni-corrected P value less than .05. Of these, 16 genes were not previously implicated in CRC susceptibility, including a gene PDE7B (6q23.3) at locus previously not reported by CRC GWAS. Gene knockdown experiments confirmed the oncogenic roles for 2 unreported genes, TRPS1 and METRNL, and a recently reported gene, C14orf166. CONCLUSION: This study discovered new putative susceptibility genes of CRC and provided novel insights into the biological mechanisms underlying CRC development.

Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data.

Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.

Genome-wide association study of prostate-specific antigen levels in 392,522 men identifies new loci and improves cross-ancestry prediction.

We conducted a multi-ancestry genome-wide association study of prostate-specific antigen (PSA) levels in 296,754 men (211,342 European ancestry; 58,236 African ancestry; 23,546 Hispanic/Latino; 3,630 Asian ancestry; 96.5% of participants were from the Million Veteran Program). We identified 318 independent genome-wide significant (p≤5e-8) variants, 184 of which were novel. Most demonstrated evidence of replication in an independent cohort (n=95,768). Meta-analyzing discovery and replication (n=392,522) identified 447 variants, of which a further 111 were novel. Out-of-sample variance in PSA explained by our new polygenic risk score reached 16.9% (95% CI=16.1%-17.8%) in European ancestry, 9.5% (95% CI=7.0%-12.2%) in African ancestry, 18.6% (95% CI=15.8%-21.4%) in Hispanic/Latino, and 15.3% (95% CI=12.7%-18.1%) in Asian ancestry, and lower for higher age. Our study highlights how including proportionally more participants from underrepresented populations improves genetic prediction of PSA levels, with potential to personalize prostate cancer screening.

Large-scale alternative polyadenylation (APA)-wide association studies to identify putative susceptibility genes in human common cancers.

Alternative polyadenylation (APA) modulates mRNA processing in the 3' untranslated regions (3'UTR), which affect mRNA stability and translation efficiency. Here, we build genetic models to predict APA levels in multiple tissues using sequencing data of 1,337 samples from the Genotype-Tissue Expression, and apply these models to assess associations between genetically predicted APA levels and cancer risk with data from large genome-wide association studies of six common cancers, including breast, ovary, prostate, colorectum, lung, and pancreas among European-ancestry populations. At a Bonferroni-corrected P □<□0.05, we identify 58 risk genes, including seven in newly identified loci. Using luciferase reporter assays, we demonstrate that risk alleles of 3'UTR variants, rs324015 ( STAT6 ), rs2280503 ( DIP2B ), rs1128450 ( FBXO38 ) and rs145220637 ( LDAH ), could significantly increase post-transcriptional activities of their target genes compared to reference alleles. Further gene knockdown experiments confirm their oncogenic roles. Our study provides additional insight into the genetic susceptibility of these common cancers.

Enhancing Disease Risk Gene Discovery by Integrating Transcription Factor-Linked Trans-located Variants into Transcriptome-Wide Association Analyses.

Transcriptome-wide association studies (TWAS) have been successful in identifying putative disease susceptibility genes by integrating gene expression predictions with genome-wide association studies (GWAS) data. However, current TWAS models only consider cis-located variants to predict gene expression. Here, we introduce transTF-TWAS, which includes transcription factor (TF)-linked trans-located variants for model building. Using data from the Genotype-Tissue Expression project, we predict alternative splicing and gene expression and applied these models to large GWAS datasets for breast, prostate, and lung cancers. Our analysis revealed 887 putative cancer susceptibility genes, including 465 in regions not yet reported by previous GWAS and 137 in known GWAS loci but not yet reported previously, at Bonferroni-corrected P < 0.05. We demonstrate that transTF-TWAS surpasses other approaches in both building gene prediction models and identifying disease-associated genes. These results have shed new light on several genetically driven key regulators and their associated regulatory networks underlying disease susceptibility.

Oral microbiome and ischemic stroke risk among elderly Chinese women.

Background: Stroke, a leading cause of disability worldwide, has been associated with periodontitis. However, whether stroke risk is related to oral microbiota remains unknown. This study aims to evaluate the associations between the oral microbiome and ischemic stroke risk. Methods: In a case-control study of 134 case-control pairs nested within a prospective cohort study, we examined pre-diagnostic oral microbiome in association with stroke risk via shotgun metagenomic sequencing. The microbial sub-community and functional profiling were performed using Latent Dirichlet Allocation and HUMAnN2. Associations of microbial diversity, sub-community structure, and individual microbial features with ischemic stroke risk were evaluated via conditional logistic regression. Results: Alpha and beta diversities differ significantly between cases and controls. One genus- and two species-level sub-communities were significantly associated with decreased ischemic stroke risk, with odds ratios (95% confidence intervals) of 0.52 (0.31-0.90), 0.51 (0.31-0.84), and 0.60 (0.36-0.99), respectively. These associations were potentially driven by the representative taxa in these sub-communities, i.e., genus Corynebacterium and Lautropia, and species Lautropia mirabilis and Neisseria elongate (p < 0.05). Additionally, 55 taxa, 1,237 gene families, and 90 metabolic pathways were associated with ischemic stroke risk at p < 0.05. Conclusion: Our study highlights the role of oral microbiota in the etiology of ischemic stroke and calls for further research.

Integrating genomics and proteomics data to identify candidate plasma biomarkers for lung cancer risk among European descendants.

BACKGROUND: Plasma proteins are potential biomarkers for complex diseases. We aimed to identify plasma protein biomarkers for lung cancer. METHODS: We investigated genetically predicted plasma levels of 1130 proteins in association with lung cancer risk among 29,266 cases and 56,450 controls of European descent. For proteins significantly associated with lung cancer risk, we evaluated associations of genetically predicted expression of their coding genes with the risk of lung cancer. RESULTS: Nine proteins were identified with genetically predicted plasma levels significantly associated with overall lung cancer risk at a false discovery rate (FDR) of <0.05. Proteins C2, MICA, AIF1, and CTSH were associated with increased lung cancer risk, while proteins SFTPB, HLA-DQA2, MICB, NRP1, and GMFG were associated with decreased lung cancer risk. Stratified analyses by histological types revealed the cross-subtype consistency of these nine associations and identified an additional protein, ICAM5, significantly associated with lung adenocarcinoma risk (FDR < 0.05). Coding genes of NRP1 and ICAM5 proteins are located at two loci that have never been reported by previous GWAS. Genetically predicted blood levels of genes C2, AIF1, and CTSH were associated with lung cancer risk, in directions consistent with those shown in protein-level analyses. CONCLUSION: Identification of novel plasma protein biomarkers provided new insights into the biology of lung cancer.

Trans-ethnic polygenic risk scores for body mass index: An international hundred K+ cohorts consortium study.

BACKGROUND: While polygenic risk scores hold significant promise in estimating an individual's risk of developing a complex trait such as obesity, their application in the clinic has, to date, been limited by a lack of data from non-European populations. As a collaboration model of the International Hundred K+ Cohorts Consortium (IHCC), we endeavored to develop a globally applicable trans-ethnic PRS for body mass index (BMI) through this relatively new international effort. METHODS: The polygenic risk score (PRS) model was developed, trained and tested at the Center for Applied Genomics (CAG) of The Children's Hospital of Philadelphia (CHOP) based on a BMI meta-analysis from the GIANT consortium. The validated PRS models were subsequently disseminated to the participating sites. Scores were generated by each site locally on their cohorts and summary statistics returned to CAG for final analysis. RESULTS: We show that in the absence of a well powered trans-ethnic GWAS from which to derive marker SNPs and effect estimates for PRS, trans-ethnic scores can be generated from European ancestry GWAS using Bayesian approaches such as LDpred, by adjusting the summary statistics using trans-ethnic linkage disequilibrium reference panels. The ported trans-ethnic scores outperform population specific-PRS across all non-European ancestry populations investigated including East Asians and three-way admixed Brazilian cohort. CONCLUSIONS: Here we show that for a truly polygenic trait such as BMI adjusting the summary statistics of a well powered European ancestry study using trans-ethnic LD reference results in a score that is predictive across a range of ancestries including East Asians and three-way admixed Brazilians.

Identification of target proteins for breast cancer genetic risk loci and blood risk biomarkers in a large study by integrating genomic and proteomic data.

Genome-wide association studies (GWAS) have identified around 200 loci associated with breast cancer risk. However, protein targets for these loci remain largely unknown. Identifying protein targets and biomarkers can improve the understanding of cancer biology and etiology and identify high-risk individuals for cancer prevention. In this study, we investigated genetically predicted levels of 1142 circulating proteins with breast cancer risk in 133 384 cases and 113 789 controls of European ancestry included in the Breast Cancer Association Consortium (BCAC). We identified 22 blood protein biomarkers associated with the risk of overall breast cancer at a false discovery rate (FDR) <0.05, including nine proteins encoded by genes located at least 500 kb away from previously reported risk variants for breast cancer. Analyses focusing on 124 encoding genes located at GWAS-identified breast cancer risk loci found 20 proteins associated with overall breast cancer risk and one protein associated with triple-negative breast cancer risk at FDR <0.05. Adjustment for the GWAS-identified risk variants significantly attenuated the association for 13 of these proteins, suggesting that these proteins may be the targets of these GWAS-identified risk loci. The identified proteins are involved in various biological processes, including glutathione conjugation, STAT5 signaling and NF-κB signaling pathways. Our study identified novel protein targets and risk biomarkers for breast cancer risk.

Serum Lipid Profiles and Cholesterol-Lowering Medication Use in Relation to Subsequent Risk of Colorectal Cancer in the UK Biobank Cohort.

BACKGROUND: Dyslipidemia is closely associated with metabolic syndrome, a known risk factor for colorectal cancer. However, the association of dyslipidemia with colorectal cancer risk is controversial. Most previous studies did not consider cholesterol-lowering medication use at the time of lipid measurements, which could bias findings. METHODS: We analyzed data from 384,862 UK Biobank participants to disentangle the associations between blood lipids and colorectal cancer risk. Serum levels of total cholesterol, high- and low-density lipoprotein cholesterol (HDL-C, LDL-C), and triglyceride were measured at study baseline. Multivariable-adjusted Cox models were used to estimate HRs and 95% confidence intervals (CI). RESULTS: During a median follow-up time of 8.2 years, 3,150 incident primary colorectal cancer cases were identified. Triglyceride levels were positively, while HDL-C levels were inversely associated with colorectal cancer risk (both Ptrend < 0.005). No significant associations were found for total cholesterol and LDL-C. However, among nonusers of cholesterol-lowering medications, a high total cholesterol level (> 6.7 mmol/L, HR = 1.11; 95% CI, 1.00-1.24) and LDL-C level (>4.1 mmol/L, HR = 1.11; 95% CI, 0.99-1.23) was associated with an increased colorectal cancer risk compared with the referent group (5.2-6.2 mmol/L and 2.6-3.4 mmol/L for total and LDL cholesterol, respectively). Compared with nonusers, cholesterol-lowering medication users had 15% increased colorectal cancer risk (HR = 1.15; 95% CI, 1.04-1.26). CONCLUSIONS: Circulating total cholesterol, LDL-C, HDL-C and triglyceride were modestly associated with colorectal cancer risk. IMPACT: Our findings call for careful consideration of cholesterol-lowering medication use in future studies of blood lipid-colorectal cancer associations.

Genome-wide association study (GWAS) of circulating vitamin D outcomes among individuals of African ancestry.

BACKGROUND: Vitamin D deficiency is more common among African-ancestry individuals and may be associated with adverse health outcomes. Vitamin D binding protein (VDBP) regulates concentrations of biologically active vitamin D. OBJECTIVE: We conducted genome-wide association study (GWAS) of VDBP and 25-hydroxyvitamin D among African-ancestry individuals. METHODS: Data were collected from 2,602 African American adults from the Southern Community Cohort Study (SCCS) and 6,934 African- or Caribbean-ancestry adults from the UK Biobank. Serum VDBP concentrations were available only in the SCCS and were measured by using the Polyclonal Human VDBP ELISA kit. Serum 25-hydroxyvitamin D concentrations for both study samples were measured by using Diasorin Liason, a chemiluminescent immunoassay. Participants were genotyped for single nucleotide polymorphisms (SNPs) with genome-wide coverage by using Illumina or Affymetrix platforms. Fine-mapping analysis was performed by using forward stepwise linear regression models including all variants with P value < 5 × 10-8 and within 250 kbps of a lead SNP. RESULTS: We identified 4 loci notably associated with VDBP concentrations in the SCCS population: rs7041 (per allele ß = 0.61 µg/mL, SE = 0.05, P = 1.4 × 10-48) and rs842998 (per allele ß = 0.39 µg/mL, SE = 0.03, P = 4.0 × 10-31) in GC, rs8427873 (per allele ß = 0.31 µg/mL, SE = 0.04, P = 3.0 × 10-14) near GC and rs11731496 (per allele ß = 0.21 µg/mL, SE = 0.03, P = 3.6 × 10-11) in between GC and NPFFR2. In conditional analyses, which included the above-mentioned SNPs, only rs7041 remained notable (P = 4.1 × 10-21). SNP rs4588 in GC was the only GWAS-identified SNP associated with 25-hydroxyvitamin D concentration. Among UK Biobank participants: per allele ß = -0.11 µg/mL, SE = 0.01, P = 1.5 × 10-13; in the SCCS: per allele ß = -0.12 µg/mL, SE = 0.06, P = 2.8 × 10-02). rs7041 and rs4588 are functional SNPs that influence the binding affinity of VDBP to 25-hydroxyvitamin D. CONCLUSIONS: Our results were in line with previous studies conducted in European-ancestry populations, showing that GC, the gene that directly encodes for VDBP, would be important for VDBP and 25-hydroxyvitamin D concentrations. The current study extends our knowledge of the genetics of vitamin D in diverse populations.